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Sample records for cancer signature identified

  1. RNA-Seq accurately identifies cancer biomarker signatures to distinguish tissue of origin.

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    Wei, Iris H; Shi, Yang; Jiang, Hui; Kumar-Sinha, Chandan; Chinnaiyan, Arul M

    2014-11-01

    Metastatic cancer of unknown primary (CUP) accounts for up to 5% of all new cancer cases, with a 5-year survival rate of only 10%. Accurate identification of tissue of origin would allow for directed, personalized therapies to improve clinical outcomes. Our objective was to use transcriptome sequencing (RNA-Seq) to identify lineage-specific biomarker signatures for the cancer types that most commonly metastasize as CUP (colorectum, kidney, liver, lung, ovary, pancreas, prostate, and stomach). RNA-Seq data of 17,471 transcripts from a total of 3,244 cancer samples across 26 different tissue types were compiled from in-house sequencing data and publically available International Cancer Genome Consortium and The Cancer Genome Atlas datasets. Robust cancer biomarker signatures were extracted using a 10-fold cross-validation method of log transformation, quantile normalization, transcript ranking by area under the receiver operating characteristic curve, and stepwise logistic regression. The entire algorithm was then repeated with a new set of randomly generated training and test sets, yielding highly concordant biomarker signatures. External validation of the cancer-specific signatures yielded high sensitivity (92.0% ± 3.15%; mean ± standard deviation) and specificity (97.7% ± 2.99%) for each cancer biomarker signature. The overall performance of this RNA-Seq biomarker-generating algorithm yielded an accuracy of 90.5%. In conclusion, we demonstrate a computational model for producing highly sensitive and specific cancer biomarker signatures from RNA-Seq data, generating signatures for the top eight cancer types responsible for CUP to accurately identify tumor origin. PMID:25425966

  2. RNA-Seq Accurately Identifies Cancer Biomarker Signatures to Distinguish Tissue of Origin1

    OpenAIRE

    Wei, Iris H.; Shi, Yang; Jiang, Hui; Kumar-Sinha, Chandan; Arul M Chinnaiyan

    2014-01-01

    Metastatic cancer of unknown primary (CUP) accounts for up to 5% of all new cancer cases, with a 5-year survival rate of only 10%. Accurate identification of tissue of origin would allow for directed, personalized therapies to improve clinical outcomes. Our objective was to use transcriptome sequencing (RNA-Seq) to identify lineage-specific biomarker signatures for the cancer types that most commonly metastasize as CUP (colorectum, kidney, liver, lung, ovary, pancreas, prostate, and stomach)....

  3. Targeted proteomics identifies liquid-biopsy signatures for extracapsular prostate cancer

    Science.gov (United States)

    Kim, Yunee; Jeon, Jouhyun; Mejia, Salvador; Yao, Cindy Q; Ignatchenko, Vladimir; Nyalwidhe, Julius O; Gramolini, Anthony O; Lance, Raymond S; Troyer, Dean A; Drake, Richard R; Boutros, Paul C; Semmes, O. John; Kislinger, Thomas

    2016-01-01

    Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers. PMID:27350604

  4. Gene expression signature analysis identifies vorinostat as a candidate therapy for gastric cancer.

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    Sofie Claerhout

    Full Text Available BACKGROUND: Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. METHODOLOGY/PRINCIPAL FINDINGS: Using microarray technology, we generated a gene expression profile of human gastric cancer-specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern. CONCLUSIONS/SIGNIFICANCE: We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment.

  5. The intestinal stem cell signature identifies colorectal cancer stem cells and predicts disease relapse

    NARCIS (Netherlands)

    Merlos-Suarez, A.; Barriga, F.M.; Jung, P.; Iglesias, M.; Cespedes, M.V.; Rossell, D.; Sevillano, M.; Hernando-Momblona, X.; da Silva-Diz, V.; Munoz, P.; Clevers, H.; Sancho, E.; Mangues, R.; Batlle, E.

    2011-01-01

    A frequent complication in colorectal cancer (CRC) is regeneration of the tumor after therapy. Here, we report that a gene signature specific for adult intestinal stem cells (ISCs) predicts disease relapse in CRC patients. ISCs are marked by high expression of the EphB2 receptor, which becomes gradu

  6. Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.

    2008-10-20

    One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic

  7. LGR5 and Nanog identify stem cell signature of pancreas beta cells which initiate pancreatic cancer.

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    Amsterdam, Abraham; Raanan, Calanit; Schreiber, Letizia; Polin, Nava; Givol, David

    2013-04-01

    Pancreas cancer, is the fourth leading cause of cancer death but its cell of origin is controversial. We compared the localization of stem cells in normal and cancerous pancreas using antibodies to the stem cell markers Nanog and LGR5. Here we show, for the first time, that LGR5 is expressed in normal pancreas, exclusively in the islets of Langerhans and it is co-localized, surprisingly, with Nanog and insulin in clusters of beta cells. In cancerous pancreas Nanog and LGR5 are expressed in the remaining islets and in all ductal cancer cells. We observed insulin staining among the ductal cancer cells, but not in metastases. This indicates that the islet's beta cells, expressing LGR5 and Nanog markers are the initiating cells of pancreas cancer, which migrated from the islets to form the ductal cancerous tissue, probably after mutation and de-differentiation. This discovery may facilitate treatment of this devastating cancer.

  8. Reverse phase protein array based tumor profiling identifies a biomarker signature for risk classification of hormone receptor-positive breast cancer

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    Johanna Sonntag

    2014-03-01

    Full Text Available A robust subclassification of luminal breast cancer, the most common molecular subtype of human breast cancer, is crucial for therapy decisions. While a part of patients is at higher risk of recurrence and requires chemo-endocrine treatment, the other part is at lower risk and also poorly responds to chemotherapeutic regimens. To approximate the risk of cancer recurrence, clinical guidelines recommend determining histologic grading and abundance of a cell proliferation marker in tumor specimens. However, this approach assigns an intermediate risk to a substantial number of patients and in addition suffers from a high interobserver variability. Therefore, the aim of our study was to identify a quantitative protein biomarker signature to facilitate risk classification. Reverse phase protein arrays (RPPA were used to obtain quantitative expression data for 128 breast cancer relevant proteins in a set of hormone receptor-positive tumors (n = 109. Proteomic data for the subset of histologic G1 (n = 14 and G3 (n = 22 samples were used for biomarker discovery serving as surrogates of low and high recurrence risk, respectively. A novel biomarker selection workflow based on combining three different classification methods identified caveolin-1, NDKA, RPS6, and Ki-67 as top candidates. NDKA, RPS6, and Ki-67 were expressed at elevated levels in high risk tumors whereas caveolin-1 was observed as downregulated. The identified biomarker signature was subsequently analyzed using an independent test set (AUC = 0.78. Further evaluation of the identified biomarker panel by Western blot and mRNA profiling confirmed the proteomic signature obtained by RPPA. In conclusion, the biomarker signature introduced supports RPPA as a tool for cancer biomarker discovery.

  9. Whole-genome bisulfite sequencing of cell-free DNA identifies signature associated with metastatic breast cancer

    OpenAIRE

    Legendre, Christophe; Gooden, Gerald C.; Johnson, Kyle; Martinez, Rae Anne; Liang, Winnie S.; Salhia, Bodour

    2015-01-01

    Background A number of clinico-pathological criteria and molecular profiles have been used to stratify patients into high- and low-risk groups. Currently, there are still no effective methods to determine which patients harbor micrometastatic disease after standard breast cancer therapy and who will eventually develop local or distant recurrence. The purpose of our study was to identify circulating DNA methylation changes that can be used for prediction of metastatic breast cancer (MBC). Resu...

  10. Association analysis of a chemo-response signature identified within The Cancer Genome Atlas aimed at predicting genetic risk for chemo-response in ovarian cancer

    Science.gov (United States)

    Salinas, Erin A; Newtson, Andreea M; Leslie, Kimberly K; Gonzalez-Bosquet, Jesus

    2016-01-01

    Background: A gene signature associated with chemo-response in ovarian cancer was created through integration of biological data in The Cancer Genome Atlas (TCGA) and validated in five independent microarray experiments. Our study aimed to determine if single nucleotide polymorphisms (SNPs) within the 422-gene signature were associated with a genetic predisposition to platinum-based chemotherapy response in serous ovarian cancer. Methods: An association analysis between SNPs within the 422-gene signature and chemo-response in serous ovarian cancer was performed under the log-additive genetic model using the ‘SNPassoc’ package within the R environment (p<0.0001). Subsequent validation of statistically significant SNPs was done in the Ovarian Cancer Association Consortium (OCAC) database. Results: 19 SNPs were found to be associated with chemo-response with statistical significance. None of the SNPs found significant in TCGA were validated within OCAC for the outcome of interest, chemo-response. Conclusions: SNPs associated with chemo-response in ovarian cancer within TGCA database were not validated in a larger database of patients and controls from OCAC. New strategies integrating somatic and germline information may help to characterize genetic predictors for treatment response in ovarian cancer. PMID:27186327

  11. A Mouse Mammary Gland Involution mRNA Signature Identifies Biological Pathways Potentially Associated with Breast Cancer Metastasis

    NARCIS (Netherlands)

    T. Stein; N. Salomonis; D.S.A. Nuyten; M.J. van de Vijver; B.A. Gusterson

    2009-01-01

    Mouse mammary gland involution resembles a wound healing response with suppressed inflammation. Wound healing and inflammation are also associated with tumour development, and a 'wound-healing' gene expression signature can predict metastasis formation and survival. Recent studies have shown that an

  12. Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

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    Kazuhide Watanabe

    Full Text Available BACKGROUND: Deregulation of canonical Wnt/CTNNB1 (beta-catenin pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. RESULTS: We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. CONCLUSION: Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  13. Real time gamma-ray signature identifier

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    Rowland, Mark; Gosnell, Tom B.; Ham, Cheryl; Perkins, Dwight; Wong, James

    2012-05-15

    A real time gamma-ray signature/source identification method and system using principal components analysis (PCA) for transforming and substantially reducing one or more comprehensive spectral libraries of nuclear materials types and configurations into a corresponding concise representation/signature(s) representing and indexing each individual predetermined spectrum in principal component (PC) space, wherein an unknown gamma-ray signature may be compared against the representative signature to find a match or at least characterize the unknown signature from among all the entries in the library with a single regression or simple projection into the PC space, so as to substantially reduce processing time and computing resources and enable real-time characterization and/or identification.

  14. Distinct microbiological signatures associated with triple negative breast cancer.

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    Banerjee, Sagarika; Wei, Zhi; Tan, Fei; Peck, Kristen N; Shih, Natalie; Feldman, Michael; Rebbeck, Timothy R; Alwine, James C; Robertson, Erle S

    2015-10-15

    Infectious agents are the third highest human cancer risk factor and may have a greater role in the origin and/or progression of cancers, and related pathogenesis. Thus, knowing the specific viruses and microbial agents associated with a cancer type may provide insights into cause, diagnosis and treatment. We utilized a pan-pathogen array technology to identify the microbial signatures associated with triple negative breast cancer (TNBC). This technology detects low copy number and fragmented genomes extracted from formalin-fixed paraffin embedded archival tissues. The results, validated by PCR and sequencing, define a microbial signature present in TNBC tissue which was underrepresented in normal tissue. Hierarchical clustering analysis displayed two broad microbial signatures, one prevalent in bacteria and parasites and one prevalent in viruses. These signatures demonstrate a new paradigm in our understanding of the link between microorganisms and cancer, as causative or commensal in the tumor microenvironment and provide new diagnostic potential.

  15. A New Batch Verifying Scheme for Identifying Illegal Signatures

    Institute of Scientific and Technical Information of China (English)

    Adrian Atanasiu

    2013-01-01

    The concept of batch verifying multiple digital signatures is to find a method by which multiple digital signatures can be verified simultaneously in a lower time complexity than separately verifying all the signatures.In this article,we analyze the complexity of the batch verifying schemes defined by Li,Hwang and Chen in 2010,and propose a new batch verifying multiple digital signature scheme,in two variants:one for RSA-by completing the Harn's schema with an identifying illegal signatures algorithm,and the other adapted for a modified Elliptic Curve Digital Signature Algorithm protocol.

  16. Gene expression signatures for colorectal cancer microsatellite status and HNPCC

    DEFF Research Database (Denmark)

    Kruhøffer, M; Jensen, J L; Laiho, P;

    2005-01-01

    is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene expression......-deficient tumours into sporadic MSI and HNPCC cases, and validated this by a mathematical cross-validation approach. The demonstration that this two-step classification approach can identify MSI as well as HNPCC cases merits further gene expression studies to identify prognostic signatures....

  17. Autophagy-related prognostic signature for breast cancer.

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    Gu, Yunyan; Li, Pengfei; Peng, Fuduan; Zhang, Mengmeng; Zhang, Yuanyuan; Liang, Haihai; Zhao, Wenyuan; Qi, Lishuang; Wang, Hongwei; Wang, Chenguang; Guo, Zheng

    2016-03-01

    Autophagy is a process that degrades intracellular constituents, such as long-lived or damaged proteins and organelles, to buffer metabolic stress under starvation conditions. Deregulation of autophagy is involved in the progression of cancer. However, the predictive value of autophagy for breast cancer prognosis remains unclear. First, based on gene expression profiling, we found that autophagy genes were implicated in breast cancer. Then, using the Cox proportional hazard regression model, we detected autophagy prognostic signature for breast cancer in a training dataset. We identified a set of eight autophagy genes (BCL2, BIRC5, EIF4EBP1, ERO1L, FOS, GAPDH, ITPR1 and VEGFA) that were significantly associated with overall survival in breast cancer. The eight autophagy genes were assigned as a autophagy-related prognostic signature for breast cancer. Based on the autophagy-related signature, the training dataset GSE21653 could be classified into high-risk and low-risk subgroups with significantly different survival times (HR = 2.72, 95% CI = (1.91, 3.87); P = 1.37 × 10(-5)). Inactivation of autophagy was associated with shortened survival of breast cancer patients. The prognostic value of the autophagy-related signature was confirmed in the testing dataset GSE3494 (HR = 2.12, 95% CI = (1.48, 3.03); P = 1.65 × 10(-3)) and GSE7390 (HR = 1.76, 95% CI = (1.22, 2.54); P = 9.95 × 10(-4)). Further analysis revealed that the prognostic value of the autophagy signature was independent of known clinical prognostic factors, including age, tumor size, grade, estrogen receptor status, progesterone receptor status, ERBB2 status, lymph node status and TP53 mutation status. Finally, we demonstrated that the autophagy signature could also predict distant metastasis-free survival for breast cancer.

  18. Lung Cancer Gene Signatures and Clinical Perspectives

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    Ruprecht Kuner

    2013-12-01

    Full Text Available Microarrays have been used for more than two decades in preclinical research. The tumor transcriptional profiles were analyzed to select cancer-associated genes for in-deep functional characterization, to stratify tumor subgroups according to the histopathology or diverse clinical courses, and to assess biological and cellular functions behind these gene sets. In lung cancer—the main type of cancer causing mortality worldwide—biomarker research focuses on different objectives: the early diagnosis of curable tumor diseases, the stratification of patients with prognostic unfavorable operable tumors to assess the need for further therapy regimens, or the selection of patients for the most efficient therapies at early and late stages. In non-small cell lung cancer, gene and miRNA signatures are valuable to differentiate between the two main subtypes’ squamous and non-squamous tumors, a discrimination which has further implications for therapeutic schemes. Further subclassification within adenocarcinoma and squamous cell carcinoma has been done to correlate histopathological phenotype with disease outcome. Those tumor subgroups were assigned by diverse transcriptional patterns including potential biomarkers and therapy targets for future diagnostic and clinical applications. In lung cancer, none of these signatures have entered clinical routine for testing so far. In this review, the status quo of lung cancer gene signatures in preclinical and clinical research will be presented in the context of future clinical perspectives.

  19. Gene expression profiles identify inflammatory signatures in dendritic cells.

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    Anna Torri

    Full Text Available Dendritic cells (DCs constitute a heterogeneous group of antigen-presenting leukocytes important in activation of both innate and adaptive immunity. We studied the gene expression patterns of DCs incubated with reagents inducing their activation or inhibition. Total RNA was isolated from DCs and gene expression profiling was performed with oligonucleotide microarrays. Using a supervised learning algorithm based on Random Forest, we generated a molecular signature of inflammation from a training set of 77 samples. We then validated this molecular signature in a testing set of 38 samples. Supervised analysis identified a set of 44 genes that distinguished very accurately between inflammatory and non inflammatory samples. The diagnostic performance of the signature genes was assessed against an independent set of samples, by qRT-PCR. Our findings suggest that the gene expression signature of DCs can provide a molecular classification for use in the selection of anti-inflammatory or adjuvant molecules with specific effects on DC activity.

  20. Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.

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    Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2015-01-01

    Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin β4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.

  1. Differentially Expressed Genes and Signature Pathways of Human Prostate Cancer.

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    Jennifer S Myers

    Full Text Available Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The "transforming growth factor-beta signaling" and "Ran regulation of mitotic spindle formation" pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran for investigation in prostate cancer pathogenesis.

  2. Discovery of signature genes in gastric cancer associated with prognosis.

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    Zhao, X; Cai, H; Wang, X; Ma, L

    2016-01-01

    Gene expression profiles of gastric cancer (GC) were analyzed with bioinformatics tools to identify signature genes associated with prognosis. Four gene expression data sets (accession number: GSE2685, GSE30727, GSE38932 and GSE26253) were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened out using significance analysis of microarrays (SAM) algorithm. P-value 1 were set as the threshold. A co-expression network was constructed for the GC-related genes with package WGCNA of R. Modules were disclosed with WGCNA algorithm. Survival-related signature genes were screened out via COX single-variable regression.A total of 3210 GC-related genes were identified from the 3 data sets. Significantly enriched GO biological process terms included cell death, cell proliferation, apoptosis, response to hormone and phosphorylation. Pathways like viral carcinogenesis, metabolism, EBV viral infection, and PI3K-AKT signaling pathway were significantly over-represented in the DEGs. A gene co-expression network including 2414 genes was constructed, from which 7 modules were revealed. A total of 17 genes were identified as signature genes, such as DAB2, ALDH2, CD58, CITED2, BNIP3L, SLC43A2, FAU and COL5A1.Many signature genes associated with prognosis of GC were identified in present study, some of which have been implicated in the pathogenesis of GC. These findings could not only improve the knowledge about GC, but also provide clues for clinical treatments. PMID:26774142

  3. Combining gene signatures improves prediction of breast cancer survival.

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    Xi Zhao

    Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves

  4. A 6-gene signature identifies four molecular subgroups of neuroblastoma

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    Kogner Per

    2011-04-01

    Full Text Available Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB; Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples. Four distinct clusters were identified by Principal Components Analysis (PCA in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics.

  5. A 6-gene signature identifies four molecular subgroups of neuroblastoma

    LENUS (Irish Health Repository)

    Abel, Frida

    2011-04-14

    Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and\\/or dead of disease, p < 0.05, Fisher\\'s exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group\\'s specific characteristics.

  6. Using a stem cell-based signature to guide therapeutic selection in cancer.

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    Shats, Igor; Gatza, Michael L; Chang, Jeffrey T; Mori, Seiichi; Wang, Jialiang; Rich, Jeremy; Nevins, Joseph R

    2011-03-01

    Given the very substantial heterogeneity of most human cancers, it is likely that most cancer therapeutics will be active in only a small fraction of any population of patients. As such, the development of new therapeutics, coupled with methods to match a therapy with the individual patient, will be critical to achieving significant gains in disease outcome. One such opportunity is the use of expression signatures to identify key oncogenic phenotypes that can serve not only as biomarkers but also as a means of identifying therapeutic compounds that might specifically target these phenotypes. Given the potential importance of targeting tumors exhibiting a stem-like phenotype, we have developed an expression signature that reflects common biological aspects of various stem-like characteristics. The consensus stemness ranking (CSR) signature is upregulated in cancer stem cell-enriched samples at advanced tumor stages and is associated with poor prognosis in multiple cancer types. Using two independent computational approaches we utilized the CSR signature to identify clinically useful compounds that could target the CSR phenotype. In vitro assays confirmed selectivity of several predicted compounds including topoisomerase inhibitors and resveratrol towards breast cancer cell lines that exhibit a high-CSR phenotype. Importantly, the CSR signature could predict clinical response of breast cancer patients to a neoadjuvant regimen that included a CSR-specific agent. Collectively, these results suggest therapeutic opportunities to target the CSR phenotype in a relevant cohort of cancer patients. PMID:21169407

  7. Researchers Identify Early Sign of Pancreatic Cancer

    Science.gov (United States)

    ... of pancreatic cancer Researchers identify early sign of pancreatic cancer September 28, 2014 Tags: PancreaticCancer Brian Wolpin, MD ... discovered a sign of the early development of pancreatic cancer – an upsurge in certain amino acids that occurs ...

  8. Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures.

    Directory of Open Access Journals (Sweden)

    Thomas Karn

    Full Text Available BACKGROUND: Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes. METHODOLOGY/PRINCIPAL FINDINGS: We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases. CONCLUSIONS/SIGNIFICANCE: Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets and a smaller (n = 26 probesets prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71-9.48; P = 0.001 and 4.08 (95% CI 1.79-9.28; P = 0.001, respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588 to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures.

  9. Investigation of radiosensitivity gene signatures in cancer cell lines.

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    John S Hall

    Full Text Available Intrinsic radiosensitivity is an important factor underlying radiotherapy response, but there is no method for its routine assessment in human tumours. Gene signatures are currently being derived and some were previously generated by expression profiling the NCI-60 cell line panel. It was hypothesised that focusing on more homogeneous tumour types would be a better approach. Two cell line cohorts were used derived from cervix [n = 16] and head and neck [n = 11] cancers. Radiosensitivity was measured as surviving fraction following irradiation with 2 Gy (SF2 by clonogenic assay. Differential gene expression between radiosensitive and radioresistant cell lines (SF2 median was investigated using Affymetrix GeneChip Exon 1.0ST (cervix or U133A Plus2 (head and neck arrays. There were differences within cell line cohorts relating to tissue of origin reflected by expression of the stratified epithelial marker p63. Of 138 genes identified as being associated with SF2, only 2 (1.4% were congruent between the cervix and head and neck carcinoma cell lines (MGST1 and TFPI, and these did not partition the published NCI-60 cell lines based on SF2. There was variable success in applying three published radiosensitivity signatures to our cohorts. One gene signature, originally trained on the NCI-60 cell lines, did partially separate sensitive and resistant cell lines in all three cell line datasets. The findings do not confirm our hypothesis but suggest that a common transcriptional signature can reflect the radiosensitivity of tumours of heterogeneous origins.

  10. Identifying cancer genes from cancer mutation profiles by cancer functions

    Institute of Scientific and Technical Information of China (English)

    LI YanHui; GUO Zheng; PENG ChunFang; LIU Qing; MA WenCai; WANG Jing; YAO Chen; ZHANG Min; ZHU Jing

    2008-01-01

    It is of great importance to identify new cancer genes from the data of large scale genome screenings of gene mutations in cancers. Considering the alternations of some essential functions are indispensable for oncogenesis, we define them as cancer functions and select, as their approximations, a group of detailed functions in GO (Gene Ontology) highly enriched with known cancer genes. To evaluate the efficiency of using cancer functions as features to identify cancer genes, we define, in the screened genes, the known protein kinase cancer genes as gold standard positives and the other kinase genes as gold standard negatives. The results show that cancer associated functions are more efficient in identifying cancer genes than the selection pressure feature. Furthermore, combining cancer functions with the number of non-silent mutations can generate more reliable positive predictions. Finally, with precision 0.42, we suggest a list of 46 kinase genes as candidate cancer genes which are annotated to cancer functions and carry at least 3 non-silent mutations.

  11. Human cancer cells express Slug-based epithelial-mesenchymal transition gene expression signature obtained in vivo

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    Anastassiou Dimitris

    2011-12-01

    Full Text Available Abstract Background The biological mechanisms underlying cancer cell motility and invasiveness remain unclear, although it has been hypothesized that they involve some type of epithelial-mesenchymal transition (EMT. Methods We used xenograft models of human cancer cells in immunocompromised mice, profiling the harvested tumors separately with species-specific probes and computationally analyzing the results. Results Here we show that human cancer cells express in vivo a precise multi-cancer invasion-associated gene expression signature that prominently includes many EMT markers, among them the transcription factor Slug, fibronectin, and α-SMA. We found that human, but not mouse, cells express the signature and Slug is the only upregulated EMT-inducing transcription factor. The signature is also present in samples from many publicly available cancer gene expression datasets, suggesting that it is produced by the cancer cells themselves in multiple cancer types, including nonepithelial cancers such as neuroblastoma. Furthermore, we found that the presence of the signature in human xenografted cells was associated with a downregulation of adipocyte markers in the mouse tissue adjacent to the invasive tumor, suggesting that the signature is triggered by contextual microenvironmental interactions when the cancer cells encounter adipocytes, as previously reported. Conclusions The known, precise and consistent gene composition of this cancer mesenchymal transition signature, particularly when combined with simultaneous analysis of the adjacent microenvironment, provides unique opportunities for shedding light on the underlying mechanisms of cancer invasiveness as well as identifying potential diagnostic markers and targets for metastasis-inhibiting therapeutics.

  12. Prioritizing therapeutics for lung cancer: an integrative meta-analysis of cancer gene signatures and chemogenomic data.

    Directory of Open Access Journals (Sweden)

    Kristen Fortney

    2015-03-01

    Full Text Available Repurposing FDA-approved drugs with the aid of gene signatures of disease can accelerate the development of new therapeutics. A major challenge to developing reliable drug predictions is heterogeneity. Different gene signatures of the same disease or drug treatment often show poor overlap across studies, as a consequence of both biological and technical variability, and this can affect the quality and reproducibility of computational drug predictions. Existing algorithms for signature-based drug repurposing use only individual signatures as input. But for many diseases, there are dozens of signatures in the public domain. Methods that exploit all available transcriptional knowledge on a disease should produce improved drug predictions. Here, we adapt an established meta-analysis framework to address the problem of drug repurposing using an ensemble of disease signatures. Our computational pipeline takes as input a collection of disease signatures, and outputs a list of drugs predicted to consistently reverse pathological gene changes. We apply our method to conduct the largest and most systematic repurposing study on lung cancer transcriptomes, using 21 signatures. We show that scaling up transcriptional knowledge significantly increases the reproducibility of top drug hits, from 44% to 78%. We extensively characterize drug hits in silico, demonstrating that they slow growth significantly in nine lung cancer cell lines from the NCI-60 collection, and identify CALM1 and PLA2G4A as promising drug targets for lung cancer. Our meta-analysis pipeline is general, and applicable to any disease context; it can be applied to improve the results of signature-based drug repurposing by leveraging the large number of disease signatures in the public domain.

  13. A new molecular signature method for prediction of driver cancer pathways from transcriptional data.

    Science.gov (United States)

    Rykunov, Dmitry; Beckmann, Noam D; Li, Hui; Uzilov, Andrew; Schadt, Eric E; Reva, Boris

    2016-06-20

    Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways. PMID:27098033

  14. Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer

    International Nuclear Information System (INIS)

    Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients. The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways. We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different

  15. Multi-study integration of brain cancer transcriptomes reveals organ-level molecular signatures.

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    Jaeyun Sung

    Full Text Available We utilized abundant transcriptomic data for the primary classes of brain cancers to study the feasibility of separating all of these diseases simultaneously based on molecular data alone. These signatures were based on a new method reported herein--Identification of Structured Signatures and Classifiers (ISSAC--that resulted in a brain cancer marker panel of 44 unique genes. Many of these genes have established relevance to the brain cancers examined herein, with others having known roles in cancer biology. Analyses on large-scale data from multiple sources must deal with significant challenges associated with heterogeneity between different published studies, for it was observed that the variation among individual studies often had a larger effect on the transcriptome than did phenotype differences, as is typical. For this reason, we restricted ourselves to studying only cases where we had at least two independent studies performed for each phenotype, and also reprocessed all the raw data from the studies using a unified pre-processing pipeline. We found that learning signatures across multiple datasets greatly enhanced reproducibility and accuracy in predictive performance on truly independent validation sets, even when keeping the size of the training set the same. This was most likely due to the meta-signature encompassing more of the heterogeneity across different sources and conditions, while amplifying signal from the repeated global characteristics of the phenotype. When molecular signatures of brain cancers were constructed from all currently available microarray data, 90% phenotype prediction accuracy, or the accuracy of identifying a particular brain cancer from the background of all phenotypes, was found. Looking forward, we discuss our approach in the context of the eventual development of organ-specific molecular signatures from peripheral fluids such as the blood.

  16. Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability

    Directory of Open Access Journals (Sweden)

    van de Vijver Marc J

    2008-08-01

    Full Text Available Abstract Background Michiels et al. (Lancet 2005; 365: 488–92 employed a resampling strategy to show that the genes identified as predictors of prognosis from resamplings of a single gene expression dataset are highly variable. The genes most frequently identified in the separate resamplings were put forward as a 'gold standard'. On a higher level, breast cancer datasets collected by different institutions can be considered as resamplings from the underlying breast cancer population. The limited overlap between published prognostic signatures confirms the trend of signature instability identified by the resampling strategy. Six breast cancer datasets, totaling 947 samples, all measured on the Affymetrix platform, are currently available. This provides a unique opportunity to employ a substantial dataset to investigate the effects of pooling datasets on classifier accuracy, signature stability and enrichment of functional categories. Results We show that the resampling strategy produces a suboptimal ranking of genes, which can not be considered to be a 'gold standard'. When pooling breast cancer datasets, we observed a synergetic effect on the classification performance in 73% of the cases. We also observe a significant positive correlation between the number of datasets that is pooled, the validation performance, the number of genes selected, and the enrichment of specific functional categories. In addition, we have evaluated the support for five explanations that have been postulated for the limited overlap of signatures. Conclusion The limited overlap of current signature genes can be attributed to small sample size. Pooling datasets results in more accurate classification and a convergence of signature genes. We therefore advocate the analysis of new data within the context of a compendium, rather than analysis in isolation.

  17. Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling.

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    Sangkyun Lee

    Full Text Available Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable

  18. Robust Selection of Cancer Survival Signatures from High-Throughput Genomic Data Using Two-Fold Subsampling

    Science.gov (United States)

    Lee, Sangkyun; Rahnenführer, Jörg; Lang, Michel; De Preter, Katleen; Mestdagh, Pieter; Koster, Jan; Versteeg, Rogier; Stallings, Raymond L.; Varesio, Luigi; Asgharzadeh, Shahab; Schulte, Johannes H.; Fielitz, Kathrin; Schwermer, Melanie; Morik, Katharina; Schramm, Alexander

    2014-01-01

    Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature

  19. A Simple Model-Based Approach to Inferring and Visualizing Cancer Mutation Signatures.

    Science.gov (United States)

    Shiraishi, Yuichi; Tremmel, Georg; Miyano, Satoru; Stephens, Matthew

    2015-12-01

    Recent advances in sequencing technologies have enabled the production of massive amounts of data on somatic mutations from cancer genomes. These data have led to the detection of characteristic patterns of somatic mutations or "mutation signatures" at an unprecedented resolution, with the potential for new insights into the causes and mechanisms of tumorigenesis. Here we present new methods for modelling, identifying and visualizing such mutation signatures. Our methods greatly simplify mutation signature models compared with existing approaches, reducing the number of parameters by orders of magnitude even while increasing the contextual factors (e.g. the number of flanking bases) that are accounted for. This improves both sensitivity and robustness of inferred signatures. We also provide a new intuitive way to visualize the signatures, analogous to the use of sequence logos to visualize transcription factor binding sites. We illustrate our new method on somatic mutation data from urothelial carcinoma of the upper urinary tract, and a larger dataset from 30 diverse cancer types. The results illustrate several important features of our methods, including the ability of our new visualization tool to clearly highlight the key features of each signature, the improved robustness of signature inferences from small sample sizes, and more detailed inference of signature characteristics such as strand biases and sequence context effects at the base two positions 5' to the mutated site. The overall framework of our work is based on probabilistic models that are closely connected with "mixed-membership models" which are widely used in population genetic admixture analysis, and in machine learning for document clustering. We argue that recognizing these relationships should help improve understanding of mutation signature extraction problems, and suggests ways to further improve the statistical methods. Our methods are implemented in an R package pmsignature (https

  20. Evaluation of frozen tissue-derived prognostic gene expression signatures in FFPE colorectal cancer samples.

    Science.gov (United States)

    Zhu, Jing; Deane, Natasha G; Lewis, Keeli B; Padmanabhan, Chandrasekhar; Washington, M Kay; Ciombor, Kristen K; Timmers, Cynthia; Goldberg, Richard M; Beauchamp, R Daniel; Chen, Xi

    2016-01-01

    Defining molecular features that can predict the recurrence of colorectal cancer (CRC) for stage II-III patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed, Paraffin-Embedded (FFPE). NanoString nCounter® and Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) are the two platforms marketed for high-throughput gene expression profiling for FFPE samples. In this study, to evaluate the gene expression of frozen tissue-derived prognostic signatures in FFPE CRC samples, we evaluated the expression of 516 genes from published frozen tissue-derived prognostic signatures in 42 FFPE CRC samples measured by both platforms. Based on HTA platform-derived data, we identified both gene (99 individual genes, FDR FFPE tumor tissues to detect frozen tissue-derived prognostic gene expression signatures for CRC patients. PMID:27623752

  1. Hunting for the Signatures of Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Giorgi, Elena Edi [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-04-26

    This prompts the ambitious question: can we find common mutations across individuals with the same cancer? And how many of these mutational patterns that are common across individuals can we attribute to particular exposures or biological processes? Distinguished postdoctoral researcher Ludmil Alexandrov, from the Los Alamos National Laboratory, has been working on this problem since his he was a PhD student at the Wellcome Trust Sanger Institute.

  2. Clinical value of prognosis gene expression signatures in colorectal cancer: a systematic review.

    Directory of Open Access Journals (Sweden)

    Rebeca Sanz-Pamplona

    Full Text Available INTRODUCTION: The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets. METHODS: A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples. RESULTS: Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system. CONCLUSIONS: The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.

  3. Subtype-specific micro-RNA expression signatures in breast cancer progression.

    Science.gov (United States)

    Haakensen, Vilde D; Nygaard, Vegard; Greger, Liliana; Aure, Miriam R; Fromm, Bastian; Bukholm, Ida R K; Lüders, Torben; Chin, Suet-Feung; Git, Anna; Caldas, Carlos; Kristensen, Vessela N; Brazma, Alvis; Børresen-Dale, Anne-Lise; Hovig, Eivind; Helland, Åslaug

    2016-09-01

    Robust markers of invasiveness may help reduce the overtreatment of in situ carcinomas. Breast cancer is a heterogeneous disease and biological mechanisms for carcinogenesis vary between subtypes. Stratification by subtype is therefore necessary to identify relevant and robust signatures of invasive disease. We have identified microRNA (miRNA) alterations during breast cancer progression in two separate datasets and used stratification and external validation to strengthen the findings. We analyzed two separate datasets (METABRIC and AHUS) consisting of a total of 186 normal breast tissue samples, 18 ductal carcinoma in situ (DCIS) and 1,338 invasive breast carcinomas. Validation in a separate dataset and stratification by molecular subtypes based on immunohistochemistry, PAM50 and integrated cluster classifications were performed. We propose subtype-specific miRNA signatures of invasive carcinoma and a validated signature of DCIS. miRNAs included in the invasive signatures include downregulation of miR-139-5p in aggressive subtypes and upregulation of miR-29c-5p expression in the luminal subtypes. No miRNAs were differentially expressed in the transition from DCIS to invasive carcinomas on the whole, indicating the need for subtype stratification. A total of 27 miRNAs were included in our proposed DCIS signature. Significant alterations of expression included upregulation of miR-21-5p and the miR-200 family and downregulation of let-7 family members in DCIS samples. The signatures proposed here can form the basis for studies exploring DCIS samples with increased invasive potential and serum biomarkers for in situ and invasive breast cancer. PMID:27082076

  4. The prognostic value of temporal in vitro and in vivo derived hypoxia gene-expression signatures in breast cancer

    International Nuclear Information System (INIS)

    Background and purpose: Recent data suggest that in vitro and in vivo derived hypoxia gene-expression signatures have prognostic power in breast and possibly other cancers. However, both tumour hypoxia and the biological adaptation to this stress are highly dynamic. Assessment of time-dependent gene-expression changes in response to hypoxia may thus provide additional biological insights and assist in predicting the impact of hypoxia on patient prognosis. Materials and methods: Transcriptome profiling was performed for three cell lines derived from diverse tumour-types after hypoxic exposure at eight time-points, which include a normoxic time-point. Time-dependent sets of co-regulated genes were identified from these data. Subsequently, gene ontology (GO) and pathway analyses were performed. The prognostic power of these novel signatures was assessed in parallel with previous in vitro and in vivo derived hypoxia signatures in a large breast cancer microarray meta-dataset (n = 2312). Results: We identified seven recurrent temporal and two general hypoxia signatures. GO and pathway analyses revealed regulation of both common and unique underlying biological processes within these signatures. None of the new or previously published in vitro signatures consisting of hypoxia-induced genes were prognostic in the large breast cancer dataset. In contrast, signatures of repressed genes, as well as the in vivo derived signatures of hypoxia-induced genes showed clear prognostic power. Conclusions: Only a subset of hypoxia-induced genes in vitro demonstrates prognostic value when evaluated in a large clinical dataset. Despite clear evidence of temporal patterns of gene-expression in vitro, the subset of prognostic hypoxia regulated genes cannot be identified based on temporal pattern alone. In vivo derived signatures appear to identify the prognostic hypoxia induced genes. The prognostic value of hypoxia-repressed genes is likely a surrogate for the known importance of

  5. Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival

    Science.gov (United States)

    von Rundstedt, Friedrich-Carl; Rajapakshe, Kimal; Ma, Jing; Arnold, James M.; Gohlke, Jie; Putluri, Vasanta; Krishnapuram, Rashmi; Piyarathna, D. Badrajee; Lotan, Yair; Gödde, Daniel; Roth, Stephan; Störkel, Stephan; Levitt, Jonathan M.; Michailidis, George; Sreekumar, Arun; Lerner, Seth P.; Coarfa, Cristian; Putluri, Nagireddy

    2016-01-01

    Purpose We used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis gene signature would have a predictive value in independent cohorts of patients with bladder cancer. Materials and Methods Pathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differential metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. Enrichment of pathways and processes associated with the metabolic signature were determined using the GO (Gene Ontology) Database and MSigDB (Molecular Signature Database). Integration of metabolite alterations with transcriptome data from TCGA (The Cancer Genome Atlas) was done to identify the molecular signature of 30 metabolic genes. Available outcome data from TCGA portal were used to determine the association with survival. Results We identified 145 metabolites, of which analysis revealed 31 differential metabolites when comparing benign and tumor tissue samples. Using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Database we identified a total of 174 genes that correlated with the altered metabolic pathways involved. By integrating these genes with the transcriptomic data from the corresponding TCGA data set we identified a metabolic signature consisting of 30 genes. The signature was significant in its prediction of survival in 95 patients with a low signature score vs 282 with a high signature score (p = 0.0458). Conclusions Targeted mass spectrometry of bladder cancer is highly sensitive for detecting metabolic alterations. Applying transcriptome data allows for integration into larger data sets and identification of relevant metabolic pathways in bladder cancer progression. PMID:26802582

  6. Preclinical Assays for Identifying Cancer Chemopreventive Phytochemicals

    OpenAIRE

    Oyama, Takeru; Yasui, Yumiko; Sugie, Shigeyuki; Tanaka, Takuji

    2009-01-01

    Dietary factors influence carcinogenesis in a variety of tissues. The consumption of fruits and vegetables is associated with a decreased risk of several types of epithelial malignancies. In addition, there are interrelationships between diet, environmental factors, and genetics that can affect cancer risk. Potential chemopreventive agents against cancer development can be found among nutritive and/or nonnutritive compounds in inedible and edible plants. To identify potential cancer chemoprev...

  7. A novel data mining method to identify assay-specific signatures in functional genomic studies

    Directory of Open Access Journals (Sweden)

    Guidarelli Jack W

    2006-08-01

    Full Text Available Abstract Background: The highly dimensional data produced by functional genomic (FG studies makes it difficult to visualize relationships between gene products and experimental conditions (i.e., assays. Although dimensionality reduction methods such as principal component analysis (PCA have been very useful, their application to identify assay-specific signatures has been limited by the lack of appropriate methodologies. This article proposes a new and powerful PCA-based method for the identification of assay-specific gene signatures in FG studies. Results: The proposed method (PM is unique for several reasons. First, it is the only one, to our knowledge, that uses gene contribution, a product of the loading and expression level, to obtain assay signatures. The PM develops and exploits two types of assay-specific contribution plots, which are new to the application of PCA in the FG area. The first type plots the assay-specific gene contribution against the given order of the genes and reveals variations in distribution between assay-specific gene signatures as well as outliers within assay groups indicating the degree of importance of the most dominant genes. The second type plots the contribution of each gene in ascending or descending order against a constantly increasing index. This type of plots reveals assay-specific gene signatures defined by the inflection points in the curve. In addition, sharp regions within the signature define the genes that contribute the most to the signature. We proposed and used the curvature as an appropriate metric to characterize these sharp regions, thus identifying the subset of genes contributing the most to the signature. Finally, the PM uses the full dataset to determine the final gene signature, thus eliminating the chance of gene exclusion by poor screening in earlier steps. The strengths of the PM are demonstrated using a simulation study, and two studies of real DNA microarray data – a study of

  8. An epigenetic signature in peripheral blood predicts active ovarian cancer.

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    Andrew E Teschendorff

    Full Text Available BACKGROUND: Recent studies have shown that DNA methylation (DNAm markers in peripheral blood may hold promise as diagnostic or early detection/risk markers for epithelial cancers. However, to date no study has evaluated the diagnostic and predictive potential of such markers in a large case control cohort and on a genome-wide basis. PRINCIPAL FINDINGS: By performing genome-wide DNAm profiling of a large ovarian cancer case control cohort, we here demonstrate that active ovarian cancer has a significant impact on the DNAm pattern in peripheral blood. Specifically, by measuring the methylation levels of over 27,000 CpGs in blood cells from 148 healthy individuals and 113 age-matched pre-treatment ovarian cancer cases, we derive a DNAm signature that can predict the presence of active ovarian cancer in blind test sets with an AUC of 0.8 (95% CI (0.74-0.87. We further validate our findings in another independent set of 122 post-treatment cases (AUC = 0.76 (0.72-0.81. In addition, we provide evidence for a significant number of candidate risk or early detection markers for ovarian cancer. Furthermore, by comparing the pattern of methylation with gene expression data from major blood cell types, we here demonstrate that age and cancer elicit common changes in the composition of peripheral blood, with a myeloid skewing that increases with age and which is further aggravated in the presence of ovarian cancer. Finally, we show that most cancer and age associated methylation variability is found at CpGs located outside of CpG islands. SIGNIFICANCE: Our results underscore the potential of DNAm profiling in peripheral blood as a tool for detection or risk-prediction of epithelial cancers, and warrants further in-depth and higher CpG coverage studies to further elucidate this role.

  9. Identification of genomic signatures in circulating tumor cells from breast cancer.

    Science.gov (United States)

    Kanwar, Nisha; Hu, Pingzhao; Bedard, Philippe; Clemons, Mark; McCready, David; Done, Susan J

    2015-07-15

    Levels of circulating tumor cells (CTCs) in blood have prognostic value in early and metastatic breast cancer. CTCs also show varying degrees of concordance with molecular markers of primary tumors they originate from. It is expected that individual cells reflect the heterogeneity and evolution of tumor cells as they acquire new functions and differential responses to chemotherapy. However, a degree of commonality is also plausible, highlighting alterations that allow tumor cells to perform CTC-defining activities such as invasion and intravasation. Using a matched tumor-normal approach, we performed high-resolution copy number profiling of CTCs from breast cancer to identify occult changes occurring during progression to metastasis. We identified a signature of recurrent gain in CTCs, consisting of 90 minimal common regions (MCRs) of copy number gain. These were predominantly found across chromosome 19 and were identified at low frequencies (3-4%) in 787 primary breast carcinomas examined. CTC genomic signatures clustered into two groups independent of subtype: a dormancy-related signature with 16 MCRs (AKT2, PTEN, CADM2); and a tumor-aggressiveness related signature with 358 MCRs (ANGPTL4, BSG, MIR-373). There were two MCRs in common between the groups on 19q13 and 21q21, containing genes involved in resistance to anoikis, TGFβ-signaling and metastasis (TFF3, LTBP4, NUMBL). Furthermore, a region harboring the ERBB2 gene was gained in a majority of patients. Regions 20q13 and 15q24 were associated with distant metastasis. The distinctiveness of CTC signatures highlights cell populations with different functional or metastatic potential. Such novel targets could help to specifically identify and block dissemination.

  10. Lung Cancer Signatures in Plasma Based on Proteome Profiling of Mouse Tumor Models

    OpenAIRE

    Taguchi, Ayumu; Politi, Katerina; Pitteri, Sharon J.; Lockwood, William W; Faça, Vitor M.; Kelly-Spratt, Karen; Wong, Chee-Hong; Zhang, Qing; Chin, Alice; Park, Kwon-Sik; Goodman, Gary; Gazdar, Adi F.; Sage, Julien; Dinulescu, Daniela M.; Kucherlapati, Raju

    2011-01-01

    We investigated the potential of in-depth quantitative proteomics to reveal plasma protein signatures that reflect lung tumor biology. We compared plasma protein profiles of four mouse models of lung cancer with profiles of models of pancreatic, ovarian, colon, prostate, and breast cancer and two models of inflammation. A protein signature for Titf1/Nkx2-1, a known lineage-survival oncogene in lung cancer, was found in plasmas of mouse models of lung adenocarcinoma. An EGFR signature was foun...

  11. Discovery and validation of an INflammatory PROtein-driven GAstric cancer Signature (INPROGAS) using antibody microarray-based oncoproteomics

    OpenAIRE

    Puig-Costa, Manuel; Codina-Cazador, Antonio; Cortés-Pastoret, Elisabet; Oliveras-Ferraros, Cristina; Cufí, Sílvia; Flaquer, Sílvia; Llopis-Puigmarti, Francesca; Pujol-Amado, Eulalia; Corominas-Faja, Bruna; Cuyàs, Elisabet; Ortiz, Rosa; Lopez-Bonet, Eugeni; Queralt, Bernardo; Guardeño, Raquel; Martin-Castillo, Begoña

    2014-01-01

    This study aimed to improve gastric cancer (GC) diagnosis by identifying and validating an INflammatory PROtein-driven GAstric cancer Signature (hereafter INPROGAS) using low-cost affinity proteomics. The detection of 120 cytokines, 43 angiogenic factors, 41 growth factors, 40 inflammatory factors and 10 metalloproteinases was performed using commercially available human antibody microarray-based arrays. We identified 21 inflammation-related proteins (INPROGAS) with significant differences in...

  12. Diagnostic and prognostic utility of a DNA hypermethylated gene signature in prostate cancer.

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    Liang Kee Goh

    Full Text Available We aimed to identify a prostate cancer DNA hypermethylation microarray signature (denoted as PHYMA that differentiates prostate cancer from benign prostate hyperplasia (BPH, high from low-grade and lethal from non-lethal cancers. This is a non-randomized retrospective study in 111 local Asian men (87 prostate cancers and 24 BPH treated from 1995 to 2009 in our institution. Archival prostate epithelia were laser-capture microdissected and genomic DNA extracted and bisulfite-converted. Samples were profiled using Illumina GoldenGate Methylation microarray, with raw data processed by GenomeStudio. A classification model was generated using support vector machine, consisting of a 55-probe DNA methylation signature of 46 genes. The model was independently validated on an internal testing dataset which yielded cancer detection sensitivity and specificity of 95.3% and 100% respectively, with overall accuracy of 96.4%. Second validation on another independent western cohort yielded 89.8% sensitivity and 66.7% specificity, with overall accuracy of 88.7%. A PHYMA score was developed for each sample based on the state of methylation in the PHYMA signature. Increasing PHYMA score was significantly associated with higher Gleason score and Gleason primary grade. Men with higher PHYMA scores have poorer survival on univariate (p = 0.0038, HR = 3.89 and multivariate analyses when controlled for (i clinical stage (p = 0.055, HR = 2.57, and (ii clinical stage and Gleason score (p = 0.043, HR = 2.61. We further performed bisulfite genomic sequencing on 2 relatively unknown genes to demonstrate robustness of the assay results. PHYMA is thus a signature with high sensitivity and specificity for discriminating tumors from BPH, and has a potential role in early detection and in predicting survival.

  13. Selection signature analysis in Holstein cattle identified genes known to affect reproduction

    Science.gov (United States)

    Using direct comparison of 45,878 SNPs between a group of Holstein cattle unselected since 1964 and contemporary Holsteins that on average take 30 days longer for successful conception than the 1964 Holsteins, we conducted selection signature analyses to identify genomic regions associated with dair...

  14. Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

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    Liu Yufeng

    2011-01-01

    Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

  15. Identifying driver mutations in sequenced cancer genomes

    DEFF Research Database (Denmark)

    Raphael, Benjamin J; Dobson, Jason R; Oesper, Layla;

    2014-01-01

    High-throughput DNA sequencing is revolutionizing the study of cancer and enabling the measurement of the somatic mutations that drive cancer development. However, the resulting sequencing datasets are large and complex, obscuring the clinically important mutations in a background of errors, noise......, and random mutations. Here, we review computational approaches to identify somatic mutations in cancer genome sequences and to distinguish the driver mutations that are responsible for cancer from random, passenger mutations. First, we describe approaches to detect somatic mutations from high-throughput DNA...... sequencing data, particularly for tumor samples that comprise heterogeneous populations of cells. Next, we review computational approaches that aim to predict driver mutations according to their frequency of occurrence in a cohort of samples, or according to their predicted functional impact on protein...

  16. A population-based gene signature is predictive of breast cancer survival and chemoresponse

    OpenAIRE

    Rathnagiriswaran, Shruti; Wan, Ying-Wooi; Abraham, Jame; Castranova, Vincent; Qian, Yong; Guo, Nancy L.

    2010-01-01

    It remains a critical issue to improve the survival rate in patients with recurrent or metastatic breast cancer. This study sought to develop a prognostic scheme based on a 28-gene signature in a broad patient population, including those with advanced disease. Clinically annotated transcriptional profiles of 1,734 breast cancer patients were obtained to validate the 28-gene signature in prognostic categorization. The 28-gene signature generated significant patient stratification with regard t...

  17. Deep sequencing identifies ethnicity-specific bacterial signatures in the oral microbiome.

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    Matthew R Mason

    Full Text Available Oral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length polymorphism (t-RFLP and 16S pyrosequencing. Ethnicity-specific clustering of microbial communities was apparent in saliva and subgingival biofilms, and a machine-learning classifier was capable of identifying an individual's ethnicity from subgingival microbial signatures. The classifier identified African Americans with a 100% sensitivity and 74% specificity and Caucasians with a 50% sensitivity and 91% specificity. The data demonstrates a significant association between ethnic affiliation and the composition of the oral microbiome; to the extent that these microbial signatures appear to be capable of discriminating between ethnicities.

  18. Gene expression signature of fibroblast serum response predicts human cancer progression: similarities between tumors and wounds.

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    Howard Y Chang

    2004-02-01

    Full Text Available Cancer invasion and metastasis have been likened to wound healing gone awry. Despite parallels in cellular behavior between cancer progression and wound healing, the molecular relationships between these two processes and their prognostic implications are unclear. In this study, based on gene expression profiles of fibroblasts from ten anatomic sites, we identify a stereotyped gene expression program in response to serum exposure that appears to reflect the multifaceted role of fibroblasts in wound healing. The genes comprising this fibroblast common serum response are coordinately regulated in many human tumors, allowing us to identify tumors with gene expression signatures suggestive of active wounds. Genes induced in the fibroblast serum-response program are expressed in tumors by the tumor cells themselves, by tumor-associated fibroblasts, or both. The molecular features that define this wound-like phenotype are evident at an early clinical stage, persist during treatment, and predict increased risk of metastasis and death in breast, lung, and gastric carcinomas. Thus, the transcriptional signature of the response of fibroblasts to serum provides a possible link between cancer progression and wound healing, as well as a powerful predictor of the clinical course in several common carcinomas.

  19. Is there a genetic signature for liver metastasis in colorectal cancer?

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Even though liver metastasis accounts for the vast majority of cancer deaths in patients with colorectal cancer (CRC), fundamental questions about the molecular and cellular mechanisms of liver metastasis still remain unanswered. Determination of gene expression profiles by microarray technology has improved our knowledge of CRC molecular pathways. However, defined gene signatures are highly variable among studies. Expression profiles and molecular markers have been specifically linked to liver metastases mechanistic paths in CRC. However, to date, none of the identified signatures or molecular markers has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice. To obtain a genetic signature for liver metastasis in CRC, measures to improve reproducibility, to increase consistency, and to validate results need to be implemented. Alternatives to expression profiling with microarray technology are continuing to be used. In the recent past, many genes codifying for proteins that are directly or indirectly involved in adhesion, invasion, angiogenesis, survival and cell growth have been linked to mechanisms of liver metastases in CRC.

  20. Most random gene expression signatures are significantly associated with breast cancer outcome.

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    David Venet

    2011-10-01

    Full Text Available Bridging the gap between animal or in vitro models and human disease is essential in medical research. Researchers often suggest that a biological mechanism is relevant to human cancer from the statistical association of a gene expression marker (a signature of this mechanism, that was discovered in an experimental system, with disease outcome in humans. We examined this argument for breast cancer. Surprisingly, we found that gene expression signatures-unrelated to cancer-of the effect of postprandial laughter, of mice social defeat and of skin fibroblast localization were all significantly associated with breast cancer outcome. We next compared 47 published breast cancer outcome signatures to signatures made of random genes. Twenty-eight of them (60% were not significantly better outcome predictors than random signatures of identical size and 11 (23% were worst predictors than the median random signature. More than 90% of random signatures >100 genes were significant outcome predictors. We next derived a metagene, called meta-PCNA, by selecting the 1% genes most positively correlated with proliferation marker PCNA in a compendium of normal tissues expression. Adjusting breast cancer expression data for meta-PCNA abrogated almost entirely the outcome association of published and random signatures. We also found that, in the absence of adjustment, the hazard ratio of outcome association of a signature strongly correlated with meta-PCNA (R(2 = 0.9. This relation also applied to single-gene expression markers. Moreover, >50% of the breast cancer transcriptome was correlated with meta-PCNA. A corollary was that purging cell cycle genes out of a signature failed to rule out the confounding effect of proliferation. Hence, it is questionable to suggest that a mechanism is relevant to human breast cancer from the finding that a gene expression marker for this mechanism predicts human breast cancer outcome, because most markers do. The methods we

  1. A target based approach identifies genomic predictors of breast cancer patient response to chemotherapy

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    Hallett Robin M

    2012-05-01

    Full Text Available Abstract Background The efficacy of chemotherapy regimens in breast cancer patients is variable and unpredictable. Whether individual patients either achieve long-term remission or suffer recurrence after therapy may be dictated by intrinsic properties of their breast tumors including genetic lesions and consequent aberrant transcriptional programs. Global gene expression profiling provides a powerful tool to identify such tumor-intrinsic transcriptional programs, whose analyses provide insight into the underlying biology of individual patient tumors. For example, multi-gene expression signatures have been identified that can predict the likelihood of disease reccurrence, and thus guide patient prognosis. Whereas such prognostic signatures are being introduced in the clinical setting, similar signatures that predict sensitivity or resistance to chemotherapy are not currently clinically available. Methods We used gene expression profiling to identify genes that were co-expressed with genes whose transcripts encode the protein targets of commonly used chemotherapeutic agents. Results Here, we present target based expression indices that predict breast tumor response to anthracycline and taxane based chemotherapy. Indeed, these signatures were independently predictive of chemotherapy response after adjusting for standard clinic-pathological variables such as age, grade, and estrogen receptor status in a cohort of 488 breast cancer patients treated with adriamycin and taxotere/taxol. Conclusions Importantly, our findings suggest the practicality of developing target based indices that predict response to therapeutics, as well as highlight the possibility of using gene signatures to guide the use of chemotherapy during treatment of breast cancer patients.

  2. Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

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    Ghosh Debashis

    2004-12-01

    Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

  3. Suppression of Cancer Stemness p21-regulating mRNA and microRNA Signatures in Recurrent Ovarian Cancer Patient Samples

    LENUS (Irish Health Repository)

    Gallagher, Michael F

    2012-01-19

    Abstract Background Malignant ovarian disease is characterised by high rates of mortality due to high rates of recurrent chemoresistant disease. Anecdotal evidence indicates this may be due to chemoresistant properties of cancer stem cells (CSCs). However, our understanding of the role of CSCs in recurrent ovarian disease remains sparse. In this study we used gene microarrays and meta-analysis of our previously published microRNA (miRNA) data to assess the involvement of cancer stemness signatures in recurrent ovarian disease. Methods Microarray analysis was used to characterise early regulation events in an embryonal carcinoma (EC) model of cancer stemness. This was then compared to our previously published microarray data from a study of primary versus recurrent ovarian disease. In parallel, meta-analysis was used to identify cancer stemness miRNA signatures in tumor patient samples. Results Microarray analysis demonstrated a 90% difference between gene expression events involved in early regulation of differentiation in murine EC (mEC) and embryonic stem (mES) cells. This contrasts the known parallels between mEC and mES cells in the undifferentiated and well-differentiated states. Genelist comparisons identified a cancer stemness signature set of genes in primary versus recurrent data, a subset of which are known p53-p21 regulators. This signature is present in primary and recurrent or in primary alone but essentially never in recurrent tumors specifically. Meta-analysis of miRNA expression showed a much stronger cancer stemness signature within tumor samples. This miRNA signature again related to p53-p21 regulation and was expressed prominently in recurrent tumors. Our data indicate that the regulation of p53-p21 in ovarian cancer involves, at least partially, a cancer stemness component. Conclusion We present a p53-p21 cancer stemness signature model for ovarian cancer. We propose that this may, at least partially, differentially regulate the p53-p21

  4. Suppression of cancer stemness p21-regulating mRNA and microRNA signatures in recurrent ovarian cancer patient samples

    Directory of Open Access Journals (Sweden)

    Gallagher Michael F

    2012-01-01

    Full Text Available Abstract Background Malignant ovarian disease is characterised by high rates of mortality due to high rates of recurrent chemoresistant disease. Anecdotal evidence indicates this may be due to chemoresistant properties of cancer stem cells (CSCs. However, our understanding of the role of CSCs in recurrent ovarian disease remains sparse. In this study we used gene microarrays and meta-analysis of our previously published microRNA (miRNA data to assess the involvement of cancer stemness signatures in recurrent ovarian disease. Methods Microarray analysis was used to characterise early regulation events in an embryonal carcinoma (EC model of cancer stemness. This was then compared to our previously published microarray data from a study of primary versus recurrent ovarian disease. In parallel, meta-analysis was used to identify cancer stemness miRNA signatures in tumor patient samples. Results Microarray analysis demonstrated a 90% difference between gene expression events involved in early regulation of differentiation in murine EC (mEC and embryonic stem (mES cells. This contrasts the known parallels between mEC and mES cells in the undifferentiated and well-differentiated states. Genelist comparisons identified a cancer stemness signature set of genes in primary versus recurrent data, a subset of which are known p53-p21 regulators. This signature is present in primary and recurrent or in primary alone but essentially never in recurrent tumors specifically. Meta-analysis of miRNA expression showed a much stronger cancer stemness signature within tumor samples. This miRNA signature again related to p53-p21 regulation and was expressed prominently in recurrent tumors. Our data indicate that the regulation of p53-p21 in ovarian cancer involves, at least partially, a cancer stemness component. Conclusion We present a p53-p21 cancer stemness signature model for ovarian cancer. We propose that this may, at least partially, differentially regulate the p

  5. Novel recurrently mutated genes and a prognostic mutation signature in colorectal cancer

    Science.gov (United States)

    Yu, Jun; Wu, William K K; Li, Xiangchun; He, Jun; Li, Xiao-Xing; Ng, Simon S M; Yu, Chang; Gao, Zhibo; Yang, Jie; Li, Miao; Wang, Qiaoxiu; Liang, Qiaoyi; Pan, Yi; Tong, Joanna H; To, Ka F; Wong, Nathalie; Zhang, Ning; Chen, Jie; Lu, Youyong; Lai, Paul B S; Chan, Francis K L; Li, Yingrui; Kung, Hsiang-Fu; Yang, Huanming; Wang, Jun; Sung, Joseph J Y

    2015-01-01

    Background Characterisation of colorectal cancer (CRC) genomes by next-generation sequencing has led to the discovery of novel recurrently mutated genes. Nevertheless, genomic data has not yet been used for CRC prognostication. Objective To identify recurrent somatic mutations with prognostic significance in patients with CRC. Method Exome sequencing was performed to identify somatic mutations in tumour tissues of 22 patients with CRC, followed by validation of 187 recurrent and pathway-related genes using targeted capture sequencing in additional 160 cases. Results Seven significantly mutated genes, including four reported (APC, TP53, KRAS and SMAD4) and three novel recurrently mutated genes (CDH10, FAT4 and DOCK2), exhibited high mutation prevalence (6–14% for novel cancer genes) and higher-than-expected number of non-silent mutations in our CRC cohort. For prognostication, a five-gene-signature (CDH10, COL6A3, SMAD4, TMEM132D, VCAN) was devised, in which mutation(s) in one or more of these genes was significantly associated with better overall survival independent of tumor-node-metastasis (TNM) staging. The median survival time was 80.4 months in the mutant group versus 42.4 months in the wild type group (p=0.0051). The prognostic significance of this signature was successfully verified using the data set from the Cancer Genome Atlas study. Conclusions The application of next-generation sequencing has led to the identification of three novel significantly mutated genes in CRC and a mutation signature that predicts survival outcomes for stratifying patients with CRC independent of TNM staging. PMID:24951259

  6. Molecular signatures of prostate stem cells reveal novel signaling pathways and provide insights into prostate cancer.

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    Roy Blum

    Full Text Available BACKGROUND: The global gene expression profiles of adult and fetal murine prostate stem cells were determined to define common and unique regulators whose misexpression might play a role in the development of prostate cancer. METHODOLOGY/PRINCIPAL FINDINGS: A distinctive core of transcriptional regulators common to both fetal and adult primitive prostate cells was identified as well as molecules that are exclusive to each population. Elements common to fetal and adult prostate stem cells include expression profiles of Wnt, Shh and other pathways identified in stem cells of other organs, signatures of the aryl-hydrocarbon receptor, and up-regulation of components of the aldehyde dehydrogenase/retinoic acid receptor axis. There is also a significant lipid metabolism signature, marked by overexpression of lipid metabolizing enzymes and the presence of the binding motif for Srebp1. The fetal stem cell population, characterized by more rapid proliferation and self-renewal, expresses regulators of the cell cycle, such as E2f, Nfy, Tead2 and Ap2, at elevated levels, while adult stem cells show a signature in which TGF-beta has a prominent role. Finally, comparison of the signatures of primitive prostate cells with previously described profiles of human prostate tumors identified stem cell molecules and pathways with deregulated expression in prostate tumors including chromatin modifiers and the oncogene, Erg. CONCLUSIONS/SIGNIFICANCE: Our data indicate that adult prostate stem or progenitor cells may acquire characteristics of self-renewing primitive fetal prostate cells during oncogenesis and suggest that aberrant activation of components of prostate stem cell pathways may contribute to the development of prostate tumors.

  7. Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Klupczynska, Agnieszka; Swiatly, Agata; Hajduk, Joanna; Matysiak, Jan; Dyszkiewicz, Wojciech; Pawlak, Krystian; Kokot, Zenon J

    2016-01-01

    Due to high mortality rates of lung cancer, there is a need for identification of new, clinically useful markers, which improve detection of this tumor in early stage of disease. In the current study, serum peptide profiling was evaluated as a diagnostic tool for non-small cell lung cancer patients. The combination of the ZipTip technology with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the analysis of peptide pattern of cancer patients (n = 153) and control subjects (n = 63) was presented for the first time. Based on the observed significant differences between cancer patients and control subjects, the classification model was created, which allowed for accurate group discrimination. The model turned out to be robust enough to discriminate a new validation set of samples with satisfactory sensitivity and specificity. Two peptides from the diagnostic pattern for non-small cell lung cancer (NSCLC) were identified as fragments of C3 and fibrinogen α chain. Since ELISA test did not confirm significant differences in the expression of complement component C3, further study will involve a quantitative approach to prove clinical utility of the other proteins from the proposed multi-peptide cancer signature. PMID:27043541

  8. Evaluating predictive pharmacogenetic signatures of adverse events in colorectal cancer patients treated with fluoropyrimidines.

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    Barbara A Jennings

    Full Text Available The potential clinical utility of genetic markers associated with response to fluoropyrimidine treatment in colorectal cancer patients remains controversial despite extensive study. Our aim was to test the clinical validity of both novel and previously identified markers of adverse events in a broad clinical setting. We have conducted an observational pharmacogenetic study of early adverse events in a cohort study of 254 colorectal cancer patients treated with 5-fluorouracil or capecitabine. Sixteen variants of nine key folate (pharmacodynamic and drug metabolising (pharmacokinetic enzymes have been analysed as individual markers and/or signatures of markers. We found a significant association between TYMP S471L (rs11479 and early dose modifications and/or severe adverse events (adjusted OR = 2.02 [1.03; 4.00], p = 0.042, adjusted OR = 2.70 [1.23; 5.92], p = 0.01 respectively. There was also a significant association between these phenotypes and a signature of DPYD mutations (Adjusted OR = 3.96 [1.17; 13.33], p = 0.03, adjusted OR = 6.76 [1.99; 22.96], p = 0.002 respectively. We did not identify any significant associations between the individual candidate pharmacodynamic markers and toxicity. If a predictive test for early adverse events analysed the TYMP and DPYD variants as a signature, the sensitivity would be 45.5 %, with a positive predictive value of just 33.9 % and thus poor clinical validity. Most studies to date have been under-powered to consider multiple pharmacokinetic and pharmacodynamic variants simultaneously but this and similar individualised data sets could be pooled in meta-analyses to resolve uncertainties about the potential clinical utility of these markers.

  9. Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

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    Srivastava Mousami

    2012-11-01

    Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

  10. Drug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional Signatures.

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    Haeseung Lee

    Full Text Available An in silico chemical genomics approach is developed to predict drug repositioning (DR candidates for three types of cancer: glioblastoma, lung cancer, and breast cancer. It is based on a recent large-scale dataset of ~20,000 drug-induced expression profiles in multiple cancer cell lines, which provides i a global impact of transcriptional perturbation of both known targets and unknown off-targets, and ii rich information on drug's mode-of-action. First, the drug-induced expression profile is shown more effective than other information, such as the drug structure or known target, using multiple HTS datasets as unbiased benchmarks. Particularly, the utility of our method was robustly demonstrated in identifying novel DR candidates. Second, we predicted 14 high-scoring DR candidates solely based on expression signatures. Eight of the fourteen drugs showed significant anti-proliferative activity against glioblastoma; i.e., ivermectin, trifluridine, astemizole, amlodipine, maprotiline, apomorphine, mometasone, and nortriptyline. Our DR score strongly correlated with that of cell-based experimental results; the top seven DR candidates were positive, corresponding to an approximately 20-fold enrichment compared with conventional HTS. Despite diverse original indications and known targets, the perturbed pathways of active DR candidates show five distinct patterns that form tight clusters together with one or more known cancer drugs, suggesting common transcriptome-level mechanisms of anti-proliferative activity.

  11. Drug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional Signatures.

    Science.gov (United States)

    Lee, Haeseung; Kang, Seungmin; Kim, Wankyu

    2016-01-01

    An in silico chemical genomics approach is developed to predict drug repositioning (DR) candidates for three types of cancer: glioblastoma, lung cancer, and breast cancer. It is based on a recent large-scale dataset of ~20,000 drug-induced expression profiles in multiple cancer cell lines, which provides i) a global impact of transcriptional perturbation of both known targets and unknown off-targets, and ii) rich information on drug's mode-of-action. First, the drug-induced expression profile is shown more effective than other information, such as the drug structure or known target, using multiple HTS datasets as unbiased benchmarks. Particularly, the utility of our method was robustly demonstrated in identifying novel DR candidates. Second, we predicted 14 high-scoring DR candidates solely based on expression signatures. Eight of the fourteen drugs showed significant anti-proliferative activity against glioblastoma; i.e., ivermectin, trifluridine, astemizole, amlodipine, maprotiline, apomorphine, mometasone, and nortriptyline. Our DR score strongly correlated with that of cell-based experimental results; the top seven DR candidates were positive, corresponding to an approximately 20-fold enrichment compared with conventional HTS. Despite diverse original indications and known targets, the perturbed pathways of active DR candidates show five distinct patterns that form tight clusters together with one or more known cancer drugs, suggesting common transcriptome-level mechanisms of anti-proliferative activity. PMID:26954019

  12. Metabolic signatures of lung cancer in biofluids: NMR-based metabonomics of blood plasma.

    Science.gov (United States)

    Rocha, Cláudia M; Carrola, Joana; Barros, António S; Gil, Ana M; Goodfellow, Brian J; Carreira, Isabel M; Bernardo, João; Gomes, Ana; Sousa, Vitor; Carvalho, Lina; Duarte, Iola F

    2011-09-01

    In this work, the variations in the metabolic profile of blood plasma from lung cancer patients and healthy controls were investigated through NMR-based metabonomics, to assess the potential of this approach for lung cancer screening and diagnosis. PLS-DA modeling of CPMG spectra from plasma, subjected to Monte Carlo Cross Validation, allowed cancer patients to be discriminated from controls with sensitivity and specificity levels of about 90%. Relatively lower HDL and higher VLDL + LDL in the patients' plasma, together with increased lactate and pyruvate and decreased levels of glucose, citrate, formate, acetate, several amino acids (alanine, glutamine, histidine, tyrosine, valine), and methanol, could be detected. These changes were found to be present at initial disease stages and could be related to known cancer biochemical hallmarks, such as enhanced glycolysis, glutaminolysis, and gluconeogenesis, together with suppressed Krebs cycle and reduced lipid catabolism, thus supporting the hypothesis of a systemic metabolic signature for lung cancer. Despite the possible confounding influence of age, smoking habits, and other uncontrolled factors, these results indicate that NMR-based metabonomics of blood plasma can be useful as a screening tool to identify suspicious cases for subsequent, more specific radiological tests, thus contributing to improved disease management. PMID:21744875

  13. Signature-based small molecule screening identifies cytosine arabinoside as an EWS/FLI modulator in Ewing sarcoma.

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    Kimberly Stegmaier

    2007-04-01

    Full Text Available BACKGROUND: The presence of tumor-specific mutations in the cancer genome represents a potential opportunity for pharmacologic intervention to therapeutic benefit. Unfortunately, many classes of oncoproteins (e.g., transcription factors are not amenable to conventional small-molecule screening. Despite the identification of tumor-specific somatic mutations, most cancer therapy still utilizes nonspecific, cytotoxic drugs. One illustrative example is the treatment of Ewing sarcoma. Although the EWS/FLI oncoprotein, present in the vast majority of Ewing tumors, was characterized over ten years ago, it has never been exploited as a target of therapy. Previously, this target has been intractable to modulation with traditional small-molecule library screening approaches. Here we describe a gene expression-based approach to identify compounds that induce a signature of EWS/FLI attenuation. We hypothesize that screening small-molecule libraries highly enriched for FDA-approved drugs will provide a more rapid path to clinical application. METHODS AND FINDINGS: A gene expression signature for the EWS/FLI off state was determined with microarray expression profiling of Ewing sarcoma cell lines with EWS/FLI-directed RNA interference. A small-molecule library enriched for FDA-approved drugs was screened with a high-throughput, ligation-mediated amplification assay with a fluorescent, bead-based detection. Screening identified cytosine arabinoside (ARA-C as a modulator of EWS/FLI. ARA-C reduced EWS/FLI protein abundance and accordingly diminished cell viability and transformation and abrogated tumor growth in a xenograft model. Given the poor outcomes of many patients with Ewing sarcoma and the well-established ARA-C safety profile, clinical trials testing ARA-C are warranted. CONCLUSIONS: We demonstrate that a gene expression-based approach to small-molecule library screening can identify, for rapid clinical testing, candidate drugs that modulate previously

  14. Identifying microRNA/mRNA dysregulations in ovarian cancer

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    Miles Gregory D

    2012-03-01

    Full Text Available Abstract Background MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC, revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA. Methods TCGA Microarray data was normalized and samples whose class labels (tumour or normal were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA. Results We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from

  15. The proteomics of colorectal cancer: identification of a protein signature associated with prognosis.

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    Donna O'Dwyer

    Full Text Available Colorectal cancer is one of the commonest types of cancer and there is requirement for the identification of prognostic biomarkers. In this study protein expression profiles have been established for colorectal cancer and normal colonic mucosa by proteomics using a combination of two dimensional gel electrophoresis with fresh frozen sections of paired Dukes B colorectal cancer and normal colorectal mucosa (n = 28, gel image analysis and high performance liquid chromatography-tandem mass spectrometry. Hierarchical cluster analysis and principal components analysis showed that the protein expression profiles of colorectal cancer and normal colonic mucosa clustered into distinct patterns of protein expression. Forty-five proteins were identified as showing at least 1.5 times increased expression in colorectal cancer and the identity of these proteins was confirmed by liquid chromatography-tandem mass spectrometry. Fifteen proteins that showed increased expression were validated by immunohistochemistry using a well characterised colorectal cancer tissue microarray containing 515 primary colorectal cancer, 224 lymph node metastasis and 50 normal colonic mucosal samples. The proteins that showed the greatest degree of overexpression in primary colorectal cancer compared with normal colonic mucosa were heat shock protein 60 (p<0.001, S100A9 (p<0.001 and translationally controlled tumour protein (p<0.001. Analysis of proteins individually identified 14-3-3β as a prognostic biomarker (χ² = 6.218, p = 0.013, HR = 0.639, 95%CI 0.448-0.913. Hierarchical cluster analysis identified distinct phenotypes associated with survival and a two-protein signature consisting of 14-3-3β and aldehyde dehydrogenase 1 was identified as showing prognostic significance (χ² = 7.306, p = 0.007, HR = 0.504, 95%CI 0.303-0.838 and that remained independently prognostic (p = 0.01, HR = 0.416, 95%CI 0.208-0.829 in a multivariate model.

  16. Genetic signatures shared in embryonic liver development and liver cancer define prognostically relevant subgroups in HCC

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    Becker Diana

    2012-08-01

    Full Text Available Abstract Multiple activations of individual genes during embryonic liver and HCC development have repeatedly prompted speculations about conserved embryonic signatures driving cancer development. Recently, the emerging discussion on cancer stem cells and the appreciation that generally tumors may develop from progenitor cells of diverse stages of cellular differentiation has shed increasing light on the overlapping genetic signatures between embryonic liver development and HCC. However there is still a lack of systematic studies investigating this area. We therefore performed a comprehensive analysis of differentially regulated genetic signaling pathways in embryonic and liver cancer development and investigated their biological relevance. Genetic signaling pathways were investigated on several publically available genome wide microarray experiments on liver development and HCC. Differentially expressed genes were investigated for pathway enrichment or underrepresentation compared to KEGG annotated pathways by Fisher exact evaluation. The comparative analysis of enrichment and under representation of differentially regulated genes in liver development and HCC demonstrated a significant overlap between multiple pathways. Most strikingly we demonstrated a significant overlap not only in pathways expected to be relevant to both conditions such as cell cycle or apoptosis but also metabolic pathways associated with carbohydrate and lipid metabolism. Furthermore, we demonstrated the clinical significance of these findings as unsupervised clustering of HCC patients on the basis of these metabolic pathways displayed significant differences in survival. These results indicate that liver development and liver cancer share similar alterations in multiple genetic signaling pathways. Several pathways with markedly similar patterns of enrichment or underrepresentation of various regulated genes between liver development and HCC are of prognostic relevance in

  17. Predictive value of Sp1/Sp3/FLIP signature for prostate cancer recurrence.

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    Roble G Bedolla

    Full Text Available Prediction of prostate cancer prognosis is challenging and predictive biomarkers of recurrence remain elusive. Although prostate specific antigen (PSA has high sensitivity (90% at a PSA level of 4.0 ng/mL, its low specificity leads to many false positive results and considerable overtreatment of patients and its performance at lower ranges is poor. Given the histopathological and molecular heterogeneity of prostate cancer, we propose that a panel of markers will be a better tool than a single marker. We tested a panel of markers composed of the anti-apoptotic protein FLIP and its transcriptional regulators Sp1 and Sp3 using prostate tissues from 64 patients with recurrent and non-recurrent cancer who underwent radical prostatectomy as primary treatment for prostate cancer and were followed with PSA measurements for at least 5 years. Immunohistochemical staining for Sp1, Sp3, and FLIP was performed on these tissues and scored based on the proportion and intensity of staining. The predictive value of the FLIP/Sp1/Sp3 signature for clinical outcome (recurrence vs. non-recurrence was explored with logistic regression, and combinations of FLIP/Sp1/Sp3 and Gleason score were analyzed with a stepwise (backward and forward logistic model. The discrimination of the markers was identified by sensitivity-specificity analysis and the diagnostic value of FLIP/Sp1/Sp3 was determined using area under the curve (AUC for receiver operator characteristic curves. The AUCs for FLIP, Sp1, Sp3, and Gleason score for predicting PSA failure and non-failure were 0.71, 0.66, 0.68, and 0.76, respectively. However, this increased to 0.93 when combined. Thus, the "biomarker signature" of FLIP/Sp1/Sp3 combined with Gleason score predicted disease recurrence and stratified patients who are likely to benefit from more aggressive treatment.

  18. Treatment of Obstructive Sleep Apnea Alters Cancer-associated Transcriptional Signatures in Circulating Leukocytes

    Science.gov (United States)

    Gharib, Sina A.; Seiger, Ashley N.; Hayes, Amanda L.; Mehra, Reena; Patel, Sanjay R.

    2014-01-01

    Rationale: Obstructive sleep apnea (OSA) has been associated with a number of chronic disorders that may improve with effective therapy. However, the molecular pathways affected by continuous positive airway pressure (CPAP) treatment are largely unknown. We sought to assess the system-wide consequences of CPAP therapy by transcriptionally profiling peripheral blood leukocytes (PBLs). Methods: Subjects in whom severe OSA was diagnosed were treated with CPAP, and whole-genome expression measurement of PBLs was performed at baseline and following therapy. We used gene set enrichment analysis (GSEA) to identify pathways that were differentially enriched. Network analysis was then applied to highlight key drivers of processes influenced by CPAP. Results: Eighteen subjects with significant OSA underwent CPAP therapy and microarray analysis of their PBLs. Treatment with CPAP improved apnea-hypopnea index (AHI), daytime sleepiness, and blood pressure, but did not affect anthropometric measures. GSEA revealed a number of enriched gene sets, many of which were involved in neoplastic processes and displayed downregulated expression patterns in response to CPAP. Network analysis identified several densely connected genes that are important modulators of cancer and tumor growth. Conclusions: Effective therapy of OSA with CPAP is associated with alterations in circulating leukocyte gene expression. Functional enrichment and network analyses highlighted transcriptional suppression in cancer-related pathways, suggesting potentially novel mechanisms linking OSA with neoplastic signatures. Citation: Gharib SA; Seiger AN; Hayes AL; Mehra R; Patel SR. Treatment of obstructive sleep apnea alters cancer-associated transcriptional signatures in circulating leukocytes. SLEEP 2014;37(4):709-714. PMID:24688164

  19. An Alzheimer's Disease-Derived Biomarker Signature Identifies Parkinson's Disease Patients with Dementia.

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    Yosef Berlyand

    Full Text Available Biomarkers from multiple modalities have been shown to correlate with cognition in Parkinson's disease (PD and in Alzheimer's disease (AD. However, the relationships of these markers with each other, and the use of multiple markers in concert to predict an outcome of interest, are areas that are much less explored. Our objectives in this study were (1 to evaluate relationships among 17 biomarkers previously reported to associate with cognition in PD or AD and (2 to test performance of a five-biomarker classifier trained to recognize AD in identifying PD with dementia (PDD. To do this, we evaluated a cross-sectional cohort of PD patients (n = 75 across a spectrum of cognitive abilities. All PD participants had 17 baseline biomarkers from clinical, genetic, biochemical, and imaging modalities measured, and correlations among biomarkers were assessed by Spearman's rho and by hierarchical clustering. We found that internal correlation among all 17 candidate biomarkers was modest, showing a maximum pairwise correlation coefficient of 0.51. However, a five-marker subset panel derived from AD (CSF total tau, CSF phosphorylated tau, CSF amyloid beta 42, APOE genotype, and SPARE-AD imaging score discriminated cognitively normal PD patients vs. PDD patients with 80% accuracy, when employed in a classifier originally trained to recognize AD. Thus, an AD-derived biomarker signature may identify PDD patients with moderately high accuracy, suggesting mechanisms shared with AD in some PDD patients. Based on five measures readily obtained during life, this AD-derived signature may prove useful in identifying PDD patients most likely to respond to AD-based crossover therapies.

  20. Identification of Gene-Expression Signatures and Protein Markers for Breast Cancer Grading and Staging.

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    Fang Yao

    Full Text Available The grade of a cancer is a measure of the cancer's malignancy level, and the stage of a cancer refers to the size and the extent that the cancer has spread. Here we present a computational method for prediction of gene signatures and blood/urine protein markers for breast cancer grades and stages based on RNA-seq data, which are retrieved from the TCGA breast cancer dataset and cover 111 pairs of disease and matching adjacent noncancerous tissues with pathologists-assigned stages and grades. By applying a differential expression and an SVM-based classification approach, we found that 324 and 227 genes in cancer have their expression levels consistently up-regulated vs. their matching controls in a grade- and stage-dependent manner, respectively. By using these genes, we predicted a 9-gene panel as a gene signature for distinguishing poorly differentiated from moderately and well differentiated breast cancers, and a 19-gene panel as a gene signature for discriminating between the moderately and well differentiated breast cancers. Similarly, a 30-gene panel and a 21-gene panel are predicted as gene signatures for distinguishing advanced stage (stages III-IV from early stage (stages I-II cancer samples and for distinguishing stage II from stage I samples, respectively. We expect these gene panels can be used as gene-expression signatures for cancer grade and stage classification. In addition, of the 324 grade-dependent genes, 188 and 66 encode proteins that are predicted to be blood-secretory and urine-excretory, respectively; and of the 227 stage-dependent genes, 123 and 51 encode proteins predicted to be blood-secretory and urine-excretory, respectively. We anticipate that some combinations of these blood and urine proteins could serve as markers for monitoring breast cancer at specific grades and stages through blood and urine tests.

  1. Detecting robust gene signature through integrated analysis of multiple types of high-throughput data in liver cancer

    Institute of Scientific and Technical Information of China (English)

    Xin-yu ZHANG; Tian-tian LI; Xiang-jun LIU

    2007-01-01

    Aim: To investigate the robust gene signature in liver cancer, we applied an integrated approach to perform a joint analysis of a highly diverse collection of liver cancer genome-wide datasets, including genomic alterations and transcrip- tion profiles. Methods: 1-class Significance Analysis of Microarrays coupled with ranking score method were used to identify the robust gene signature in liver tumor tissue. Results: In total, 1 625 051 gene expression measurements from 16 public microarrays, 2 pairs of serial analyses of gene expression experiments, and 252 loss of heterozygosity reports obtained from 568 publications were used in this integrated study. The resulting robust gene signatures included 90 genes, which may be of great importance to liver cancer research. A system assessment analysis revealed that our integrative method had an accuracy of 92% and a correlation coefficient value of 0.88. Conclusion: The system assessment results indicated that our method had the ability of integrating the datasets from various types of sources, and eliciting more accurate results, as can be very useful in the study of liver cancer.

  2. Leptin, BMI, and a Metabolic Gene Expression Signature Associated with Clinical Outcome to VEGF Inhibition in Colorectal Cancer.

    Science.gov (United States)

    Pommier, Aurélien J C; Farren, Matthew; Patel, Bhavika; Wappett, Mark; Michopoulos, Filippos; Smith, Neil R; Kendrew, Jane; Frith, Jeremy; Huby, Russell; Eberlein, Catherine; Campbell, Hayley; Womack, Christopher; Smith, Paul D; Robertson, Jane; Morgan, Shethah; Critchlow, Susan E; Barry, Simon T

    2016-01-12

    VEGF (vascular endothelial growth factor) signaling inhibitors are widely used in different cancer types; however, patient selection remains a challenge. Analyses of samples from a phase III clinical trial in metastatic colorectal cancer testing chemotherapy versus chemotherapy with the small molecule VEGF receptors inhibitor cediranib identified circulating leptin levels, BMI, and a tumor metabolic and angiogenic gene expression signature associated with improved clinical outcome in patients treated with cediranib. Patients with a glycolytic and hypoxic/angiogenic profile were associated with increased benefit from cediranib, whereas patients with a high lipogenic, oxidative phosphorylation and serine biosynthesis signature did not gain benefit. These findings translated to pre-clinical tumor xenograft models where the same metabolic gene expression profiles were associated with in vivo sensitivity to cediranib as monotherapy. These findings suggest a link between patient physiology, tumor biology, and response to antiangiogenics, which may guide patient selection for VEGF therapy in the future. PMID:26626460

  3. Immunological network signatures of cancer progression and survival

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    Lavelle Timothy J

    2011-03-01

    Full Text Available Abstract Background The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors. Methods To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions. Results The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival. Conclusions The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding

  4. Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression.

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    Byungwoo Ryu

    Full Text Available BACKGROUND: Gene expression profiling has revolutionized our ability to molecularly classify primary human tumors and significantly enhanced the development of novel tumor markers and therapies; however, progress in the diagnosis and treatment of melanoma over the past 3 decades has been limited, and there is currently no approved therapy that significantly extends lifespan in patients with advanced disease. Profiling studies of melanoma to date have been inconsistent due to the heterogeneous nature of this malignancy and the limited availability of informative tissue specimens from early stages of disease. METHODOLOGY/PRINCIPLE FINDINGS: In order to gain an improved understanding of the molecular basis of melanoma progression, we have compared gene expression profiles from a series of melanoma cell lines representing discrete stages of malignant progression that recapitulate critical characteristics of the primary lesions from which they were derived. Here we describe the unsupervised hierarchical clustering of profiling data from melanoma cell lines and melanocytes. This clustering identifies two distinctive molecular subclasses of melanoma segregating aggressive metastatic tumor cell lines from less-aggressive primary tumor cell lines. Further analysis of expression signatures associated with melanoma progression using functional annotations categorized these transcripts into three classes of genes: 1 Upregulation of activators of cell cycle progression, DNA replication and repair (CDCA2, NCAPH, NCAPG, NCAPG2, PBK, NUSAP1, BIRC5, ESCO2, HELLS, MELK, GINS1, GINS4, RAD54L, TYMS, and DHFR, 2 Loss of genes associated with cellular adhesion and melanocyte differentiation (CDH3, CDH1, c-KIT, PAX3, CITED1/MSG-1, TYR, MELANA, MC1R, and OCA2, 3 Upregulation of genes associated with resistance to apoptosis (BIRC5/survivin. While these broad classes of transcripts have previously been implicated in the progression of melanoma and other malignancies, the

  5. Lipidomic Profiling of Adipose Tissue Reveals an Inflammatory Signature in Cancer-Related and Primary Lymphedema.

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    Lisa M Sedger

    Full Text Available Cancer-related and primary lymphedema (LE are associated with the production of adipose tissue (AT. Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained within the normal range, with no alterations in individual fatty acids. The lipidomic analysis also identified 275 lipid-based molecules, including triacylglycerides, diacylglycerides, fatty acids and phospholipids in AT oil and fat. Although the majority of lipid molecules were present in a similar abundance in LE and non-LE samples, there were several small changes: increased C20:5-containing triacylglycerides, reduced C10:0 caprinic and C24:1 nervonic acids. LE AT oil also contained a signature of increased cyclopropane-type fatty acids and inflammatory mediators arachidonic acid and ceramides. Interestingly C20:5 and C22:6 omega-3-type lipids are increased in LE AT, correlating with LE years. Hence, LE AT has a normal lipid profile containing a signature of inflammation and omega-3-lipids. It remains unclear, however, whether these differences reflect a small-scale global metabolic disturbance or effects within localised inflammatory foci.

  6. Lipidomic Profiling of Adipose Tissue Reveals an Inflammatory Signature in Cancer-Related and Primary Lymphedema

    Science.gov (United States)

    Sedger, Lisa M.; Tull, Dedreia L.; McConville, Malcolm J.; De Souza, David P.; Rupasinghe, Thusitha W. T.; Williams, Spencer J.; Dayalan, Saravanan; Lanzer, Daniel; Mackie, Helen; Lam, Thomas C.; Boyages, John

    2016-01-01

    Cancer-related and primary lymphedema (LE) are associated with the production of adipose tissue (AT). Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained within the normal range, with no alterations in individual fatty acids. The lipidomic analysis also identified 275 lipid-based molecules, including triacylglycerides, diacylglycerides, fatty acids and phospholipids in AT oil and fat. Although the majority of lipid molecules were present in a similar abundance in LE and non-LE samples, there were several small changes: increased C20:5-containing triacylglycerides, reduced C10:0 caprinic and C24:1 nervonic acids. LE AT oil also contained a signature of increased cyclopropane-type fatty acids and inflammatory mediators arachidonic acid and ceramides. Interestingly C20:5 and C22:6 omega-3-type lipids are increased in LE AT, correlating with LE years. Hence, LE AT has a normal lipid profile containing a signature of inflammation and omega-3-lipids. It remains unclear, however, whether these differences reflect a small-scale global metabolic disturbance or effects within localised inflammatory foci. PMID:27182733

  7. Lipidomic Profiling of Adipose Tissue Reveals an Inflammatory Signature in Cancer-Related and Primary Lymphedema.

    Science.gov (United States)

    Sedger, Lisa M; Tull, Dedreia L; McConville, Malcolm J; De Souza, David P; Rupasinghe, Thusitha W T; Williams, Spencer J; Dayalan, Saravanan; Lanzer, Daniel; Mackie, Helen; Lam, Thomas C; Boyages, John

    2016-01-01

    Cancer-related and primary lymphedema (LE) are associated with the production of adipose tissue (AT). Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained within the normal range, with no alterations in individual fatty acids. The lipidomic analysis also identified 275 lipid-based molecules, including triacylglycerides, diacylglycerides, fatty acids and phospholipids in AT oil and fat. Although the majority of lipid molecules were present in a similar abundance in LE and non-LE samples, there were several small changes: increased C20:5-containing triacylglycerides, reduced C10:0 caprinic and C24:1 nervonic acids. LE AT oil also contained a signature of increased cyclopropane-type fatty acids and inflammatory mediators arachidonic acid and ceramides. Interestingly C20:5 and C22:6 omega-3-type lipids are increased in LE AT, correlating with LE years. Hence, LE AT has a normal lipid profile containing a signature of inflammation and omega-3-lipids. It remains unclear, however, whether these differences reflect a small-scale global metabolic disturbance or effects within localised inflammatory foci. PMID:27182733

  8. Identifying signatures of natural selection in Tibetan and Andean populations using dense genome scan data.

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    Abigail Bigham

    2010-09-01

    Full Text Available High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2, shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association

  9. Gene-expression signature predicts postoperative recurrence in stage I non-small cell lung cancer patients.

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    Yan Lu

    Full Text Available About 30% stage I non-small cell lung cancer (NSCLC patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset -142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = -0.83, P85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients.

  10. Multi-tissue microarray analysis identifies a molecular signature of regeneration.

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    Sarah E Mercer

    Full Text Available The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine.

  11. Magnetic signature of overbank sediment in industry impacted floodplains identified by data mining methods

    Science.gov (United States)

    Chudaničová, Monika; Hutchinson, Simon M.

    2016-11-01

    Our study attempts to identify a characteristic magnetic signature of overbank sediments exhibiting anthropogenically induced magnetic enhancement and thereby to distinguish them from unenhanced sediments with weak magnetic background values, using a novel approach based on data mining methods, thus providing a mean of rapid pollution determination. Data were obtained from 539 bulk samples from vertical profiles through overbank sediment, collected on seven rivers in the eastern Czech Republic and three rivers in northwest England. k-Means clustering and hierarchical clustering methods, paired group (UPGMA) and Ward's method, were used to divide the samples to natural groups according to their attributes. Interparametric ratios: SIRM/χ; SIRM/ARM; and S-0.1T were chosen as attributes for analyses making the resultant model more widely applicable as magnetic concentration values can differ by two orders. Division into three clusters appeared to be optimal and corresponded to inherent clusters in the data scatter. Clustering managed to separate samples with relatively weak anthropogenically induced enhancement, relatively strong anthropogenically induced enhancement and samples lacking enhancement. To describe the clusters explicitly and thus obtain a discrete magnetic signature, classification rules (JRip method) and decision trees (J4.8 and Simple Cart methods) were used. Samples lacking anthropogenic enhancement typically exhibited an S-0.1T 0.5. Samples with relatively stronger anthropogenic enhancement were unequivocally distinguished from the samples with weaker enhancement by an SIRM/ARM > c. 150. Samples with SIRM/ARM in a range c. 126-150 were classified as relatively strongly enhanced when their SIRM/χ > 18 000 A m-1 and relatively less enhanced when their SIRM/χ 6 per cent from anthropogenically enhanced clusters as samples with natural magnetic enhancement. The characteristics of the clusters resulted mainly from the relationship between SIRM/ARM and

  12. MicroRNA signatures as clinical biomarkers in lung cancer

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    Markou A

    2015-05-01

    Full Text Available Athina Markou, Martha Zavridou, Evi S Lianidou Analysis of Circulating Tumor Cells, Lab of Analytical Chemistry, Department of Chemistry, University of Athens, Athens, Greece Abstract: Even if early lung cancer detection has been recently significantly improved, the invasive nature of current diagnostic procedures, and a relatively high percentage of false positives, is limiting the application of modern detection tools. The discovery and clinical evaluation of novel specific and robust non-invasive biomarkers for diagnosis of lung cancer at an early stage, as well as for better prognosis and prediction of therapy response, is very challenging. MicroRNAs (miRNAs can play an important role in the diagnosis and management of lung cancer patients, as important and reliable biomarkers for cancer detection and prognostic prediction, and even as promising as novel targets for cancer therapy. miRNAs are important in cancer pathogenesis, and deregulation of their expression levels has been detected not only in lung cancer but in many other human tumor types. Numerous studies strongly support the potential of miRNAs as biomarkers in non-small-cell lung cancer, and there is increasing evidence that altered miRNA expression is associated with tumor progression and survival. It is worth mentioning also that detection of miRNAs circulating in plasma or serum has enormous potential, because miRNAs serve as non-invasive biomarkers not only for the diagnosis and prognosis of the disease, but also as novel response and sensitivity predictors for cancer treatment. In this review, we summarize the current findings on the critical role of miRNAs in lung cancer tumorigenesis and highlight their potential as circulating biomarkers in lung cancer. Our review is based on papers that have been published after 2011, and includes the key words “miRNAs” and “lung cancer”. Keywords: non-small-cell lung carcinoma, miRNAs, tumor biomarkers, circulating miRNAs, liquid

  13. Transcriptional profiling of whole blood identifies a unique 5-gene signature for myelofibrosis and imminent myelofibrosis transformation.

    Directory of Open Access Journals (Sweden)

    Hans Carl Hasselbalch

    Full Text Available Identifying a distinct gene signature for myelofibrosis may yield novel information of the genes, which are responsible for progression of essential thrombocythemia and polycythemia vera towards myelofibrosis. We aimed at identifying a simple gene signature - composed of a few genes - which were selectively and highly deregulated in myelofibrosis patients. Gene expression microarray studies have been performed on whole blood from 69 patients with myeloproliferative neoplasms. Amongst the top-20 of the most upregulated genes in PMF compared to controls, we identified 5 genes (DEFA4, ELA2, OLFM4, CTSG, and AZU1, which were highly significantly deregulated in PMF only. None of these genes were significantly regulated in ET and PV patients. However, hierarchical cluster analysis showed that these genes were also highly expressed in a subset of patients with ET (n = 1 and PV (n = 4 transforming towards myelofibrosis and/or being featured by an aggressive phenotype. We have identified a simple 5-gene signature, which is uniquely and highly significantly deregulated in patients in transitional stages of ET and PV towards myelofibrosis and in patients with PMF only. Some of these genes are considered to be responsible for the derangement of bone marrow stroma in myelofibrosis. Accordingly, this gene-signature may reflect key processes in the pathogenesis and pathophysiology of myelofibrosis development.

  14. Gene signature of the post-Chernobyl papillary thyroid cancer

    International Nuclear Information System (INIS)

    Following the nuclear accidents in Chernobyl and later in Fukushima, the nuclear community has been faced with important issues concerning how to search for and diagnose biological consequences of low-dose internal radiation contamination. Although after the Chernobyl accident an increase in childhood papillary thyroid cancer (PTC) was observed, it is still not clear whether the molecular biology of PTCs associated with low-dose radiation exposure differs from that of sporadic PTC. We investigated tissue samples from 65 children/young adults with PTC using DNA microarray (Affymetrix, Human Genome U133 2.0 Plus) with the aim of identifying molecular differences between radiation-induced (exposed to Chernobyl radiation, ECR) and sporadic PTC. All participants were resident in the same region so that confounding factors related to genetics or environment were minimized. There were small but significant differences in the gene expression profiles between ECR and non-ECR PTC (global test, p < 0.01), with 300 differently expressed probe sets (p < 0.001) corresponding to 239 genes. Multifactorial analysis of variance showed that besides radiation exposure history, the BRAF mutation exhibited independent effects on the PTC expression profile; the histological subset and patient age at diagnosis had negligible effects. Ten genes (PPME1, HDAC11, SOCS7, CIC, THRA, ERBB2, PPP1R9A, HDGF, RAD51AP1, and CDK1) from the 19 investigated with quantitative RT-PCR were confirmed as being associated with radiation exposure in an independent, validation set of samples. Significant, but subtle, differences in gene expression in the post-Chernobyl PTC are associated with previous low-dose radiation exposure. (orig.)

  15. Gene signature of the post-Chernobyl papillary thyroid cancer

    Energy Technology Data Exchange (ETDEWEB)

    Handkiewicz-Junak, Daria; Rusinek, Dagmara; Oczko-Wojciechowska, Malgorzata; Kowalska, Malgorzata; Jarzab, Barbara [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Department of Nuclear Medicine and Endocrine Oncology, Gliwice (Poland); Swierniak, Michal [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Department of Nuclear Medicine and Endocrine Oncology, Gliwice (Poland); Medical University of Warsaw, Genomic Medicine, Department of General, Transplant and Liver Surgery, Warsaw (Poland); Dom, Genevieve; Maenhaut, Carine; Detours, Vincent [Universite libre de Bruxelles (ULB), Institute of Interdisciplinary Research, Bruxelles (Belgium); Unger, Kristian [Imperial College London Hammersmith Hospital, Human Cancer Studies Group, Division of Surgery and Cancer, London (United Kingdom); Helmholtz-Zentrum, Research Unit Radiation Cytogenetics, Munich (Germany); Bogdanova, Tetiana [Institute of Endocrinology and Metabolism, Kiev (Ukraine); Thomas, Geraldine [Imperial College London Hammersmith Hospital, Human Cancer Studies Group, Division of Surgery and Cancer, London (United Kingdom); Likhtarov, Ilya [Academy of Technological Sciences of Ukraine, Radiation Protection Institute, Kiev (Ukraine); Jaksik, Roman [Silesian University of Technology, Systems Engineering Group, Faculty of Automatic Control, Electronics and Informatics, Gliwice (Poland); Chmielik, Ewa [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Department of Tumour Pathology, Gliwice (Poland); Jarzab, Michal [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, IIIrd Department of Radiation Therapy, Gliwice (Poland); Swierniak, Andrzej [Silesian University of Technology, Department of Automatic Control, Gliwice (Poland)

    2016-07-15

    Following the nuclear accidents in Chernobyl and later in Fukushima, the nuclear community has been faced with important issues concerning how to search for and diagnose biological consequences of low-dose internal radiation contamination. Although after the Chernobyl accident an increase in childhood papillary thyroid cancer (PTC) was observed, it is still not clear whether the molecular biology of PTCs associated with low-dose radiation exposure differs from that of sporadic PTC. We investigated tissue samples from 65 children/young adults with PTC using DNA microarray (Affymetrix, Human Genome U133 2.0 Plus) with the aim of identifying molecular differences between radiation-induced (exposed to Chernobyl radiation, ECR) and sporadic PTC. All participants were resident in the same region so that confounding factors related to genetics or environment were minimized. There were small but significant differences in the gene expression profiles between ECR and non-ECR PTC (global test, p < 0.01), with 300 differently expressed probe sets (p < 0.001) corresponding to 239 genes. Multifactorial analysis of variance showed that besides radiation exposure history, the BRAF mutation exhibited independent effects on the PTC expression profile; the histological subset and patient age at diagnosis had negligible effects. Ten genes (PPME1, HDAC11, SOCS7, CIC, THRA, ERBB2, PPP1R9A, HDGF, RAD51AP1, and CDK1) from the 19 investigated with quantitative RT-PCR were confirmed as being associated with radiation exposure in an independent, validation set of samples. Significant, but subtle, differences in gene expression in the post-Chernobyl PTC are associated with previous low-dose radiation exposure. (orig.)

  16. Identifying patients at risk of emergency admission for colorectal cancer

    OpenAIRE

    Wallace, D.; Walker, K.; Kuryba, A; Finan, P; Scott, N.; Van Der Meulen, J.

    2014-01-01

    Background: Patients whose colorectal cancer is treated after an emergency admission tend to have late-stage cancer and a poor prognosis. We identified risk factors for an emergency admission by linking data from the National Bowel Cancer Audit (NBCA) and the English Hospital Episode Statistics (HES), an administrative database of all admissions to English National Health Service hospitals, which includes data on mode of admission. Methods: We identified all adults included in the NBCA with a...

  17. Deep Learning for Identifying Metastatic Breast Cancer

    OpenAIRE

    Wang, Dayong; Khosla, Aditya; Gargeya, Rishab; Irshad, Humayun; Beck, Andrew H

    2016-01-01

    The International Symposium on Biomedical Imaging (ISBI) held a grand challenge to evaluate computational systems for the automated detection of metastatic breast cancer in whole slide images of sentinel lymph node biopsies. Our team won both competitions in the grand challenge, obtaining an area under the receiver operating curve (AUC) of 0.925 for the task of whole slide image classification and a score of 0.7051 for the tumor localization task. A pathologist independently reviewed the same...

  18. Breast cancer genome and transcriptome integration implicates specific mutational signatures with immune cell infiltration

    NARCIS (Netherlands)

    M. Smid (Marcel); F.G. Rodriguez-Gonzalez (F. German); A.M. Sieuwerts (Anieta); R. Salgado (Roberto); W.J.C. Prager-van der Smissen (Wendy); Vlugt-Daane, M.V.D. (Michelle Van Der); A. van Galen (Anne); S. Nik-Zainal (Serena); J. Staaf (Johan); A.B. Brinkman (Arie B.); M.J. Vijver (Marc ); A.L. Richardson (Andrea); A. Fatima (Aquila); Berentsen, K. (Kim); A. Butler (Adam); S. Martin (Sandra); H. Davies (Helen); J.E.M.A. Debets (Reno); M.E.M.-V. Gelder (Marion E. Meijer-Van); C.H.M. van Deurzen (Carolien); Macgrogan, G. (Gaëtan); Van Den Eynden, G.G.G.M. (Gert G. G. M.); C.A. Purdie (Colin A.); A.M. Thompson (Alastair M.); C. Caldas (Carlos); P.N. Span (Paul); Simpson, P.T. (Peter T.); S. Lakhani (Sunil); S.J. van Laere (Steven); C. Desmedt (Christine); Ringnér, M. (Markus); Tommasi, S. (Stefania); Eyford, J. (Jorunn); A. Broeks (Annegien); A. Vincent-Salomon (Anne); Futreal, P.A. (P. Andrew); S. Knappskog (Stian); King, T. (Tari); G. Thomas (Gilles); Viari, A. (Alain); Langerød, A. (Anita); A.-L. Borresen-Dale (Anne-Lise); E. Birney (Ewan); H. Stunnenberg (Henk); M.R. Stratton (Michael); J.A. Foekens (John); J.W.M. Martens (John)

    2016-01-01

    textabstractA recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtype-specific aberrations show concordant expression changes for, for example, TP

  19. Leptin’s Pro-Angiogenic Signature in Breast Cancer

    Directory of Open Access Journals (Sweden)

    Gale Newman

    2013-09-01

    Full Text Available Obesity is linked to increased incidence of breast cancer. The precise causes and mechanisms of these morbid relationships are unknown. Contradictory data on leptin angiogenic actions have been published. However, accumulating evidence would suggest that leptin’s pro-angiogenic effects in cancer play an essential role in the disease. Leptin, the main adipokine secreted by adipose tissue, is also abnormally expressed together with its receptor (OB-R by breast cancer cells. Leptin induces proliferation and angiogenic differentiation of endothelial cells upregulates VEGF/VEGFR2 and transactivates VEGFR2 independent of VEGF. Leptin induces two angiogenic factors: IL-1 and Notch that can increase VEGF expression. Additionally, leptin induces the secretion and synthesis of proteases and adhesion molecules needed for the development of angiogenesis. Leptin’s paracrine actions can further affect stromal cells and tumor associated macrophages, which express OB-R and secrete VEGF and IL-1, respectively. A complex crosstalk between leptin, Notch and IL-1 (NILCO that induces VEGF/VEGFR2 is found in breast cancer. Leptin actions in tumor angiogenesis could amplify, be redundant and/or compensatory to VEGF signaling. Current failure of breast cancer anti-angiogenic therapies emphasizes the necessity of targeting the contribution of other pro-angiogenic factors in breast cancer. Leptin’s impact on tumor angiogenesis could be a novel target for breast cancer, especially in obese patients. However, more research is needed to establish the importance of leptin in tumor angiogenesis. This review is focused on updated information on how leptin could contribute to tumor angiogenesis.

  20. Leptin’s Pro-Angiogenic Signature in Breast Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez-Perez, Ruben Rene, E-mail: rgonzalez@msm.edu; Lanier, Viola; Newman, Gale [Department of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, 720 Westview Dr. SW., Atlanta, GA 30310 (United States)

    2013-09-06

    Obesity is linked to increased incidence of breast cancer. The precise causes and mechanisms of these morbid relationships are unknown. Contradictory data on leptin angiogenic actions have been published. However, accumulating evidence would suggest that leptin’s pro-angiogenic effects in cancer play an essential role in the disease. Leptin, the main adipokine secreted by adipose tissue, is also abnormally expressed together with its receptor (OB-R) by breast cancer cells. Leptin induces proliferation and angiogenic differentiation of endothelial cells upregulates VEGF/VEGFR2 and transactivates VEGFR2 independent of VEGF. Leptin induces two angiogenic factors: IL-1 and Notch that can increase VEGF expression. Additionally, leptin induces the secretion and synthesis of proteases and adhesion molecules needed for the development of angiogenesis. Leptin’s paracrine actions can further affect stromal cells and tumor associated macrophages, which express OB-R and secrete VEGF and IL-1, respectively. A complex crosstalk between leptin, Notch and IL-1 (NILCO) that induces VEGF/VEGFR2 is found in breast cancer. Leptin actions in tumor angiogenesis could amplify, be redundant and/or compensatory to VEGF signaling. Current failure of breast cancer anti-angiogenic therapies emphasizes the necessity of targeting the contribution of other pro-angiogenic factors in breast cancer. Leptin’s impact on tumor angiogenesis could be a novel target for breast cancer, especially in obese patients. However, more research is needed to establish the importance of leptin in tumor angiogenesis. This review is focused on updated information on how leptin could contribute to tumor angiogenesis.

  1. Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells

    Directory of Open Access Journals (Sweden)

    Kim Han

    2012-07-01

    Full Text Available Abstract Background In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy. Results Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2 Gy (SF2, range from 0 to 1 was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2. Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway. Conclusions Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that

  2. Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

    Directory of Open Access Journals (Sweden)

    Victor M. Bii

    2016-10-01

    Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.

  3. Computational approaches to identify functional genetic variants in cancer genomes

    Science.gov (United States)

    Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris; Ritchie, Graham R.S.; Creixell, Pau; Karchin, Rachel; Vazquez, Miguel; Fink, J. Lynn; Kassahn, Karin S.; Pearson, John V.; Bader, Gary; Boutros, Paul C.; Muthuswamy, Lakshmi; Ouellette, B.F. Francis; Reimand, Jüri; Linding, Rune; Shibata, Tatsuhiro; Valencia, Alfonso; Butler, Adam; Dronov, Serge; Flicek, Paul; Shannon, Nick B.; Carter, Hannah; Ding, Li; Sander, Chris; Stuart, Josh M.; Stein, Lincoln D.; Lopez-Bigas, Nuria

    2014-01-01

    The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor, but only a minority drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype. PMID:23900255

  4. Identifying Genes Responsible for Tamoxifen Resistance in Breast Cancer

    NARCIS (Netherlands)

    D. Meijer (Daniëlle)

    2008-01-01

    textabstractBreast cancer is one of the leading causes of death of women in western countries. It affects one out of eight females in the USA (1) and one out of nine females in The Netherlands (www.kankerregistratie.nl) during their lifetime. Many risk factors for breast cancer have been identified

  5. A gene expression and pre-mRNA splicing signature that marks the adenoma-adenocarcinoma progression in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Marine Pesson

    Full Text Available It is widely accepted that most colorectal cancers (CRCs arise from colorectal adenomas (CRAs, but transcriptomic data characterizing the progression from colorectal normal mucosa to adenoma, and then to adenocarcinoma are scarce. These transition steps were investigated using microarrays, both at the level of gene expression and alternative pre-mRNA splicing. Many genes and exons were abnormally expressed in CRAs, even more than in CRCs, as compared to normal mucosae. Known biological pathways involved in CRC were altered in CRA, but several new enriched pathways were also recognized, such as the complement and coagulation cascades. We also identified four intersectional transcriptional signatures that could distinguish CRAs from normal mucosae or CRCs, including a signature of 40 genes differentially deregulated in both CRA and CRC samples. A majority of these genes had been described in different cancers, including FBLN1 or INHBA, but only a few in CRC. Several of these changes were also observed at the protein level. In addition, 20% of these genes (i.e. CFH, CRYAB, DPT, FBLN1, ITIH5, NR3C2, SLIT3 and TIMP1 showed altered pre-mRNA splicing in CRAs. As a global variation occurring since the CRA stage, and maintained in CRC, the expression and splicing changes of this 40-gene set may mark the risk of cancer occurrence from analysis of CRA biopsies.

  6. Spectral signatures : a way to identify species and conditions of vegetables

    OpenAIRE

    Sandoval, José; Gor, Sergio; Ramallo, Jacqueline; Sfer, Ana; Colombo, Elisa; Vilaseca Ricart, Meritxell; Pujol Ramo, Jaume

    2012-01-01

    This work shows the results obtained by the application of suitable techniques for the acquisition and processing of spectral absorbance data of several vegetable species, allowing its identification –assignment of each spectral signature to one specific plant- which in turn allows the control of origin of products (foodstuffs or not) and their characteristics. Spectral measurements of absorbance were performed on samples of two sugarcane varieties and four citrus types (orange, lemo...

  7. Functional heterogeneity within the CD44 high human breast cancer stem cell-like compartment reveals a gene signature predictive of distant metastasis

    DEFF Research Database (Denmark)

    Leth-Larsen, Rikke; Terp, Mikkel Green; Christensen, Anne G;

    2012-01-01

    The CD44(hi) compartment in human breast cancer is enriched in tumor-initiating cells; however the functional heterogeneity within this subpopulation remains poorly defined. We used a triple-negative breast cancer cell line with a known bi-lineage phenotype to isolate and clone CD44(hi) single...... performed comparative quantitative proteomic and gene array analyses of these cells and identified potential novel markers of breast cancer cells with tumor-initiating features, such as LSR, RAB25, S100A14 and MUC1, as well as a novel 31-gene signature capable of predicting distant metastasis in cohorts...... of estrogen receptor-negative human breast cancers. These findings strongly favor functional heterogeneity in the breast cancer cell compartment and hold promise for further refinements of prognostic marker profiling. Our work confirms that, in addition to cancer stem cells with mesenchymal-like morphology...

  8. Rank-Based miRNA Signatures for Early Cancer Detection

    Directory of Open Access Journals (Sweden)

    Mario Lauria

    2014-01-01

    Full Text Available We describe a new signature definition and analysis method to be used as biomarker for early cancer detection. Our new approach is based on the construction of a reference map of transcriptional signatures of both healthy and cancer affected individuals using circulating miRNA from a large number of subjects. Once such a map is available, the diagnosis for a new patient can be performed by observing the relative position on the map of his/her transcriptional signature. To demonstrate its efficacy for this specific application we report the results of the application of our method to published datasets of circulating miRNA, and we quantify its performance compared to current state-of-the-art methods. A number of additional features make this method an ideal candidate for large-scale use, for example, as a mass screening tool for early cancer detection or for at-home diagnostics. Specifically, our method is minimally invasive (because it works well with circulating miRNA, it is robust with respect to lab-to-lab protocol variability and batch effects (it requires that only the relative ranking of expression value of miRNA in a profile be accurate not their absolute values, and it is scalable to a large number of subjects. Finally we discuss the need for HPC capability in a widespread application of our or similar methods.

  9. A putative biomarker signature for clinically effective AKT inhibition: correlation of in vitro, in vivo and clinical data identifies the importance of modulation of the mTORC1 pathway.

    Science.gov (United States)

    Cheraghchi-Bashi, Azadeh; Parker, Christine A; Curry, Ed; Salazar, Jean-Frederic; Gungor, Hatice; Saleem, Azeem; Cunnea, Paula; Rama, Nona; Salinas, Cristian; Mills, Gordon B; Morris, Shannon R; Kumar, Rakesh; Gabra, Hani; Stronach, Euan A

    2015-12-01

    Our identification of dysregulation of the AKT pathway in ovarian cancer as a platinum resistance specific event led to a comprehensive analysis of in vitro, in vivo and clinical behaviour of the AKT inhibitor GSK2141795. Proteomic biomarker signatures correlating with effects of GSK2141795 were developed using in vitro and in vivo models, well characterised for related molecular, phenotypic and imaging endpoints. Signatures were validated in temporally paired biopsies from patients treated with GSK2141795 in a clinical study. GSK2141795 caused growth-arrest as single agent in vitro, enhanced cisplatin-induced apoptosis in vitro and reduced tumour volume in combination with platinum in vivo. GSK2141795 treatment in vitro and in vivo resulted in ~50-90% decrease in phospho-PRAS40 and 20-80% decrease in fluoro-deoxyglucose (FDG) uptake. Proteomic analysis of GSK2141795 in vitro and in vivo identified a signature of pathway inhibition including changes in AKT and p38 phosphorylation and total Bim, IGF1R, AR and YB1 levels. In patient biopsies, prior to treatment with GSK2141795 in a phase 1 clinical trial, this signature was predictive of post-treatment changes in the response marker CA125. Development of this signature represents an opportunity to demonstrate the clinical importance of AKT inhibition for re-sensitisation of platinum resistant ovarian cancer to platinum. PMID:26497682

  10. Exome sequencing of contralateral breast cancer identifies metastatic disease.

    Science.gov (United States)

    Klevebring, Daniel; Lindberg, Johan; Rockberg, Julia; Hilliges, Camilla; Hall, Per; Sandberg, Maria; Czene, Kamila

    2015-06-01

    Women with contralateral breast cancer (CBC) have significantly worse prognosis compared to women with unilateral cancer. A possible explanation of the poor prognosis of patients with CBC is that in a subset of patients, the second cancer is not a new primary tumor but a metastasis of the first cancer that has potentially obtained aggressive characteristics through selection of treatment. Exome and whole-genome sequencing of solid tumors has previously been used to investigate the clonal relationship between primary tumors and metastases in several diseases. In order to assess the relationship between the first and the second cancer, we performed exome sequencing to identify somatic mutations in both first and second cancers, and compared paired normal tissue of 25 patients with metachronous CBC. For three patients, we identified shared somatic mutations indicating a common clonal origin thereby demonstrating that the second tumor is a metastasis of the first cancer, rather than a new primary cancer. Accordingly, these patients all developed distant metastasis within 3 years of the second diagnosis, compared with 7 out of 22 patients with non-shared somatic profiles. Genomic profiling of both tumors help the clinicians distinguish between true CBCs and subsequent metastases. PMID:25922084

  11. Protein signature for non-small cell lung cancer prognosis

    Science.gov (United States)

    Liu, Wei; Wu, Yong; Wang, Libo; Gao, Ling; Wang, Yingping; Liu, Xiaoliang; Zhang, Kai; Song, Jena; Wang, Hongxia; Bayer, Thomas A; Glaser, Laurel; Sun, Yezhou; Zhang, Weijia; Cutaia, Michael; Zhang, David Y; Ye, Fei

    2014-01-01

    Background: Current histopathological classification and TNM staging have limited accuracy in predicting survival and stratifying patients for appropriate treatment. The goal of the study is to determine whether the expression pattern of functionally important regulatory proteins can add additional values for more accurate classification and prognostication of non-small lung cancer (NSCLC). Methods: The expression of 108 proteins and phosphoproteins in 30 paired NSCLC samples were assessed using Protein Pathway Array (PPA). The differentially expressed proteins were further confirmed using a tissue microarray (TMA) containing 94 NSCLC samples and were correlated with clinical data and survival. Results: Twelve of 108 proteins (p-CREB(Ser133), p-ERK1/2(Thr202/Tyr204), Cyclin B1, p-PDK1(Ser241), CDK4, CDK2, HSP90, CDC2p34, β-catenin, EGFR, XIAP and PCNA) were selected to build the predictor to classify normal and tumor samples with 97% accuracy. Five proteins (CDC2p34, HSP90, XIAP, CDK4 and CREB) were confirmed to be differentially expressed between NSCLC (n=94) and benign lung tumor (n=19). Over-expression of CDK4 and HSP90 in tumors correlated with a favorable overall survival in all NSCLC patients and the over-expression of p-CREB(Ser133) and CREB in NSCLC correlated with a favorable survival in smokers and those with squamous cell carcinoma, respectively. Finally, the four proteins (CDK4, HSP90, p-CREB and CREB) were used to calculate the risk score of each individual patient with NSCLC to predict survival. Conclusion: In summary, our data demonstrated a broad disturbance of functionally important regulatory proteins in NSCLC and some of these can be selected as clinically useful biomarkers for diagnosis, classification and prognosis. PMID:24959380

  12. Identifying incident oral and pharyngeal cancer cases using Medicare claims

    Directory of Open Access Journals (Sweden)

    Mahnken Jonathan D

    2013-01-01

    Full Text Available Abstract Background Baseline and trend data for oral and pharyngeal cancer incidence is limited. A new algorithm was derived using the Surveillance, Epidemiology, and End Results (SEER-Medicare linked database to create an algorithm to identify incident cases of oral and pharyngeal cancer using Medicare claims. Methods Using a split-sample approach, Medicare claims’ procedure and diagnosis codes were used to generate a new algorithm to identify oral and pharyngeal cancer cases and validate its operating characteristics. Results The algorithm had high sensitivity (95% and specificity (97%, which varied little by age group, sex, and race and ethnicity. Conclusion Examples of the utility of this algorithm and its operating characteristics include using it to derive baseline and trend estimates of oral and pharyngeal cancer incidence. Such measures could be used to provide incidence estimates where they are lacking or to serve as comparator estimates for tumor registries.

  13. Evaluating localized prostate cancer and identifying candidates for focal therapy.

    Science.gov (United States)

    Sartor, A Oliver; Hricak, Hedvig; Wheeler, Thomas M; Coleman, Jonathan; Penson, David F; Carroll, Peter R; Rubin, Mark A; Scardino, Peter T

    2008-12-01

    Can focal therapy successfully control prostate cancer? Also, if so, which patients should be considered eligible? With limited data available from relatively few patients, these questions are difficult to answer. At this writing, the most likely candidates for focal therapy are patients with low-risk, small-volume tumors, located in 1 region or sector of the prostate, who would benefit from early intervention. The difficulty lies in reliably identifying these men. The larger number of cores obtained in each needle biopsy session has increased both the detection of prostate cancer and the potential risk of overtreating many patients whose cancers pose very little risk to life or health. Urologists typically perform at least a 12-core template biopsy. Although the debate continues about the optimal template, laterally and peripherally directed biopsies have been shown to improve the diagnostic yield. However, as many as 25% of tumors arise anteriorly and can be missed with peripherally directed techniques. Prostate cancer tends to be multifocal, even in its earliest stages. However, the secondary cancers are usually smaller and less aggressive than the index cancer. They appear similar to the incidental cancers found in cystoprostatectomy specimens and appear to have little effect on prognosis in surgical series. When a single focus of cancer is found in 1 core, physicians rightly suspect that more foci of cancer are present in the prostate. Assessing the risk in these patients is challenging when determined by the biopsy data alone. To predict the presence of a very low-risk or "indolent" cancer, nomograms have been developed to incorporate clinical stage, Gleason grade, prostate-specific antigen levels, and prostate volume, along with the quantitative analysis of the biopsy results. Transperineal "mapping" or "saturation" biopsies have been advocated to detect cancers missed or underestimated by previous transrectal biopsies. This approach could provide the

  14. ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

    Science.gov (United States)

    Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

    2015-01-01

    Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

  15. Computational approaches to identify functional genetic variants in cancer genomes

    DEFF Research Database (Denmark)

    Gonzalez-Perez, Abel; Mustonen, Ville; Reva, Boris;

    2013-01-01

    The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discu...... of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype....

  16. Gene signatures derived from a c-MET-driven liver cancer mouse model predict survival of patients with hepatocellular carcinoma.

    Directory of Open Access Journals (Sweden)

    Irena Ivanovska

    Full Text Available Biomarkers derived from gene expression profiling data may have a high false-positive rate and must be rigorously validated using independent clinical data sets, which are not always available. Although animal model systems could provide alternative data sets to formulate hypotheses and limit the number of signatures to be tested in clinical samples, the predictive power of such an approach is not yet proven. The present study aims to analyze the molecular signatures of liver cancer in a c-MET-transgenic mouse model and investigate its prognostic relevance to human hepatocellular carcinoma (HCC. Tissue samples were obtained from tumor (TU, adjacent non-tumor (AN and distant normal (DN liver in Tet-operator regulated (TRE human c-MET transgenic mice (n = 21 as well as from a Chinese cohort of 272 HBV- and 9 HCV-associated HCC patients. Whole genome microarray expression profiling was conducted in Affymetrix gene expression chips, and prognostic significances of gene expression signatures were evaluated across the two species. Our data revealed parallels between mouse and human liver tumors, including down-regulation of metabolic pathways and up-regulation of cell cycle processes. The mouse tumors were most similar to a subset of patient samples characterized by activation of the Wnt pathway, but distinctive in the p53 pathway signals. Of potential clinical utility, we identified a set of genes that were down regulated in both mouse tumors and human HCC having significant predictive power on overall and disease-free survival, which were highly enriched for metabolic functions. In conclusions, this study provides evidence that a disease model can serve as a possible platform for generating hypotheses to be tested in human tissues and highlights an efficient method for generating biomarker signatures before extensive clinical trials have been initiated.

  17. Plasma Proteomic Profiling in Hereditary Breast Cancer Reveals a BRCA1-Specific Signature: Diagnostic and Functional Implications.

    Directory of Open Access Journals (Sweden)

    Domenica Scumaci

    Full Text Available Breast cancer (BC is a leading cause of death among women. Among the major risk factors, an important role is played by familial history of BC. Germ-line mutations in BRCA1/2 genes account for most of the hereditary breast and/or ovarian cancers. Gene expression profiling studies have disclosed specific molecular signatures for BRCA1/2-related breast tumors as compared to sporadic cases, which might help diagnosis and clinical follow-up. Even though, a clear hallmark of BRCA1/2-positive BC is still lacking. Many diseases are correlated with quantitative changes of proteins in body fluids. Plasma potentially carries important information whose knowledge could help to improve early disease detection, prognosis, and response to therapeutic treatments. The aim of this study was to develop a comprehensive approach finalized to improve the recovery of specific biomarkers from plasma samples of subjects affected by hereditary BC.To perform this analysis, we used samples from patients belonging to highly homogeneous population previously reported. Depletion of high abundant plasma proteins, 2D gel analysis, liquid chromatography-tandem mass spectrometry (LC-MS/MS and bioinformatics analysis were used into an integrated approach to investigate tumor-specific changes in the plasma proteome of BC patients and healthy family members sharing the same BRCA1 gene founder mutation (5083del19, previously reported by our group, with the aim to identify specific signatures.The comparative analysis of the experimental results led to the identification of gelsolin as the most promising biomarker.Further analyses, performed using a panel of breast cancer cell lines, allowed us to further elucidate the signaling network that might modulate the expression of gelsolin in breast cancer.

  18. Raman spectroscopy identifies radiation response in human non-small cell lung cancer xenografts

    Science.gov (United States)

    Harder, Samantha J.; Isabelle, Martin; Devorkin, Lindsay; Smazynski, Julian; Beckham, Wayne; Brolo, Alexandre G.; Lum, Julian J.; Jirasek, Andrew

    2016-02-01

    External beam radiation therapy is a standard form of treatment for numerous cancers. Despite this, there are no approved methods to account for patient specific radiation sensitivity. In this report, Raman spectroscopy (RS) was used to identify radiation-induced biochemical changes in human non-small cell lung cancer xenografts. Chemometric analysis revealed unique radiation-related Raman signatures that were specific to nucleic acid, lipid, protein and carbohydrate spectral features. Among these changes was a dramatic shift in the accumulation of glycogen spectral bands for doses of 5 or 15 Gy when compared to unirradiated tumours. When spatial mapping was applied in this analysis there was considerable variability as we found substantial intra- and inter-tumour heterogeneity in the distribution of glycogen and other RS spectral features. Collectively, these data provide unique insight into the biochemical response of tumours, irradiated in vivo, and demonstrate the utility of RS for detecting distinct radiobiological responses in human tumour xenografts.

  19. Risk estimation of distant metastasis in node-negative, estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic expression signature

    Directory of Open Access Journals (Sweden)

    Gray Joe

    2008-11-01

    Full Text Available Abstract Background Given the large number of genes purported to be prognostic for breast cancer, it would be optimal if the genes identified are not confounded by the continuously changing systemic therapies. The aim of this study was to discover and validate a breast cancer prognostic expression signature for distant metastasis in untreated, early stage, lymph node-negative (N- estrogen receptor-positive (ER+ patients with extensive follow-up times. Methods 197 genes previously associated with metastasis and ER status were profiled from 142 untreated breast cancer subjects. A "metastasis score" (MS representing fourteen differentially expressed genes was developed and evaluated for its association with distant-metastasis-free survival (DMFS. Categorical risk classification was established from the continuous MS and further evaluated on an independent set of 279 untreated subjects. A third set of 45 subjects was tested to determine the prognostic performance of the MS in tamoxifen-treated women. Results A 14-gene signature was found to be significantly associated (p Conclusion The 14-gene signature is significantly associated with risk of distant metastasis. The signature has a predominance of proliferation genes which have prognostic significance above that of Ki-67 LI and may aid in prioritizing future mechanistic studies and therapeutic interventions.

  20. A gene sets approach for identifying prognostic gene signatures for outcome prediction

    OpenAIRE

    Kim Yong Sung; Kim Seon-Young

    2008-01-01

    Abstract Background Gene expression profiling is a promising approach to better estimate patient prognosis; however, there are still unresolved problems, including little overlap among similarly developed gene sets and poor performance of a developed gene set in other datasets. Results We applied a gene sets approach to develop a prognostic gene set from multiple gene expression datasets. By analyzing 12 independent breast cancer gene expression datasets comprising 1,756 tissues with 2,411 pr...

  1. A novel volume-age-KPS (VAK glioblastoma classification identifies a prognostic cognate microRNA-gene signature.

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    Pascal O Zinn

    Full Text Available BACKGROUND: Several studies have established Glioblastoma Multiforme (GBM prognostic and predictive models based on age and Karnofsky Performance Status (KPS, while very few studies evaluated the prognostic and predictive significance of preoperative MR-imaging. However, to date, there is no simple preoperative GBM classification that also correlates with a highly prognostic genomic signature. Thus, we present for the first time a biologically relevant, and clinically applicable tumor Volume, patient Age, and KPS (VAK GBM classification that can easily and non-invasively be determined upon patient admission. METHODS: We quantitatively analyzed the volumes of 78 GBM patient MRIs present in The Cancer Imaging Archive (TCIA corresponding to patients in The Cancer Genome Atlas (TCGA with VAK annotation. The variables were then combined using a simple 3-point scoring system to form the VAK classification. A validation set (N = 64 from both the TCGA and Rembrandt databases was used to confirm the classification. Transcription factor and genomic correlations were performed using the gene pattern suite and Ingenuity Pathway Analysis. RESULTS: VAK-A and VAK-B classes showed significant median survival differences in discovery (P = 0.007 and validation sets (P = 0.008. VAK-A is significantly associated with P53 activation, while VAK-B shows significant P53 inhibition. Furthermore, a molecular gene signature comprised of a total of 25 genes and microRNAs was significantly associated with the classes and predicted survival in an independent validation set (P = 0.001. A favorable MGMT promoter methylation status resulted in a 10.5 months additional survival benefit for VAK-A compared to VAK-B patients. CONCLUSIONS: The non-invasively determined VAK classification with its implication of VAK-specific molecular regulatory networks, can serve as a very robust initial prognostic tool, clinical trial selection criteria, and important step toward

  2. Identifying a few foot-and-mouth disease virus signature nucleotide strings for computational genotyping

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    Xu Lizhe

    2008-06-01

    Full Text Available Abstract Background Serotypes of the Foot-and-Mouth disease viruses (FMDVs were generally determined by biological experiments. The computational genotyping is not well studied even with the availability of whole viral genomes, due to uneven evolution among genes as well as frequent genetic recombination. Naively using sequence comparison for genotyping is only able to achieve a limited extent of success. Results We used 129 FMDV strains with known serotype as training strains to select as many as 140 most serotype-specific nucleotide strings. We then constructed a linear-kernel Support Vector Machine classifier using these 140 strings. Under the leave-one-out cross validation scheme, this classifier was able to assign correct serotype to 127 of these 129 strains, achieving 98.45% accuracy. It also assigned serotype correctly to an independent test set of 83 other FMDV strains downloaded separately from NCBI GenBank. Conclusion Computational genotyping is much faster and much cheaper than the wet-lab based biological experiments, upon the availability of the detailed molecular sequences. The high accuracy of our proposed method suggests the potential of utilizing a few signature nucleotide strings instead of whole genomes to determine the serotypes of novel FMDV strains.

  3. Interaction of cellular-localized signature modules in response to prostate cancer

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Rapid progress in high-throughput biotechnologies (e. g. microarrays) and exponential accumulation of gene functional knowledge makes it promising for systematic understanding of complex human diseases at the functional modules level. Current modular categorizations can be defined and selected more specifically and precisely in terms of both biological processes and cellular locations, aiming at uncovering the modular molecular networks highly relevant to cancers. Based on Gene Ontology, we identifed the functional modules enriched with differentially expressed genes and characterized by biological processes and specific cellular locations. Then, according to the ranking of the disease discriminating abilities of the pre-selected functional modules, we further defined and filtered signature modules which have higher relevance to the cancer under study. Applications of the proposed method to the analysis of a prostate cancer dataset revealed insightful biological modules.

  4. Discovery and validation of an INflammatory PROtein-driven GAstric cancer Signature (INPROGAS) using antibody microarray-based oncoproteomics

    Science.gov (United States)

    Puig-Costa, Manuel; Codina-Cazador, Antonio; Cortés-Pastoret, Elisabet; Oliveras-Ferraros, Cristina; Cufí, Sílvia; Flaquer, Sílvia; Llopis-Puigmarti, Francesca; Pujol-Amado, Eulalia; Corominas-Faja, Bruna; Cuyàs, Elisabet; Ortiz, Rosa; Lopez-Bonet, Eugeni; Queralt, Bernardo; Guardeño, Raquel; Martin-Castillo, Begoña; Roig, Josep; Joven, Jorge; Menendez, Javier A.

    2014-01-01

    This study aimed to improve gastric cancer (GC) diagnosis by identifying and validating an INflammatory PROtein-driven GAstric cancer Signature (hereafter INPROGAS) using low-cost affinity proteomics. The detection of 120 cytokines, 43 angiogenic factors, 41 growth factors, 40 inflammatory factors and 10 metalloproteinases was performed using commercially available human antibody microarray-based arrays. We identified 21 inflammation-related proteins (INPROGAS) with significant differences in expression between GC tissues and normal gastric mucosa in a discovery cohort of matched pairs (n=10) of tumor/normal gastric tissues. Ingenuity pathway analysis confirmed the “inflammatory response”, “cellular movement” and “immune cell trafficking” as the most overrepresented biofunctions within INPROGAS. Using an expanded independent validation cohort (n = 22), INPROGAS classified gastric samples as “GC” or “non-GC” with a sensitivity of 82% (95% CI 59-94) and a specificity of 73% (95% CI 49-89). The positive predictive value and negative predictive value in this validation cohort were 75% (95% CI 53-90) and 80% (95% CI 56-94), respectively. The positive predictive value and negative predictive value in this validation cohort were 75% (95% CI 53-90) and 80% (95% CI 56-94), respectively. Antibody microarray analyses of the GC-associated inflammatory proteome identified a 21-protein INPROGAS that accurately discriminated GC from noncancerous gastric mucosa. PMID:24722433

  5. Identifying molecular targets of lifestyle modifications in colon cancer prevention

    Directory of Open Access Journals (Sweden)

    Molly Marie Derry

    2013-05-01

    Full Text Available One in four deaths in the United States is cancer-related, and colorectal cancer (CRC is the second leading cause of cancer-associated deaths. Screening strategies are utilized but have not reduced disease incidence or mortality. In this regard, there is an interest in cancer preventive strategies focusing on lifestyle intervention, where specific etiologic factors involved in cancer initiation, promotion, and progression could be targeted. For example, exposure to dietary carcinogens, such as nitrosamines and polycyclic aromatic hydrocarbons influences colon carcinogenesis. Furthermore, dietary deficiencies could alter sensitivity to genetic damage and influence carcinogen metabolism contributing to CRC. High alcohol consumption increases the risk of mutations including the fact that acetaldehyde, an ethanol metabolite, is classified as a group 1 carcinogen. Tobacco smoke exposure is also a risk factor for cancer development; ~20% of CRCs are associated with smoking. Additionally, obese patients have a higher risk of cancer development, which is further supported by the fact that physical activity decreases CRC risk by 55%. Similarly, chronic inflammatory conditions also increase the risk of CRC development. Moreover, the circadian clock alters digestion and regulates other biochemical, physiological and behavioral processes that could positively influence CRC. Taken together, colon carcinogenesis involves a number of etiological factors, and therefore, to create effective preventive strategies, molecular targets need to be identified and beleaguered prior to disease progression. With this in mind, the following is a comprehensive review identifying downstream target proteins of the above lifestyle risk factors, which are modulated during colon carcinogenesis and could be targeted for CRC prevention by novel agents including phytochemicals.

  6. Gene Expression Signature TOPFOX Reflecting Chromosomal Instability Refines Prediction of Prognosis in Grade 2 Breast Cancer

    DEFF Research Database (Denmark)

    Szasz, A.; Li, Qiyuan; Sztupinszki, Z.;

    2011-01-01

    were diagnosed between 1999–2002 at the Budai MA´ V Hospital. 187 formalinfixed, paraffin-embedded breast cancer samples were included in the qPCR-based measurement of expression of AURKA, FOXM1, TOP2A and TPX2 genes. The expression of the genes were correlated to recurrencefree survival (RFS) and...... immunophenotypical characterization of tumours. 1509 samples were in silico analyzed for further validation of the selected genes. Results: Grade 1 and 3 groups were used as training set for the selected genes. The 4-gene signature was able to split grade 2 carcinomas (n = 62) into a good and a poor prognosis group...

  7. Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer.

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    Ning An

    Full Text Available Immune response-related genes play a major role in colorectal carcinogenesis by mediating inflammation or immune-surveillance evasion. Although remarkable progress has been made to investigate the underlying mechanism, the understanding of the complicated carcinogenesis process was enormously hindered by large-scale tumor heterogeneity. Development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. The association between embryonic development and carcinogenesis makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Here we proposed that the immune genes, responsible for intra-immune cooperativity disorientation (defined in this study as disruption of developmental expression correlation patterns during carcinogenesis, probably contain untapped prognostic resource of colorectal cancer. In this study, we determined the mRNA expression profile of 137 human biopsy samples, including samples from different stages of human colonic development, colorectal precancerous progression and colorectal cancer samples, among which 60 were also used to generate miRNA expression profile. We originally established Spearman correlation transition model to quantify the cooperativity disorientation associated with the transition from normal to precancerous to cancer tissue, in conjunction with miRNA-mRNA regulatory network and machine learning algorithm to identify genes with prognostic value. Finally, a 12-gene signature was extracted, whose prognostic value was evaluated using Kaplan-Meier survival analysis in five independent datasets. Using the log-rank test, the 12-gene signature was closely related to overall survival in four datasets (GSE17536, n = 177, p = 0.0054; GSE17537, n = 55, p = 0.0039; GSE39582, n = 562, p = 0.13; GSE39084, n = 70, p = 0.11, and significantly associated with disease

  8. Discovery of a Novel Immune Gene Signature with Profound Prognostic Value in Colorectal Cancer: A Model of Cooperativity Disorientation Created in the Process from Development to Cancer.

    Science.gov (United States)

    An, Ning; Shi, Xiaoyu; Zhang, Yueming; Lv, Ning; Feng, Lin; Di, Xuebing; Han, Naijun; Wang, Guiqi; Cheng, Shujun; Zhang, Kaitai

    2015-01-01

    Immune response-related genes play a major role in colorectal carcinogenesis by mediating inflammation or immune-surveillance evasion. Although remarkable progress has been made to investigate the underlying mechanism, the understanding of the complicated carcinogenesis process was enormously hindered by large-scale tumor heterogeneity. Development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. The association between embryonic development and carcinogenesis makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Here we proposed that the immune genes, responsible for intra-immune cooperativity disorientation (defined in this study as disruption of developmental expression correlation patterns during carcinogenesis), probably contain untapped prognostic resource of colorectal cancer. In this study, we determined the mRNA expression profile of 137 human biopsy samples, including samples from different stages of human colonic development, colorectal precancerous progression and colorectal cancer samples, among which 60 were also used to generate miRNA expression profile. We originally established Spearman correlation transition model to quantify the cooperativity disorientation associated with the transition from normal to precancerous to cancer tissue, in conjunction with miRNA-mRNA regulatory network and machine learning algorithm to identify genes with prognostic value. Finally, a 12-gene signature was extracted, whose prognostic value was evaluated using Kaplan-Meier survival analysis in five independent datasets. Using the log-rank test, the 12-gene signature was closely related to overall survival in four datasets (GSE17536, n = 177, p = 0.0054; GSE17537, n = 55, p = 0.0039; GSE39582, n = 562, p = 0.13; GSE39084, n = 70, p = 0.11), and significantly associated with disease-free survival in four

  9. Transcriptome Analysis Identifies the Dysregulation of Ultraviolet Target Genes in Human Skin Cancers

    Science.gov (United States)

    Shen, Yao; Kim, Arianna L.; Du, Rong; Liu, Liang

    2016-01-01

    Exposure to ultraviolet radiation (UVR) is a major risk factor for both melanoma and non-melanoma skin cancers. In addition to its mutagenic effect, UVR can also induce substantial transcriptional instability in skin cells affecting thousands of genes, including many cancer genes, suggesting that transcriptional instability may be another important etiological factor in skin photocarcinogenesis. In this study, we performed detailed transcriptomic profiling studies to characterize the kinetic changes in global gene expression in human keratinocytes exposed to different UVR conditions. We identified a subset of UV-responsive genes as UV signature genes (UVSGs) based on 1) conserved UV-responsiveness of this subset of genes among different keratinocyte lines; and 2) UV-induced persistent changes in their mRNA levels long after exposure. Interestingly, 11 of the UVSGs were shown to be critical to skin cancer cell proliferation and survival. Through computational Gene Set Enrichment Analysis, we demonstrated that a significant portion of the UVSGs were dysregulated in human skin squamous cell carcinomas, but not in other human malignancies. This highlights the potential and specificity of the UVSGs in clinical diagnosis of UV damage and stratification of skin cancer risk. PMID:27643989

  10. Transcriptome Analysis Identifies the Dysregulation of Ultraviolet Target Genes in Human Skin Cancers.

    Science.gov (United States)

    Shen, Yao; Kim, Arianna L; Du, Rong; Liu, Liang

    2016-01-01

    Exposure to ultraviolet radiation (UVR) is a major risk factor for both melanoma and non-melanoma skin cancers. In addition to its mutagenic effect, UVR can also induce substantial transcriptional instability in skin cells affecting thousands of genes, including many cancer genes, suggesting that transcriptional instability may be another important etiological factor in skin photocarcinogenesis. In this study, we performed detailed transcriptomic profiling studies to characterize the kinetic changes in global gene expression in human keratinocytes exposed to different UVR conditions. We identified a subset of UV-responsive genes as UV signature genes (UVSGs) based on 1) conserved UV-responsiveness of this subset of genes among different keratinocyte lines; and 2) UV-induced persistent changes in their mRNA levels long after exposure. Interestingly, 11 of the UVSGs were shown to be critical to skin cancer cell proliferation and survival. Through computational Gene Set Enrichment Analysis, we demonstrated that a significant portion of the UVSGs were dysregulated in human skin squamous cell carcinomas, but not in other human malignancies. This highlights the potential and specificity of the UVSGs in clinical diagnosis of UV damage and stratification of skin cancer risk. PMID:27643989

  11. The nanomechanical signature of liver cancer tissues and its molecular origin

    Science.gov (United States)

    Tian, Mengxin; Li, Yiran; Liu, Weiren; Jin, Lei; Jiang, Xifei; Wang, Xinyan; Ding, Zhenbin; Peng, Yuanfei; Zhou, Jian; Fan, Jia; Cao, Yi; Wang, Wei; Shi, Yinghong

    2015-07-01

    Patients with cirrhosis are at higher risk of developing hepatocellular carcinoma (HCC), the second most frequent cause of cancer-related deaths. Although HCC diagnosis based on conventional morphological characteristics serves as the ``gold standard'' in the clinic, there is a high demand for more convenient and effective diagnostic methods that employ new biophysical perspectives. Here, we show that the nanomechanical signature of liver tissue is directly correlated with the development of HCC. Using indentation-type atomic force microscopy (IT-AFM), we demonstrate that the lowest elasticity peak (LEP) in the Young's modulus distribution of surgically removed liver cancer tissues can serve as a mechanical fingerprint to evaluate the malignancy of liver cancer. Cirrhotic tissues shared the same LEP as normal tissues. However, a noticeable downward shift in the LEP was detected when the cirrhotic tissues progressed to a malignant state, making the tumor tissues more prone to microvascular invasion. Cell-level mechanistic studies revealed that the expression level of a Rho-family effector (mDia1) was consistent with the mechanical trend exhibited by the tissue. Our findings indicate that the mechanical profiles of liver cancer tissues directly varied with tumor progression, providing an additional platform for the future diagnosis of HCC.Patients with cirrhosis are at higher risk of developing hepatocellular carcinoma (HCC), the second most frequent cause of cancer-related deaths. Although HCC diagnosis based on conventional morphological characteristics serves as the ``gold standard'' in the clinic, there is a high demand for more convenient and effective diagnostic methods that employ new biophysical perspectives. Here, we show that the nanomechanical signature of liver tissue is directly correlated with the development of HCC. Using indentation-type atomic force microscopy (IT-AFM), we demonstrate that the lowest elasticity peak (LEP) in the Young's modulus

  12. Genetic tests to identify risk for breast cancer

    Science.gov (United States)

    Lynch, Julie; Venne, Vickie; Berse, Brygida

    2016-01-01

    Objectives To describe the currently available genetic tests that identify hereditary risk for breast cancer. Data sources Systematic review of scientific literature, clinical practice guidelines, and data published by test manufacturers. Conclusion Changes in gene patent laws and advances in sequencing technologies have resulted in rapid expansion of genetic testing. While BRCA1/2 are the most recognized genes linked to breast cancer, several laboratories now offer multi-gene panels to detect many risk-related mutations. Implication for Nursing Practice Genetic testing will be increasingly important in the prevention, diagnosis, and treatment of breast cancer. Oncology and advanced practice nurses need to understand risk factors, significance of various genetic tests, and patient counseling. PMID:25951739

  13. Integrated genomics identifies five medulloblastoma subtypes with distinct genetic profiles, pathway signatures and clinicopathological features.

    Directory of Open Access Journals (Sweden)

    Marcel Kool

    Full Text Available BACKGROUND: Medulloblastoma is the most common malignant brain tumor in children. Despite recent improvements in cure rates, prediction of disease outcome remains a major challenge and survivors suffer from serious therapy-related side-effects. Recent data showed that patients with WNT-activated tumors have a favorable prognosis, suggesting that these patients could be treated less intensively, thereby reducing the side-effects. This illustrates the potential benefits of a robust classification of medulloblastoma patients and a detailed knowledge of associated biological mechanisms. METHODS AND FINDINGS: To get a better insight into the molecular biology of medulloblastoma we established mRNA expression profiles of 62 medulloblastomas and analyzed 52 of them also by comparative genomic hybridization (CGH arrays. Five molecular subtypes were identified, characterized by WNT signaling (A; 9 cases, SHH signaling (B; 15 cases, expression of neuronal differentiation genes (C and D; 16 and 11 cases, respectively or photoreceptor genes (D and E; both 11 cases. Mutations in beta-catenin were identified in all 9 type A tumors, but not in any other tumor. PTCH1 mutations were exclusively identified in type B tumors. CGH analysis identified several fully or partly subtype-specific chromosomal aberrations. Monosomy of chromosome 6 occurred only in type A tumors, loss of 9q mostly occurred in type B tumors, whereas chromosome 17 aberrations, most common in medulloblastoma, were strongly associated with type C or D tumors. Loss of the inactivated X-chromosome was highly specific for female cases of type C, D and E tumors. Gene expression levels faithfully reflected the chromosomal copy number changes. Clinicopathological features significantly different between the 5 subtypes included metastatic disease and age at diagnosis and histology. Metastatic disease at diagnosis was significantly associated with subtypes C and D and most strongly with subtype E

  14. Occupation as a risk identifier for breast cancer.

    Science.gov (United States)

    Rubin, C H; Burnett, C A; Halperin, W E; Seligman, P J

    1993-01-01

    OBJECTIVES. Breast cancer mortality may be reduced if the disease is detected early through targeted screening programs. Current screening guidelines are based solely on a woman's age. Because working populations are accessible for intervention, occupational identification may be a way of helping to define and locate risk groups and target prevention. METHODS. We used a database consisting of 2.9 million occupationally coded death certificates collected from 23 states between 1979 and 1987 to calculate age-adjusted, race-specific proportionate mortality ratios for breast cancer according to occupation. We performed case-control analyses on occupational groups and on stratifications within the teaching profession. RESULTS. We found a number of significant associations between occupation and frequency of breast cancer. For example, white female professional, managerial, and clerical workers all had high proportions of breast cancer death. High rates of breast cancer in teachers were found in both proportionate mortality ratio and case-control analyses. CONCLUSIONS. These findings may serve as in an aid in the effective targeting of work-site health promotion programs. They suggest that occupationally coded mortality data can be a useful adjunct in the difficult task of identifying groups at risk of preventable disease. PMID:8363008

  15. Unique proteomic signature for radiation sensitive patients; a comparative study between normo-sensitive and radiation sensitive breast cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Skiöld, Sara [Center for Radiation Protection Research, Department of Molecular Biosciences, The Wernner-Gren Institute, Stockholm University, Stockholm (Sweden); Azimzadeh, Omid [Institute of Radiation Biology, German Research Center for Environmental Health, Helmholtz Zentrum München (Germany); Merl-Pham, Juliane [Research Unit Protein Science, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg (Germany); Naslund, Ingemar; Wersall, Peter; Lidbrink, Elisabet [Division of Radiotherapy, Radiumhemmet, Karolinska University Hospital, Stockholm (Sweden); Tapio, Soile [Institute of Radiation Biology, German Research Center for Environmental Health, Helmholtz Zentrum München (Germany); Harms-Ringdahl, Mats [Center for Radiation Protection Research, Department of Molecular Biosciences, The Wernner-Gren Institute, Stockholm University, Stockholm (Sweden); Haghdoost, Siamak, E-mail: Siamak.Haghdoost@su.se [Center for Radiation Protection Research, Department of Molecular Biosciences, The Wernner-Gren Institute, Stockholm University, Stockholm (Sweden)

    2015-06-15

    Highlights: • The unique protein expression profiles were found that separate radiosensitive from normal sensitive breast cancer patients. • The oxidative stress response, coagulation properties and acute phase response suggested to be the hallmarks of radiation sensitivity. - Abstract: Radiation therapy is a cornerstone of modern cancer treatment. Understanding the mechanisms behind normal tissue sensitivity is essential in order to minimize adverse side effects and yet to prevent local cancer reoccurrence. The aim of this study was to identify biomarkers of radiation sensitivity to enable personalized cancer treatment. To investigate the mechanisms behind radiation sensitivity a pilot study was made where eight radiation-sensitive and nine normo-sensitive patients were selected from a cohort of 2914 breast cancer patients, based on acute tissue reactions after radiation therapy. Whole blood was sampled and irradiated in vitro with 0, 1, or 150 mGy followed by 3 h incubation at 37 °C. The leukocytes of the two groups were isolated, pooled and protein expression profiles were investigated using isotope-coded protein labeling method (ICPL). First, leukocytes from the in vitro irradiated whole blood from normo-sensitive and extremely sensitive patients were compared to the non-irradiated controls. To validate this first study a second ICPL analysis comparing only the non-irradiated samples was conducted. Both approaches showed unique proteomic signatures separating the two groups at the basal level and after doses of 1 and 150 mGy. Pathway analyses of both proteomic approaches suggest that oxidative stress response, coagulation properties and acute phase response are hallmarks of radiation sensitivity supporting our previous study on oxidative stress response. This investigation provides unique characteristics of radiation sensitivity essential for individualized radiation therapy.

  16. Unique proteomic signature for radiation sensitive patients; a comparative study between normo-sensitive and radiation sensitive breast cancer patients

    International Nuclear Information System (INIS)

    Highlights: • The unique protein expression profiles were found that separate radiosensitive from normal sensitive breast cancer patients. • The oxidative stress response, coagulation properties and acute phase response suggested to be the hallmarks of radiation sensitivity. - Abstract: Radiation therapy is a cornerstone of modern cancer treatment. Understanding the mechanisms behind normal tissue sensitivity is essential in order to minimize adverse side effects and yet to prevent local cancer reoccurrence. The aim of this study was to identify biomarkers of radiation sensitivity to enable personalized cancer treatment. To investigate the mechanisms behind radiation sensitivity a pilot study was made where eight radiation-sensitive and nine normo-sensitive patients were selected from a cohort of 2914 breast cancer patients, based on acute tissue reactions after radiation therapy. Whole blood was sampled and irradiated in vitro with 0, 1, or 150 mGy followed by 3 h incubation at 37 °C. The leukocytes of the two groups were isolated, pooled and protein expression profiles were investigated using isotope-coded protein labeling method (ICPL). First, leukocytes from the in vitro irradiated whole blood from normo-sensitive and extremely sensitive patients were compared to the non-irradiated controls. To validate this first study a second ICPL analysis comparing only the non-irradiated samples was conducted. Both approaches showed unique proteomic signatures separating the two groups at the basal level and after doses of 1 and 150 mGy. Pathway analyses of both proteomic approaches suggest that oxidative stress response, coagulation properties and acute phase response are hallmarks of radiation sensitivity supporting our previous study on oxidative stress response. This investigation provides unique characteristics of radiation sensitivity essential for individualized radiation therapy

  17. Toward the Autism Motor Signature: Gesture patterns during smart tablet gameplay identify children with autism.

    Science.gov (United States)

    Anzulewicz, Anna; Sobota, Krzysztof; Delafield-Butt, Jonathan T

    2016-01-01

    Autism is a developmental disorder evident from infancy. Yet, its clinical identification requires expert diagnostic training. New evidence indicates disruption to motor timing and integration may underpin the disorder, providing a potential new computational marker for its early identification. In this study, we employed smart tablet computers with touch-sensitive screens and embedded inertial movement sensors to record the movement kinematics and gesture forces made by 37 children 3-6 years old with autism and 45 age- and gender-matched children developing typically. Machine learning analysis of the children's motor patterns identified autism with up to 93% accuracy. Analysis revealed these patterns consisted of greater forces at contact and with a different distribution of forces within a gesture, and gesture kinematics were faster and larger, with more distal use of space. These data support the notion disruption to movement is core feature of autism, and demonstrate autism can be computationally assessed by fun, smart device gameplay. PMID:27553971

  18. A systems biology pipeline identifies new immune and disease related molecular signatures and networks in human cells during microgravity exposure

    Science.gov (United States)

    Mukhopadhyay, Sayak; Saha, Rohini; Palanisamy, Anbarasi; Ghosh, Madhurima; Biswas, Anupriya; Roy, Saheli; Pal, Arijit; Sarkar, Kathakali; Bagh, Sangram

    2016-05-01

    Microgravity is a prominent health hazard for astronauts, yet we understand little about its effect at the molecular systems level. In this study, we have integrated a set of systems-biology tools and databases and have analysed more than 8000 molecular pathways on published global gene expression datasets of human cells in microgravity. Hundreds of new pathways have been identified with statistical confidence for each dataset and despite the difference in cell types and experiments, around 100 of the new pathways are appeared common across the datasets. They are related to reduced inflammation, autoimmunity, diabetes and asthma. We have identified downregulation of NfκB pathway via Notch1 signalling as new pathway for reduced immunity in microgravity. Induction of few cancer types including liver cancer and leukaemia and increased drug response to cancer in microgravity are also found. Increase in olfactory signal transduction is also identified. Genes, based on their expression pattern, are clustered and mathematically stable clusters are identified. The network mapping of genes within a cluster indicates the plausible functional connections in microgravity. This pipeline gives a new systems level picture of human cells under microgravity, generates testable hypothesis and may help estimating risk and developing medicine for space missions.

  19. Signatures of selection identify loci associated with fat tail in sheep.

    Science.gov (United States)

    Moioli, B; Pilla, F; Ciani, E

    2015-10-01

    Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most challenging applications of dense marker panels in animal genetics. In this study, a genomewide scan using approximately 50,000 SNP was performed in an attempt to identify genomic regions associated with fat deposition in sheep, the importance of this not only being limited to livestock facing future climate changes but also for elucidating the physiology of lipid metabolism. The genotyping results obtained with the Ovine SNP50K BeadChip in 2 fat tail breeds were compared with those obtained in 13 thin tail breeds. Direct sequencing of the annotated genes located in proximity to the markers with opposite allele frequency in thin tail vs. fat tail sheep gave additional SNP of interest. To further confirm the results of the genomewide scan, we genotyped the SNP within these genes in the 2 groups of sheep. A missense mutation in the gene, with different allele frequency in the 2 groups, was detected. The results indicated and as the most probable genes involved in the fat tail phenotype.

  20. Deep RNA profiling identified CLOCK and molecular clock genes as pathophysiological signatures in collagen VI myopathy.

    Science.gov (United States)

    Scotton, Chiara; Bovolenta, Matteo; Schwartz, Elena; Falzarano, Maria Sofia; Martoni, Elena; Passarelli, Chiara; Armaroli, Annarita; Osman, Hana; Rodolico, Carmelo; Messina, Sonia; Pegoraro, Elena; D'Amico, Adele; Bertini, Enrico; Gualandi, Francesca; Neri, Marcella; Selvatici, Rita; Boffi, Patrizia; Maioli, Maria Antonietta; Lochmüller, Hanns; Straub, Volker; Bushby, Katherine; Castrignanò, Tiziana; Pesole, Graziano; Sabatelli, Patrizia; Merlini, Luciano; Braghetta, Paola; Bonaldo, Paolo; Bernardi, Paolo; Foley, Reghan; Cirak, Sebahattin; Zaharieva, Irina; Muntoni, Francesco; Capitanio, Daniele; Gelfi, Cecilia; Kotelnikova, Ekaterina; Yuryev, Anton; Lebowitz, Michael; Zhang, Xiping; Hodge, Brian A; Esser, Karyn A; Ferlini, Alessandra

    2016-04-15

    Collagen VI myopathies are genetic disorders caused by mutations in collagen 6 A1, A2 and A3 genes, ranging from the severe Ullrich congenital muscular dystrophy to the milder Bethlem myopathy, which is recapitulated by collagen-VI-null (Col6a1(-/-)) mice. Abnormalities in mitochondria and autophagic pathway have been proposed as pathogenic causes of collagen VI myopathies, but the link between collagen VI defects and these metabolic circuits remains unknown. To unravel the expression profiling perturbation in muscles with collagen VI myopathies, we performed a deep RNA profiling in bothCol6a1(-/-)mice and patients with collagen VI pathology. The interactome map identified common pathways suggesting a previously undetected connection between circadian genes and collagen VI pathology. Intriguingly,Bmal1(-/-)(also known asArntl) mice, a well-characterized model displaying arrhythmic circadian rhythms, showed profound deregulation of the collagen VI pathway and of autophagy-related genes. The involvement of circadian rhythms in collagen VI myopathies is new and links autophagy and mitochondrial abnormalities. It also opens new avenues for therapies of hereditary myopathies to modulate the molecular clock or potential gene-environment interactions that might modify muscle damage pathogenesis. PMID:26945058

  1. Deep RNA profiling identified CLOCK and molecular clock genes as pathophysiological signatures in collagen VI myopathy.

    Science.gov (United States)

    Scotton, Chiara; Bovolenta, Matteo; Schwartz, Elena; Falzarano, Maria Sofia; Martoni, Elena; Passarelli, Chiara; Armaroli, Annarita; Osman, Hana; Rodolico, Carmelo; Messina, Sonia; Pegoraro, Elena; D'Amico, Adele; Bertini, Enrico; Gualandi, Francesca; Neri, Marcella; Selvatici, Rita; Boffi, Patrizia; Maioli, Maria Antonietta; Lochmüller, Hanns; Straub, Volker; Bushby, Katherine; Castrignanò, Tiziana; Pesole, Graziano; Sabatelli, Patrizia; Merlini, Luciano; Braghetta, Paola; Bonaldo, Paolo; Bernardi, Paolo; Foley, Reghan; Cirak, Sebahattin; Zaharieva, Irina; Muntoni, Francesco; Capitanio, Daniele; Gelfi, Cecilia; Kotelnikova, Ekaterina; Yuryev, Anton; Lebowitz, Michael; Zhang, Xiping; Hodge, Brian A; Esser, Karyn A; Ferlini, Alessandra

    2016-04-15

    Collagen VI myopathies are genetic disorders caused by mutations in collagen 6 A1, A2 and A3 genes, ranging from the severe Ullrich congenital muscular dystrophy to the milder Bethlem myopathy, which is recapitulated by collagen-VI-null (Col6a1(-/-)) mice. Abnormalities in mitochondria and autophagic pathway have been proposed as pathogenic causes of collagen VI myopathies, but the link between collagen VI defects and these metabolic circuits remains unknown. To unravel the expression profiling perturbation in muscles with collagen VI myopathies, we performed a deep RNA profiling in both Col6a1(-/-)mice and patients with collagen VI pathology. The interactome map identified common pathways suggesting a previously undetected connection between circadian genes and collagen VI pathology. Intriguingly, Bmal1(-/-)(also known as Arntl) mice, a well-characterized model displaying arrhythmic circadian rhythms, showed profound deregulation of the collagen VI pathway and of autophagy-related genes. The involvement of circadian rhythms in collagen VI myopathies is new and links autophagy and mitochondrial abnormalities. It also opens new avenues for therapies of hereditary myopathies to modulate the molecular clock or potential gene-environment interactions that might modify muscle damage pathogenesis.

  2. Carbon and nitrogen isotopic signatures and nitrogen profile to identify adulteration in organic fertilizers.

    Science.gov (United States)

    Verenitch, Sergei; Mazumder, Asit

    2012-08-29

    Recently it has been shown that stable isotopes of nitrogen can be used to discriminate between organic and synthetic fertilizers, but the robustness of the approach is questionable. This work developed a comprehensive method that is far more robust in identifying an adulteration of organic nitrogen fertilizers. Organic fertilizers of various types (manures, composts, blood meal, bone meal, fish meal, products of poultry and plant productions, molasses and seaweed based, and others) available on the North American market were analyzed to reveal the most sensitive criteria as well as their quantitative ranges, which can be used in their authentication. Organic nitrogen fertilizers of known origins with a wide δ(15)N range between -0.55 and 28.85‰ (n = 1258) were characterized for C and N content, δ(13)C, δ(15)N, viscosity, pH, and nitrogen profile (urea, ammonia, organic N, water insoluble N, and NO3). A statistically significant data set of characterized unique organic nitrogen fertilizers (n = 335) of various known origins has been assembled. Deliberately adulterated samples of different types of organic fertilizers mixed with synthetic fertilizers at a wide range of proportions have been used to develop the quantitative critical characteristics of organic fertilizers as the key indicators of their adulteration. Statistical analysis based on the discriminant functions of the quantitative critical characteristics of organic nitrogen fertilizers from 14 different source materials revealed a very high average rate of correct classification. The developed methodology has been successfully used as a source identification tool for numerous commercial nitrogen fertilizers available on the North American market.

  3. An integrative data mining approach to identifying adverse outcome pathway signatures.

    Science.gov (United States)

    Oki, Noffisat O; Edwards, Stephen W

    2016-03-28

    The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or population. Computational approaches to explore and determine these connections can accelerate the assembly of AOPs. By leveraging the wealth of publicly available data covering chemical effects on biological systems, computationally-predicted AOPs (cpAOPs) were assembled via data mining of high-throughput screening (HTS) in vitro data, in vivo data and other disease phenotype information. Frequent Itemset Mining (FIM) was used to find associations between the gene targets of ToxCast HTS assays and disease data from Comparative Toxicogenomics Database (CTD) by using the chemicals as the common aggregators between datasets. The method was also used to map gene expression data to disease data from CTD. A cpAOP network was defined by considering genes and diseases as nodes and FIM associations as edges. This network contained 18,283 gene to disease associations for the ToxCast data and 110,253 for CTD gene expression. Two case studies show the value of the cpAOP network by extracting subnetworks focused either on fatty liver disease or the Aryl Hydrocarbon Receptor (AHR). The subnetwork surrounding fatty liver disease included many genes known to play a role in this disease. When querying the cpAOP network with the AHR gene, an interesting subnetwork including glaucoma was identified. While substantial literature exists to support the potential for AHR ligands to elicit glaucoma, it was not explicitly captured in the public annotation information in CTD. The subnetwork from this analysis suggests a cpAOP that includes changes in CYP1B1 expression, which has been previously established in the literature as a primary cause of glaucoma. These case studies highlight the value in integrating multiple data

  4. The nanomechanical signature of liver cancer tissues and its molecular origin.

    Science.gov (United States)

    Tian, Mengxin; Li, Yiran; Liu, Weiren; Jin, Lei; Jiang, Xifei; Wang, Xinyan; Ding, Zhenbin; Peng, Yuanfei; Zhou, Jian; Fan, Jia; Cao, Yi; Wang, Wei; Shi, Yinghong

    2015-08-14

    Patients with cirrhosis are at higher risk of developing hepatocellular carcinoma (HCC), the second most frequent cause of cancer-related deaths. Although HCC diagnosis based on conventional morphological characteristics serves as the "gold standard" in the clinic, there is a high demand for more convenient and effective diagnostic methods that employ new biophysical perspectives. Here, we show that the nanomechanical signature of liver tissue is directly correlated with the development of HCC. Using indentation-type atomic force microscopy (IT-AFM), we demonstrate that the lowest elasticity peak (LEP) in the Young's modulus distribution of surgically removed liver cancer tissues can serve as a mechanical fingerprint to evaluate the malignancy of liver cancer. Cirrhotic tissues shared the same LEP as normal tissues. However, a noticeable downward shift in the LEP was detected when the cirrhotic tissues progressed to a malignant state, making the tumor tissues more prone to microvascular invasion. Cell-level mechanistic studies revealed that the expression level of a Rho-family effector (mDia1) was consistent with the mechanical trend exhibited by the tissue. Our findings indicate that the mechanical profiles of liver cancer tissues directly varied with tumor progression, providing an additional platform for the future diagnosis of HCC.

  5. Application of δ13C and δ15N isotopic signatures of organic matter fractions sequentially separated from adjacent arable and forest soils to identify carbon stabilization mechanisms

    OpenAIRE

    Kayler, Z.E.; Kaiser, M; Gessler, A.; Ellerbrock, R. H.; M. Sommer

    2011-01-01

    Identifying the chemical mechanisms behind soil carbon bound in organo-mineral complexes is necessary to determine the degree to which soil organic carbon is stabilized belowground. Analysis of δ13C and δ15N isotopic signatures of stabilized OM fractions along with soil mineral characteristics may yield important information about OM-mineral associations and their processing history. We anlayzed the δ13C and δ15N isotopic signatures from two organic matter (OM) fractio...

  6. Identification of Y-box binding protein 1 as a core regulator of MEK/ERK pathway-dependent gene signatures in colorectal cancer cells.

    Directory of Open Access Journals (Sweden)

    Karsten Jürchott

    Full Text Available Transcriptional signatures are an indispensible source of correlative information on disease-related molecular alterations on a genome-wide level. Numerous candidate genes involved in disease and in factors of predictive, as well as of prognostic, value have been deduced from such molecular portraits, e.g. in cancer. However, mechanistic insights into the regulatory principles governing global transcriptional changes are lagging behind extensive compilations of deregulated genes. To identify regulators of transcriptome alterations, we used an integrated approach combining transcriptional profiling of colorectal cancer cell lines treated with inhibitors targeting the receptor tyrosine kinase (RTK/RAS/mitogen-activated protein kinase pathway, computational prediction of regulatory elements in promoters of co-regulated genes, chromatin-based and functional cellular assays. We identified commonly co-regulated, proliferation-associated target genes that respond to the MAPK pathway. We recognized E2F and NFY transcription factor binding sites as prevalent motifs in those pathway-responsive genes and confirmed the predicted regulatory role of Y-box binding protein 1 (YBX1 by reporter gene, gel shift, and chromatin immunoprecipitation assays. We also validated the MAPK-dependent gene signature in colorectal cancers and provided evidence for the association of YBX1 with poor prognosis in colorectal cancer patients. This suggests that MEK/ERK-dependent, YBX1-regulated target genes are involved in executing malignant properties.

  7. Signature of Nonstationarity in Precipitation Extremes over Urbanizing Regions in India Identified through a Multivariate Frequency Analyses

    Science.gov (United States)

    Singh, Jitendra; Hari, Vittal; Sharma, Tarul; Karmakar, Subhankar; Ghosh, Subimal

    2016-04-01

    The statistical assumption of stationarity in hydrologic extreme time/event series has been relied heavily in frequency analysis. However, due to the analytically perceivable impacts of climate change, urbanization and concomitant land use pattern, assumption of stationarity in hydrologic time series will draw erroneous results, which in turn may affect the policy and decision-making. Past studies provided sufficient evidences on changes in the characteristics of Indian monsoon precipitation extremes and further it has been attributed to climate change and urbanization, which shows need of nonstationary analysis on the Indian monsoon extremes. Therefore, a comprehensive multivariate nonstationary frequency analysis has been conducted for the entire India to identify the precipitation characteristics (intensity, duration and depth) responsible for significant nonstationarity in the Indian monsoon. We use 1o resolution of precipitation data for a period of 1901-2004, in a Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework. A cluster of GAMLSS models has been developed by considering nonstationarity in different combinations of distribution parameters through different regression techniques, and the best-fit model is further applied for bivariate analysis. A population density data has been utilized to identify the urban, urbanizing and rural regions. The results showed significant differences in the stationary and nonstationary bivariate return periods for the urbanizing grids, when compared to urbanized and rural grids. A comprehensive multivariate analysis has also been conducted to identify the precipitation characteristics particularly responsible for imprinting signature of nonstationarity.

  8. New Molecular Features of Colorectal Cancer Identified - Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    Investigators from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) who comprehensively analyzed 95 human colorectal tumor samples, have determined how gene alterations identified in previous analyses of the same samples

  9. MuSiC: identifying mutational significance in cancer genomes.

    Science.gov (United States)

    Dees, Nathan D; Zhang, Qunyuan; Kandoth, Cyriac; Wendl, Michael C; Schierding, William; Koboldt, Daniel C; Mooney, Thomas B; Callaway, Matthew B; Dooling, David; Mardis, Elaine R; Wilson, Richard K; Ding, Li

    2012-08-01

    Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery.

  10. MuSiC: Identifying mutational significance in cancer genomes

    Science.gov (United States)

    Dees, Nathan D.; Zhang, Qunyuan; Kandoth, Cyriac; Wendl, Michael C.; Schierding, William; Koboldt, Daniel C.; Mooney, Thomas B.; Callaway, Matthew B.; Dooling, David; Mardis, Elaine R.; Wilson, Richard K.; Ding, Li

    2012-01-01

    Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly significant events. In other words, we aim to determine the Mutational Significance in Cancer (MuSiC) for these large data sets. The integration of analytical operations in the MuSiC framework is widely applicable to a broad set of tumor types and offers the benefits of automation as well as standardization. Herein, we describe the computational structure and statistical underpinnings of the MuSiC pipeline and demonstrate its performance using 316 ovarian cancer samples from the TCGA ovarian cancer project. MuSiC correctly confirms many expected results, and identifies several potentially novel avenues for discovery. PMID:22759861

  11. Towards a 'Lyon molecular signature' to individualize the treatment of rectal cancer. Prognostic analysis of a prospective cohort of 94 rectal cancers T1-2-3 Nx MO to be the basis of a molecular signature

    International Nuclear Information System (INIS)

    Purpose. - In 1998 a translational research was initiated in Lyon aiming at identifying a prognostic 'bio-molecular signature' in rectal cancer. This paper presents the clinical outcome of the patients included in this study. Patients and methods. - A total of 94 patients were included between 1998 and 2001. A staging with recto-scopy and biopsies was performed before treatment. In case of surgery, the operative specimen was analysed to evaluate the pathological response. There were two types of treatment: neoadjuvant radiotherapy (with or without concurrent chemotherapy) followed by surgery (76 cases) and radiotherapy alone with 'contactherapy' often associated with external beam radiotherapy (18 patients). Results. - The patients had a mean age of 63 years. Stage was T1: 4, T2: 24, T3: 65 and T4: 1. The overall survival of the 94 patients was 62% at 8 years with a rate of distant metastases of 29%. Rate of local recurrence at 8 years was 6% in the neoadjuvant group and 16% in the radiotherapy group with an overall 8 years survival in both groups respectively: 64% and 53%. There was a trend towards more metastases in cT3, tumour diameter above 4 cm, circumferential extension. There was a significant increase in the risk of metastases for ypT3, ypN1-2 and Dworak score 1-2-3. In multivariate analysis ypT3 was significantly associated with a high rate of metastases (55%; P = 0.0003). Conclusion. - The rate of distant metastases is a major prognostic factor. These clinical results will serve as the base line to identify a 'bio-molecular signature' which could complement the TN(M) classification. (authors)

  12. Multi-epoch Spectroscopy of Dwarf Galaxies with AGN Signatures: Identifying Sources with Persistent Broad Hα Emission

    Science.gov (United States)

    Baldassare, Vivienne F.; Reines, Amy E.; Gallo, Elena; Greene, Jenny E.; Graur, Or; Geha, Marla; Hainline, Kevin; Carroll, Christopher M.; Hickox, Ryan C.

    2016-09-01

    We use time-domain optical spectroscopy to distinguish between broad emission lines powered by accreting black holes (BHs) and stellar processes (i.e., supernovae) for 16 galaxies identified as active galactic nucleus (AGN) candidates by Reines et al (2013). Our study is primarily focused on those objects with narrow emission line ratios dominated by star formation, for which the origin of the broad Hα emission was unclear. Based on follow-up spectroscopy, we find that the broad Hα emission has faded or was ambiguous for all of the star-forming objects (14/16), over baselines ranging from 5-14 years, suggesting a transient stellar process was responsible for the broad emission in previous Sloan Digital Sky Survey observations. For the two objects in our follow-up sample with narrow-line AGN signatures (RGG 9 and RGG 119), we find persistent broad Hα emission consistent with an AGN origin. Additionally, we use high spectral resolution observations to measure stellar velocity dispersions for 15 objects in the Reines et al. (2013) sample, all with narrow-line ratios indicating the presence of an AGN. Stellar masses range from ˜ 5× {10}8 to 3× {10}9 M ⊙, and we measure {σ }* in the range of 28{--}71 {km} {{{s}}}-1. These {σ }* correspond to some of the lowest-mass galaxies with optical signatures of AGN activity. We show that RGG 119, the one object that has both a measured {σ }* and persistent broad Hα emission, falls near the extrapolation of the {\\text{}}{M}{BH}-{σ }\\star relation to the low-mass end.

  13. A Specific miRNA Signature Correlates With Complete Pathological Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Della Vittoria Scarpati, Giuseppina [Department of Molecular and Clinical Endocrinology and Oncology, University of Naples Federico II, Naples (Italy); Falcetta, Francesca [Laboratory of Cancer Pharmacology, Department of Oncology, ' Mario Negri' Institute for Pharmacological Research, Milan (Italy); Carlomagno, Chiara, E-mail: chiara.carlomagno@unina.it [Department of Molecular and Clinical Endocrinology and Oncology, University of Naples Federico II, Naples (Italy); Ubezio, Paolo; Marchini, Sergio [Laboratory of Cancer Pharmacology, Department of Oncology, ' Mario Negri' Institute for Pharmacological Research, Milan (Italy); De Stefano, Alfonso [Department of Molecular and Clinical Endocrinology and Oncology, University of Naples Federico II, Naples (Italy); Singh, Vijay Kumar [Cancer Genomics Laboratory, Fondazione ' Edo ed Elvo Tempia Valenta' , Biella (Italy); D' Incalci, Maurizio [Laboratory of Cancer Pharmacology, Department of Oncology, ' Mario Negri' Institute for Pharmacological Research, Milan (Italy); De Placido, Sabino [Department of Molecular and Clinical Endocrinology and Oncology, University of Naples Federico II, Naples (Italy); Pepe, Stefano [Division of Oncology, University of Salerno (Italy)

    2012-07-15

    Purpose: MicroRNAs (miRNAs) are small, noncoding RNA molecules that can be down- or upregulated in colorectal cancer and have been associated to prognosis and response to treatment. We studied miRNA expression in tumor biopsies of patients with rectal cancer to identify a specific 'signature' correlating with pathological complete response (pCR) after neoadjuvant chemoradiotherapy. Methods and Materials: A total of 38 T3-4/N+ rectal cancer patients received capecitabine-oxaliplatin and radiotherapy followed by surgery. Pathologic response was scored according to the Mandard TRG scale. MiRNA expression was analyzed by microarray and confirmed by real-time Reverse Transcription Polymerase Chain Reaction (qRT-PCR) on frozen biopsies obtained before treatment. The correlation between miRNA expression and TRG, coded as TRG1 (pCR) vs. TRG >1 (no pCR), was assessed by methods specifically designed for this study. Results: Microarray analysis selected 14 miRNAs as being differentially expressed in TRG1 patients, and 13 were confirmed by qRT-PCR: 11 miRNAs (miR-1183, miR-483-5p, miR-622, miR-125a-3p, miR-1224-5p, miR-188-5p, miR-1471, miR-671-5p, miR-1909 Asterisk-Operator , miR-630, miR-765) were significantly upregulated in TRG1 patients, 2 (miR-1274b, miR-720) were downexpressed. MiR-622 and miR-630 had a 100% sensitivity and specificity in selecting TRG1 cases. Conclusions: A set of 13 miRNAs is strongly associated with pCR and may represent a specific predictor of response to chemoradiotherapy in rectal cancer patients.

  14. Drosophila Cancer Models Identify Functional Differences between Ret Fusions.

    Science.gov (United States)

    Levinson, Sarah; Cagan, Ross L

    2016-09-13

    We generated and compared Drosophila models of RET fusions CCDC6-RET and NCOA4-RET. Both RET fusions directed cells to migrate, delaminate, and undergo EMT, and both resulted in lethality when broadly expressed. In all phenotypes examined, NCOA4-RET was more severe than CCDC6-RET, mirroring their effects on patients. A functional screen against the Drosophila kinome and a library of cancer drugs found that CCDC6-RET and NCOA4-RET acted through different signaling networks and displayed distinct drug sensitivities. Combining data from the kinome and drug screens identified the WEE1 inhibitor AZD1775 plus the multi-kinase inhibitor sorafenib as a synergistic drug combination that is specific for NCOA4-RET. Our work emphasizes the importance of identifying and tailoring a patient's treatment to their specific RET fusion isoform and identifies a multi-targeted therapy that may prove effective against tumors containing the NCOA4-RET fusion. PMID:27626672

  15. Identification of Gene and MicroRNA Signatures for Oral Cancer Developed from Oral Leukoplakia

    OpenAIRE

    Guanghui Zhu; Yuan He; Shaofang Yang; Beimin Chen; Min Zhou; Xin-Jian Xu

    2015-01-01

    In clinic, oral leukoplakia (OLK) may develop into oral cancer. However, the mechanism underlying this transformation is still unclear. In this work, we present a new pipeline to identify oral cancer related genes and microRNAs (miRNAs) by integrating both gene and miRNA expression profiles. In particular, we find some network modules as well as their miRNA regulators that play important roles in the development of OLK to oral cancer. Among these network modules, 91.67% of genes and 37.5% of ...

  16. Functional genomics identifies therapeutic targets for MYC-driven cancer

    OpenAIRE

    Toyoshima, Masafumi; Howie, Heather L; Imakura, Maki; Walsh, Ryan M.; Annis, James E.; Chang, Aaron N; Frazier, Jason; Chau, B. Nelson; Loboda, Andrey; Linsley, Peter S; Cleary, Michele A.; Park, Julie R.; Grandori, Carla

    2012-01-01

    MYC oncogene family members are broadly implicated in human cancers, yet are considered “undruggable” as they encode transcription factors. MYC also carries out essential functions in proliferative tissues, suggesting that its inhibition could cause severe side effects. We elected to identify synthetic lethal interactions with c-MYC overexpression (MYC-SL) in a collection of ∼3,300 druggable genes, using high-throughput siRNA screening. Of 49 genes selected for follow-up, 48 were confirmed by...

  17. An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies

    Directory of Open Access Journals (Sweden)

    Rollins Derrick K

    2010-12-01

    Full Text Available Abstract Background Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR and statistical power (SP which is the ability to correctly identify important genes. Results This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i exposing E. coli cells to two different ethanol levels; (ii application of myostatin to two groups of mice; and (iii a simulated data study derived from the properties of (ii. The proposed method (PM effectively identified critical genes in these studies based on comparison with the current method (CM. The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. Conclusions PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

  18. A novel gene signature for molecular diagnosis of human prostate cancer by RT-qPCR.

    Directory of Open Access Journals (Sweden)

    Federica Rizzi

    Full Text Available BACKGROUND: Prostate cancer (CaP is one of the most relevant causes of cancer death in Western Countries. Although detection of CaP at early curable stage is highly desirable, actual screening methods present limitations and new molecular approaches are needed. Gene expression analysis increases our knowledge about the biology of CaP and may render novel molecular tools, but the identification of accurate biomarkers for reliable molecular diagnosis is a real challenge. We describe here the diagnostic power of a novel 8-genes signature: ornithine decarboxylase (ODC, ornithine decarboxylase antizyme (OAZ, adenosylmethionine decarboxylase (AdoMetDC, spermidine/spermine N(1-acetyltransferase (SSAT, histone H3 (H3, growth arrest specific gene (GAS1, glyceraldehyde 3-phosphate dehydrogenase (GAPDH and Clusterin (CLU in tumour detection/classification of human CaP. METHODOLOGY/PRINCIPAL FINDINGS: The 8-gene signature was detected by retrotranscription real-time quantitative PCR (RT-qPCR in frozen prostate surgical specimens obtained from 41 patients diagnosed with CaP and recommended to undergo radical prostatectomy (RP. No therapy was given to patients at any time before RP. The bio-bank used for the study consisted of 66 specimens: 44 were benign-CaP paired from the same patient. Thirty-five were classified as benign and 31 as CaP after final pathological examination. Only molecular data were used for classification of specimens. The Nearest Neighbour (NN classifier was used in order to discriminate CaP from benign tissue. Validation of final results was obtained with 10-fold cross-validation procedure. CaP versus benign specimens were discriminated with (80+/-5% accuracy, (81+/-6% sensitivity and (78+/-7% specificity. The method also correctly classified 71% of patients with Gleason score or =7, an important predictor of final outcome. CONCLUSIONS/SIGNIFICANCE: The method showed high sensitivity in a collection of specimens in which a significant

  19. Identifying Cancer Biomarkers Via Node Classification within a Mapreduce Framework

    Directory of Open Access Journals (Sweden)

    Taysir Hassan A. Soliman

    2015-12-01

    Full Text Available Big data are giving new research challenges in the life sciences domain because of their variety, volume, veracity, velocity, and value. Predicting gene biomarkers is one of the vital research issues in bioinformatics field, where microarray gene expression and network based methods can be used. These datasets suffer from the huge data voluminous, causing main memory problems. In this paper, a Random Committee Node Classifier algorithm (RCNC is proposed for identifying cancer biomarkers, which is based on microarray gene expression data and Protein-Protein Interaction (PPI data. Data are enriched from other public databases, such as IntACT1 and UniProt2 and Gene Ontology3 (GO. Cancer Biomarkers are identified when applied to different datasets with an accuracy rate an accuracy rate 99.16%, 99.96% precision, 99.24% recall, 99.16% F1-measure and 99.6 ROC. To speed up the performance, it is run within a MapReduce framework, where RCNC MapReduce algorithm is much faster than RCNC sequential algorithm when having large datasets.

  20. Multi-epoch Spectroscopy of Dwarf Galaxies with AGN Signatures: Identifying Sources with Persistent Broad H-alpha Emission

    CERN Document Server

    Baldassare, Vivienne F; Gallo, Elena; Greene, Jenny E; Graur, Or; Geha, Marla; Hainline, Kevin; Carroll, Christopher M; Hickox, Ryan C

    2016-01-01

    We use time-domain optical spectroscopy to distinguish between broad emission lines powered by accreting black holes (BHs) or stellar processes (i.e., supernovae) for 16 galaxies identified as AGN candidates by Reines et al. (2013). 14 of these have star-formation--dominated narrow-line emission ratios, one is a narrow-line AGN, and the last is a star-forming--AGN composite. We find that broad H$\\alpha$ emission has faded for 11/16 targets, based on spectra taken with the Magellan Echellette Spectrograph (MagE), the Dual Imaging Spectrograph, and the Ohio State Multi-Object Spectrograph with baselines ranging from 5 to 14 years. The 11 faded systems all have narrow-line ratios consistent with recent star formation, suggesting the broad emission for those targets was produced by a transient stellar process. The two objects with narrow-line AGN signatures (RGG 9 and RGG 119) have persistent broad H$\\alpha$ emission consistent with previous SDSS observations. The final three star-forming objects are classified a...

  1. Urinary microRNA-based signature improves accuracy of detection of clinically relevant prostate cancer within the prostate-specific antigen grey zone

    OpenAIRE

    SALIDO-GUADARRAMA, ALBERTO IVAN; MORALES-MONTOR, JORGE GUSTAVO; Rangel-Escareño, Claudia; Langley, Elizabeth; Peralta-Zaragoza, Oscar; COLIN, JOSE LUIS CRUZ; Rodriguez-dorantes, Mauricio

    2016-01-01

    At present, prostate-specific antigen (PSA) is used as a clinical biomarker for prostate cancer (PCa) diagnosis; however, a large number of patients with benign prostate hyperplasia (BPH) with PSA levels in the ʻgray areaʼ (4–10 ng/ml) are currently subjected to unnecessary biopsy due to overdiagnosis. Certain microRNAs (miRs) have been proven to be useful biomarkers, several of which are detectable in bodily fluids. The present study identified and validated a urinary miR-based signature to ...

  2. TCGA researchers identify 4 subtypes of stomach cancer

    Science.gov (United States)

    Stomach cancers fall into four distinct molecular subtypes, researchers with The Cancer Genome Atlas (TCGA) Network have found. Scientists report that this discovery could change how researchers think about developing treatments for stomach cancer, also c

  3. [HPV-associated head and neck cancer : mutational signature and genomic aberrations].

    Science.gov (United States)

    Wagner, S; Würdemann, N; Hübbers, C; Reuschenbach, M; Prigge, E-S; Wichmann, G; Hess, J; Dietz, A; Dürst, M; Tinhofer, I; von Knebel-Döberitz, M; Wittekindt, C; Klussmann, J P

    2015-11-01

    A significantly increasing proportion of oropharyngeal head and neck carcinomas (OSCC) in North America and Europe are associated with human papillomavirus (HPV) infections. HPV-related OSCC is regarded as a distinct tumor type with regard to its cellular, biologic, and clinical characteristics. Patients with HPV-related OSCC have significantly better local control, but higher rates of regional lymph node and distant metastases as compared to patients with HPV-negative OSCC. Classical molecular genetic investigations demonstrated specific chromosomal aberration signatures in HPV-related OSCC, and recent developments in next generation sequencing (NGS) technology have rendered possible the sequencing of entire genomes, and thus detection of specific mutations, in just a few days. Initial data from The Cancer Genome Atlas (TCGA) project obtained by using genome-wide high throughput methods have confirmed that HPV-related OSCC contain fewer, albeit more specific mutations than HPV-negative tumors. Additionally, these data revealed the presence of specific-potentially therapeutically targetable-activating driver mutations in subgroups of HPV-positive OSCC, some of which have a prognostic impact. Specific targeted NGS technologies provide new possibilities for identification of diagnostic, prognostic, and predictive biomarkers and the development of personalized cancer treatment. Patients with HPV-positive tumors are likely to profit from these developments in the future, since the genetic alterations are relatively homogenous and frequently lead to signal pathway activation. There is an urgent need for network research activities to carry out the necessary basic research in prospective cohort studies.

  4. The Relationship Between Eight GWAS-Identified Single-Nucleotide Polymorphisms and Primary Breast Cancer Outcomes

    OpenAIRE

    Bayraktar, Soley; Thompson, Patricia A.; Yoo, Suk-Young; Do, Kim-Anh; Sahin, Aysegul A.; Arun, Banu K; Bondy, Melissa L.; Brewster, Abenaa M.

    2013-01-01

    Several single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified through genome-wide association studies. This study investigated the association of eight risk SNPs with breast cancer disease-free survival and overall survival rates. Results suggest that two previously identified breast cancer risk susceptibility loci may influence breast cancer prognosis or comorbid conditions associated with overall survival.

  5. A BRCA1-mutation associated DNA methylation signature in blood cells predicts sporadic breast cancer incidence and survival.

    OpenAIRE

    Anjum, S; Fourkala, E O; Zikan, M.; Wong, A.; Gentry-Maharaj, A.; Jones, A.; HARDY, R.; Cibula, D.; Kuh, D.; Jacobs, I. J.; Teschendorff, A.E.; Menon, U; Widschwendter, M

    2014-01-01

    Background BRCA1 mutation carriers have an 85% risk of developing breast cancer but the risk of developing non-hereditary breast cancer is difficult to assess. Our objective is to test whether a DNA methylation (DNAme) signature derived from BRCA1 mutation carriers is able to predict non-hereditary breast cancer. Methods In a case/control setting (72 BRCA1 mutation carriers and 72 BRCA1/2 wild type controls) blood cell DNA samples were profiled on the Illumina 27 k methylation array. Using th...

  6. Gene expression analysis identifies global gene dosage sensitivity in cancer

    DEFF Research Database (Denmark)

    Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata;

    2015-01-01

    Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gene...... expression. We reanalyzed 77,840 expression profiles and observed a limited set of 'transcriptional components' that describe well-known biology, explain the vast majority of variation in gene expression and enable us to predict the biological function of genes. On correcting expression profiles...... for these components, we observed that the residual expression levels (in 'functional genomic mRNA' profiling) correlated strongly with copy number. DNA copy number correlated positively with expression levels for 99% of all abundantly expressed human genes, indicating global gene dosage sensitivity. By applying...

  7. Comparison of molecular signatures in large scale protein interaction networks in normal and cancer conditions of brain, cervix, lung, ovary and prostate

    Directory of Open Access Journals (Sweden)

    Rajat Suvra Banik

    2016-04-01

    Full Text Available Background Cancer, the disease of intricateness, has remained beyond our complete perception so far. Network systems biology (termed NSB is one of the most recent approaches to understand the unsolved problems of cancer development. From this perspective, differential protein networks (PINs have been developed based on the expression and interaction data of brain, cervix, lung, ovary and prostate for normal and cancer conditions. Methods Differential expression database GeneHub-GEPIS and interaction database STRING were applied for primary data retrieval. Cytoscape platform and related plugins named network analyzer; MCODE and ModuLand were used for visualization of complex networks and subsequent analysis. Results Significant differences were observedamong different common network parameters between normal and cancer states. Moreover, molecular complex numbers and overlapping modularization found to be varying significantly between normal and cancerous tissues. The number of the ranked molecular complex and the nodes involved in the overlapping modules were meaningfully higher in cancer condition.We identified79 commonly up regulated and 6 down regulated proteins in all five tissues. Number of nodes, edges; multi edge node pair, and average number of neighbor are found with significant fluctuations in case of cervix and ovarian tissues.Cluster analysis showed that the association of Myc and Cdk4 proteins is very close with other proteins within the network.Cervix and ovarian tissue showed higher increment of the molecular complex number and overlapping module network during cancer in comparison to normal state. Conclusions The differential molecular signatures identified from the work can be studied further to understand the cancer signaling process, and potential therapeutic and detection approach. [Biomed Res Ther 2016; 3(4.000: 605-615

  8. Genomic analyses identify molecular subtypes of pancreatic cancer.

    Science.gov (United States)

    Bailey, Peter; Chang, David K; Nones, Katia; Johns, Amber L; Patch, Ann-Marie; Gingras, Marie-Claude; Miller, David K; Christ, Angelika N; Bruxner, Tim J C; Quinn, Michael C; Nourse, Craig; Murtaugh, L Charles; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourbakhsh, Ehsan; Wani, Shivangi; Fink, Lynn; Holmes, Oliver; Chin, Venessa; Anderson, Matthew J; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Xu, Qinying; Wilson, Peter J; Cloonan, Nicole; Kassahn, Karin S; Taylor, Darrin; Quek, Kelly; Robertson, Alan; Pantano, Lorena; Mincarelli, Laura; Sanchez, Luis N; Evers, Lisa; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chantrill, Lorraine A; Mawson, Amanda; Humphris, Jeremy; Chou, Angela; Pajic, Marina; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Moran-Jones, Kim; Jamieson, Nigel B; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Grützmann, Robert; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Rusev, Borislav; Capelli, Paola; Salvia, Roberto; Tortora, Giampaolo; Mukhopadhyay, Debabrata; Petersen, Gloria M; Munzy, Donna M; Fisher, William E; Karim, Saadia A; Eshleman, James R; Hruban, Ralph H; Pilarsky, Christian; Morton, Jennifer P; Sansom, Owen J; Scarpa, Aldo; Musgrove, Elizabeth A; Bailey, Ulla-Maja Hagbo; Hofmann, Oliver; Sutherland, Robert L; Wheeler, David A; Gill, Anthony J; Gibbs, Richard A; Pearson, John V; Waddell, Nicola; Biankin, Andrew V; Grimmond, Sean M

    2016-03-01

    Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

  9. Clinicopathologic factors identify sporadic mismatch repair-defective colon cancers

    DEFF Research Database (Denmark)

    Halvarsson, Britta; Anderson, Harald; Domanska, Katarina;

    2008-01-01

    Identification of sporadic mismatch repair (MMR)-defective colon cancers is increasingly demanded for decisions on adjuvant therapies. We evaluated clinicopathologic factors for the identification of these prognostically favorable tumors. Histopathologic features in 238 consecutive colon cancers...... and excluded 61.5% of the tumors from MMR testing. This clinicopathologic index thus successfully selects MMR-defective colon cancers. Udgivelsesdato: 2008-Feb...

  10. Obesity and prostate cancer: gene expression signature of human periprostatic adipose tissue

    Directory of Open Access Journals (Sweden)

    Ribeiro Ricardo

    2012-09-01

    Full Text Available Abstract Background Periprostatic (PP adipose tissue surrounds the prostate, an organ with a high predisposition to become malignant. Frequently, growing prostatic tumor cells extend beyond the prostatic organ towards this fat depot. This study aimed to determine the genome-wide expression of genes in PP adipose tissue in obesity/overweight (OB/OW and prostate cancer patients. Methods Differentially expressed genes in human PP adipose tissue were identified using microarrays. Analyses were conducted according to the donors' body mass index characteristics (OB/OW versus lean and prostate disease (extra prostatic cancer versus organ confined prostate cancer versus benign prostatic hyperplasia. Selected genes with altered expression were validated by real-time PCR. Ingenuity Pathway Analysis (IPA was used to investigate gene ontology, canonical pathways and functional networks. Results In the PP adipose tissue of OB/OW subjects, we found altered expression of genes encoding molecules involved in adipogenic/anti-lipolytic, proliferative/anti-apoptotic, and mild immunoinflammatory processes (for example, FADS1, down-regulated, and LEP and ANGPT1, both up-regulated. Conversely, in the PP adipose tissue of subjects with prostate cancer, altered genes were related to adipose tissue cellular activity (increased cell proliferation/differentiation, cell cycle activation and anti-apoptosis, whereas a downward impact on immunity and inflammation was also observed, mostly related to the complement (down-regulation of CFH. Interestingly, we found that the microRNA MIRLET7A2 was overexpressed in the PP adipose tissue of prostate cancer patients. Conclusions Obesity and excess adiposity modified the expression of PP adipose tissue genes to ultimately foster fat mass growth. In patients with prostate cancer the expression profile of PP adipose tissue accounted for hypercellularity and reduced immunosurveillance. Both findings may be liable to promote a favorable

  11. Gene expression signature in organized and growth arrested mammaryacini predicts good outcome in breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Fournier, Marcia V.; Martin, Katherine J.; Kenny, Paraic A.; Xhaja, Kris; Bosch, Irene; Yaswen, Paul; Bissell, Mina J.

    2006-02-08

    To understand how non-malignant human mammary epithelial cells (HMEC) transit from a disorganized proliferating to an organized growth arrested state, and to relate this process to the changes that occur in breast cancer, we studied gene expression changes in non-malignant HMEC grown in three-dimensional cultures, and in a previously published panel of microarray data for 295 breast cancer samples. We hypothesized that the gene expression pattern of organized and growth arrested mammary acini would share similarities with breast tumors with good prognoses. Using Affymetrix HG-U133A microarrays, we analyzed the expression of 22,283 gene transcripts in two HMEC cell lines, 184 (finite life span) and HMT3522 S1 (immortal non-malignant), on successive days post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7. We identified gene expression changes with the same temporal pattern in both lines. We show that genes that are significantly lower in the organized, growth arrested HMEC than in their proliferating counterparts can be used to classify breast cancer patients into poor and good prognosis groups with high accuracy. This study represents a novel unsupervised approach to identifying breast cancer markers that may be of use clinically.

  12. DNA methylation signatures for prediction of biochemical recurrence after radical prostatectomy of clinically localized prostate cancer

    DEFF Research Database (Denmark)

    Haldrup, Christa; Mundbjerg, Kamilla; Vestergaard, Else Marie;

    2013-01-01

    Purpose Diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, causing overtreatment of indolent PC and risk of delayed treatment of aggressive PC. Here, we identify six novel candidate DNA methylation markers for PC with promising diagnostic and prognostic potential. Methods...... Microarray-based screening and bisulfite sequencing of 20 nonmalignant and 29 PC tissue specimens were used to identify new candidate DNA hypermethylation markers for PC. Diagnostic and prognostic potential was evaluated in 35 nonmalignant prostate tissue samples, 293 radical prostatectomy (RP) samples...... assessed using log-rank tests and univariate and multivariate Cox regression analyses. Results Hypermethylation of AOX1, C1orf114, GAS6, HAPLN3, KLF8, and MOB3B was highly cancer specific (area under the curve, 0.89 to 0.98). Furthermore, high C1orf114 methylation was significantly (P

  13. Systematic Functional Interrogation of Rare Cancer Variants Identifies Oncogenic Alleles | Office of Cancer Genomics

    Science.gov (United States)

    Cancer genome characterization efforts now provide an initial view of the somatic alterations in primary tumors. However, most point mutations occur at low frequency, and the function of these alleles remains undefined. We have developed a scalable systematic approach to interrogate the function of cancer-associated gene variants. We subjected 474 mutant alleles curated from 5,338 tumors to pooled in vivo tumor formation assays and gene expression profiling. We identified 12 transforming alleles, including two in genes (PIK3CB, POT1) that have not been shown to be tumorigenic.

  14. PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity

    Directory of Open Access Journals (Sweden)

    Dwivedi Bhakti

    2012-03-01

    Full Text Available Abstract Background Phages (viruses that infect bacteria have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or "signature genes" present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples; however, there is currently no existing computational tool that biologists can use for this purpose. Results Here we present PhiSiGns, a web-based and standalone application that performs a pairwise comparison of each gene present in user-selected phage genomes, identifies signature genes, generates alignments of these genes, and designs potential PCR primer pairs. PhiSiGns is available at (http://www.phantome.org/phisigns/; http://phisigns.sourceforge.net/ with a link to the source code. Here we describe the specifications of PhiSiGns and demonstrate its application with a case study. Conclusions PhiSiGns provides phage biologists with a user-friendly tool to identify signature genes and design PCR primers to amplify related genes from uncultured phages in environmental samples. This bioinformatics tool will facilitate the development of novel signature genes for use as molecular markers in studies of phage diversity, phylogeny, and evolution.

  15. Plasma Proteomic Profiling in Hereditary Breast Cancer Reveals a BRCA1-Specific Signature: Diagnostic and Functional Implications

    OpenAIRE

    Domenica Scumaci; Laura Tammè; Claudia Vincenza Fiumara; Giusi Pappaianni; Antonio Concolino; Emanuela Leone; Maria Concetta Faniello; Barbara Quaresima; Enrico Ricevuto; Francesco Saverio Costanzo; Giovanni Cuda

    2015-01-01

    Background Breast cancer (BC) is a leading cause of death among women. Among the major risk factors, an important role is played by familial history of BC. Germ-line mutations in BRCA1/2 genes account for most of the hereditary breast and/or ovarian cancers. Gene expression profiling studies have disclosed specific molecular signatures for BRCA1/2-related breast tumors as compared to sporadic cases, which might help diagnosis and clinical follow-up. Even though, a clear hallmark of BRCA1/2-po...

  16. Candidate serological biomarkers for cancer identified from the secretomes of 23 cancer cell lines and the human protein atlas.

    Science.gov (United States)

    Wu, Chih-Ching; Hsu, Chia-Wei; Chen, Chi-De; Yu, Chia-Jung; Chang, Kai-Ping; Tai, Dar-In; Liu, Hao-Ping; Su, Wen-Hui; Chang, Yu-Sun; Yu, Jau-Song

    2010-06-01

    Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretion-predictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6-137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Human Protein Atlas represent a focused reservoir of potential cancer biomarkers.

  17. Transcriptome profiling identifies genes and pathways deregulated upon floxuridine treatment in colorectal cancer cells harboring GOF mutant p53

    Directory of Open Access Journals (Sweden)

    Arindam Datta

    2016-06-01

    Full Text Available Mutation in TP53 is a common genetic alteration in human cancers. Certain tumor associated p53 missense mutants acquire gain-of-function (GOF properties and confer oncogenic phenotypes including enhanced chemoresistance. The colorectal cancers (CRC harboring mutant p53 are generally aggressive in nature and difficult to treat. To identify a potential gene expression signature of GOF mutant p53-driven acquired chemoresistance in CRC, we performed transcriptome profiling of floxuridine (FUdR treated SW480 cells expressing mutant p53R273H (GEO#: GSE77533. We obtained several genes differentially regulated between FUdR treated and untreated cells. Further, functional characterization and pathway analysis revealed significant enrichment of crucial biological processes and pathways upon FUdR treatment in SW480 cells. Our data suggest that in response to chemotherapeutics treatment, cancer cells with GOF mutant p53 can modulate key cellular pathways to withstand the cytotoxic effect of the drugs. The genes and pathways identified in the present study can be further validated and targeted for better chemotherapy response in colorectal cancer patients harboring mutant p53.

  18. NIH scientists identify molecular link between metabolism and breast cancer

    Science.gov (United States)

    A protein associated with conditions of metabolic imbalance, such as diabetes and obesity, may play a role in the development of aggressive forms of breast cancer, according to new findings by researchers at the National Cancer Institute (NCI), part of th

  19. A Multiple Survival Screening algorithm (MSS) for identifying high-quality cancer prognostic markers

    OpenAIRE

    sprotocols

    2015-01-01

    We have developed a Multiple Survival Screening algorithm (MSS) for identifying high-quality cancer prognostic markers from the gene expression profiles of cancer samples. By applying the MSS algorithm to breast cancer samples, we have identified several marker sets which showed ~90% predicting accuracy across 8 independent breast cancer cohorts. We realized that the algorithm could be used for finding other biomarkers including drug response markers. We are describing the protocol with some ...

  20. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    Directory of Open Access Journals (Sweden)

    Jesús Lascorz

    2011-01-01

    Full Text Available Background: A large number of gene expression profiling (GEP studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9% had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO categories or Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

  1. Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

    Directory of Open Access Journals (Sweden)

    Joseph Andrews

    Full Text Available BACKGROUND: We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis. METHODOLOGY/PRINCIPAL FINDINGS: We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model using Affymetrix gene expression (U133, promoter (1.0R, and SNP/CNV (SNP 6.0 microarray platforms to correlate data from gene expression, epigenetic (DNA methylation, and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo methylation with the loss (or gain of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis. CONCLUSIONS/SIGNIFICANCE: Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer

  2. Transcriptome sequencing in prostate cancer identifies inter-tumor heterogeneity

    Directory of Open Access Journals (Sweden)

    Janet Mendonca

    2015-06-01

    Full Text Available Given the dearth of gene mutations in prostate cancer, [1] ,[2] it is likely that genomic rearrangements play a significant role in the evolution of prostate cancer. However, in the search for recurrent genomic alterations, "private alterations" have received less attention. Such alterations may provide insights into the evolution, behavior, and clinical outcome of an individual tumor. In a recent report in "Genome Biology" Wyatt et al. [3] defines unique alterations in a cohort of high-risk prostate cancer patient with a lethal phenotype. Utilizing a transcriptome sequencing approach they observe high inter-tumor heterogeneity; however, the genes altered distill into three distinct cancer-relevant pathways. Their analysis reveals the presence of several non-ETS fusions, which may contribute to the phenotype of individual tumors, and have significance for disease progression.

  3. Integrative Functional Genomics Analysis of Sustained Polyploidy Phenotypes in Breast Cancer Cells Identifies an Oncogenic Profile for GINS2

    Directory of Open Access Journals (Sweden)

    Juha K. Rantala

    2010-11-01

    Full Text Available Aneuploidy is among the most obvious differences between normal and cancer cells. However, mechanisms contributing to development and maintenance of aneuploid cell growth are diverse and incompletely understood. Functional genomics analyses have shown that aneuploidy in cancer cells is correlated with diffuse gene expression signatures and aneuploidy can arise by a variety of mechanisms, including cytokinesis failures, DNA endoreplication, and possibly through polyploid intermediate states. To identify molecular processes contributing to development of aneuploidy, we used a cell spot microarray technique to identify genes inducing polyploidy and/or allowing maintenance of polyploid cell growth in breast cancer cells. Of 5760 human genes screened, 177 were found to induce severe DNA content alterations on prolonged transient silencing. Association with response to DNA damage stimulus and DNA repair was found to be the most enriched cellular processes among the candidate genes. Functional validation analysis of these genes highlighted GINS2 as the highest ranking candidate inducing polyploidy, accumulation of endogenous DNA damage, and impairing cell proliferation on inhibition. The cell growth inhibition and induction of polyploidy by suppression of GINS2 was verified in a panel of breast cancer cell lines. Bioinformatic analysis of published gene expression and DNA copy number studies of clinical breast tumors suggested GINS2 to be associated with the aggressive characteristics of a subgroup of breast cancers in vivo. In addition, nuclear GINS2 protein levels distinguished actively proliferating cancer cells suggesting potential use of GINS2 staining as a biomarker of cell proliferation as well as a potential therapeutic target.

  4. Gene expression signature of estrogen receptor α status in breast cancer

    Directory of Open Access Journals (Sweden)

    Baggerly Keith

    2005-03-01

    Full Text Available Abstract Background Estrogens are known to regulate the proliferation of breast cancer cells and to modify their phenotypic properties. Identification of estrogen-regulated genes in human breast tumors is an essential step toward understanding the molecular mechanisms of estrogen action in cancer. To this end we generated and compared the Serial Analysis of Gene Expression (SAGE profiles of 26 human breast carcinomas based on their estrogen receptor α (ER status. Thus, producing a breast cancer SAGE database of almost 2.5 million tags, representing over 50,000 transcripts. Results We identified 520 transcripts differentially expressed between ERα-positive (+ and ERα-negative (- primary breast tumors (Fold change ≥ 2; p Estrogen Responsive Elements (EREs distributed on the promoter regions of 163 out of the 473 up-modulated genes in ERα (+ breast tumors. In brief, we observed predominantly up-regulation of cell growth related genes, DNA binding and transcription factor activity related genes based on Gene Ontology (GO biological functional annotation. GO terms over-representation analysis showed a statistically significant enrichment of various transcript families including: metal ion binding related transcripts (p = 0.011, calcium ion binding related transcripts (p = 0.033 and steroid hormone receptor activity related transcripts (p = 0.031. SAGE data associated with ERα status was compared with reported information from breast cancer DNA microarrays studies. A significant proportion of ERα associated gene expression changes was validated by this cross-platform comparison. However, our SAGE study also identified novel sets of genes as highly expressed in ERα (+ invasive breast tumors not previously reported. These observations were further validated in an independent set of human breast tumors by means of real time RT-PCR. Conclusion The integration of the breast cancer comparative transcriptome analysis based on ERα status coupled to

  5. Application of δ13C and δ15N isotopic signatures of organic matter fractions sequentially separated from adjacent arable and forest soils to identify carbon stabilization mechanisms

    Directory of Open Access Journals (Sweden)

    M. Sommer

    2011-03-01

    Full Text Available Identifying the chemical mechanisms behind soil carbon bound in organo-mineral complexes is necessary to determine the degree to which soil organic carbon is stabilized belowground. We used the δ13C and δ15N isotopic signatures from two organic matter (OM fractions from soil to identify the likely binding mechanisms involved. We used OM fractions hypothesized to contain carbon stabilized through organo-mineral complexes: (1 OM separated chemically with sodium pyrophosphate (OM(PY and (2 OM stabilized in microstructures found in the chemical extraction residue (OM(ER. Furthermore, because the OM fractions were separated from five different soils with paired forest and arable land use histories, we could address the impact of land use change on carbon binding and processing mechanisms within these soils. We used partial least squares regression to analyze patterns in the isotopic signature of OM with established proxies of different binding mechanisms. Parsing soil OM into different fractions is a systematic method of dissection, however, we are primarily interested in how OM is bound in soil as a whole, requiring a means of re-assembly. Thus, we implemented the recent zonal framework described by Kleber et al. (2007 to relate our findings to undisturbed soil. The δ15N signature of OM fractions served as a reliable indicator for microbial processed carbon in both arable and forest land use types. The δ13C signature of OM fractions in arable sites did not correlate well with proxies of soil mineral properties while a consistent pattern of enrichment was seen in the δ13C of OM fractions in the forest sites. We found a significant difference in δ13C of pooled OM fractions between the forest and arable land use type although it was relatively small (<1‰. We found different binding mechanisms predominate in each land use type. The isotopic signatures of OM fractions from arable soils were highly related to the clay and silt size particles

  6. Application of δ13C and δ15N isotopic signatures of organic matter fractions sequentially separated from adjacent arable and forest soils to identify carbon stabilization mechanisms

    Science.gov (United States)

    Kayler, Z. E.; Kaiser, M.; Gessler, A.; Ellerbrock, R. H.; Sommer, M.

    2011-03-01

    Identifying the chemical mechanisms behind soil carbon bound in organo-mineral complexes is necessary to determine the degree to which soil organic carbon is stabilized belowground. We used the δ13C and δ15N isotopic signatures from two organic matter (OM) fractions from soil to identify the likely binding mechanisms involved. We used OM fractions hypothesized to contain carbon stabilized through organo-mineral complexes: (1) OM separated chemically with sodium pyrophosphate (OM(PY)) and (2) OM stabilized in microstructures found in the chemical extraction residue (OM(ER)). Furthermore, because the OM fractions were separated from five different soils with paired forest and arable land use histories, we could address the impact of land use change on carbon binding and processing mechanisms within these soils. We used partial least squares regression to analyze patterns in the isotopic signature of OM with established proxies of different binding mechanisms. Parsing soil OM into different fractions is a systematic method of dissection, however, we are primarily interested in how OM is bound in soil as a whole, requiring a means of re-assembly. Thus, we implemented the recent zonal framework described by Kleber et al. (2007) to relate our findings to undisturbed soil. The δ15N signature of OM fractions served as a reliable indicator for microbial processed carbon in both arable and forest land use types. The δ13C signature of OM fractions in arable sites did not correlate well with proxies of soil mineral properties while a consistent pattern of enrichment was seen in the δ13C of OM fractions in the forest sites. We found a significant difference in δ13C of pooled OM fractions between the forest and arable land use type although it was relatively small (<1‰). We found different binding mechanisms predominate in each land use type. The isotopic signatures of OM fractions from arable soils were highly related to the clay and silt size particles amount while

  7. The Interferon-signature of Sjögren’s Syndrome: How Unique Biomarkers Can Identify Underlying Inflammatory and Immunopathological Mechanisms of Specific Diseases

    Directory of Open Access Journals (Sweden)

    Cuong eNguyen

    2013-07-01

    Full Text Available Innate immune responses direct the nature and specificity of downstream adaptive responses in autoimmune diseases. One of the strongest markers of innate immunity is the up-regulated expression of interferon (IFN and IFN-responsive/stimulated genes (IRGs/ISGs. While multiple IRGs are induced during the innate phase of host responses, transcriptome data suggest unique IRG-signatures for different diseases. Sjögren’s syndrome (SjS is characterized by chronic immune attacks against exocrine glands leading to exocrine dysfunction, plus strong up-regulated expressions of IFN IRG transcripts. Genome-wide transcriptome analyses indicate that differentially-expressed IRGs are restricted during disease development and therefore define underlying etiopathological mechanisms. Here we review the innate immune-associated IFN-signature of SjS and show how differential gene expressions of IRG/ISG sets interact molecularly and biologically to identify critical details of SjS etiopathogenesis.

  8. Genome-wide association analysis identifies three new breast cancer susceptibility loci

    DEFF Research Database (Denmark)

    Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki;

    2012-01-01

    Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ...

  9. Genome-wide association analysis identifies three new breast cancer susceptibility loci

    NARCIS (Netherlands)

    Ghoussaini, M.; Fletcher, O.; Michailidou, K.; Turnbull, C.; Schmidt, M.K.; Dicks, E.; Dennis, J.; Wang, Q.; Humphreys, M.K.; Luccarini, C.; Baynes, C.; Conroy, D.; Maranian, M.; Ahmed, S.; Driver, K.; Johnson, N.; Orr, N.; dos Santos Silva, I.; Waisfisz, Q.; Meijers-Heijboer, H.; Uitterlinden, A.G.; Rivadeneira, F.; Hall, P.; Czene, K.; Irwanto, A.; Liu, J.; Nevanlinna, H.; Aittomaki, K.; Blomqvist, C.; Meindl, A.; Schmutzler, R.K.; Muller-Myhsok, B.; Lichtner, P.; Chang-Claude, J.; Hein, R.; Nickels, S.; Flesch-Janys, D.; Tsimiklis, H.; Makalic, E.; Schmidt, D.; Bui, M.; Hopper, J.L.; Apicella, C.; Park, D.J.; Southey, M.; Hunter, D.J.; Chanock, S.J.; Broeks, A.; Verhoef, S.; Hogervorst, F.B.; Fasching, P.A.; Lux, M.P.; Beckmann, M.W.; Ekici, A.B.; Sawyer, E.; Tomlinson, I.; Kerin, M.; Marme, F.; Schneeweiss, A.; Sohn, C.; Burwinkel, B.; Guenel, P.; Truong, T.; Cordina-Duverger, E.; Menegaux, F.; Bojesen, S.E.; Nordestgaard, B.G.; Nielsen, S.F.; Flyger, H.; Milne, R.L.; Alonso, M.R.; Gonzalez-Neira, A.; Benitez, J.; Anton-Culver, H.; Ziogas, A.; Bernstein, L.; Dur, C.C.; Brenner, H.; Muller, H.; Arndt, V.; Stegmaier, C.; Justenhoven, C.; Brauch, H.; Bruning, T.; Wang-Gohrke, S.; Eilber, U.; Dork, T.; Schurmann, P.; Bremer, M.; Hillemanns, P.; Bogdanova, N.V.; Antonenkova, N.N.; Rogov, Y.I.; Karstens, J.H.; Bermisheva, M.; Prokofieva, D.; Ligtenberg, M.J.

    2012-01-01

    Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for approximately 8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies

  10. Large-scale genotyping identifies 41 new loci associated with breast cancer risk

    DEFF Research Database (Denmark)

    Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna;

    2013-01-01

    Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ∼9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10...

  11. A hypoxic signature marks tumors formed by disseminated tumor cells in the BALB-neuT mammary cancer model.

    Science.gov (United States)

    Msaki, Aichi; Pastò, Anna; Curtarello, Matteo; Arigoni, Maddalena; Barutello, Giuseppina; Calogero, Raffaele Adolfo; Macagno, Marco; Cavallo, Federica; Amadori, Alberto; Indraccolo, Stefano

    2016-05-31

    Metastasis is the final stage of cancer progression. Some evidence indicates that tumor cell dissemination occurs early in the natural history of cancer progression. Disseminated tumor cells (DTC) have been described in the bone marrow (BM) of cancer patients as well as in experimental models, where they correlate with later development of metastasis. However, little is known about the tumorigenic features of DTC obtained at different time points along tumor progression. Here, we found that early DTC isolated from BM of 15-17 week-old Her2/neu transgenic (BALB-neuT) mice were not tumorigenic in immunodeficient mice. In contrast, DTC-derived tumors were easily detectable when late DTC obtained from 19-22 week-old BALB-neuT mice were injected. Angiogenesis, which contributes to regulate tumor dormancy, appeared dispensable to reactivate late DTC, although it accelerated growth of secondary DTC tumors. Compared with parental mammary tumors, gene expression profiling disclosed a distinctive transcriptional signature of late DTC tumors which was enriched for hypoxia-related transcripts and was maintained in ex-vivo cell culture. Altogether, these findings highlight a different tumorigenic potential of early and late DTC in the BALB-neuT model and describe a HIF-1α-related transcriptional signature in DTC tumors, which may render DTC angiogenesis-competent, when placed in a favourable environment.

  12. Xmrk, kras and myc transgenic zebrafish liver cancer models share molecular signatures with subsets of human hepatocellular carcinoma.

    Directory of Open Access Journals (Sweden)

    Weiling Zheng

    Full Text Available Previously three oncogene transgenic zebrafish lines with inducible expression of xmrk, kras or Myc in the liver have been generated and these transgenic lines develop oncogene-addicted liver tumors upon chemical induction. In the current study, comparative transcriptomic approaches were used to examine the correlation of the three induced transgenic liver cancers with human liver cancers. RNA profiles from the three zebrafish tumors indicated relatively small overlaps of significantly deregulated genes and biological pathways. Nevertheless, the three transgenic tumor signatures all showed significant correlation with advanced or very advanced human hepatocellular carcinoma (HCC. Interestingly, molecular signature from each oncogene-induced zebrafish liver tumor correlated with only a small subset of human HCC samples (24-29% and there were conserved up-regulated pathways between the zebrafish and correlated human HCC subgroup. The three zebrafish liver cancer models together represented nearly half (47.2% of human HCCs while some human HCCs showed significant correlation with more than one signature defined from the three oncogene-addicted zebrafish tumors. In contrast, commonly deregulated genes (21 up and 16 down in the three zebrafish tumor models generally showed accordant deregulation in the majority of human HCCs, suggesting that these genes might be more consistently deregulated in a broad range of human HCCs with different molecular mechanisms and thus serve as common diagnosis markers and therapeutic targets. Thus, these transgenic zebrafish models with well-defined oncogene-induced tumors are valuable tools for molecular classification of human HCCs and for understanding of molecular drivers in hepatocarcinogenesis in each human HCC subgroup.

  13. Genome-wide sequencing of cellular microRNAs identifies a combinatorial expression signature diagnostic of sepsis.

    Directory of Open Access Journals (Sweden)

    Yuqian Ma

    Full Text Available RATIONALE: Sepsis is a common cause of death in the intensive care unit with mortality up to 70% when accompanied by multiple organ dysfunction. Rapid diagnosis and the institution of appropriate antibiotic therapy and pressor support are therefore critical for survival. MicroRNAs are small non-coding RNAs that play an important role in the regulation of numerous cellular processes, including inflammation and immunity. OBJECTIVES: We hypothesized changes in expression of microRNAs during sepsis may be of diagnostic value in the intensive care unit (ICU. METHODS: Massively parallel sequencing of microRNAs was utilised for screening microRNA candidates. Putative microRNAs were validated using quantitative real-time PCR (qRT-PCR. This study includes data from both a training cohort (UK and an independent validation cohort (Sweden. A linear discriminant statistical model was employed to construct a diagnostic microRNA signature. RESULTS: A panel of known and novel microRNAs were detectable in the blood of patients with sepsis. After qRT-PCR validation, microRNA miR-150 and miR-4772-5p-iso were able to discriminate between patients who have systemic inflammatory response syndrome and patients with sepsis. This finding was also validated in independent cohort with an average diagnostic accuracy of 86%. Fractionating the cellular components of blood reveals miR-4772-5p-iso is expressed differentially in monocytes. Functional experiments using primary human monocytes demonstrate that it expressed in response to TLR ligation. CONCLUSIONS: Taken together, these data provide a novel microRNA signature of sepsis that should allow rapid point-of-care diagnostic assessment of patients on ICU and also provide greater insight into the pathobiology of this severe disease.

  14. EphB2: a signature of colorectal cancer stem cells to predict relapse

    Institute of Scientific and Technical Information of China (English)

    Xiaoxue Zhang

    2011-01-01

    @@ Colorectal cancer is one of the most commonly diagnosed cancers and is the second leading cause of death from cancer.Currently, the conventional treatment in clinics is surgery combined with chemotherapy or radiation therapy.Although new drugs have been developed, relapse and metastasis occur in nearly half of colorectal cancer patients.

  15. Differential display identifies overexpression of the USP36 gene, encoding a deubiquitinating enzyme, in ovarian cancer

    Directory of Open Access Journals (Sweden)

    Jianduan Li, Lisa M. Olson, Zhengyan Zhang, Lina Li, Miri Bidder, Loan Nguyen, John Pfeifer, Janet S. Rader

    2008-01-01

    Full Text Available Objectives. To find potential diagnostic markers or therapeutic targets, we used differential display technique to identify genes that are over or under expressed in human ovarian cancer. Methods. Genes were initially identified by differential display between two human ovarian surface epithelium cultures and two ovarian cancer cell lines, A2780 and Caov-3. Genes were validated by relative quantitative RT-PCR and RNA in situ hybridization. Results. Twenty-eight non-redundant sequences were expressed differentially in the normal ovarian epithelium and ovarian cancer cell lines. Seven of the 28 sequences showed differential expression between normal ovary and ovarian cancer tissue by RT-PCR. USP36 was over-expressed in ovarian cancer cell lines and tissues by RT-PCR and RNA in situ hybridization. Northern blot analysis and RT-PCR revealed two transcripts for USP36 in ovarian tissue. The major transcript was more specific for ovarian cancer and was detected by RT-PCR in 9/9 ovarian cancer tissues, 3/3 cancerous ascites, 5/14 (36% sera from patients with ovarian cancer, and 0/7 sera from women without ovarian cancer. Conclusion. USP36 is overexpressed in ovarian cancer compared to normal ovary and its transcripts were identified in ascites and serum of ovarian cancer patients.

  16. MuSiC: Identifying mutational significance in cancer genomes

    OpenAIRE

    Dees, Nathan D.; Zhang, Qunyuan; Kandoth, Cyriac; Wendl, Michael C.; Schierding, William; Koboldt, Daniel C.; Mooney, Thomas B.; Matthew B Callaway; Dooling, David; Elaine R Mardis; Wilson, Richard K.; Ding, Li

    2012-01-01

    Massively parallel sequencing technology and the associated rapidly decreasing sequencing costs have enabled systemic analyses of somatic mutations in large cohorts of cancer cases. Here we introduce a comprehensive mutational analysis pipeline that uses standardized sequence-based inputs along with multiple types of clinical data to establish correlations among mutation sites, affected genes and pathways, and to ultimately separate the commonly abundant passenger mutations from the truly sig...

  17. The potential diagnostic value of serum microRNA signature in patients with pancreatic cancer

    DEFF Research Database (Denmark)

    Johansen, Julia S; Calatayud, Dan; Albieri, Vanna;

    2016-01-01

    Biomarkers for early diagnosis of patients with pancreatic cancer (PC) are needed. Our aim was to identify panels of miRNAs in serum in combination with CA 19-9 for use in the diagnosis of PC. Four hundred seventeen patients with PC were included prospectively from Denmark (n = 306) and Germany (n...... = 111). Controls included 59 patients with chronic pancreatitis (CP) and 248 healthy subjects (HS). MiRNAs were analyzed in pretreatment serum samples from 3 cohorts: discovery cohort (754 human miRNAs, TaqMan(®) Human MicroRNA assay, Applied Biosystem; PC n = 133, controls n = 72); training cohort (34...

  18. Urinary microRNA-based signature improves accuracy of detection of clinically relevant prostate cancer within the prostate-specific antigen grey zone.

    Science.gov (United States)

    Salido-Guadarrama, Alberto Ivan; Morales-Montor, Jorge Gustavo; Rangel-Escareño, Claudia; Langley, Elizabeth; Peralta-Zaragoza, Oscar; Cruz Colin, Jose Luis; Rodriguez-Dorantes, Mauricio

    2016-06-01

    At present, prostate-specific antigen (PSA) is used as a clinical biomarker for prostate cancer (PCa) diagnosis; however, a large number of patients with benign prostate hyperplasia (BPH) with PSA levels in the 'gray area' (4-10 ng/ml) are currently subjected to unnecessary biopsy due to overdiagnosis. Certain microRNAs (miRs) have been proven to be useful biomarkers, several of which are detectable in bodily fluids. The present study identified and validated a urinary miR‑based signature to enhance the specificity of PCa diagnosis and to reduce the number of patients with benign conditions undergoing biopsy. Seventy‑three urine samples from Mexican patients with diagnosis of PCa with a Gleason score ≥7 and 70 patients diagnosed with BPH were collected after digital rectal examination (DRE) of the prostate. miR expression profiles were determined using TaqMan Low Density Array experiments, and normalized Ct values for the miRs were compared between PCa and BPH groups. Receiver operating characteristic (ROC) curve analysis was performed to evaluate whether miR detection in urine is suitable for distinguishing patients with PCa from those with BPH. The identified miR‑100/200b signature was significantly correlated with PCa. Using a multivariable logistic regression approach, a base model including the clinical variables age, prostate‑specific antigen (PSA), the percentage of free PSA and DRE was generated, and a second base model additionally contained the miR‑100/200b signature. ROC analysis demonstrated that the combined model significantly outperformed the capacity of PSA (P<0.001) and the base model (P=0.01) to discriminate between PCa and BPH patients. In terms of evaluation of the sub‑group of patients in the gray zone of PSA levels, the performance of the combined model for predicting PCa cases was significantly superior to PSA level determination (P<0.001) and the base model (P=0.009). In addition, decision curve analysis demonstrated that the

  19. Signature MicroRNA expression patterns identified in humans with 22q11.2 deletion/DiGeorge syndrome.

    Science.gov (United States)

    de la Morena, M Teresa; Eitson, Jennifer L; Dozmorov, Igor M; Belkaya, Serkan; Hoover, Ashley R; Anguiano, Esperanza; Pascual, M Virginia; van Oers, Nicolai S C

    2013-04-01

    Patients with 22q11.2 deletion syndrome have heterogeneous clinical presentations including immunodeficiency, cardiac anomalies, and hypocalcemia. The syndrome arises from hemizygous deletions of up to 3Mb on chromosome 22q11.2, a region that contains 60 genes and 4 microRNAs. MicroRNAs are important post-transcriptional regulators of gene expression, with mutations in several microRNAs causal to specific human diseases. We characterized the microRNA expression patterns in the peripheral blood of patients with 22q11.2 deletion syndrome (n=31) compared to normal controls (n=22). Eighteen microRNAs had a statistically significant differential expression (p<0.05), with miR-185 expressed at 0.4× normal levels. The 22q11.2 deletion syndrome cohort exhibited microRNA expression hyper-variability and group dysregulation. Selected microRNAs distinguished patients with cardiac anomalies, hypocalcemia, and/or low circulating T cell counts. In summary, microRNA profiling of chromosome 22q11.2 deletion syndrome/DiGeorge patients revealed a signature microRNA expression pattern distinct from normal controls with clinical relevance.

  20. Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

    Science.gov (United States)

    Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

    2015-12-01

    Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

  1. Application of δ13C and δ15N isotopic signatures of organic matter fractions sequentially separated from adjacent arable and forest soils to identify carbon stabilization mechanisms

    Directory of Open Access Journals (Sweden)

    M. Sommer

    2011-10-01

    Full Text Available Identifying the chemical mechanisms behind soil carbon bound in organo-mineral complexes is necessary to determine the degree to which soil organic carbon is stabilized belowground. Analysis of δ13C and δ15N isotopic signatures of stabilized OM fractions along with soil mineral characteristics may yield important information about OM-mineral associations and their processing history. We anlayzed the δ13C and δ15N isotopic signatures from two organic matter (OM fractions along with soil mineral proxies to identify the likely binding mechanisms involved. We analyzed OM fractions hypothesized to contain carbon stabilized through organo-mineral complexes: (1 OM separated chemically with sodium pyrophosphate (OM(PY and (2 OM occluded in micro-structures found in the chemical extraction residue (OM(ER. Because the OM fractions were separated from five different soils with paired forest and arable land use histories, we could address the impact of land use change on carbon binding and processing mechanisms. We used partial least squares regression to analyze patterns in the isotopic signature of OM with established mineral and chemical proxies indicative for certain binding mechanisms. We found different mechanisms predominate in each land use type. For arable soils, the formation of OM(PY-Ca-mineral associations was identified as an important OM binding mechanism. Therefore, we hypothesize an increased stabilization of microbial processed OM(PY through Ca2+ interactions. In general, we found the forest soils to contain on average 10% more stabilized carbon relative to total carbon stocks, than the agricultural counter part. In forest soils, we found a positive relationship between isotopic signatures of OM(PY and the ratio of soil organic carbon content to soil surface area (SOC/SSA. This indicates that the OM(PY fractions of forest soils represent layers of slower exchange not directly attached to mineral surfaces. From the isotopic composition

  2. Cancer biomarkers defined by autoantibody signatures to aberrant O-glycopeptide epitopes

    DEFF Research Database (Denmark)

    Wandall, Hans H; Blixt, Ola; Tarp, Mads A;

    2010-01-01

    -glycopeptide microarray was developed that detected IgG antibodies to aberrant O-glycopeptide epitopes in patients vaccinated with a keyhole limpet hemocyanin-conjugated truncated MUC1 peptide. We detected cancer-associated IgG autoantibodies in sera from breast, ovarian, and prostate cancer patients against different...... evaluated whether autoantibodies generated to aberrant O-glycoforms of MUC1 might serve as sensitive diagnostic biomarkers for cancer. Using an antibody-based glycoprofiling ELISA assay, we documented that aberrant truncated glycoforms were not detected in sera of cancer patients. An O......Autoantibodies to cancer antigens hold promise as biomarkers for early detection of cancer. Proteins that are aberrantly processed in cancer cells are likely to present autoantibody targets. The extracellular mucin MUC1 is overexpressed and aberrantly glycosylated in many cancers; thus, we...

  3. Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues.

    Science.gov (United States)

    Hwang, S-I; Thumar, J; Lundgren, D H; Rezaul, K; Mayya, V; Wu, L; Eng, J; Wright, M E; Han, D K

    2007-01-01

    Successful treatment of multiple cancer types requires early detection and identification of reliable biomarkers present in specific cancer tissues. To test the feasibility of identifying proteins from archival cancer tissues, we have developed a methodology, termed direct tissue proteomics (DTP), which can be used to identify proteins directly from formalin-fixed paraffin-embedded prostate cancer tissue samples. Using minute prostate biopsy sections, we demonstrate the identification of 428 prostate-expressed proteins using the shotgun method. Because the DTP method is not quantitative, we employed the absolute quantification method and demonstrate picogram level quantification of prostate-specific antigen. In depth bioinformatics analysis of these expressed proteins affords the categorization of metabolic pathways that may be important for distinct stages of prostate carcinogenesis. Furthermore, we validate Wnt-3 as an upregulated protein in cancerous prostate cells by immunohistochemistry. We propose that this general strategy provides a roadmap for successful identification of critical molecular targets of multiple cancer types.

  4. Identifying the unique ground motion signatures of supershear earthquakes - The one-two punch effect on high-rise buildings

    Science.gov (United States)

    Rosakis, A.; Mello, M.; Bhat, H.; Krishnan, S.; Kanamori, H.

    2011-12-01

    Directly studying earthquakes presents a host of insurmountable difficulties, the least of which is our inability to trigger earthquakes of various magnitudes at will and the lack of means of scrutinizing the behavior at depth while the quake propagates. We have developed techniques to produce miniature (or surrogate) laboratory earthquakes and follow their progress with high-speed imaging tools. Our laboratory quakes mimic actual ones, and have allowed us to demonstrate the existence of ruptures of super-shear or intersonic rupture speeds. The propagating fronts of such supershear ruptures feature a Mach-cone of shear shock waves similar to that of supersonic aircraft. For earthquake ruptures transitioning from sub-Rayleigh to supershear rupture speeds, this unusual shear Mach cone feature is also followed by a trailing Rayleigh disturbance which is all that remains of the old sub-Rayleigh rupture after transition is complete. Each propagating disturbance contributes to the unique ground motion signature in the near field. We refer to this as a one-two punch scenario. In particular, ground motion associated with passage of the shear Mach features a dominant fault-parallel velocity component while ground motion from the trailing Rayleigh field is characterized by a dominant fault-normal velocity component (characteristic of common, sub-shear earthquake ruptures). Appropriate scaling of the laboratory ground velocity measurements are used to shake 3-D numerical models of high-rise buildings (located in near fault locations) with hypothetical supershear and sub-Rayleigh earthquakes with unexpected implication to building safety and seismic hazard analysis.

  5. Novel circulating microRNA signature as a potential non-invasive multi-marker test in ER-positive early-stage breast cancer

    DEFF Research Database (Denmark)

    Kodahl, Annette R; Lyng, Maria Bibi; Binder, Harald;

    2014-01-01

    specific algorithm based on the 9 miRNA signature, the risk for future individuals can be predicted. Since microRNAs are highly stable in blood components, this signature might be useful in the development of a blood-based multi-marker test to improve early detection of breast cancer. Such a test could......INTRODUCTION: There are currently no highly sensitive and specific minimally invasive biomarkers for detection of early-stage breast cancer. MicroRNAs (miRNAs) are present in the circulation and may be unique biomarkers for early diagnosis of human cancers. The aim of this study was to investigate...... the differential expression of miRNAs in the serum of breast cancer patients and healthy controls. METHODS: Global miRNA analysis was performed on serum from 48 patients with ER-positive early-stage breast cancer obtained at diagnosis (24 lymph node-positive and 24 lymph node-negative) and 24 age...

  6. Meta-Analysis of Public Microarray Datasets Reveals Voltage-Gated Calcium Gene Signatures in Clinical Cancer Patients.

    Directory of Open Access Journals (Sweden)

    Chih-Yang Wang

    Full Text Available Voltage-gated calcium channels (VGCCs are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org, a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment.

  7. Age-specific gene expression signatures for breast tumors and cross-species conserved potential cancer progression markers in young women.

    Directory of Open Access Journals (Sweden)

    Dilek Colak

    Full Text Available Breast cancer in young women is more aggressive with a poorer prognosis and overall survival compared to older women diagnosed with the disease. Despite recent research, the underlying biology and molecular alterations that drive the aggressive nature of breast tumors associated with breast cancer in young women have yet to be elucidated. In this study, we performed transcriptomic profile and network analyses of breast tumors arising in Middle Eastern women to identify age-specific gene signatures. Moreover, we studied molecular alterations associated with cancer progression in young women using cross-species comparative genomics approach coupled with copy number alterations (CNA associated with breast cancers from independent studies. We identified 63 genes specific to tumors in young women that showed alterations distinct from two age cohorts of older women. The network analyses revealed potential critical regulatory roles for Myc, PI3K/Akt, NF-κB, and IL-1 in disease characteristics of breast tumors arising in young women. Cross-species comparative genomics analysis of progression from pre-invasive ductal carcinoma in situ (DCIS to invasive ductal carcinoma (IDC revealed 16 genes with concomitant genomic alterations, CCNB2, UBE2C, TOP2A, CEP55, TPX2, BIRC5, KIAA0101, SHCBP1, UBE2T, PTTG1, NUSAP1, DEPDC1, HELLS, CCNB1, KIF4A, and RRM2, that may be involved in tumorigenesis and in the processes of invasion and progression of disease. Array findings were validated using qRT-PCR, immunohistochemistry, and extensive in silico analyses of independently performed microarray datasets. To our knowledge, this study provides the first comprehensive genomic analysis of breast cancer in Middle Eastern women in age-specific cohorts and potential markers for cancer progression in young women. Our data demonstrate that cancer appearing in young women contain distinct biological characteristics and deregulated signaling pathways. Moreover, our integrative

  8. Detection of the Odor Signature of Ovarian Cancer using DNA-Decorated Carbon Nanotube Field Effect Transistor Arrays

    Science.gov (United States)

    Kehayias, Christopher; Kybert, Nicholas; Yodh, Jeremy; Johnson, A. T. Charlie

    Carbon nanotubes are low-dimensional materials that exhibit remarkable chemical and bio-sensing properties and have excellent compatibility with electronic systems. Here, we present a study that uses an electronic olfaction system based on a large array of DNA-carbon nanotube field effect transistors vapor sensors to analyze the VOCs of blood plasma samples collected from patients with malignant ovarian cancer, patients with benign ovarian lesions, and age-matched healthy subjects. Initial investigations involved coating each CNT sensor with single-stranded DNA of a particular base sequence. 10 distinct DNA oligomers were used to functionalize the carbon nanotube field effect transistors, providing a 10-dimensional sensor array output response. Upon performing a statistical analysis of the 10-dimensional sensor array responses, we showed that blood samples from patients with malignant cancer can be reliably differentiated from those of healthy control subjects with a p-value of 3 x 10-5. The results provide preliminary evidence that the blood of ovarian cancer patients contains a discernable volatile chemical signature that can be detected using DNA-CNT nanoelectronic vapor sensors, a first step towards a minimally invasive electronic diagnostic technology for ovarian cancer.

  9. Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior

    International Nuclear Information System (INIS)

    Colon cancer patients with the same stage show diverse clinical behavior due to tumor heterogeneity. We aimed to discover distinct classes of tumors based on microarray expression patterns, to analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters and to study differences in the survival. Hierarchical clustering was performed for class discovery in 88 colon tumors (stages I to IV). Pathways analysis and correlations between clinical parameters and our classification were analyzed. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the main subtype was generated using the 3-Nearest-Neighbor method. Coincidences with other prognostic predictors were assesed. Hierarchical clustering identified four robust tumor subtypes with biologically and clinically distinct behavior. Stromal components (p < 0.001), nuclear β-catenin (p = 0.021), mucinous histology (p = 0.001), microsatellite-instability (p = 0.039) and BRAF mutations (p < 0.001) were associated to this classification but it was independent of Dukes stages (p = 0.646). Molecular subtypes were established from stage I. High-stroma-subtype showed increased levels of genes and altered pathways distinctive of tumour-associated-stroma and components of the extracellular matrix in contrast to Low-stroma-subtype. Mucinous-subtype was reflected by the increased expression of trefoil factors and mucins as well as by a higher proportion of MSI and BRAF mutations. Tumor subtypes were validated using an external set of 78 patients. A 167 gene signature associated to the Low-stroma-subtype distinguished low risk patients from high risk patients in the external cohort (Dukes B and C:HR = 8.56(2.53-29.01); Dukes B,C and D:HR = 1.87(1.07-3.25)). Eight different reported survival gene signatures segregated our tumors into two groups the Low-stroma-subtype and the other tumor subtypes. We have identified novel

  10. A 26-Gene Hypoxia Signature Predicts Benefit from Hypoxia-Modifying Therapy in Laryngeal Cancer but Not Bladder Cancer

    NARCIS (Netherlands)

    Eustace, A.; Mani, N.; Span, P.N.; Irlam, J.J.; Taylor, J.; Betts, G.N.; Denley, H.; Miller, C.J.; Homer, J.J.; Rojas, A.M.; Hoskin, P.J.; Buffa, F.M.; Harris, A.L.; Kaanders, J.H.A.M.; West, C.M.

    2013-01-01

    PURPOSE: Tumor hypoxia is associated with a poor prognosis, hypoxia modification improves outcome, and hypoxic status predicts benefit from treatment. Yet, there is no universal measure of clinical hypoxia. The aim of this study was to investigate whether a 26-gene hypoxia signature predicted benefi

  11. Identifying priority actions for improving patient satisfaction with outpatient cancer care.

    Science.gov (United States)

    Gesell, Sabina B; Gregory, Nancy

    2004-01-01

    In parallel to developing new cancer therapies, the healthcare community has the responsibility of creating positive treatment experiences for patients. Data from 5907 cancer outpatients treated at 23 hospitals across the United States were analyzed to identify the top priorities for service improvement in outpatient cancer treatment facilities. They included meeting patients' emotional needs, providing information to patients and family members, reducing waiting times, and providing convenience and coordinated care among physicians and other care providers.

  12. Researchers Use a Kinome Screen to Identify New Therapeutic Targets | Office of Cancer Genomics

    Science.gov (United States)

    The tumor suppressor p53 is mutated in over 50% of head and neck squamous cell carcinomas (HNSCC), yet there are currently no available therapies to target it. CTD2 researchers at the Fred Hutchison Cancer Research Center hypothesized that HNSCC cancer cells with p53 mutations are dependent on particular kinases for survival. In a study published in Clinical Cancer Research, they sought to identify these kinases using RNAi against known kinase genes in mouse and human cell lines.

  13. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    OpenAIRE

    Jesús Lascorz; Kari Hemminki; Asta Försti

    2011-01-01

    Background: A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-r...

  14. Transcriptional Profiling of Whole Blood Identifies a Unique 5-Gene Signature for Myelofibrosis and Imminent Myelofibrosis Transformation

    DEFF Research Database (Denmark)

    Hasselbalch, Hans Carl; Skov, Vibe; Stauffer Larsen, Thomas;

    2014-01-01

    selectively and highly deregulated in myelofibrosis patients. Gene expression microarray studies have been performed on whole blood from 69 patients with myeloproliferative neoplasms. Amongst the top-20 of the most upregulated genes in PMF compared to controls, we identified 5 genes (DEFA4, ELA2, OLFM4, CTSG...

  15. Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis

    Institute of Scientific and Technical Information of China (English)

    Kai; Shi; Zhi-Tong; Bing; Gui-Qun; Cao; Ling; Guo; Ya-Na; Cao; Hai-Ou; Jiang; Mei-Xia; Zhang

    2015-01-01

    AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.

  16. Metabolic Signatures of Lung Cancer in Biofluids: NMR-Based Metabonomics of Blood Plasma

    OpenAIRE

    Rocha, Cláudia M.; Carrola, Joana; Barros, António S.; Gil, Ana M; Goodfellow, Brian J; Carreira, Isabel M; Bernardo, Joao; Gomes, Ana; Sousa, Vitor; Carvalho, Lina; Duarte, Iola F.

    2011-01-01

    In this work, the variations in the metabolic profile of blood plasma from lung cancer patients and healthy controls were investigated through NMR-based metabonomics, to assess the potential of this approach for lung cancer screening and diagnosis. PLS-DA modeling of CPMG spectra from plasma, subjected to Monte Carlo Cross Validation, allowed cancer patients to be discriminated from controls with sensitivity and specificity levels of about 90%. Relatively lower HDL and higher VLDL + LDL in th...

  17. Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

    DEFF Research Database (Denmark)

    Kote-Jarai, Zsofia; Olama, Ali Amin Al; Giles, Graham G;

    2011-01-01

    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results...

  18. Seven prostate cancer susceptibility loci identified by a multi-stage genome-wide association study

    DEFF Research Database (Denmark)

    Kote-Jarai, Zsofia; Olama, Ali Amin Al; Giles, Graham G;

    2011-01-01

    Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of st...

  19. Transcriptome analysis of recurrently deregulated genes across multiple cancers identifies new pan-cancer biomarkers

    DEFF Research Database (Denmark)

    Kaczkowski, Bogumil; Tanaka, Yuji; Kawaji, Hideya;

    2016-01-01

    RNAs which are upregulated in cancer, defining promoters which overlap with repetitive elements (especially SINE/Alu and LTR/ERV1 elements) that are often upregulated in cancer. Lastly, we documented for the first time upregulation of multiple copies of the REP522 interspersed repeat in cancer. Overall...

  20. A Microbial Signature Approach to Identify Fecal Pollution in the Waters Off an Urbanized Coast of Lake Michigan

    OpenAIRE

    Ryan J Newton; Bootsma, Melinda J.; Morrison, Hilary G; Sogin, Mitchell L.; McLellan, Sandra L.

    2013-01-01

    Urban coasts receive watershed drainage from ecosystems that include highly developed lands with sewer and stormwater infrastructure. In these complex ecosystems, coastal waters are often contaminated with fecal pollution, where multiple delivery mechanisms that often contain multiple fecal sources make it difficult to mitigate the pollution. Here, we exploit bacterial community sequencing of the V6 and V6V4 hypervariable regions of the bacterial 16S rRNA gene to identify bacterial distributi...

  1. Virulence determinants of Salmonella Gallinarum biovar Pullorum identified by PCR signature-tagged mutagenesis and the spiC mutant as a candidate live attenuated vaccine.

    Science.gov (United States)

    Geng, Shizhong; Jiao, Xinan; Barrow, Paul; Pan, Zhiming; Chen, Xiang

    2014-01-31

    Salmonella Gallinarum biovar Pullorum (S. Gallinarum biovar Pullorum) is the causative agent of pullorum disease (PD) in chickens which results in considerable economic losses to the poultry industries in developing countries. PCR-Signature Tagged Mutagenesis was used to identify virulence determinants of S. Gallinarum biovar Pullorum and novel attenuated live vaccine candidates for use against this disease. A library of 1800 signature-tagged S. Gallinarum biovar Pullorum mutants was constructed and screened for virulence-associated genes in chickens. The attenuation of 10 mutants was confirmed by in vivo and in vitro competitive index (CI) studies. The transposons were found to be located in SPI-1 (2/10 mutants), SPI-2 (3/10), the virulence plasmid (1/10) and non-SPI genes (4/10). One highly attenuated spiC mutant persisted in spleen and liver for less than 10 days and induced high levels of circulating antibody and protective immunity against oral challenge in young broiler chickens. The spiC mutant is a potential new vaccine candidate for use with chickens against this disease. PMID:24355532

  2. A loss-of-function genetic screening identifies novel mediators of thyroid cancer cell viability

    Science.gov (United States)

    Cantisani, Maria Carmela; Parascandolo, Alessia; Perälä, Merja; Allocca, Chiara; Fey, Vidal; Sahlberg, Niko; Merolla, Francesco; Basolo, Fulvio; Laukkanen, Mikko O.; Kallioniemi, Olli Pekka; Santoro, Massimo; Castellone, Maria Domenica

    2016-01-01

    RET, BRAF and other protein kinases have been identified as major molecular players in thyroid cancer. To identify novel kinases required for the viability of thyroid carcinoma cells, we performed a RNA interference screening in the RET/PTC1(CCDC6-RET)-positive papillary thyroid cancer cell line TPC1 using a library of synthetic small interfering RNAs (siRNAs) targeting the human kinome and related proteins. We identified 14 hits whose silencing was able to significantly reduce the viability and the proliferation of TPC1 cells; most of them were active also in BRAF-mutant BCPAP (papillary thyroid cancer) and 8505C (anaplastic thyroid cancer) and in RAS-mutant CAL62 (anaplastic thyroid cancer) cells. These included members of EPH receptor tyrosine kinase family as well as SRC and MAPK (mitogen activated protein kinases) families. Importantly, silencing of the identified hits did not affect significantly the viability of Nthy-ori 3-1 (hereafter referred to as NTHY) cells derived from normal thyroid tissue, suggesting cancer cell specificity. The identified proteins are worth exploring as potential novel druggable thyroid cancer targets. PMID:27058903

  3. Role in virulence and protective efficacy in pigs of Salmonella enterica serovar Typhimurium secreted components identified by signature-tagged mutagenesis.

    Science.gov (United States)

    Carnell, Sonya C; Bowen, Alison; Morgan, Eirwen; Maskell, Duncan J; Wallis, Timothy S; Stevens, Mark P

    2007-06-01

    Salmonella enterica serovar Typhimurium (S. Typhimurium) is a zoonotic enteric pathogen of worldwide importance and pigs are a significant reservoir of human infection. Signature-tagged transposon mutagenesis (STM) was used to identify genes required by S. Typhimurium to colonize porcine intestines. A library of 1045 signature-tagged mutants of S. Typhimurium ST4/74 Nal(R) was screened following oral inoculation of pigs in duplicate. A total of 119 attenuating mutations were identified in 95 different genes, many of which encode known or putative secreted or surface-anchored molecules. A large number of attenuating mutations were located within Salmonella pathogenicity islands (SPI)-1 and -2, confirming important roles for type III secretion systems (T3SS)-1 and -2 in intestinal colonization of pigs. Roles for genes encoded in other pathogenicity islands and islets, including the SPI-6-encoded Saf atypical fimbriae, were also identified. Given the role of secreted factors and the protection conferred against other pathogens by vaccination with extracellular and type III secreted proteins, the efficacy of a secreted protein vaccine from wild-type S. Typhimurium following intramuscular vaccination of pigs was evaluated. Serum IgG responses against type III secreted proteins were induced following vaccination and a significant reduction in faecal excretion of S. Typhimurium was observed in the acute phase of infection compared to mock-vaccinated animals. Vaccination with secreted proteins from an isogenic S. Typhimurium prgH mutant produced comparable levels of protection to vaccination with the preparation from the parent strain, indicating that protection was not reliant on T3SS-1 secreted proteins. The data provide valuable information for the control of Salmonella in pigs.

  4. The Development of an Angiogenic Protein "Signature" in Ovarian Cancer Ascites as a Tool for Biologic and Prognostic Profiling.

    Science.gov (United States)

    Trachana, Sofia-Paraskevi; Pilalis, Eleftherios; Gavalas, Nikos G; Tzannis, Kimon; Papadodima, Olga; Liontos, Michalis; Rodolakis, Alexandros; Vlachos, Georgios; Thomakos, Nikolaos; Haidopoulos, Dimitrios; Lykka, Maria; Koutsoukos, Konstantinos; Kostouros, Efthimios; Terpos, Evagelos; Chatziioannou, Aristotelis; Dimopoulos, Meletios-Athanasios; Bamias, Aristotelis

    2016-01-01

    Advanced ovarian cancer (AOC) is one of the leading lethal gynecological cancers in developed countries. Based on the important role of angiogenesis in ovarian cancer oncogenesis and expansion, we hypothesized that the development of an "angiogenic signature" might be helpful in prediction of prognosis and efficacy of anti-angiogenic therapies in this disease. Sixty-nine samples of ascitic fluid- 35 from platinum sensitive and 34 from platinum resistant patients managed with cytoreductive surgery and 1st-line carboplatin-based chemotherapy- were analyzed using the Proteome ProfilerTM Human Angiogenesis Array Kit, screening for the presence of 55 soluble angiogenesis-related factors. A protein profile based on the expression of a subset of 25 factors could accurately separate resistant from sensitive patients with a success rate of approximately 90%. The protein profile corresponding to the "sensitive" subset was associated with significantly longer PFS (8 [95% Confidence Interval {CI}: 8-9] vs. 20 months [95% CI: 15-28]; Hazard ratio {HR}: 8.3, pAOC, which can be used, after appropriate validation, as a prognostic marker and a tool for selection for anti-angiogenic therapies. PMID:27258020

  5. The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil

    OpenAIRE

    Cuezva José M; Sánchez-Aragó María

    2011-01-01

    Abstract Background Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase). The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH), which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a ...

  6. Using NLP to identify cancer cases in imaging reports drawn from radiology information systems.

    Science.gov (United States)

    Patrick, Jon; Asgari, Pooyan; Li, Min; Nguyen, Dung

    2013-01-01

    A Natural Language processing (NLP) classifier has been developed for the Victorian and NSW Cancer Registries with the purpose of automatically identifying cancer reports from imaging services, transmitting them to the Registries and then extracting pertinent cancer information. Large scale trials conducted on over 40,000 reports show the sensitivity for identifying reportable cancer reports is above 98% with a specificity above 96%. Detection of tumour stream, report purpose, and a variety of extracted content is generally above 90% specificity. The differences between report layout and authoring strategies across imaging services appear to require different classifiers to retain this high level of accuracy. Linkage of the imaging data with existing registry records (hospital and pathology reports) to derive stage and recurrence of cancer has commenced and shown very promising results. PMID:23823294

  7. Simulated annealing based algorithm for identifying mutated driver pathways in cancer.

    Science.gov (United States)

    Li, Hai-Tao; Zhang, Yu-Lang; Zheng, Chun-Hou; Wang, Hong-Qiang

    2014-01-01

    With the development of next-generation DNA sequencing technologies, large-scale cancer genomics projects can be implemented to help researchers to identify driver genes, driver mutations, and driver pathways, which promote cancer proliferation in large numbers of cancer patients. Hence, one of the remaining challenges is to distinguish functional mutations vital for cancer development, and filter out the unfunctional and random "passenger mutations." In this study, we introduce a modified method to solve the so-called maximum weight submatrix problem which is used to identify mutated driver pathways in cancer. The problem is based on two combinatorial properties, that is, coverage and exclusivity. Particularly, we enhance an integrative model which combines gene mutation and expression data. The experimental results on simulated data show that, compared with the other methods, our method is more efficient. Finally, we apply the proposed method on two real biological datasets. The results show that our proposed method is also applicable in real practice. PMID:24982873

  8. Identified metabolic signature for assessing red blood cell unit quality is associated with endothelial damage markers and clinical outcomes

    DEFF Research Database (Denmark)

    Bordbar, Aarash; Johansson, Pär I.; Paglia, Giuseppe;

    2016-01-01

    multivariate statistics, we identified a nonlinear decay process exhibiting three distinct metabolic states (Days 0-10, 10-17, and 17-42). Hematologic variables traditionally measured in the transfusion setting (e.g., pH, hemolysis, RBC indices) did not distinguish these three states. Systemic changes in...... were profiled using quantitative metabolomics over 42 days of storage in SAGM with 3- to 4-day time intervals. Metabolic pathway usage during storage was assessed using systems biology methods. The detected time intervals of the metabolic states were compared to clinical outcomes. RESULTS: Using...... years and endothelial damage markers in healthy volunteers undergoing autologous transfusions. CONCLUSION: The state of RBC metabolism may be a better indicator of cellular quality than traditional hematologic variables....

  9. Non-targeted metabolomics identified a common metabolic signature of lethal ventricular tachyarrhythmia (LVTA) in two rat models.

    Science.gov (United States)

    Wang, Xingxing; Wang, Dian; Yu, Xiaojun; Zhang, Guohong; Wu, Jiayan; Zhu, Guanghui; Su, Ruibing; Lv, Junyao

    2016-06-21

    Lethal ventricular tachyarrhythmia (LVTA) is the predominant underlying mechanism of sudden cardiac death (SCD). The aim of this study is to characterize the metabolic features of myocardia following LVTA, and identify potential biomarkers to diagnose LVTA. We developed two LVTA rat models induced by aconitine injection or coronary artery ligation, which represent cardiac ion channel disease-related and cardiac ischemia-related SCD, respectively. The myocardial metabolic profile was investigated by gas chromatography-mass spectrometry and proton nuclear magnetic resonance-based metabolomics. Twenty-three aconitine-injected and 14 coronary artery ligation-treated rats developed LVTA SCD. A total of 38 differential metabolites of myocardia were identified in aconitine-induced LVTA rats, of which 31 metabolites showed a similar change in coronary artery ligation-related LVTA rats. Fatty acids (stearic, palmitic, linoleic, elaidic, and myristic) and branched-chain amino acids (valine, leucine, and isoleucine) were the most down-regulated metabolites. Furthermore, elevated ADP, phosphate, lactate, glutamate, aspartate, threonine, choline and arginine were also observed. Major pathways regarding these dysregulated metabolites post LVTA are energy excessive consumption and deficit, ionic imbalance, oxidative stress, cardiac cytotoxicity and membrane injury. Valine, stearic acid and leucine collectively enable a precision of 92.9% to distinguish LVTA from its control, and are correlated with several arrhythmia indices. Our results uncovered a common metabolic feature of LVTA in myocardia in two rat models, which represent cardiac ion channel disease and cardiac ischemia, respectively. l-Valine, l-leucine and stearic acid jointly confer good potential for distinguishing LVTA, which might be potential biomarkers of LVTA-related SCD. PMID:27138062

  10. HIV and cancer registry linkage identifies a substantial burden of cancers in persons with HIV in India.

    Science.gov (United States)

    Godbole, Sheela V; Nandy, Karabi; Gauniyal, Mansi; Nalawade, Pallavi; Sane, Suvarna; Koyande, Shravani; Toyama, Joy; Hegde, Asha; Virgo, Phil; Bhatia, Kishor; Paranjape, Ramesh S; Risbud, Arun R; Mbulaiteye, Sam M; Mitsuyasu, Ronald T

    2016-09-01

    We utilized computerized record-linkage methods to link HIV and cancer databases with limited unique identifiers in Pune, India, to determine feasibility of linkage and obtain preliminary estimates of cancer risk in persons living with HIV (PLHIV) as compared with the general population.Records of 32,575 PLHIV were linked to 31,754 Pune Cancer Registry records (1996-2008) using a probabilistic-matching algorithm. Cancer risk was estimated by calculating standardized incidence ratios (SIRs) in the early (4-27 months after HIV registration), late (28-60 months), and overall (4-60 months) incidence periods. Cancers diagnosed prior to or within 3 months of HIV registration were considered prevalent.Of 613 linked cancers to PLHIV, 188 were prevalent, 106 early incident, and 319 late incident. Incident cancers comprised 11.5% AIDS-defining cancers (ADCs), including cervical cancer and non-Hodgkin lymphoma (NHL), but not Kaposi sarcoma (KS), and 88.5% non-AIDS-defining cancers (NADCs). Risk for any incident cancer diagnosis in early, late, and combined periods was significantly elevated among PLHIV (SIRs: 5.6 [95% CI 4.6-6.8], 17.7 [95% CI 15.8-19.8], and 11.5 [95% CI 10-12.6], respectively). Cervical cancer risk was elevated in both incidence periods (SIRs: 9.6 [95% CI 4.8-17.2] and 22.6 [95% CI 14.3-33.9], respectively), while NHL risk was elevated only in the late incidence period (SIR: 18.0 [95% CI 9.8-30.20]). Risks for NADCs were dramatically elevated (SIR > 100) for eye-orbit, substantially (SIR > 20) for all-mouth, esophagus, breast, unspecified-leukemia, colon-rectum-anus, and other/unspecified cancers; moderately elevated (SIR > 10) for salivary gland, penis, nasopharynx, and brain-nervous system, and mildly elevated (SIR > 5) for stomach. Risks for 6 NADCs (small intestine, testis, lymphocytic leukemia, prostate, ovary, and melanoma) were not elevated and 5 cancers, including multiple myeloma not seen.Our study demonstrates the feasibility of

  11. High incidence of nasopharyngeal cancer: similarity for 60% of mitochondrial DNA signatures between the Bidayuhs of Borneo and the Bai-yue of Southern China

    Institute of Scientific and Technical Information of China (English)

    Joseph Wee; Tam Cam Ha; Susan Loong; Chao-Nan Qian

    2012-01-01

    Populations in Southern China (Bai-yue) and Borneo (Bidayuh) with high incidence of nasopharyngeal cancer (NPC) share similar mitochondrial DNA signatures,supporting the hypothesis that these two populations may share the same genetic predisposition for NPC,which may have first appeared in a common ancestral reference population before the sea levels rose after the last ice age.

  12. Analysis of molecular intra-patient variation and delineation of a prognostic 12-gene signature in non-muscle invasive bladder cancer; technology transfer from microarrays to PCR

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Reinert, Thomas; Novoradovsky, A;

    2012-01-01

    Background: Multiple clinical risk factors and genetic profiles have been demonstrated to predict progression of non-muscle invasive bladder cancer; however, no easily clinical applicable gene signature has been developed to predict disease progression independent of disease stage and grade. Meth...

  13. Additional value of the 70-gene signature and levels of ER and PR for the prediction of outcome in tamoxifen-treated ER-positive breast cancer

    NARCIS (Netherlands)

    Kok, M. de; Koornstra, R.H.; Mook, S.; Hauptmann, M.; Fles, R.; Jansen, M.P.; Berns, E.M.; Linn, S.C.; Veer, L.J. van 't

    2012-01-01

    BACKGROUND: Breast cancer patients with node positive disease can have an excellent outcome with tamoxifen only. It is unclear whether analysing both the 70-gene signature and hormone receptors provides superior prediction of outcome in tamoxifen-treated patients than either alone. METHODS: Three se

  14. Diagnostic and prognostic signatures from the small non-coding RNA transcriptome in prostate cancer

    DEFF Research Database (Denmark)

    Martens-Uzunova, E S; Jalava, S E; Dits, N F;

    2011-01-01

    Prostate cancer (PCa) is the most frequent male malignancy and the second most common cause of cancer-related death in Western countries. Current clinical and pathological methods are limited in the prediction of postoperative outcome. It is becoming increasingly evident that small non-coding RNA...... RNAs (snoRNAs) and transfer RNAs (tRNAs). From microarray analysis, we derived a miRNA diagnostic classifier that accurately distinguishes normal from cancer samples. Furthermore, we were able to construct a PCa prognostic predictor that independently forecasts postoperative outcome. Importantly...

  15. Novel Somatic Copy Number Alteration Identified for Cervical Cancer in the Mexican American Population

    Directory of Open Access Journals (Sweden)

    Alireza Torabi

    2016-08-01

    Full Text Available Cervical cancer affects millions of Americans, but the rate for cervical cancer in the Mexican American is approximately twice that for non-Mexican Americans. The etiologies of cervical cancer are still not fully understood. A number of somatic mutations, including several copy number alterations (CNAs, have been identified in the pathogenesis of cervical carcinomas in non-Mexican Americans. Thus, the purpose of this study was to investigate CNAs in association with cervical cancer in the Mexican American population. We conducted a pilot study of genome-wide CNA analysis using 2.5 million markers in four diagnostic groups: reference (n = 125, low grade dysplasia (cervical intraepithelial neoplasia (CIN-I, n = 4, high grade dysplasia (CIN-II and -III, n = 5 and invasive carcinoma (squamous cell carcinoma (SCC, n = 5 followed by data analyses using Partek. We observed a statistically-significant difference of CNA burden between case and reference groups of different sizes (>100 kb, 10–100 kb and 1–10 kb of CNAs that included deletions and amplifications, e.g., a statistically-significant difference of >100 kb deletions was observed between the reference (6.6% and pre-cancer and cancer (91.3% groups. Recurrent aberrations of 98 CNA regions were also identified in cases only. However, none of the CNAs have an impact on cancer progression. A total of 32 CNA regions identified contained tumor suppressor genes and oncogenes. Moreover, the pathway analysis revealed endometrial cancer and estrogen signaling pathways associated with this cancer (p < 0.05 using Kyoto Encyclopedia of Genes and Genomes (KEGG. This is the first report of CNAs identified for cervical cancer in the U.S. Latino population using high density markers. We are aware of the small sample size in the study. Thus, additional studies with a larger sample are needed to confirm the current findings.

  16. Evaluation of the ability of adjuvant tamoxifen-benefit gene signatures to predict outcome of hormone-naive estrogen receptor-positive breast cancer patients treated with tamoxifen in the advanced setting

    DEFF Research Database (Denmark)

    Sieuwerts, Anieta M; Lyng, Maria Bibi; Meijer-van Gelder, Marion E;

    2014-01-01

    To identify molecular markers indicative of response to tamoxifen and easily implemented in the routine setting, we recently reported three gene signatures that could stratify post-menopausal tamoxifen-treated, estrogen receptor-positive (ER+) patients according to outcome in the adjuvant setting....... Here, we evaluated the predictive potential of the total of 14 genes included in the 3 gene signatures using 2 hormone-naïve Dutch ER+ cohorts of a total of 285 recurrent breast cancer patients treated with first-line tamoxifen. mRNA levels were measured by reverse transcriptase quantitative PCR (RT......-qPCR) and the length of progression-free survival (PFS) was used as the primary endpoint. A Mann-Whitney U test was used to select for differentially expressed genes between tumors of patients who showed or did not show progressive disease within 6 months after start of tamoxifen treatment. Cox univariate...

  17. Pan-cancer analysis of genomic scar signatures associated with homologous recombination deficiency suggests novel indications for existing cancer drugs

    DEFF Research Database (Denmark)

    Marquard, Andrea Marion; Eklund, Aron Charles; Joshi, Tejal;

    2015-01-01

    Ovarian and triple-negative breast cancers with BRCA1 or BRCA2 loss are highly sensitive to treatment with PARP inhibitors and platinum-based cytotoxic agents and show an accumulation of genomic scars in the form of gross DNA copy number aberrations. Cancers without BRCA1 or BRCA2 loss but with a...

  18. A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

    Science.gov (United States)

    Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

    2016-09-01

    In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

  19. Co-regulation analysis of closely linked genes identifies a highly recurrent gain on chromosome 17q25.3 in prostate cancer

    International Nuclear Information System (INIS)

    Transcriptional profiling of prostate cancer (PC) has unveiled new markers of neoplasia and allowed insights into mechanisms underlying this disease. Genomewide analyses have also identified new chromosomal abnormalities associated with PC. The combination of both classes of data for the same sample cohort might provide better criteria for identifying relevant factors involved in neoplasia. Here we describe transcriptional signatures identifying distinct normal and tumoral prostate tissue compartments, and the inference and demonstration of a new, highly recurrent copy number gain on chromosome 17q25.3. We have applied transcriptional profiling to tumoral and non-tumoral prostate samples with relatively homogeneous epithelial representations as well as pure stromal tissue from peripheral prostate and cultured cell lines, followed by quantitative RT-PCR validations and immunohistochemical analysis. In addition, we have performed in silico colocalization analysis of co-regulated genes and validation by fluorescent in situ hybridization (FISH). The transcriptomic analysis has allowed us to identify signatures corresponding to non-tumoral luminal and tumoral epithelium, basal epithelial cells, and prostate stromal tissue. In addition, in silico analysis of co-regulated expression of physically linked genes has allowed us to predict the occurrence of a copy number gain at chromosomal region 17q25.3. This computational inference was validated by fluorescent in situ hybridization, which showed gains in this region in over 65% of primary and metastatic tumoral samples. Our approach permits to directly link gene copy number variations with transcript co-regulation in association with neoplastic states. Therefore, transcriptomic studies of carefully selected samples can unveil new diagnostic markers and transcriptional signatures highly specific of PC, and lead to the discovery of novel genomic abnormalities that may provide additional insights into the causes and mechanisms

  20. Co-regulation analysis of closely linked genes identifies a highly recurrent gain on chromosome 17q25.3 in prostate cancer

    Directory of Open Access Journals (Sweden)

    Martínez-A Carlos

    2008-10-01

    Full Text Available Abstract Background Transcriptional profiling of prostate cancer (PC has unveiled new markers of neoplasia and allowed insights into mechanisms underlying this disease. Genomewide analyses have also identified new chromosomal abnormalities associated with PC. The combination of both classes of data for the same sample cohort might provide better criteria for identifying relevant factors involved in neoplasia. Here we describe transcriptional signatures identifying distinct normal and tumoral prostate tissue compartments, and the inference and demonstration of a new, highly recurrent copy number gain on chromosome 17q25.3. Methods We have applied transcriptional profiling to tumoral and non-tumoral prostate samples with relatively homogeneous epithelial representations as well as pure stromal tissue from peripheral prostate and cultured cell lines, followed by quantitative RT-PCR validations and immunohistochemical analysis. In addition, we have performed in silico colocalization analysis of co-regulated genes and validation by fluorescent in situ hybridization (FISH. Results The transcriptomic analysis has allowed us to identify signatures corresponding to non-tumoral luminal and tumoral epithelium, basal epithelial cells, and prostate stromal tissue. In addition, in silico analysis of co-regulated expression of physically linked genes has allowed us to predict the occurrence of a copy number gain at chromosomal region 17q25.3. This computational inference was validated by fluorescent in situ hybridization, which showed gains in this region in over 65% of primary and metastatic tumoral samples. Conclusion Our approach permits to directly link gene copy number variations with transcript co-regulation in association with neoplastic states. Therefore, transcriptomic studies of carefully selected samples can unveil new diagnostic markers and transcriptional signatures highly specific of PC, and lead to the discovery of novel genomic abnormalities

  1. A novel murine model of rhinoscleroma identifies Mikulicz cells, the disease signature, as IL-10 dependent derivatives of inflammatory monocytes.

    Science.gov (United States)

    Fevre, Cindy; Almeida, Ana S; Taront, Solenne; Pedron, Thierry; Huerre, Michel; Prevost, Marie-Christine; Kieusseian, Aurélie; Cumano, Ana; Brisse, Sylvain; Sansonetti, Philippe J; Tournebize, Régis

    2013-04-01

    Rhinoscleroma is a human specific chronic disease characterized by the formation of granuloma in the airways, caused by the bacterium Klebsiella pneumoniae subspecies rhinoscleromatis, a species very closely related to K. pneumoniae subspecies pneumoniae. It is characterized by the appearance of specific foamy macrophages called Mikulicz cells. However, very little is known about the pathophysiological processes underlying rhinoscleroma. Herein, we characterized a murine model recapitulating the formation of Mikulicz cells in lungs and identified them as atypical inflammatory monocytes specifically recruited from the bone marrow upon K. rhinoscleromatis infection in a CCR2-independent manner. While K. pneumoniae and K. rhinoscleromatis infections induced a classical inflammatory reaction, K. rhinoscleromatis infection was characterized by a strong production of IL-10 concomitant to the appearance of Mikulicz cells. Strikingly, in the absence of IL-10, very few Mikulicz cells were observed, confirming a crucial role of IL-10 in the establishment of a proper environment leading to the maturation of these atypical monocytes. This is the first characterization of the environment leading to Mikulicz cells maturation and their identification as inflammatory monocytes.

  2. Embryonic mammary signature subsets are activated in Brca1-/- and basal-like breast cancers

    OpenAIRE

    Zvelebil, Marketa; Oliemuller, Erik; Gao, Qiong; Wansbury, Olivia; Mackay, Alan; Kendrick, Howard; Matthew J Smalley; Reis-Filho, Jorge S.; Howard, Beatrice A

    2013-01-01

    Introduction Cancer is often suggested to result from development gone awry. Links between normal embryonic development and cancer biology have been postulated, but no defined genetic basis has been established. We recently published the first transcriptomic analysis of embryonic mammary cell populations. Embryonic mammary epithelial cells are an immature progenitor cell population, lacking differentiation markers, which is reflected in their very distinct genetic profiles when compared with ...

  3. Identifying the Sources of Methane in Shallow Groundwaters in Parker and Hood Counties, Texas through Noble Gas Signatures

    Science.gov (United States)

    Wen, T.; Castro, M. C.; Nicot, J. P.; Hall, C. M.; Mickler, P. J.; Darvari, R.

    2015-12-01

    With rising demands for cleaner domestic energy resources, horizontal drilling and hydraulic fracturing techniques in unconventional hydrocarbon exploration have been extensively developed. However, the observation that some water wells have showed elevated concentrations of dissolved methane and other light hydrocarbons has caused public concern regarding unconventional energy extraction. In this contribution, we present noble gas data of production shale gases from the Barnett and Strawn Formations, as well as nearby groundwater samples in south-central Texas. The Barnett Shale located in the Fort Worth Basin at an average depth of ~2300 m is one of the most prominent shale gas plays in the U.S. This DOE-sponsored study explores the potential of noble gases for fingerprinting shale gas and thus, for identifying the sources of gas in aquifers overlying the Barnett Shale, due either to natural hydrocarbon occurrences or potentially related to gas production from unconventional energy resources. A total of 35 groundwater samples were collected in Parker and Hood counties in areas where high amounts of methane (>10 mg/L) were detected in shallow groundwater. Two gas samples were also collected directly from groundwater wells where bubbling methane was present. Preliminary results show that He concentrations in water samples, in excess of up to three orders of magnitude higher than expected atmospheric values are directly correlated with methane concentrations. 3He/4He ratio values vary from 0.030 to 0.889 times the atmospheric ratio with the lowest, more pure radiogenic contributions being associated with highest methane levels. The presence of crustally-produced radiogenic 40Ar is also apparent in groundwater samples with 40Ar/36Ar ratios up to 316. A combined analysis of 40Ar/36Ar ratios from groundwater wells bubbling gas and that of shale gas suggests that the source of this methane is not the heavily exploited Barnett Shale, but rather, the Strawn Formation.

  4. Avian resistance to Campylobacter jejuni colonization is associated with an intestinal immunogene expression signature identified by mRNA sequencing.

    Directory of Open Access Journals (Sweden)

    Sarah Connell

    Full Text Available Campylobacter jejuni is the most common cause of human bacterial gastroenteritis and is associated with several post-infectious manifestations, including onset of the autoimmune neuropathy Guillain-Barré syndrome, causing significant morbidity and mortality. Poorly-cooked chicken meat is the most frequent source of infection as C. jejuni colonizes the avian intestine in a commensal relationship. However, not all chickens are equally colonized and resistance seems to be genetically determined. We hypothesize that differences in immune response may contribute to variation in colonization levels between susceptible and resistant birds. Using high-throughput sequencing in an avian infection model, we investigate gene expression associated with resistance or susceptibility to colonization of the gastrointestinal tract with C. jejuni and find that gut related immune mechanisms are critical for regulating colonization. Amongst a single population of 300 4-week old chickens, there was clear segregation in levels of C. jejuni colonization 48 hours post-exposure. RNAseq analysis of caecal tissue from 14 C. jejuni-susceptible and 14 C. jejuni-resistant birds generated over 363 million short mRNA sequences which were investigated to identify 219 differentially expressed genes. Significantly higher expression of genes involved in the innate immune response, cytokine signaling, B cell and T cell activation and immunoglobulin production, as well as the renin-angiotensin system was observed in resistant birds, suggesting an early active immune response to C. jejuni. Lower expression of these genes in colonized birds suggests suppression or inhibition of a clearing immune response thus facilitating commensal colonization and generating vectors for zoonotic transmission. This study describes biological processes regulating C. jejuni colonization of the avian intestine and gives insight into the differential immune mechanisms incited in response to commensal

  5. Genomic profiling identifies GATA6 as a candidate oncogene amplified in pancreatobiliary cancer.

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    Kevin A Kwei

    2008-05-01

    Full Text Available Pancreatobiliary cancers have among the highest mortality rates of any cancer type. Discovering the full spectrum of molecular genetic alterations may suggest new avenues for therapy. To catalogue genomic alterations, we carried out array-based genomic profiling of 31 exocrine pancreatic cancers and 6 distal bile duct cancers, expanded as xenografts to enrich the tumor cell fraction. We identified numerous focal DNA amplifications and deletions, including in 19% of pancreatobiliary cases gain at cytoband 18q11.2, a locus uncommonly amplified in other tumor types. The smallest shared amplification at 18q11.2 included GATA6, a transcriptional regulator previously linked to normal pancreas development. When amplified, GATA6 was overexpressed at both the mRNA and protein levels, and strong immunostaining was observed in 25 of 54 (46% primary pancreatic cancers compared to 0 of 33 normal pancreas specimens surveyed. GATA6 expression in xenografts was associated with specific microarray gene-expression patterns, enriched for GATA binding sites and mitochondrial oxidative phosphorylation activity. siRNA mediated knockdown of GATA6 in pancreatic cancer cell lines with amplification led to reduced cell proliferation, cell cycle progression, and colony formation. Our findings indicate that GATA6 amplification and overexpression contribute to the oncogenic phenotypes of pancreatic cancer cells, and identify GATA6 as a candidate lineage-specific oncogene in pancreatobiliary cancer, with implications for novel treatment strategies.

  6. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

    Science.gov (United States)

    Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

    2016-04-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

  7. Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development.

    Science.gov (United States)

    Takeda, Haruna; Rust, Alistair G; Ward, Jerrold M; Yew, Christopher Chin Kuan; Jenkins, Nancy A; Copeland, Neal G

    2016-04-01

    Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4(+/-) mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC. PMID:27006499

  8. A core MYC gene expression signature is prominent in basal-like breast cancer but only partially overlaps the core serum response.

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    Sanjay Chandriani

    Full Text Available BACKGROUND: The MYC oncogene contributes to induction and growth of many cancers but the full spectrum of the MYC transcriptional response remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: Using microarrays, we conducted a detailed kinetic study of genes that respond to MYCN or MYCNDeltaMBII induction in primary human fibroblasts. In parallel, we determined the response to steady state overexpression of MYCN and MYCNDeltaMBII in the same cell type. An overlapping set of 398 genes from the two protocols was designated a 'Core MYC Signature' and used for further analysis. Comparison of the Core MYC Signature to a published study of the genes induced by serum stimulation revealed that only 7.4% of the Core MYC Signature genes are in the Core Serum Response and display similar expression changes to both MYC and serum. Furthermore, more than 50% of the Core MYC Signature genes were not influenced by serum stimulation. In contrast, comparison to a panel of breast cancers revealed a strong concordance in gene expression between the Core MYC Signature and the basal-like breast tumor subtype, which is a subtype with poor prognosis. This concordance was supported by the higher average level of MYC expression in the same tumor samples. CONCLUSIONS/SIGNIFICANCE: The Core MYC Signature has clinical relevance as this profile can be used to deduce an underlying genetic program that is likely to contribute to a clinical phenotype. Therefore, the presence of the Core MYC Signature may predict clinical responsiveness to therapeutics that are designed to disrupt MYC-mediated phenotypes.

  9. Maximizing biomarker discovery by minimizing gene signatures

    Directory of Open Access Journals (Sweden)

    Chang Chang

    2011-12-01

    Full Text Available Abstract Background The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II, trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications. Results We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II. Conclusions Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the

  10. A computational approach to identifying gene-microRNA modules in cancer.

    Science.gov (United States)

    Jin, Daeyong; Lee, Hyunju

    2015-01-01

    MicroRNAs (miRNAs) play key roles in the initiation and progression of various cancers by regulating genes. Regulatory interactions between genes and miRNAs are complex, as multiple miRNAs can regulate multiple genes. In addtion, these interactions vary from patient to patient and even among patients with the same cancer type, as cancer development is a heterogeneous process. These relationships are more complicated because transcription factors and other regulatory molecules can also regulate miRNAs and genes. Hence, it is important to identify the complex relationships between genes and miRNAs in cancer. In this study, we propose a computational approach to constructing modules that represent these relationships by integrating the expression data of genes and miRNAs with gene-gene interaction data. First, we used a biclustering algorithm to construct modules consisting of a subset of genes and a subset of samples to incorporate the heterogeneity of cancer cells. Second, we combined gene-gene interactions to include genes that play important roles in cancer-related pathways. Then, we selected miRNAs that are closely associated with genes in the modules based on a Gaussian Bayesian network and Bayesian Information Criteria. When we applied our approach to ovarian cancer and glioblastoma (GBM) data sets, 33 and 54 modules were constructed, respectively. In these modules, 91% and 94% of ovarian cancer and GBM modules, respectively, were explained either by direct regulation between genes and miRNAs or by indirect relationships via transcription factors. In addition, 48.4% and 74.0% of modules from ovarian cancer and GBM, respectively, were enriched with cancer-related pathways, and 51.7% and 71.7% of miRNAs in modules were ovarian cancer-related miRNAs and GBM-related miRNAs, respectively. Finally, we extensively analyzed significant modules and showed that most genes in these modules were related to ovarian cancer and GBM. PMID:25611546

  11. A computational approach to identifying gene-microRNA modules in cancer.

    Directory of Open Access Journals (Sweden)

    Daeyong Jin

    2015-01-01

    Full Text Available MicroRNAs (miRNAs play key roles in the initiation and progression of various cancers by regulating genes. Regulatory interactions between genes and miRNAs are complex, as multiple miRNAs can regulate multiple genes. In addtion, these interactions vary from patient to patient and even among patients with the same cancer type, as cancer development is a heterogeneous process. These relationships are more complicated because transcription factors and other regulatory molecules can also regulate miRNAs and genes. Hence, it is important to identify the complex relationships between genes and miRNAs in cancer. In this study, we propose a computational approach to constructing modules that represent these relationships by integrating the expression data of genes and miRNAs with gene-gene interaction data. First, we used a biclustering algorithm to construct modules consisting of a subset of genes and a subset of samples to incorporate the heterogeneity of cancer cells. Second, we combined gene-gene interactions to include genes that play important roles in cancer-related pathways. Then, we selected miRNAs that are closely associated with genes in the modules based on a Gaussian Bayesian network and Bayesian Information Criteria. When we applied our approach to ovarian cancer and glioblastoma (GBM data sets, 33 and 54 modules were constructed, respectively. In these modules, 91% and 94% of ovarian cancer and GBM modules, respectively, were explained either by direct regulation between genes and miRNAs or by indirect relationships via transcription factors. In addition, 48.4% and 74.0% of modules from ovarian cancer and GBM, respectively, were enriched with cancer-related pathways, and 51.7% and 71.7% of miRNAs in modules were ovarian cancer-related miRNAs and GBM-related miRNAs, respectively. Finally, we extensively analyzed significant modules and showed that most genes in these modules were related to ovarian cancer and GBM.

  12. A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

    Directory of Open Access Journals (Sweden)

    Mao Yu

    2009-07-01

    Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From

  13. Leptin pro-angiogenic signature in breast cancer is linked to IL-1 signalling

    OpenAIRE

    Zhou, W.; Guo, S.; Gonzalez-Perez, R R

    2010-01-01

    Background: Leptin and interleukin-1 (IL-1) upregulate vascular endothelial growth factor (VEGF), promote angiogenesis and are related to worse prognosis of breast cancer. However, it is unknown whether leptin regulates IL-1, and whether these effects are related to leptin-induction of VEGF/VEGFR2 in breast cancer. Methods: Several genetic and pharmacological approaches were used to determine the mechanisms involved in leptin regulation of IL-1 system (IL-1α, IL-1β, IL-1Ra and IL-1R tI) and t...

  14. Genome-wide multi-omics profiling of colorectal cancer identifies immune determinants strongly associated with relapse

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    Subha eMadhavan

    2013-11-01

    Full Text Available The use and benefit of adjuvant chemotherapy to treat state II colorectal cancer (CRC patients is not well understood since the majority of these patients are cured by surgery alone. Identification of biological markers of relapse is a critical challenge to effectively target treatments to the ~20% of patients destined to relapse. We have integrated molecular profiling results of several ‘omics’ data types to determine the most reliable prognostic biomarkers for relapse in CRC, using data from 40 stage I and II CRC patients. We identified 31 multi-omics features that highly correlate with relapse. The data types were integrated using multi-step analytical approach with consecutive elimination of redundant molecular features. For each data type a systems biology analysis was performed to identify pathways, biological processes and disease categories most affected in relapse. The biomarkers detected in tumors, urine and blood of patients indicated a strong association of immune processes, including aberrant regulation of T-cell and B-cell activation that could lead to overall differences in lymphocyte recruitment for tumor infiltration and markers indicating likelihood of future relapse. The immune response was the biologically most coherent signature that emerged from our analyses among several other biological processes, and corroborates other studies showing a strong immune response in patients less likely to relapse.

  15. High-throughput drug library screening identifies colchicine as a thyroid cancer inhibitor

    Science.gov (United States)

    Zhang, Le; Yang, Zhaoying; Granieri, Letizia; Pasculescu, Adrian; Datti, Alessandro; Asa, Sylvia L.; Xu, Zheli; Ezzat, Shereen

    2016-01-01

    We employed a high-throughput drug library screening platform to identify novel agents affecting thyroid cancer cells. We used human thyroid cancer cell lines to screen a collection of approximately 5200 small molecules with biological and/or pharmacologial properties. Parallel primary screens yielded a number of hits differentially active between thyroid and melanoma cells. Amongst compounds specifically targeting thyroid cancer cells, colchicine emerged as an effective candidate. Colchicine inhibited cell growth which correlated with G2 cell cycle arrest and apoptosis. These effects were hampered through inhibition of MEK1/2 and JNK. In contrast, inhibition of p38-MAPK had little effect, and AKT had no impact on colchicine action. Systemic colchicine inhibited thyroid cancer progression in xenografted mice. These findings demonstrate that our screening platform is an effective vehicle for drug reposition and show that colchicine warrants further attention in well-defined clinical niches such as thyroid cancer. PMID:26942566

  16. Pathway analysis of bladder cancer genome-wide association study identifies novel pathways involved in bladder cancer development

    Science.gov (United States)

    Chen, Meng; Rothman, Nathaniel; Ye, Yuanqing; Gu, Jian; Scheet, Paul A.; Huang, Maosheng; Chang, David W.; Dinney, Colin P.; Silverman, Debra T.; Figueroa, Jonine D.; Chanock, Stephen J.; Wu, Xifeng

    2016-01-01

    Genome-wide association studies (GWAS) are designed to identify individual regions associated with cancer risk, but only explain a small fraction of the inherited variability. Alternative approach analyzing genetic variants within biological pathways has been proposed to discover networks of susceptibility genes with additional effects. The gene set enrichment analysis (GSEA) may complement and expand traditional GWAS analysis to identify novel genes and pathways associated with bladder cancer risk. We selected three GSEA methods: Gen-Gen, Aligator, and the SNP Ratio Test to evaluate cellular signaling pathways involved in bladder cancer susceptibility in a Texas GWAS population. The candidate genetic polymorphisms from the significant pathway selected by GSEA were validated in an independent NCI GWAS. We identified 18 novel pathways (P < 0.05) significantly associated with bladder cancer risk. Five of the most promising pathways (P ≤ 0.001 in any of the three GSEA methods) among the 18 pathways included two cell cycle pathways and neural cell adhesion molecule (NCAM), platelet-derived growth factor (PDGF), and unfolded protein response pathways. We validated the candidate polymorphisms in the NCI GWAS and found variants of RAPGEF1, SKP1, HERPUD1, CACNB2, CACNA1C, CACNA1S, COL4A2, SRC, and CACNA1C were associated with bladder cancer risk. Two CCNE1 variants, rs8102137 and rs997669, from cell cycle pathways showed the strongest associations; the CCNE1 signal at 19q12 has already been reported in previous GWAS. These findings offer additional etiologic insights highlighting the specific genes and pathways associated with bladder cancer development. GSEA may be a complementary tool to GWAS to identify additional loci of cancer susceptibility.

  17. Identifying Gender-Preferred Communication Styles within Online Cancer Communities: A Retrospective, Longitudinal Analysis

    OpenAIRE

    Durant, Kathleen T.; McCray, Alexa T.; Charles Safran

    2012-01-01

    BACKGROUND: The goal of this research is to determine if different gender-preferred social styles can be observed within the user interactions at an online cancer community. To achieve this goal, we identify and measure variables that pertain to each gender-specific social style. METHODS AND FINDINGS: We perform social network and statistical analysis on the communication flow of 8,388 members at six different cancer forums over eight years. Kruskal-Wallis tests were conducted to measure the ...

  18. Enriched transcription factor signatures in triple negative breast cancer indicates possible targeted therapies with existing drugs

    Directory of Open Access Journals (Sweden)

    Scooter Willis

    2015-06-01

    Conclusion: With the increasing number of large sample size breast cancer cohorts, an exploratory analysis of genes that are consistently enriched in TN sharing common promoter motifs allows for the identification of possible therapeutic targets with extensive validation in patient derived data sets.

  19. Identification of a microRNA signature in dendritic cell vaccines for cancer immunotherapy

    DEFF Research Database (Denmark)

    Holmstrøm, Kim; Pedersen, Ayako Wakatsuki; Claesson, Mogens Helweg;

    2010-01-01

    Dendritic cells (DCs) exposed to tumor antigens followed by treatment with T(h)1-polarizing differentiation signals have paved the way for the development of DC-based cancer vaccines. Critical parameters for assessment of the optimal functional state of DCs and prediction of the vaccine potency o...

  20. An effect from anticipation also in hereditary nonpolyposis colorectal cancer families without identified mutations

    DEFF Research Database (Denmark)

    Timshel, Susanne; Therkildsen, Christina; Bendahl, Pär-Ola;

    2009-01-01

    Optimal prevention of hereditary cancer is central and requires initiation of surveillance programmes and/or prophylactic measures at a safe age. Anticipation, expressed as an earlier age at onset in successive generations, has been demonstrated in hereditary nonpolyposis colorectal cancer (HNPCC...... the Amsterdam criteria for HNPCC and showed normal MMR function and/or lack of disease-predisposing MMR gene mutation. In total, 319 cancers from 212 parent-child pairs in 99 families were identified. A paired t-test and a bivariate statistical model were used to assess anticipation. Both methods demonstrated...

  1. Tools to identify the men with prostate cancer most appropriate for active surveillance?

    Directory of Open Access Journals (Sweden)

    Robert H Getzenberg

    2014-02-01

    Full Text Available A great deal of effort is underway in order to identify those men with prostate cancer felicitous for active surveillance with greater precision than that afforded to us today. In the manuscript by Irshad et al. the authors evaluate a novel set of genes associated with senescence and aging as tools that can provide guidance regarding the indolent nature of an individual's prostate cancer with validation using both mRNA and protein analyses. While additional studies are required to understand the full impact of these findings, the innovative approach taken enhances our understanding of distinct phenotypes of prostate cancer.

  2. Secretome Identifies Tenascin-X as a Potent Marker of Ovarian Cancer

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    Marianne Kramer

    2015-01-01

    Full Text Available CA-125 has been a valuable marker for the follow-up of ovarian cancer patients but it is not sensitive enough to be used as diagnostic marker. We had already used secretomic methods to identify proteins differentially secreted by serous ovarian cancer cells compared to healthy ovarian cells. Here, we evaluated the secretion of these proteins by ovarian cancer cells during the follow-up of one patient. Proteins that correlated with CA-125 levels were screened using serum samples from ovarian cancer patients as well as benign and healthy controls. Tenascin-X secretion was shown to correlate with CA-125 value in the initial case study. The immunohistochemical detection of increased amount of tenascin-X in ovarian cancer tissues compared to healthy tissues confirms the potent interest in tenascin-X as marker. We then quantified the tenascin-X level in serum of patients and identified tenascin-X as potent marker for ovarian cancer, showing that secretomic analysis is suitable for the identification of protein biomarkers when combined with protein immunoassay. Using this method, we determined tenascin-X as a new potent marker for serous ovarian cancer.

  3. Large-scale genotyping identifies 41 new loci associated with breast cancer risk

    Science.gov (United States)

    Michailidou, Kyriaki; Hall, Per; Gonzalez-Neira, Anna; Ghoussaini, Maya; Dennis, Joe; Milne, Roger L; Schmidt, Marjanka K; Chang-Claude, Jenny; Bojesen, Stig E; Bolla, Manjeet K; Wang, Qin; Dicks, Ed; Lee, Andrew; Turnbull, Clare; Rahman, Nazneen; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; Silva, Isabel dos Santos; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel; van der Luijt, Rob B; Hein, Rebecca; Dahmen, Norbert; Beckman, Lars; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Hopper, John L; Southey, Melissa C; Makalic, Enes; Schmidt, Daniel F; Uitterlinden, Andre G; Hofman, Albert; Hunter, David J; Chanock, Stephen J; Vincent, Daniel; Bacot, François; Tessier, Daniel C; Canisius, Sander; Wessels, Lodewyk F A; Haiman, Christopher A; Shah, Mitul; Luben, Robert; Brown, Judith; Luccarini, Craig; Schoof, Nils; Humphreys, Keith; Li, Jingmei; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Couch, Fergus J; Wang, Xianshu; Vachon, Celine; Stevens, Kristen N; Lambrechts, Diether; Moisse, Matthieu; Paridaens, Robert; Christiaens, Marie-Rose; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Johnson, Nichola; Aitken, Zoe; Aaltonen, Kirsimari; Heikkinen, Tuomas; Broeks, Annegien; Van’t Veer, Laura J; van der Schoot, C Ellen; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Zamora, M Pilar; Perez, Jose Ignacio Arias; Pita, Guillermo; Alonso, M Rosario; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W R; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Lindblom, Annika; Margolin, Sara; Hooning, Maartje J; Hollestelle, Antoinette; van den Ouweland, Ans M W; Jager, Agnes; Bui, Quang M; Stone, Jennifer; Dite, Gillian S; Apicella, Carmel; Tsimiklis, Helen; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; Fasching, Peter A; Haeberle, Lothar; Ekici, Arif B; Beckmann, Matthias W; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Jones, Michael; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bonanni, Bernardo; Devilee, Peter; Tollenaar, Rob A E M; Seynaeve, Caroline; van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Bogdanova, Natalia V; Antonenkova, Natalia N; Dörk, Thilo; Kristensen, Vessela N; Anton-Culver, Hoda; Slager, Susan; Toland, Amanda E; Edge, Stephen; Fostira, Florentia; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Sueta, Aiko; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Teo, Soo Hwang; Yip, Cheng Har; Phuah, Sze Yee; Cornes, Belinda K; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Sng, Jen-Hwei; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Ding, Shian-Ling; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Blot, William J; Signorello, Lisa B; Cai, Qiuyin; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Simard, Jacques; Garcia-Closas, Montse; Pharoah, Paul D P; Chenevix-Trench, Georgia; Dunning, Alison M; Benitez, Javier; Easton, Douglas F

    2013-01-01

    Breast cancer is the most common cancer among women. Common variants at 27 loci have been identified as associated with susceptibility to breast cancer, and these account for ~9% of the familial risk of the disease. We report here a meta-analysis of 9 genome-wide association studies, including 10,052 breast cancer cases and 12,575 controls of European ancestry, from which we selected 29,807 SNPs for further genotyping. These SNPs were genotyped in 45,290 cases and 41,880 controls of European ancestry from 41 studies in the Breast Cancer Association Consortium (BCAC). The SNPs were genotyped as part of a collaborative genotyping experiment involving four consortia (Collaborative Oncological Gene-environment Study, COGS) and used a custom Illumina iSelect genotyping array, iCOGS, comprising more than 200,000 SNPs. We identified SNPs at 41 new breast cancer susceptibility loci at genome-wide significance (P < 5 × 10−8). Further analyses suggest that more than 1,000 additional loci are involved in breast cancer susceptibility. PMID:23535729

  4. A genomics approach to identify susceptibilities of breast cancer cells to “fever-range” hyperthermia

    International Nuclear Information System (INIS)

    Preclinical and clinical studies have shown for decades that tumor cells demonstrate significantly enhanced sensitivity to “fever range” hyperthermia (increasing the intratumoral temperature to 42-45°C) than normal cells, although it is unknown why cancer cells exhibit this distinctive susceptibility. To address this issue, mammary epithelial cells and three malignant breast cancer lines were subjected to hyperthermic shock and microarray, bioinformatics, and network analysis of the global transcription changes was subsequently performed. Bioinformatics analysis differentiated the gene expression patterns that distinguish the heat shock response of normal cells from malignant breast cancer cells, revealing that the gene expression profiles of mammary epithelial cells are completely distinct from malignant breast cancer lines following this treatment. Using gene network analysis, we identified altered expression of transcripts involved in mitotic regulators, histones, and non-protein coding RNAs as the significant processes that differed between the hyperthermic response of mammary epithelial cells and breast cancer cells. We confirmed our data via qPCR and flow cytometric analysis to demonstrate that hyperthermia specifically disrupts the expression of key mitotic regulators and G2/M phase progression in the breast cancer cells. These data have identified molecular mechanisms by which breast cancer lines may exhibit enhanced susceptibility to hyperthermic shock

  5. Serum Proteome Signature of Radiation Response: Upregulation of Inflammation-Related Factors and Downregulation of Apolipoproteins and Coagulation Factors in Cancer Patients Treated With Radiation Therapy—A Pilot Study

    International Nuclear Information System (INIS)

    Purpose: Ionizing radiation affects the proteome of irradiated cells and tissue, yet data concerning changes induced during radiation therapy (RT) in human blood are fragmentary and inconclusive. We aimed to identify features of serum proteome and associated processes involved in response to partial body irradiation during cancer treatment. Methods and Materials: Twenty patients with head and neck squamous cell cancer (HNSCC) and 20 patients with prostate cancer received definitive intensity modulated RT. Blood samples were collected before RT, just after RT, and 1 month after the end of RT. Complete serum proteome was analyzed in individual samples, using a shotgun liquid chromatography-tandem mass spectrometry approach which allowed identification of approximately 450 proteins. Approximately 100 unique proteins were quantified in all samples after exclusion of immunoglobulins, and statistical significance of differences among consecutive samples was assessed. Processes associated with quantified proteins and their functional interactions were predicted using gene ontology tools. Results: RT-induced changes were marked in the HNSCC patient group: 22 upregulated and 33 downregulated proteins were detected in post-RT sera. Most of the changes reversed during follow-up, yet levels of some proteins remained affected 1 month after the end of RT. RT-upregulated proteins were associated with acute phase, inflammatory response, and complement activation. RT-downregulated proteins were associated with transport and metabolism of lipids (plasma apolipoproteins) and blood coagulation. RT-induced changes were much weaker in prostate cancer patients, which corresponded to differences in acute radiation toxicity observed in both groups. Nevertheless, general patterns of RT-induced sera proteome changes were similar in both of the groups of cancer patients. Conclusions: In this pilot study, we proposed to identify a molecular signature of radiation response, based on specific

  6. Serum Proteome Signature of Radiation Response: Upregulation of Inflammation-Related Factors and Downregulation of Apolipoproteins and Coagulation Factors in Cancer Patients Treated With Radiation Therapy—A Pilot Study

    Energy Technology Data Exchange (ETDEWEB)

    Widlak, Piotr, E-mail: widlak@io.gliwice.pl [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice (Poland); Jelonek, Karol; Wojakowska, Anna; Pietrowska, Monika [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice (Poland); Polanska, Joanna [Institute of Automatics Control, Silesian University of Technology, Gliwice (Poland); Marczak, Łukasz [Institute of Bioorganic Chemistry of the Polish Academy of Sciences, Poznan (Poland); Miszczyk, Leszek; Składowski, Krzysztof [Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice (Poland)

    2015-08-01

    Purpose: Ionizing radiation affects the proteome of irradiated cells and tissue, yet data concerning changes induced during radiation therapy (RT) in human blood are fragmentary and inconclusive. We aimed to identify features of serum proteome and associated processes involved in response to partial body irradiation during cancer treatment. Methods and Materials: Twenty patients with head and neck squamous cell cancer (HNSCC) and 20 patients with prostate cancer received definitive intensity modulated RT. Blood samples were collected before RT, just after RT, and 1 month after the end of RT. Complete serum proteome was analyzed in individual samples, using a shotgun liquid chromatography-tandem mass spectrometry approach which allowed identification of approximately 450 proteins. Approximately 100 unique proteins were quantified in all samples after exclusion of immunoglobulins, and statistical significance of differences among consecutive samples was assessed. Processes associated with quantified proteins and their functional interactions were predicted using gene ontology tools. Results: RT-induced changes were marked in the HNSCC patient group: 22 upregulated and 33 downregulated proteins were detected in post-RT sera. Most of the changes reversed during follow-up, yet levels of some proteins remained affected 1 month after the end of RT. RT-upregulated proteins were associated with acute phase, inflammatory response, and complement activation. RT-downregulated proteins were associated with transport and metabolism of lipids (plasma apolipoproteins) and blood coagulation. RT-induced changes were much weaker in prostate cancer patients, which corresponded to differences in acute radiation toxicity observed in both groups. Nevertheless, general patterns of RT-induced sera proteome changes were similar in both of the groups of cancer patients. Conclusions: In this pilot study, we proposed to identify a molecular signature of radiation response, based on specific

  7. Transcriptomic signature of Bexarotene (Rexinoid LGD1069 on mammary gland from three transgenic mouse mammary cancer models

    Directory of Open Access Journals (Sweden)

    Bissonnette Reid P

    2008-09-01

    Full Text Available Abstract Background The rexinoid bexarotene (LGD1069, Targretin is a highly selective retinoid × receptor (RXR agonist that inhibits the growth of pre-malignant and malignant breast cells. Bexarotene was shown to suppress the development of breast cancer in transgenic mice models without side effects. The chemopreventive effects of bexarotene are due to transcriptional modulation of cell proliferation, differentiation and apoptosis. Our goal in the present study was to obtain a profile of the genes modulated by bexarotene on mammary gland from three transgenic mouse mammary cancer models in an effort to elucidate its molecular mechanism of action and for the identification of biomarkers of effectiveness. Methods Serial analysis of gene expression (SAGE was employed to profile the transcriptome of p53-null, MMTV-ErbB2, and C3(1-SV40 mammary cells obtained from mice treated with bexarotene and their corresponding controls. Results This resulted in a dataset of approximately 360,000 transcript tags representing over 20,000 mRNAs from a total of 6 different SAGE libraries. Analysis of gene expression changes induced by bexarotene in mammary gland revealed that 89 genes were dysregulated among the three transgenic mouse mammary models. From these, 9 genes were common to the three models studied. Conclusion Analysis of the indicated core of transcripts and protein-protein interactions of this commonly modulated genes indicate two functional modules significantly affected by rexinoid bexarotene related to protein biosynthesis and bioenergetics signatures, in addition to the targeting of cancer-causing genes related with cell proliferation, differentiation and apoptosis.

  8. Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival

    DEFF Research Database (Denmark)

    Thomassen, Mads; Jochumsen, Kirsten M; Mogensen, Ole;

    2009-01-01

    the relation of gene expression and chromosomal position to identify chromosomal regions of importance for early recurrence of ovarian cancer. By use of *Gene Set Enrichment Analysis*, we have ranked chromosomal regions according to their association to survival. Over-representation analysis including 1......Ovarian cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth, whereas others are causal for metastasis and recurrence. By using publicly available data sets, we have investigated......-4 consecutive cytogenetic bands identified regions with increased expression for chromosome 5q12-14, and a very large region of chromosome 7 with the strongest signal at 7p15-13 among tumors from short-living patients. Reduced gene expression was identified at 4q26-32, 6p12-q15, 9p21-q32, and 11p14-11. We...

  9. A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24

    DEFF Research Database (Denmark)

    Goode, Ellen L; Chenevix-Trench, Georgia; Song, Honglin;

    2010-01-01

    Ovarian cancer accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance ovarian cancer susceptibility genes, we conducted a genome-wide association study of 507,094 SNPs in 1,768 individuals with ovarian cancer (cases) and 2,354 controls, with foll...

  10. Unique proteome signature of post-chemotherapy ovarian cancer ascites-derived tumor cells.

    Science.gov (United States)

    Ahmed, Nuzhat; Greening, David; Samardzija, Chantel; Escalona, Ruth M; Chen, Maoshan; Findlay, Jock K; Kannourakis, George

    2016-01-01

    Eighty % of ovarian cancer patients diagnosed at an advanced-stage have complete remission after initial surgery and chemotherapy. However, most patients die within identification of 353 proteins. There were significant differences in proteins encoding for immune surveillance, DNA repair mechanisms, cytoskeleton rearrangement, cell-cell adhesion, cell cycle pathways, cellular transport, and proteins involved with glycine/proline/arginine synthesis in tumor cells isolated from CR relative to CN patients. Pathway analyses revealed enrichment of metabolic pathways, DNA repair mechanisms and energy metabolism pathways in CR tumor cells. In conclusion, this is the first proteomics study to comprehensively analyze ascites-derived tumor cells from CN and CR ovarian cancer patients. PMID:27470985

  11. Lipidomic Profiling of Adipose Tissue Reveals an Inflammatory Signature in Cancer-Related and Primary Lymphedema

    OpenAIRE

    Sedger, Lisa M.; Tull, Dedreia L.; Malcolm J McConville; De Souza, David P.; Rupasinghe, Thusitha W. T.; Williams, Spencer J; Saravanan Dayalan; Daniel Lanzer; Helen Mackie; Lam, Thomas C.; John Boyages

    2016-01-01

    Cancer-related and primary lymphedema (LE) are associated with the production of adipose tissue (AT). Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained ...

  12. Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data.

    Directory of Open Access Journals (Sweden)

    Taosheng Xu

    Full Text Available Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes.In this paper, we propose a method, weighted similarity network fusion (WSNF, to utilise the information in the complex miRNA-TF-mRNA regulatory network in identifying cancer subtypes. We firstly build the regulatory network where the nodes represent the features, i.e. the microRNAs (miRNAs, transcription factors (TFs and messenger RNAs (mRNAs and the edges indicate the interactions between the features. The interactions are retrieved from various interatomic databases. We then use the network information and the expression data of the miRNAs, TFs and mRNAs to calculate the weight of the features, representing the level of importance of the features. The feature weight is then integrated into a network fusion approach to cluster the samples (patients and thus to identify cancer subtypes. We applied our method to the TCGA breast invasive carcinoma (BRCA and glioblastoma multiforme (GBM datasets. The experimental results show that WSNF performs better than the other commonly used computational methods, and the information from miRNA-TF-mRNA regulatory network contributes to the performance improvement. The WSNF method successfully identified five breast cancer subtypes and three GBM subtypes which show significantly different survival patterns. We observed that the expression patterns of the features in some mi

  13. A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

    DEFF Research Database (Denmark)

    Al Olama, Ali Amin; Kote-Jarai, Zsofia; Berndt, Sonja I;

    2014-01-01

    Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of > 10 million SNPs in 43,303 prostate cancer...

  14. Sorghum expressed sequence tags identify signature genes for drought, pathogenesis, and skotomorphogenesis from a milestone set of 16,801 unique transcripts.

    Science.gov (United States)

    Pratt, Lee H; Liang, Chun; Shah, Manish; Sun, Feng; Wang, Haiming; Reid, St Patrick; Gingle, Alan R; Paterson, Andrew H; Wing, Rod; Dean, Ralph; Klein, Robert; Nguyen, Henry T; Ma, Hong-Mei; Zhao, Xin; Morishige, Daryl T; Mullet, John E; Cordonnier-Pratt, Marie-Michèle

    2005-10-01

    Improved knowledge of the sorghum transcriptome will enhance basic understanding of how plants respond to stresses and serve as a source of genes of value to agriculture. Toward this goal, Sorghum bicolor L. Moench cDNA libraries were prepared from light- and dark-grown seedlings, drought-stressed plants, Colletotrichum-infected seedlings and plants, ovaries, embryos, and immature panicles. Other libraries were prepared with meristems from Sorghum propinquum (Kunth) Hitchc. that had been photoperiodically induced to flower, and with rhizomes from S. propinquum and johnsongrass (Sorghum halepense L. Pers.). A total of 117,682 expressed sequence tags (ESTs) were obtained representing both 3' and 5' sequences from about half that number of cDNA clones. A total of 16,801 unique transcripts, representing tentative UniScripts (TUs), were identified from 55,783 3' ESTs. Of these TUs, 9,032 are represented by two or more ESTs. Collectively, these libraries were predicted to contain a total of approximately 31,000 TUs. Individual libraries, however, were predicted to contain no more than about 6,000 to 9,000, with the exception of light-grown seedlings, which yielded an estimate of close to 13,000. In addition, each library exhibits about the same level of complexity with respect to both the number of TUs preferentially expressed in that library and the frequency with which two or more ESTs is found in only that library. These results indicate that the sorghum genome is expressed in highly selective fashion in the individual organs and in response to the environmental conditions surveyed here. Close to 2,000 differentially expressed TUs were identified among the cDNA libraries examined, of which 775 were differentially expressed at a confidence level of 98%. From these 775 TUs, signature genes were identified defining drought, Colletotrichum infection, skotomorphogenesis (etiolation), ovary, immature panicle, and embryo.

  15. A Core MYC Gene Expression Signature Is Prominent in Basal-Like Breast Cancer but Only Partially Overlaps the Core Serum Response

    Science.gov (United States)

    Chandriani, Sanjay; Frengen, Eirik; Cowling, Victoria H.; Pendergrass, Sarah A.; Perou, Charles M.; Whitfield, Michael L.; Cole, Michael D.

    2009-01-01

    Background The MYC oncogene contributes to induction and growth of many cancers but the full spectrum of the MYC transcriptional response remains unclear. Methodology/Principal Findings Using microarrays, we conducted a detailed kinetic study of genes that respond to MYCN or MYCNΔMBII induction in primary human fibroblasts. In parallel, we determined the response to steady state overexpression of MYCN and MYCNΔMBII in the same cell type. An overlapping set of 398 genes from the two protocols was designated a ‘Core MYC Signature’ and used for further analysis. Comparison of the Core MYC Signature to a published study of the genes induced by serum stimulation revealed that only 7.4% of the Core MYC Signature genes are in the Core Serum Response and display similar expression changes to both MYC and serum. Furthermore, more than 50% of the Core MYC Signature genes were not influenced by serum stimulation. In contrast, comparison to a panel of breast cancers revealed a strong concordance in gene expression between the Core MYC Signature and the basal-like breast tumor subtype, which is a subtype with poor prognosis. This concordance was supported by the higher average level of MYC expression in the same tumor samples. Conclusions/Significance The Core MYC Signature has clinical relevance as this profile can be used to deduce an underlying genetic program that is likely to contribute to a clinical phenotype. Therefore, the presence of the Core MYC Signature may predict clinical responsiveness to therapeutics that are designed to disrupt MYC-mediated phenotypes. PMID:19690609

  16. The bioenergetic signature of isogenic colon cancer cells predicts the cell death response to treatment with 3-bromopyruvate, iodoacetate or 5-fluorouracil

    Directory of Open Access Journals (Sweden)

    Cuezva José M

    2011-02-01

    Full Text Available Abstract Background Metabolic reprogramming resulting in enhanced glycolysis is a phenotypic trait of cancer cells, which is imposed by the tumor microenvironment and is linked to the down-regulation of the catalytic subunit of the mitochondrial H+-ATPase (β-F1-ATPase. The bioenergetic signature is a protein ratio (β-F1-ATPase/GAPDH, which provides an estimate of glucose metabolism in tumors and serves as a prognostic indicator for cancer patients. Targeting energetic metabolism could be a viable alternative to conventional anticancer chemotherapies. Herein, we document that the bioenergetic signature of isogenic colon cancer cells provides a gauge to predict the cell-death response to the metabolic inhibitors, 3-bromopyruvate (3BrP and iodoacetate (IA, and the anti-metabolite, 5-fluorouracil (5-FU. Methods The bioenergetic signature of the cells was determined by western blotting. Aerobic glycolysis was determined from lactate production rates. The cell death was analyzed by fluorescence microscopy and flow cytometry. Cellular ATP concentrations were determined using bioluminiscence. Pearson's correlation coefficient was applied to assess the relationship between the bioenergetic signature and the cell death response. In vivo tumor regression activities of the compounds were assessed using a xenograft mouse model injected with the highly glycolytic HCT116 colocarcinoma cells. Results We demonstrate that the bioenergetic signature of isogenic HCT116 cancer cells inversely correlates with the potential to execute necrosis in response to 3BrP or IA treatment. Conversely, the bioenergetic signature directly correlates with the potential to execute apoptosis in response to 5-FU treatment in the same cells. However, despite the large differences observed in the in vitro cell-death responses associated with 3BrP, IA and 5-FU, the in vivo tumor regression activities of these agents were comparable. Conclusions Overall, we suggest that the

  17. TAGCNA: a method to identify significant consensus events of copy number alterations in cancer.

    Science.gov (United States)

    Yuan, Xiguo; Zhang, Junying; Yang, Liying; Zhang, Shengli; Chen, Baodi; Geng, Yaojun; Wang, Yue

    2012-01-01

    Somatic copy number alteration (CNA) is a common phenomenon in cancer genome. Distinguishing significant consensus events (SCEs) from random background CNAs in a set of subjects has been proven to be a valuable tool to study cancer. In order to identify SCEs with an acceptable type I error rate, better computational approaches should be developed based on reasonable statistics and null distributions. In this article, we propose a new approach named TAGCNA for identifying SCEs in somatic CNAs that may encompass cancer driver genes. TAGCNA employs a peel-off permutation scheme to generate a reasonable null distribution based on a prior step of selecting tag CNA markers from the genome being considered. We demonstrate the statistical power of TAGCNA on simulated ground truth data, and validate its applicability using two publicly available cancer datasets: lung and prostate adenocarcinoma. TAGCNA identifies SCEs that are known to be involved with proto-oncogenes (e.g. EGFR, CDK4) and tumor suppressor genes (e.g. CDKN2A, CDKN2B), and provides many additional SCEs with potential biological relevance in these data. TAGCNA can be used to analyze the significance of CNAs in various cancers. It is implemented in R and is freely available at http://tagcna.sourceforge.net/. PMID:22815924

  18. TAGCNA: a method to identify significant consensus events of copy number alterations in cancer.

    Directory of Open Access Journals (Sweden)

    Xiguo Yuan

    Full Text Available Somatic copy number alteration (CNA is a common phenomenon in cancer genome. Distinguishing significant consensus events (SCEs from random background CNAs in a set of subjects has been proven to be a valuable tool to study cancer. In order to identify SCEs with an acceptable type I error rate, better computational approaches should be developed based on reasonable statistics and null distributions. In this article, we propose a new approach named TAGCNA for identifying SCEs in somatic CNAs that may encompass cancer driver genes. TAGCNA employs a peel-off permutation scheme to generate a reasonable null distribution based on a prior step of selecting tag CNA markers from the genome being considered. We demonstrate the statistical power of TAGCNA on simulated ground truth data, and validate its applicability using two publicly available cancer datasets: lung and prostate adenocarcinoma. TAGCNA identifies SCEs that are known to be involved with proto-oncogenes (e.g. EGFR, CDK4 and tumor suppressor genes (e.g. CDKN2A, CDKN2B, and provides many additional SCEs with potential biological relevance in these data. TAGCNA can be used to analyze the significance of CNAs in various cancers. It is implemented in R and is freely available at http://tagcna.sourceforge.net/.

  19. Differential microRNA expression signatures and cell type-specific association with Taxol resistance in ovarian cancer cells.

    Science.gov (United States)

    Kim, Yong-Wan; Kim, Eun Young; Jeon, Doin; Liu, Juinn-Lin; Kim, Helena Suhyun; Choi, Jin Woo; Ahn, Woong Shick

    2014-01-01

    Paclitaxel (Taxol) resistance remains a major obstacle for the successful treatment of ovarian cancer. MicroRNAs (miRNAs) have oncogenic and tumor suppressor activity and are associated with poor prognosis phenotypes. miRNA screenings for this drug resistance are needed to estimate the prognosis of the disease and find better drug targets. miRNAs that were differentially expressed in Taxol-resistant ovarian cancer cells, compared with Taxol-sensitive cells, were screened by Illumina Human MicroRNA Expression BeadChips. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was used to identify target genes of selected miRNAs. Kaplan-Meier survival analysis was applied to identify dysregulated miRNAs in ovarian cancer patients using data from The Cancer Genome Atlas. A total of 82 miRNAs were identified in ovarian carcinoma cells compared to normal ovarian cells. miR-141, miR-106a, miR-200c, miR-96, and miR-378 were overexpressed, and miR-411, miR-432, miR-494, miR-409-3p, and miR-655 were underexpressed in ovarian cancer cells. Seventeen miRNAs were overexpressed in Taxol-resistant cells, including miR-663, miR-622, and HS_188. Underexpressed miRNAs in Taxol-sensitive cells included miR-497, miR-187, miR-195, and miR-107. We further showed miR-663 and miR-622 as significant prognosis markers of the chemo-resistant patient group. In particular, the downregulation of the two miRNAs was associated with better survival, perhaps increasing the sensitivity of cancer cells to Taxol. In the chemo-sensitive patient group, only miR-647 could be a prognosis marker. These miRNAs inhibit several interacting genes of p53 networks, especially in TUOS-3 and TUOS-4, and showed cell line-specific inhibition effects. Taken together, the data indicate that the three miRNAs are closely associated with Taxol resistance and potentially better prognosis factors. Our results suggest that these miRNAs were successfully and reliably identified and would be used in the

  20. A microRNA DNA methylation signature for human cancer metastasis

    OpenAIRE

    Lujambio, Amaia; Calin, George A; Villanueva, Alberto; Ropero, Santiago; Sánchez-Céspedes, Montserrat; Blanco, David; Montuenga, Luis M.; Rossi, Simona; Nicoloso, Milena S.; Faller, William J.; Gallagher, William M.; Eccles, Suzanne A; Croce, Carlo M.; Esteller, Manel

    2008-01-01

    MicroRNAs (miRNAs) are small, noncoding RNAs that can contribute to cancer development and progression by acting as oncogenes or tumor suppressor genes. Recent studies have also linked different sets of miRNAs to metastasis through either the promotion or suppression of this malignant process. Interestingly, epigenetic silencing of miRNAs with tumor suppressor features by CpG island hypermethylation is also emerging as a common hallmark of human tumors. Thus, we wondered whether there was a m...

  1. Identifying novel hypoxia-associated markers of chemoresistance in ovarian cancer.

    LENUS (Irish Health Repository)

    McEvoy, Lynda M

    2015-01-01

    Ovarian cancer is associated with poor long-term survival due to late diagnosis and development of chemoresistance. Tumour hypoxia is associated with many features of tumour aggressiveness including increased cellular proliferation, inhibition of apoptosis, increased invasion and metastasis, and chemoresistance, mostly mediated through hypoxia-inducible factor (HIF)-1α. While HIF-1α has been associated with platinum resistance in a variety of cancers, including ovarian, relatively little is known about the importance of the duration of hypoxia. Similarly, the gene pathways activated in ovarian cancer which cause chemoresistance as a result of hypoxia are poorly understood. This study aimed to firstly investigate the effect of hypoxia duration on resistance to cisplatin in an ovarian cancer chemoresistance cell line model and to identify genes whose expression was associated with hypoxia-induced chemoresistance.

  2. The potential of circulating extracellular small RNAs (smexRNA in veterinary diagnostics—Identifying biomarker signatures by multivariate data analysis

    Directory of Open Access Journals (Sweden)

    Spornraft Melanie

    2015-09-01

    After running the data evaluation pipeline, the proportion of miRNAs (microRNAs and piRNAs (PIWI-interacting small non-coding RNAs on the total sequenced reads was calculated. Additionally, top 10 signatures were compared which revealed that the readcount data sets were highly affected by the most abundant miRNA and piRNA profiles. To evaluate the discriminative power of multivariate data analyses to identify animals after veterinary drug application on the basis of smexRNAs, OPLS-DA was performed. In summary, the quality of miRNA models using all mapped reads for both treatment groups (animals treated with steroid hormones or the β-agonist clenbuterol is predominant to those generated with combined data sets or piRNAs alone. Using multivariate projection methodologies like OPLS-DA have proven the best potential to generate discriminative miRNA models, supported by small RNA-Seq data. Based on the presented comparative OPLS-DA, miRNAs are the favorable smexRNA biomarker candidates in the research field of veterinary drug abuse.

  3. Convergence of mutation and epigenetic alterations identifies common genes in cancer that predict for poor prognosis.

    Directory of Open Access Journals (Sweden)

    Timothy A Chan

    2008-05-01

    Full Text Available BACKGROUND: The identification and characterization of tumor suppressor genes has enhanced our understanding of the biology of cancer and enabled the development of new diagnostic and therapeutic modalities. Whereas in past decades, a handful of tumor suppressors have been slowly identified using techniques such as linkage analysis, large-scale sequencing of the cancer genome has enabled the rapid identification of a large number of genes that are mutated in cancer. However, determining which of these many genes play key roles in cancer development has proven challenging. Specifically, recent sequencing of human breast and colon cancers has revealed a large number of somatic gene mutations, but virtually all are heterozygous, occur at low frequency, and are tumor-type specific. We hypothesize that key tumor suppressor genes in cancer may be subject to mutation or hypermethylation. METHODS AND FINDINGS: Here, we show that combined genetic and epigenetic analysis of these genes reveals many with a higher putative tumor suppressor status than would otherwise be appreciated. At least 36 of the 189 genes newly recognized to be mutated are targets of promoter CpG island hypermethylation, often in both colon and breast cancer cell lines. Analyses of primary tumors show that 18 of these genes are hypermethylated strictly in primary cancers and often with an incidence that is much higher than for the mutations and which is not restricted to a single tumor-type. In the identical breast cancer cell lines in which the mutations were identified, hypermethylation is usually, but not always, mutually exclusive from genetic changes for a given tumor, and there is a high incidence of concomitant loss of expression. Sixteen out of 18 (89% of these genes map to loci deleted in human cancers. Lastly, and most importantly, the reduced expression of a subset of these genes strongly correlates with poor clinical outcome. CONCLUSIONS: Using an unbiased genome

  4. Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

    Science.gov (United States)

    Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

    2016-09-01

    Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. PMID:27235586

  5. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures.

    Science.gov (United States)

    Yu, Kun-Hsing; Levine, Douglas A; Zhang, Hui; Chan, Daniel W; Zhang, Zhen; Snyder, Michael

    2016-08-01

    Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers. PMID:27312948

  6. Differential Aspartate Usage Identifies a Subset of Cancer Cells Particularly Dependent on OGDH

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    Eric L. Allen

    2016-10-01

    Full Text Available Although aberrant metabolism in tumors has been well described, the identification of cancer subsets with particular metabolic vulnerabilities has remained challenging. Here, we conducted an siRNA screen focusing on enzymes involved in the tricarboxylic acid (TCA cycle and uncovered a striking range of cancer cell dependencies on OGDH, the E1 subunit of the alpha-ketoglutarate dehydrogenase complex. Using an integrative metabolomics approach, we identified differential aspartate utilization, via the malate-aspartate shuttle, as a predictor of whether OGDH is required for proliferation in 3D culture assays and for the growth of xenograft tumors. These findings highlight an anaplerotic role of aspartate and, more broadly, suggest that differential nutrient utilization patterns can identify subsets of cancers with distinct metabolic dependencies for potential pharmacological intervention.

  7. Differential microRNA expression signatures and cell type-specific association with Taxol resistance in ovarian cancer cells

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    Kim YW

    2014-02-01

    Full Text Available Yong-Wan Kim,1 Eun Young Kim,1 Doin Jeon,1 Juinn-Lin Liu,2 Helena Suhyun Kim,3 Jin Woo Choi,4 Woong Shick Ahn5 1Cancer Research Institute of Medical Science, The Catholic University of Korea, Seoul, Republic of Korea; 2Brain Tumor Center, Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, TX, USA; 3Cancer Rehab Laboratory, RH Healthcare Systems Inc, TX, USA; 4Harvard Medical School and Wellman Center for Photomedicine, Cambridge, MA, USA; 5Department of Obstetrics and Gynecology, The Catholic University of Korea, Seoul, Republic of Korea Abstract: Paclitaxel (Taxol resistance remains a major obstacle for the successful treatment of ovarian cancer. MicroRNAs (miRNAs have oncogenic and tumor suppressor activity and are associated with poor prognosis phenotypes. miRNA screenings for this drug resistance are needed to estimate the prognosis of the disease and find better drug targets. miRNAs that were differentially expressed in Taxol-resistant ovarian cancer cells, compared with Taxol-sensitive cells, were screened by Illumina Human MicroRNA Expression BeadChips. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR was used to identify target genes of selected miRNAs. Kaplan–Meier survival analysis was applied to identify dysregulated miRNAs in ovarian cancer patients using data from The Cancer Genome Atlas. A total of 82 miRNAs were identified in ovarian carcinoma cells compared to normal ovarian cells. miR-141, miR-106a, miR-200c, miR-96, and miR-378 were overexpressed, and miR-411, miR-432, miR-494, miR-409-3p, and miR-655 were underexpressed in ovarian cancer cells. Seventeen miRNAs were overexpressed in Taxol-resistant cells, including miR-663, miR-622, and HS_188. Underexpressed miRNAs in Taxol-sensitive cells included miR-497, miR-187, miR-195, and miR-107. We further showed miR-663 and miR-622 as significant prognosis markers of the chemo-resistant patient group. In particular, the

  8. Combined and interactive effects of environmental and GWAS-identified risk factors in ovarian cancer

    DEFF Research Database (Denmark)

    Pearce, Celeste Leigh; Rossing, Mary Anne; Lee, Alice W;

    2013-01-01

    There are several well-established environmental risk factors for ovarian cancer, and recent genome-wide association studies have also identified six variants that influence disease risk. However, the interplay between such risk factors and susceptibility loci has not been studied....

  9. Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

    DEFF Research Database (Denmark)

    Orr, Nick; Dudbridge, Frank; Dryden, Nicola;

    2015-01-01

    We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further...

  10. In-Depth, Label-Free Analysis of the Erythrocyte Cytoplasmic Proteome in Diamond Blackfan Anemia Identifies a Unique Inflammatory Signature.

    Directory of Open Access Journals (Sweden)

    Esther N Pesciotta

    Full Text Available Diamond Blackfan Anemia (DBA is a rare, congenital erythrocyte aplasia that is usually caused by haploinsufficiency of ribosomal proteins due to diverse mutations in one of several ribosomal genes. A striking feature of this disease is that a range of different mutations in ribosomal proteins results in similar disease phenotypes primarily characterized by erythrocyte abnormalities and macrocytic anemia, while most other cell types in the body are minimally affected. Previously, we analyzed the erythrocyte membrane proteomes of several DBA patients and identified several proteins that are not typically associated with this cell type and that suggested inflammatory mechanisms contribute to the pathogenesis of DBA. In this study, we evaluated the erythrocyte cytosolic proteome of DBA patients through in-depth analysis of hemoglobin-depleted erythrocyte cytosols. Simple, reproducible, hemoglobin depletion using nickel columns enabled in-depth analysis of over 1000 cytosolic erythrocyte proteins with only moderate total analysis time per proteome. Label-free quantitation and statistical analysis identified 29 proteins with significantly altered abundance levels in DBA patients compared to matched healthy control donors. Proteins that were significantly increased in DBA erythrocyte cytoplasms included three proteasome subunit beta proteins that make up the immunoproteasome and proteins induced by interferon-γ such as n-myc interactor and interferon-induced 35 kDa protein [NMI and IFI35 respectively]. Pathway analysis confirmed the presence of an inflammatory signature in erythrocytes of DBA patients and predicted key upstream regulators including mitogen activated kinase 1, interferon-γ, tumor suppressor p53, and tumor necrosis factor. These results show that erythrocytes in DBA patients are intrinsically different from those in healthy controls which may be due to an inflammatory response resulting from the inherent molecular defect of ribosomal

  11. To the Root of the Curl: A Signature of a Recent Selective Sweep Identifies a Mutation That Defines the Cornish Rex Cat Breed.

    Directory of Open Access Journals (Sweden)

    Barbara Gandolfi

    Full Text Available The cat (Felis silvestris catus shows significant variation in pelage, morphological, and behavioral phenotypes amongst its over 40 domesticated breeds. The majority of the breed specific phenotypic presentations originated through artificial selection, especially on desired novel phenotypic characteristics that arose only a few hundred years ago. Variations in coat texture and color of hair often delineate breeds amongst domestic animals. Although the genetic basis of several feline coat colors and hair lengths are characterized, less is known about the genes influencing variation in coat growth and texture, especially rexoid - curly coated types. Cornish Rex is a cat breed defined by a fixed recessive curly coat trait. Genome-wide analyses for selection (di, Tajima's D and nucleotide diversity were performed in the Cornish Rex breed and in 11 phenotypically diverse breeds and two random bred populations. Approximately 63K SNPs were used in the analysis that aimed to localize the locus controlling the rexoid hair texture. A region with a strong signature of recent selective sweep was identified in the Cornish Rex breed on chromosome A1, as well as a consensus block of homozygosity that spans approximately 3 Mb. Inspection of the region for candidate genes led to the identification of the lysophosphatidic acid receptor 6 (LPAR6. A 4 bp deletion in exon 5, c.250_253_delTTTG, which induces a premature stop codon in the receptor, was identified via Sanger sequencing. The mutation is fixed in Cornish Rex, absent in all straight haired cats analyzed, and is also segregating in the German Rex breed. LPAR6 encodes a G protein-coupled receptor essential for maintaining the structural integrity of the hair shaft; and has mutations resulting in a wooly hair phenotype in humans.

  12. Identifying factors to improve oral cancer screening uptake: a qualitative study.

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    Fatemeh Vida Zohoori

    Full Text Available AIMS: To engage with high risk groups to identify knowledge and awareness of oral cancer signs and symptoms and the factors likely to contribute to improved screening uptake. METHODS: Focus group discussions were undertaken with 18 males; 40+ years of age; smokers and/or drinkers (15+ cigarettes per day and/or 15+ units of alcohol per week, irregular dental attenders living in economically deprived areas of Teesside. RESULTS: There was a striking reported lack of knowledge and awareness of oral cancer and its signs and symptoms among the participants. When oral/mouth cancer leaflets produced by Cancer Research UK were presented to the participants, they claimed that they would seek help on noticing such a condition. There was a preference to seek help from their general practitioner rather than their dentist due to perceptions that a dentist is 'inaccessible' on a physical and psychological level, costly, a 'tooth specialist' not a 'mouth specialist', and also not able to prescribe medication and make referrals to specialists. Interestingly, none of the 18 participants who were offered a free oral cancer examination at a dental practice took up this offer. CONCLUSIONS: The uptake of oral cancer screening may be improved by increasing knowledge of the existence and signs and symptoms of oral cancer. Other factors that may increase uptake are increased awareness of the role of dentists in diagnosing oral cancer, promotion of oral cancer screening by health professionals during routine health checks, and the use of a "health" screening setting as opposed to a "dental" setting for such checks.

  13. Novel Morphologic and Genetic Analysis of Cancer Cells in a 3D Microenvironment Identifies STAT3 as a Regulator of Tumor Permeability Barrier Function.

    Science.gov (United States)

    Park, Min Chul; Jeong, Hyobin; Son, Sung Hwa; Kim, YounHa; Han, Daeyoung; Goughnour, Peter C; Kang, Taehee; Kwon, Nam Hoon; Moon, Hyo Eun; Paek, Sun Ha; Hwang, Daehee; Seol, Ho Jun; Nam, Do-Hyun; Kim, Sunghoon

    2016-03-01

    Tumor permeability is a critical determinant of drug delivery and sensitivity, but systematic methods to identify factors that perform permeability barrier functions in the tumor microenvironment are not yet available. Multicellular tumor spheroids have become tractable in vitro models to study the impact of a three-dimensional (3D) environment on cellular behavior. In this study, we characterized the spheroid-forming potential of cancer cells and correlated the resulting spheroid morphologies with genetic information to identify conserved cellular processes associated with spheroid structure. Spheroids generated from 100 different cancer cell lines were classified into four distinct groups based on morphology. In particular, round and compact spheroids exhibited highly hypoxic inner cores and permeability barriers against anticancer drugs. Through systematic and correlative analysis, we reveal JAK-STAT signaling as one of the signature pathways activated in round spheroids. Accordingly, STAT3 inhibition in spheroids generated from the established cancer cells and primary glioblastoma patient-derived cells altered the rounded morphology and increased drug sensitivity. Furthermore, combined administration of the STAT3 inhibitor and 5-fluorouracil to a mouse xenograft model markedly reduced tumor growth compared with monotherapy. Collectively, our findings demonstrate the ability to integrate 3D culture and genetic profiling to determine the factors underlying the integrity of the permeability barrier in the tumor microenvironment, and may help to identify and exploit novel mechanisms of drug resistance.

  14. Identifying Driver Genes in Cancer by Triangulating Gene Expression, Gene Location, and Survival Data

    Science.gov (United States)

    Rouam, Sigrid; Miller, Lance D; Karuturi, R Krishna Murthy

    2014-01-01

    Driver genes are directly responsible for oncogenesis and identifying them is essential in order to fully understand the mechanisms of cancer. However, it is difficult to delineate them from the larger pool of genes that are deregulated in cancer (ie, passenger genes). In order to address this problem, we developed an approach called TRIAngulating Gene Expression (TRIAGE through clinico-genomic intersects). Here, we present a refinement of this approach incorporating a new scoring methodology to identify putative driver genes that are deregulated in cancer. TRIAGE triangulates – or integrates – three levels of information: gene expression, gene location, and patient survival. First, TRIAGE identifies regions of deregulated expression (ie, expression footprints) by deriving a newly established measure called the Local Singular Value Decomposition (LSVD) score for each locus. Driver genes are then distinguished from passenger genes using dual survival analyses. Incorporating measurements of gene expression and weighting them according to the LSVD weight of each tumor, these analyses are performed using the genes located in significant expression footprints. Here, we first use simulated data to characterize the newly established LSVD score. We then present the results of our application of this refined version of TRIAGE to gene expression data from five cancer types. This refined version of TRIAGE not only allowed us to identify known prominent driver genes, such as MMP1, IL8, and COL1A2, but it also led us to identify several novel ones. These results illustrate that TRIAGE complements existing tools, allows for the identification of genes that drive cancer and could perhaps elucidate potential future targets of novel anticancer therapeutics. PMID:25949096

  15. Systematic repurposing screening in xenograft models identifies approved drugs with novel anti-cancer activity.

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    Jeffrey J Roix

    Full Text Available Approved drugs target approximately 400 different mechanisms of action, of which as few as 60 are currently used as anti-cancer therapies. Given that on average it takes 10-15 years for a new cancer therapeutic to be approved, and the recent success of drug repurposing for agents such as thalidomide, we hypothesized that effective, safe cancer treatments may be found by testing approved drugs in new therapeutic settings. Here, we report in-vivo testing of a broad compound collection in cancer xenograft models. Using 182 compounds that target 125 unique target mechanisms, we identified 3 drugs that displayed reproducible activity in combination with the chemotherapeutic temozolomide. Candidate drugs appear effective at dose equivalents that exceed current prescription levels, suggesting that additional pre-clinical efforts will be needed before these drugs can be tested for efficacy in clinical trials. In total, we suggest drug repurposing is a relatively resource-intensive method that can identify approved medicines with a narrow margin of anti-cancer activity.

  16. Simulated Annealing Based Algorithm for Identifying Mutated Driver Pathways in Cancer

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    Hai-Tao Li

    2014-01-01

    Full Text Available With the development of next-generation DNA sequencing technologies, large-scale cancer genomics projects can be implemented to help researchers to identify driver genes, driver mutations, and driver pathways, which promote cancer proliferation in large numbers of cancer patients. Hence, one of the remaining challenges is to distinguish functional mutations vital for cancer development, and filter out the unfunctional and random “passenger mutations.” In this study, we introduce a modified method to solve the so-called maximum weight submatrix problem which is used to identify mutated driver pathways in cancer. The problem is based on two combinatorial properties, that is, coverage and exclusivity. Particularly, we enhance an integrative model which combines gene mutation and expression data. The experimental results on simulated data show that, compared with the other methods, our method is more efficient. Finally, we apply the proposed method on two real biological datasets. The results show that our proposed method is also applicable in real practice.

  17. Regulators of genetic risk of breast cancer identified by integrative network analysis.

    Science.gov (United States)

    Castro, Mauro A A; de Santiago, Ines; Campbell, Thomas M; Vaughn, Courtney; Hickey, Theresa E; Ross, Edith; Tilley, Wayne D; Markowetz, Florian; Ponder, Bruce A J; Meyer, Kerstin B

    2016-01-01

    Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.

  18. Comprehensive annotation of bidirectional promoters identifies co-regulation among breast and ovarian cancer genes.

    Directory of Open Access Journals (Sweden)

    Mary Q Yang

    2007-04-01

    Full Text Available A "bidirectional gene pair" comprises two adjacent genes whose transcription start sites are neighboring and directed away from each other. The intervening regulatory region is called a "bidirectional promoter." These promoters are often associated with genes that function in DNA repair, with the potential to participate in the development of cancer. No connection between these gene pairs and cancer has been previously investigated. Using the database of spliced-expressed sequence tags (ESTs, we identified the most complete collection of human transcripts under the control of bidirectional promoters. A rigorous screen of the spliced EST data identified new bidirectional promoters, many of which functioned as alternative promoters or regulated novel transcripts. Additionally, we show a highly significant enrichment of bidirectional promoters in genes implicated in somatic cancer, including a substantial number of genes implicated in breast and ovarian cancers. The repeated use of this promoter structure in the human genome suggests it could regulate co-expression patterns among groups of genes. Using microarray expression data from 79 human tissues, we verify regulatory networks among genes controlled by bidirectional promoters. Subsets of these promoters contain similar combinations of transcription factor binding sites, including evolutionarily conserved ETS factor binding sites in ERBB2, FANCD2, and BRCA2. Interpreting the regulation of genes involved in co-expression networks, especially those involved in cancer, will be an important step toward defining molecular events that may contribute to disease.

  19. Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer.

    Science.gov (United States)

    O'Mara, Tracy A; Glubb, Dylan M; Painter, Jodie N; Cheng, Timothy; Dennis, Joe; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Ashton, Katie; Proietto, Tony; Otton, Geoffrey; Shah, Mitul; Ahmed, Shahana; Healey, Catherine S; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dürst, Matthias; Runnebaum, Ingo; Hillemanns, Peter; Dörk, Thilo; Lambrechts, Diether; Depreeuw, Jeroen; Annibali, Daniela; Amant, Frederic; Zhao, Hui; Goode, Ellen L; Dowdy, Sean C; Fridley, Brooke L; Winham, Stacey J; Salvesen, Helga B; Njølstad, Tormund S; Trovik, Jone; Werner, Henrica M J; Tham, Emma; Liu, Tao; Mints, Miriam; Bolla, Manjeet K; Michailidou, Kyriaki; Tyrer, Jonathan P; Wang, Qin; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Pharoah, Paul D P; Dunning, Alison M; Tomlinson, Ian; Easton, Douglas F; Thompson, Deborah J; Spurdle, Amanda B

    2015-10-01

    Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86×10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76×10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types. PMID:26330482

  20. Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer.

    Science.gov (United States)

    Kim, Kyoungmi; Taylor, Sandra L; Ganti, Sheila; Guo, Lining; Osier, Michael V; Weiss, Robert H

    2011-05-01

    Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy. PMID:21348635

  1. Alternative splicing in colon, bladder, and prostate cancer identified by exon-array analysis

    DEFF Research Database (Denmark)

    Thorsen, Kasper; Sørensen, Karina D.; Brems-Eskildsen, Anne Sofie;

    2008-01-01

    Alternative splicing enhances proteome diversity and modulates cancer-associated proteins. To identify tissue- and tumor-specific alternative splicing, we used the GeneChip Human Exon 1.0 ST Array to measure whole-genome exon expression in 102 normal and cancer tissue samples of different stages......, and 18 candidate tumor-specific splicing alterations in colon, bladder, and prostate, respectively, were selected for RT-PCR validation on an independent set of 81 normal and tumor tissue samples. In total, seven genes with tumor-specific splice variants were identified (ACTN1, CALD1, COL6A3, LRRFIP2...... from colon, urinary bladder, and prostate. We identified 2069 candidate alternative splicing events between normal tissue samples from colon, bladder, and prostate and selected 15 splicing events for RT-PCR validation, 10 of which were successfully validated by RT-PCR and sequencing. Furthermore 23, 19...

  2. The potential of circulating extracellular small RNAs (smexRNA) in veterinary diagnostics-Identifying biomarker signatures by multivariate data analysis.

    Science.gov (United States)

    Melanie, Spornraft; Benedikt, Kirchner; Pfaffl, Michael W; Irmgard, Riedmaier

    2015-09-01

    Worldwide growth and performance-enhancing substances are used in cattle husbandry to increase productivity. In certain countries however e.g., in the EU, these practices are forbidden to prevent the consumers from potential health risks of substance residues in food. To maximize economic profit, 'black sheep' among farmers might circumvent the detection methods used in routine controls, which highlights the need for an innovative and reliable detection method. Transcriptomics is a promising new approach in the discovery of veterinary medicine biomarkers and also a missing puzzle piece, as up to date, metabolomics and proteomics are paramount. Due to increased stability and easy sampling, circulating extracellular small RNAs (smexRNAs) in bovine plasma were small RNA-sequenced and their potential to serve as biomarker candidates was evaluated using multivariate data analysis tools. After running the data evaluation pipeline, the proportion of miRNAs (microRNAs) and piRNAs (PIWI-interacting small non-coding RNAs) on the total sequenced reads was calculated. Additionally, top 10 signatures were compared which revealed that the readcount data sets were highly affected by the most abundant miRNA and piRNA profiles. To evaluate the discriminative power of multivariate data analyses to identify animals after veterinary drug application on the basis of smexRNAs, OPLS-DA was performed. In summary, the quality of miRNA models using all mapped reads for both treatment groups (animals treated with steroid hormones or the β-agonist clenbuterol) is predominant to those generated with combined data sets or piRNAs alone. Using multivariate projection methodologies like OPLS-DA have proven the best potential to generate discriminative miRNA models, supported by small RNA-Seq data. Based on the presented comparative OPLS-DA, miRNAs are the favorable smexRNA biomarker candidates in the research field of veterinary drug abuse.

  3. Transcriptomics in Interferon-α-Treated Patients Identifies Inflammation-, Neuroplasticity- and Oxidative Stress-Related Signatures as Predictors and Correlates of Depression.

    Science.gov (United States)

    Hepgul, Nilay; Cattaneo, Annamaria; Agarwal, Kosh; Baraldi, Sara; Borsini, Alessandra; Bufalino, Chiara; Forton, Daniel M; Mondelli, Valeria; Nikkheslat, Naghmeh; Lopizzo, Nicola; Riva, Marco A; Russell, Alice; Hotopf, Matthew; Pariante, Carmine M

    2016-09-01

    Owing to the unique opportunity to assess individuals before and after they develop depression within a short timeframe, interferon-α (IFN-α) treatment for chronic hepatitis C virus (HCV) infection is an ideal model to identify molecular mechanisms relevant to major depression, especially in the context of enhanced inflammation. Fifty-eight patients were assessed prospectively, at baseline and monthly over 24 weeks of IFN-α treatment. New-onset cases of depression were determined using the Mini International Neuropsychiatric Interview (MINI). Whole-blood transcriptomic analyses were conducted to investigate the following: (1) baseline gene expression differences associated with future development of IFN-α-induced depression, before IFN-α, and (2) longitudinal gene expression changes from baseline to weeks 4 or 24 of IFN-α treatment, separately in those who did and did not develop depression. Transcriptomics data were analyzed using Partek Genomics Suite (1.4-fold, FDR adjusted p⩽0.05) and Ingenuity Pathway Analysis Software. Twenty patients (34%) developed IFN-α-induced depression. At baseline, 73 genes were differentially expressed in patients who later developed depression compared with those who did not. After 4 weeks of IFN-α treatment, 592 genes were modulated in the whole sample, representing primarily IFN-α-responsive genes. Substantially more genes were modulated only in patients who developed depression (n=506, compared with n=70 in patients who did not), with enrichment in inflammation-, neuroplasticity- and oxidative stress-related pathways. A similar picture was observed at week 24. Our data indicate that patients who develop IFN-α-induced depression have an increased biological sensitivity to IFN-α, as shown by larger gene expression changes, and specific signatures both as predictors and as correlates. PMID:27067128

  4. Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

    NARCIS (Netherlands)

    Couch, Fergus J.; Wang, Xianshu; McGuffog, Lesley; Lee, Andrew; Olswold, Curtis; Kuchenbaecker, Karoline B.; Soucy, Penny; Fredericksen, Zachary; Barrowdale, Daniel; Dennis, Joe; Gaudet, Mia M.; Dicks, Ed; Kosel, Matthew; Healey, Sue; Sinilnikova, Olga M.; Lee, Adam; Bacot, Francois; Vincent, Daniel; Hogervorst, Frans B. L.; Peock, Susan; Stoppa-Lyonnet, Dominique; Jakubowska, Anna; Radice, Paolo; Schmutzler, Rita Katharina; Domchek, Susan M.; Piedmonte, Marion; Singer, Christian F.; Friedman, Eitan; Thomassen, Mads; Hansen, Thomas V. O.; Neuhausen, Susan L.; Szabo, Csilla I.; Blanco, Ignacio; Greene, Mark H.; Karlan, Beth Y.; Garber, Judy; Phelan, Catherine M.; Weitzel, Jeffrey N.; Montagna, Marco; Olah, Edith; Andrulis, Irene L.; Godwin, Andrew K.; Yannoukakos, Drakoulis; Goldgar, David E.; Caldes, Trinidad; Nevanlinna, Heli; Osorio, Ana; Terry, Mary Beth; Daly, Mary B.; van Rensburg, Elizabeth J.; Hamann, Ute; Ramus, Susan J.; Toland, Amanda Ewart; Caligo, Maria A.; Olopade, Olufunmilayo I.; Tung, Nadine; Claes, Kathleen; Beattie, Mary S.; Southey, Melissa C.; Imyanitov, Evgeny N.; Tischkowitz, Marc; Janavicius, Ramunas; John, Esther M.; Kwong, Ava; Diez, Orland; Balmana, Judith; Barkardottir, Rosa B.; Arun, Banu K.; Rennert, Gad; Teo, Soo-Hwang; Ganz, Patricia A.; Campbell, Ian; van der Hout, Annemarie H.; van Deurzen, Carolien H. M.; Seynaeve, Caroline; Garcia, Encarna B. Gomez; van Leeuwen, Flora E.; Meijers-Heijboer, Hanne E. J.; Gille, Johannes J. P.; Ausems, Margreet G. E. M.; Blok, Marinus J.; Ligtenberg, Marjolijn J. L.; Rookus, Matti A.; Devilee, Peter; Verhoef, Senno; van Os, Theo A. M.; Wijnen, Juul T.; Frost, Debra; Ellis, Steve; Fineberg, Elena; Platte, Radka; Evans, D. Gareth; Izatt, Louise; Eeles, Rosalind A.; Adlard, Julian; Eccles, Diana M.; Cook, Jackie; Brewer, Carole; Douglas, Fiona; Hodgson, Shirley; Morrison, Patrick J.; Side, Lucy E.; Donaldson, Alan; Houghton, Catherine; Rogers, Mark T.; Dorkins, Huw; Eason, Jacqueline; Gregory, Helen; McCann, Emma; Murray, Alex; Calender, Alain; Hardouin, Agnes; Berthet, Pascaline; Delnatte, Capucine; Nogues, Catherine; Lasset, Christine; Houdayer, Claude; Leroux, Dominique; Rouleau, Etienne; Prieur, Fabienne; Damiola, Francesca; Sobol, Hagay; Coupier, Isabelle; Venat-Bouvet, Laurence; Castera, Laurent; Gauthier-Villars, Marion; Leone, Melanie; Pujol, Pascal; Mazoyer, Sylvie; Bignon, Yves-Jean; Zlowocka-Perlowska, Elzbieta; Gronwald, Jacek; Lubinski, Jan; Durda, Katarzyna; Jaworska, Katarzyna; Huzarski, Tomasz; Spurdle, Amanda B.; Viel, Alessandra; Peissel, Bernard; Bonanni, Bernardo; Melloni, Giulia; Ottini, Laura; Papi, Laura; Varesco, Liliana; Tibiletti, Maria Grazia; Peterlongo, Paolo; Volorio, Sara; Manoukian, Siranoush; Pensotti, Valeria; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Gadzicki, Dorothea; Gehrig, Andrea; Kast, Karin; Rhiem, Kerstin; Meindl, Alfons; Niederacher, Dieter; Ditsch, Nina; Plendl, Hansjoerg; Preisler-Adams, Sabine; Engert, Stefanie; Sutter, Christian; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Weber, Bernhard H. F.; Arver, Brita; Stenmark-Askmalm, Marie; Loman, Niklas; Rosenquist, Richard; Einbeigi, Zakaria; Nathanson, Katherine L.; Rebbeck, Timothy R.; Blank, Stephanie V.; Cohn, David E.; Rodriguez, Gustavo C.; Small, Laurie; Friedlander, Michael; Bae-Jump, Victoria L.; Fink-Retter, Anneliese; Rappaport, Christine; Gschwantler-Kaulich, Daphne; Pfeiler, Georg; Tea, Muy-Kheng; Lindor, Noralane M.; Kaufman, Bella; Paluch, Shani Shimon; Laitman, Yael; Skytte, Anne-Bine; Gerdes, Anne-Marie; Pedersen, Inge Sokilde; Moeller, Sanne Traasdahl; Kruse, Torben A.; Jensen, Uffe Birk; Vijai, Joseph; Sarrel, Kara; Robson, Mark; Kauff, Noah; Mulligan, Anna Marie; Glendon, Gord; Ozcelik, Hilmi; Ejlertsen, Bent; Nielsen, Finn C.; Jonson, Lars; Andersen, Mette K.; Ding, Yuan Chun; Steele, Linda; Foretova, Lenka; Teule, Alex; Lazaro, Conxi; Brunet, Joan; Angel Pujana, Miquel; Mai, Phuong L.; Loud, Jennifer T.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Narod, Steven A.; Herzog, Josef; Sand, Sharon R.; Tognazzo, Silvia; Agata, Simona; Vaszko, Tibor; Weaver, Joellen; Stavropoulou, Alexandra V.; Buys, Saundra S.; Romero, Atocha; de la Hoya, Miguel; Aittomaki, Kristiina; Muranen, Taru A.; Duran, Mercedes; Chung, Wendy K.; Lasa, Adriana; Dorfling, Cecilia M.; Miron, Alexander; Benitez, Javier; Senter, Leigha; Huo, Dezheng; Chan, Salina B.; Sokolenko, Anna P.; Chiquette, Jocelyne; Tihomirova, Laima; Friebel, Tara M.; Agnarsson, Bjarni A.; Lu, Karen H.; Lejbkowicz, Flavio; James, Paul A.; Hall, Per; Dunning, Alison M.

    2013-01-01

    BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a furthe

  5. Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

    NARCIS (Netherlands)

    F.J. Couch (Fergus); X. Wang (Xing); L. McGuffog (Lesley); A. Lee; C. Olswold (Curtis); K.B. Kuchenbaecker (Karoline); P. Soucy (Penny); Z. Fredericksen (Zachary); D. Barrowdale (Daniel); J. Dennis (Joe); M.M. Gaudet (Mia); E. Dicks (Ed); M. Kosel (Matthew); S. Healey (Sue); O. Sinilnikova (Olga); F. Bacot (Francois); D. Vincent (Daniel); F.B.L. Hogervorst (Frans); S. Peock (Susan); D. Stoppa-Lyonnet (Dominique); A. Jakubowska (Anna); P. Radice (Paolo); R.K. Schmutzler (Rita); S.M. Domchek (Susan); M. Piedmonte (Marion); C.F. Singer (Christian); E. Friedman (Eitan); M. Thomassen (Mads); T.V.O. Hansen (Thomas); S.L. Neuhausen (Susan); C. Szabo (Csilla); I. Blanco (Ignacio); M.H. Greene (Mark); B. Karlan; J. Garber; C. Phelan (Catherine); J.N. Weitzel (Jeffrey); M. Montagna (Marco); E. Olah; I.L. Andrulis (Irene); A.K. Godwin (Andrew); D. Yannoukakos (Drakoulis); D. Goldgar (David); T. Caldes (Trinidad); H. Nevanlinna (Heli); A. Osorio (Ana); M.-B. Terry (Mary-Beth); M.B. Daly (Mary); E.J. van Rensburg (Elizabeth); U. Hamann (Ute); S.J. Ramus (Susan); A. Ewart-Toland (Amanda); M.A. Caligo (Maria); O.I. Olopade (Olofunmilayo); N. Tung (Nadine); K. Claes (Kathleen); M.S. Beattie (Mary); M.C. Southey (Melissa); E.N. Imyanitov (Evgeny); M. Tischkowitz (Marc); R. Janavicius (Ramunas); E.M. John (Esther); A. Kwong (Ava); O. Diez (Orland); J. Balmana (Judith); R.B. Barkardottir (Rosa); B.K. Arun (Banu); G. Rennert (Gad); S.-H. Teo; P.A. Ganz (Patricia); I. Campbell (Ian); A.H. van der Hout (Annemarie); C.H.M. van Deurzen (Carolien); C.M. Seynaeve (Caroline); E.B. Gómez García (Encarna); F.E. van Leeuwen (F.); H.E.J. Meijers-Heijboer (Hanne E.); J.J. Gille (Johan); M.G.E.M. Ausems (Margreet); M.J. Blok (Marinus); M.J. Ligtenberg (Marjolijn); M.A. Rookus (Matti); P. Devilee (Peter); S. Verhoef; T.A.M. van Os (Theo); J.T. Wijnen (Juul); D. Frost (Debra); S. Ellis (Steve); E. Fineberg (Elena); R. Platte (Radka); D.G. Evans (Gareth); L. Izatt (Louise); R. Eeles (Rosalind); J.W. Adlard (Julian); D. Eccles (Diana); J. Cook (Jackie); C. Brewer (C.); F. Douglas (Fiona); S.V. Hodgson (Shirley); P.J. Morrison (Patrick); L. Side (Lucy); A. Donaldson (Alan); C. Houghton (Catherine); M.T. Rogers (Mark); H. Dorkins (Huw); J. Eason (Jacqueline); H. Gregory (Helen); E. McCann (Emma); A. Murray (Alexandra); A. Calender (Alain); A. Hardouin (Agnès); P. Berthet (Pascaline); C.D. Delnatte (Capucine); C. Nogues (Catherine); C. Lasset (Christine); C. Houdayer (Claude); D. Leroux (Dominique); E. Rouleau (Etienne); F. Prieur (Fabienne); F. Damiola (Francesca); H. Sobol (Hagay); I. Coupier (Isabelle); L. Vénat-Bouvet (Laurence); L. Castera (Laurent); M. Gauthier-Villars (Marion); M. Léone (Mélanie); P. Pujol (Pascal); S. Mazoyer (Sylvie); Y.-J. Bignon (Yves-Jean); E. Złowocka-Perłowska (Elzbieta); J. Gronwald (Jacek); J. Lubinski (Jan); K. Durda (Katarzyna); K. Jaworska (Katarzyna); T. Huzarski (Tomasz); A.B. Spurdle (Amanda); A. Viel (Alessandra); B. Peissel (Bernard); B. Bonnani (Bernardo); G. Melloni (Giulia); L. Ottini (Laura); L. Papi (Laura); L. Varesco (Liliana); M.G. Tibiletti (Maria Grazia); P. Peterlongo (Paolo); S. Volorio (Sara); S. Manoukian (Siranoush); V. Pensotti (Valeria); N. Arnold (Norbert); C. Engel (Christoph); H. Deissler (Helmut); D. Gadzicki (Dorothea); P.A. Gehrig (Paola A.); K. Kast (Karin); K. Rhiem (Kerstin); A. Meindl (Alfons); D. Niederacher (Dieter); N. Ditsch (Nina); H. Plendl (Hansjoerg); S. Preisler-Adams (Sabine); S. Engert (Stefanie); C. Sutter (Christian); R. Varon-Mateeva (Raymonda); B. Wapenschmidt (Barbara); B.H.F. Weber (Bernhard); B. Arver (Brita Wasteson); M. Stenmark-Askmalm (M.); N. Loman (Niklas); R. Rosenquist (R.); Z. Einbeigi (Zakaria); K.L. Nathanson (Katherine); R. Rebbeck (Timothy); S.V. Blank (Stephanie); D.E. Cohn (David); G.C. Rodriguez (Gustavo); L. Small (Laurie); M. Friedlander (Michael); V.L. Bae-Jump (Victoria L.); A. Fink-Retter (Anneliese); C. Rappaport (Christine); D. Gschwantler-Kaulich (Daphne); G. Pfeiler (Georg); M.-K. Tea; N.M. Lindor (Noralane); B. Kaufman (Bella); S. Shimon Paluch (Shani); Y. Laitman (Yael); A.-B. Skytte (Anne-Bine); A-M. Gerdes (Anne-Marie); I.S. Pedersen (Inge Sokilde); S.T. Moeller (Sanne Traasdahl); T.A. Kruse (Torben); U.B. Jensen; J. Vijai (Joseph); K. Sarrel (Kara); M. Robson (Mark); N. Kauff (Noah); A.M. Mulligan (Anna Marie); G. Glendon (Gord); H. Ozcelik (Hilmi); B. Ejlertsen (Bent); F.C. Nielsen (Finn); L. Jønson (Lars); M.K. Andersen (Mette); Y.C. Ding (Yuan); L. Steele (Linda); L. Foretova (Lenka); A. Teulé (A.); C. Lazaro (Conxi); J. Brunet (Joan); M.A. Pujana (Miguel); P.L. Mai (Phuong); J.T. Loud (Jennifer); C.S. Walsh (Christine); K.J. Lester (Kathryn); S. Orsulic (Sandra); S. Narod (Steven); J. Herzog (Josef); S.R. Sand (Sharon); S. Tognazzo (Silvia); S. Agata (Simona); T. Vaszko (Tibor); J. Weaver (JoEllen); A. Stavropoulou (Alexandra); S.S. Buys (Saundra); A. Romero (Alfonso); M. de La Hoya (Miguel); K. Aittomäki (Kristiina); T.A. Muranen (Taru); M. Duran; W.K. Chung (Wendy); A. Lasa (Adriana); C.M. Dorfling (Cecelia); A. Miron (Alexander); J. Benítez (Javier); L. Senter (Leigha); D. Huo (Dezheng); S. Chan (Salina); A. Sokolenko (Anna); J. Chiquette (Jocelyne); L. Tihomirova (Laima); M.O.W. Friebel (Mark ); B.A. Agnarsson (Bjarni); K.H. Lu (Karen); F. Lejbkowicz (Flavio); P.A. James (Paul ); A.S. Hall (Alistair); A.M. Dunning (Alison); Y. Tessier (Yann); J. Cunningham (Jane); S. Slager (Susan); C. Wang (Chen); S. Hart (Stewart); K. Stevens (Kristen); J. Simard (Jacques); T. Pastinen (Tomi); V.S. Pankratz (Shane); K. Offit (Kenneth); D.F. Easton (Douglas); G. Chenevix-Trench (Georgia); A.C. Antoniou (Antonis); H. Thorne (Heather); E. Niedermayr (Eveline); Å. Borg (Åke); H. Olsson; H. Jernström (H.); K. Henriksson (Karin); K. Harbst (Katja); M. Soller (Maria); U. Kristoffersson (Ulf); A. Öfverholm (Anna); M. Nordling (Margareta); P. Karlsson (Per); A. von Wachenfeldt (Anna); A. Liljegren (Annelie); A. Lindblom (Annika); G.B. Bustinza; J. Rantala (Johanna); B. Melin (Beatrice); C.E. Ardnor (Christina Edwinsdotter); M. Emanuelsson (Monica); H. Ehrencrona (Hans); M.H. Pigg (Maritta ); S. Liedgren (Sigrun); M.A. Rookus (M.); S. Verhoef (S.); F.E. van Leeuwen (F.); M.K. Schmidt (Marjanka); J.L. de Lange (J.); J.M. Collee (Margriet); A.M.W. van den Ouweland (Ans); M.J. Hooning (Maartje); C.J. van Asperen (Christi); J.T. Wijnen (Juul); R.A.E.M. Tollenaar (Rob); P. Devilee (Peter); T.C.T.E.F. van Cronenburg; C.M. Kets; A.R. Mensenkamp (Arjen); R.B. van der Luijt (Rob); C.M. Aalfs (Cora); T.A.M. van Os (Theo); Q. Waisfisz (Quinten); E.J. Meijers-Heijboer (Hanne); E.B. Gomez Garcia (Encarna); J.C. Oosterwijk (Jan); M.J. Mourits; G.H. de Bock (Geertruida); S.D. Ellis (Steve); E. Fineberg (Elena); Z. Miedzybrodzka (Zosia); L. Jeffers (Lisa); T.J. Cole (Trevor); K.-R. Ong (Kai-Ren); J. Hoffman (Jonathan); M. James (Margaret); J. Paterson (Joan); A. Taylor (Amy); A. Murray (Anna); M.J. Kennedy (John); D.E. Barton (David); M.E. Porteous (Mary); S. Drummond (Sarah); C. Brewer (Carole); E. Kivuva (Emma); A. Searle (Anne); S. Goodman (Selina); R. Davidson (Rosemarie); V. Murday (Victoria); N. Bradshaw (Nicola); L. Snadden (Lesley); M. Longmuir (Mark); C. Watt (Catherine); S. Gibson (Sarah); E. Haque (Eshika); E. Tobias (Ed); A. Duncan (Alexis); L. Izatt (Louise); C. Jacobs (Chris); C. Langman (Caroline); A.F. Brady (Angela); S.A. Melville (Scott); K. Randhawa (Kashmir); J. Barwell (Julian); G. Serra-Feliu (Gemma); I.O. Ellis (Ian); F. Lalloo (Fiona); J. Taylor (James); A. Male (Alison); C. Berlin (Cheryl); R. Collier (Rebecca); F. Douglas (Fiona); O. Claber (Oonagh); I. Jobson (Irene); L.J. Walker (Lisa); D. McLeod (Diane); D. Halliday (Dorothy); S. Durell (Sarah); B. Stayner (Barbara); S. Shanley (Susan); N. Rahman (Nazneen); R. Houlston (Richard); A. Stormorken (Astrid); E. Bancroft (Elizabeth); E. Page (Elizabeth); A. Ardern-Jones (Audrey); K. Kohut (Kelly); J. Wiggins (Jennifer); E. Castro (Elena); S.R. Killick; S. Martin (Sue); D. Rea (Dan); A. Kulkarni (Anjana); O. Quarrell (Oliver); C. Bardsley (Cathryn); S. Goff (Sheila); G. Brice (Glen); L. Winchester (Lizzie); C. Eddy (Charlotte); V. Tripathi (Vishakha); V. Attard (Virginia); A. Lehmann (Anna); A. Lucassen (Anneke); G. Crawford (Gabe); D. McBride (Donna); S. Smalley (Sarah); S. Mazoyer (Sylvie); F. Damiola (Francesca); L. Barjhoux (Laure); C. Verny-Pierre (Carole); S. Giraud (Sophie); D. Stoppa-Lyonnet (Dominique); B. Buecher (Bruno); V. Moncoutier (Virginie); M. Belotti (Muriel); C. Tirapo (Carole); A. de Pauw (Antoine); B. Bressac-de Paillerets (Brigitte); O. Caron (Olivier); Y.-J. Bignon (Yves-Jean); N. Uhrhammer (Nancy); V. Bonadona (Valérie); S. Handallou (Sandrine); A. hardouin (Agnès); H. Sobol (Hagay); V. Bourdon (Violaine); T. Noguchi (Tetsuro); A. Remenieras (Audrey); F. Eisinger (François); J.-P. Peyrat; J. Fournier (Joëlle); F. Révillion (Françoise); P. Vennin (Philippe); C. Adenis (Claude); R. Lidereau (Rosette); L. Demange (Liliane); D.W. Muller (Danièle); J.P. Fricker (Jean Pierre); E. Barouk-Simonet (Emmanuelle); F. Bonnet (Françoise); V. Bubien (Virginie); N. Sevenet (Nicolas); M. Longy (Michel); C. Toulas (Christine); R. Guimbaud (Rosine); L. Gladieff (Laurence); V. Feillel (Viviane); H. Dreyfus (Hélène); C. Rebischung (Christine); M. Peysselon (Magalie); F. Coron (Fanny); L. Faivre (Laurence); M. Lebrun (Marine); C. Kientz (Caroline); S.F. Ferrer; M. Frenay (Marc); I. Mortemousque (Isabelle); F. Coulet (Florence); C. Colas (Chrystelle); F. Soubrier; J. Sokolowska (Johanna); M. Bronner (Myriam); H. Lynch (Henry); C.L. Snyder (Carrie); M. Angelakos (Maggie); J. Maskiell (Judi); G.S. Dite (Gillian)

    2013-01-01

    textabstractBRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), w

  6. Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia.

    NARCIS (Netherlands)

    Lan, Q.; Hsiung, C.A.; Matsuo, K.; Hong, Y.C.; Seow, A.; Wang, Z.; Hosgood, H.D.; Chen, K.; Wang, J.C.; Chatterjee, N.; Hu, W.; Wong, M.P.; Zheng, W.; Caporaso, N.; Park, J.Y.; Chen, C.J.; Kim, Y.H.; Kim, Y.T.; Landi, M.T.; Shen, H.; Lawrence, C.; Burdett, L.; Yeager, M.; Yuenger, J.; Jacobs, K.B.; Chang, I.S.; Mitsudomi, T.; Kim, H.N.; Chang, G.C.; Bassig, B.A.; Tucker, M.; Wei, F.; Yin, Y.; Wu, C.; An, S.J.; Qian, B.; Lee, V.H.; Lu, D.; Liu, J.; Jeon, H.S.; Hsiao, C.F.; Sung, J.S.; Kim, J.H.; Gao, Y.T.; Tsai, Y.H.; Jung, Y.J.; Guo, H.; Hu, Z.; Hutchinson, A.; Wang, W.C.; Klein, R.; Chung, C.C.; Oh, I.J.; Chen, K.Y.; Berndt, S.I.; He, X.; Wu, W.; Chang, J.; Zhang, X.C.; Huang, M.S.; Zheng, H.; Wang, J.; Zhao, X.; Li, Y.; Choi, J.E.; Su, W.C.; Park, K.H.; Sung, S.W.; Shu, X.O.; Chen, Y.M.; Liu, L.; Kang, C.H.; Hu, L.; Chen, C.H.; Pao, W.; Kim, Y.C.; Yang, T.Y.; Xu, J.; Guan, P.; Tan, W.; Su, J.; Wang, C.L.; Li, H.; Sihoe, A.D.; Zhao, Z.; Chen, Y.; Choi, Y.Y.; Hung, J.Y.; Kim, J.S.; Yoon, H.I.; Cai, Q.; Lin, C.C.; Park, I.K.; Xu, P.; Dong, J.; Kim, C.; He, Q; Perng, R.P.; Kohno, T.; Kweon, S.S.; Chen, C.Y.; Vermeulen, R.; Wu, J.; Lim, W.Y.; Chen, K.C.; Chow, W.H.; Ji, B.T.; Chan, J.K.; Chu, M.; Li, Y.J.; Yokota, J.; Li, J.; Chen, H.; Xiang, Y.B.; Yu, C.J.; Kunitoh, H.; Wu, G.; Jin, L.; Lo, Y.L.; Shiraishi, K.; Chen, Y.H.; Lin, H.C.; Wu, T.; WU, Y.; Yang, P.C.; Zhou, B.; Shin, M.H.; Fraumeni, J.F.; Lin, D.; Chanock, S.J.; Rothman, N.

    2012-01-01

    To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland Ch

  7. Trichloroethylene and Cancer: Systematic and Quantitative Review of Epidemiologic Evidence for Identifying Hazards

    Directory of Open Access Journals (Sweden)

    Cheryl Siegel Scott

    2011-11-01

    Full Text Available We conducted a meta-analysis focusing on studies with high potential for trichloroethylene (TCE exposure to provide quantitative evaluations of the evidence for associations between TCE exposure and kidney, liver, and non-Hodgkin lymphoma (NHL cancers. A systematic review documenting essential design features, exposure assessment approaches, statistical analyses, and potential sources of confounding and bias identified twenty-four cohort and case-control studies on TCE and the three cancers of interest with high potential for exposure, including five recently published case-control studies of kidney cancer or NHL. Fixed- and random-effects models were fitted to the data on overall exposure and on the highest exposure group. Sensitivity analyses examined the influence of individual studies and of alternative risk estimate selections. For overall TCE exposure and kidney cancer, the summary relative risk (RRm estimate from the random effects model was 1.27 (95% CI: 1.13, 1.43, with a higher RRm for the highest exposure groups (1.58, 95% CI: 1.28, 1.96. The RRm estimates were not overly sensitive to alternative risk estimate selections or to removal of an individual study. There was no apparent heterogeneity or publication bias. For NHL, RRm estimates for overall exposure and for the highest exposure group, respectively, were 1.23 (95% CI: 1.07, 1.42 and 1.43 (95% CI: 1.13, 1.82 and, for liver cancer, 1.29 (95% CI: 1.07, 1.56 and 1.28 (95% CI: 0.93, 1.77. Our findings provide strong support for a causal association between TCE exposure and kidney cancer. The support is strong but less robust for NHL, where issues of study heterogeneity, potential publication bias, and weaker exposure-response results contribute uncertainty, and more limited for liver cancer, where only cohort studies with small numbers of cases were available.

  8. A rare HBV subgenotype D4 with unique genomic signatures identified in north-eastern India--an emerging clinical challenge?

    Directory of Open Access Journals (Sweden)

    Priyanka Banerjee

    Full Text Available BACKGROUND/AIMS: HBV has been classified into ten genotypes (A-J and multiple subgenotypes, some of which strongly influence disease outcome and their distribution also correlate with human migration. HBV infection is highly prevalent in India and its diverse population provides an excellent opportunity to study the distinctiveness of HBV, its evolution and disease biology in variegated ethnic groups. The North-East India, having international frontiers on three sides, is one of the most ethnically and linguistically diverse region of the country. Given the paucity of information on molecular epidemiology of HBV in this region, the study aimed to carry out an in-depth genetic characterization of HBV prevailing in North-East state of Tripura. METHODS: From sera of chronically HBV infected patients biochemical/serological tests, HBV DNA quantification, PCR-amplification, sequencing of PreS/S or full-length HBV genomes were done. HBV genotype/subgenotype determination and sequence variability were assessed by MEGA5-software. The evolutionary divergence times of different HBV subgenotypes were estimated by DNAMLK/PHYLIP program while jpHMM method was used to detect any recombination event in HBV genomes. RESULTS: HBV genotypes D (89.5%, C (6.6% and A (3.9% were detected among chronic carriers. While all HBV/A and HBV/C isolates belonged to subgenotype-A1 and C1 respectively, five subgenotypes of HBV/D (D1-D5 were identified including the first detection of rare D4. These non-recombinant Indian D4 (IndD4 formed a distinct phylogenetic clade, had 2.7% nucleotide divergence and recent evolutionary radiation than other global D4. Ten unique amino acids and 9 novel nucleotide substitutions were identified as IndD4 signatures. All IndD4 carried T120 and R129 in ORF-S that may cause immune/vaccine/diagnostic escape and N128 in ORF-P, implicated as compensatory Lamivudine resistance mutation. CONCLUSIONS: IndD4 has potential to undermine vaccination

  9. Functional screen identifies kinases driving prostate cancer visceral and bone metastasis.

    Science.gov (United States)

    Faltermeier, Claire M; Drake, Justin M; Clark, Peter M; Smith, Bryan A; Zong, Yang; Volpe, Carmen; Mathis, Colleen; Morrissey, Colm; Castor, Brandon; Huang, Jiaoti; Witte, Owen N

    2016-01-12

    Mutationally activated kinases play an important role in the progression and metastasis of many cancers. Despite numerous oncogenic alterations implicated in metastatic prostate cancer, mutations of kinases are rare. Several lines of evidence suggest that nonmutated kinases and their pathways are involved in prostate cancer progression, but few kinases have been mechanistically linked to metastasis. Using a mass spectrometry-based phosphoproteomics dataset in concert with gene expression analysis, we selected over 100 kinases potentially implicated in human metastatic prostate cancer for functional evaluation. A primary in vivo screen based on overexpression of candidate kinases in murine prostate cells identified 20 wild-type kinases that promote metastasis. We queried these 20 kinases in a secondary in vivo screen using human prostate cells. Strikingly, all three RAF family members, MERTK, and NTRK2 drove the formation of bone and visceral metastasis confirmed by positron-emission tomography combined with computed tomography imaging and histology. Immunohistochemistry of tissue microarrays indicated that these kinases are highly expressed in human metastatic castration-resistant prostate cancer tissues. Our functional studies reveal the strong capability of select wild-type protein kinases to drive critical steps of the metastatic cascade, and implicate these kinases in possible therapeutic intervention. PMID:26621741

  10. Steady state or non-steady state? Identifying driving mechanisms of oxygen isotope signatures of leaf transpiration in functionally distinct plant species

    Science.gov (United States)

    Dubbert, Maren; Kübert, Angelika; Cuntz, Matthias; Werner, Christiane

    2015-04-01

    Isotope techniques are widely applied in ecosystem studies. For example, isoflux models are used to separate soil evaporation from transpiration in ecosystems. These models often assume that plant transpiration occurs at isotopic steady state, i.e. that the transpired water shows the same isotopic signature as the source water. Yet, several studies found that transpiration did not occur at isotopic steady state, under both controlled and field conditions. Here we focused on identifying the internal and external factors which drive the isotopic signature of leaf transpiration. Using cavity ring-down spectroscopy (CRDS), the effect of both environmental variables and leaf physiological traits on δ18OT was investigated under controlled conditions. Six plant species with distinct leaf physiological traits were exposed to step changes in relative air humidity (RH), their response in δ18OT and gas exchange parameters and their leaf physiological traits were assessed. Moreover, two functionally distinct plant types (tree, i.e. Quercus suber, and grassland) of a semi-arid Mediterranean oak-woodland where observed under natural conditions throughout an entire growth period in the field. The species differed substantially in their leaf physiological traits and their turn-over times of leaf water. They could be grouped in species with fast (240 min.) turn-over times, mostly due to differences in stomatal conductance, leaf water content or a combination of both. Changes in RH caused an immediate response in δ18OT, which were similarly strong in all species, while leaf physiological traits affected the subsequent response in δ18OT. The turn-over time of leaf water determined the speed of return to the isotopic steady or a stable δ18OT value (Dubbert & Kübert et al., in prep.). Under natural conditions, changes in environmental conditions over the diurnal cycle had a huge impact on the diurnal development of δ18OT in both observed plant functional types. However, in

  11. Leukocyte DNA methylation signature differentiates pancreatic cancer patients from healthy controls.

    Directory of Open Access Journals (Sweden)

    Katrina S Pedersen

    Full Text Available Pancreatic adenocarcinoma (PaC is one of most difficult tumors to treat. Much of this is attributed to the late diagnosis. To identify biomarkers for early detection, we examined DNA methylation differences in leukocyte DNA between PaC cases and controls in a two-phase study. In phase I, we measured methylation levels at 1,505 CpG sites in treatment-naïve leukocyte DNA from 132 never-smoker PaC patients and 60 never-smoker healthy controls. We found significant differences in 110 CpG sites (false discovery rate <0.05. In phase II, we tested and validated 88 of 96 phase I selected CpG sites in 240 PaC cases and 240 matched controls (p≤0.05. Using penalized logistic regression, we built a prediction model consisting of five CpG sites (IL10_P348, LCN2_P86, ZAP70_P220, AIM2_P624, TAL1_P817 that discriminated PaC patients from controls (C-statistic = 0.85 in phase I; 0.76 in phase II. Interestingly, one CpG site (LCN2_P86 alone could discriminate resectable patients from controls (C-statistic= 0.78 in phase I; 0.74 in phase II. We also performed methylation quantitative trait loci (methQTL analysis and identified three CpG sites (AGXT_P180_F, ALOX12_E85_R, JAK3_P1075_R where the methylation levels were significantly associated with single nucleotide polymorphisms (SNPs (false discovery rate <0.05. Our results demonstrate that epigenetic variation in easily obtainable leukocyte DNA, manifested by reproducible methylation differences, may be used to detect PaC patients. The methylation differences at certain CpG sites are partially attributable to genetic variation. This study strongly supports future epigenome-wide association study using leukocyte DNA for biomarker discovery in human diseases.

  12. Dissecting genetic and environmental mutation signatures with model organisms.

    Science.gov (United States)

    Segovia, Romulo; Tam, Annie S; Stirling, Peter C

    2015-08-01

    Deep sequencing has impacted on cancer research by enabling routine sequencing of genomes and exomes to identify genetic changes associated with carcinogenesis. Researchers can now use the frequency, type, and context of all mutations in tumor genomes to extract mutation signatures that reflect the driving mutational processes. Identifying mutation signatures, however, may not immediately suggest a mechanism. Consequently, several recent studies have employed deep sequencing of model organisms exposed to discrete genetic or environmental perturbations. These studies exploit the simpler genomes and availability of powerful genetic tools in model organisms to analyze mutation signatures under controlled conditions, forging mechanistic links between mutational processes and signatures. We discuss the power of this approach and suggest that many such studies may be on the horizon. PMID:25940384

  13. Identifying Factors to Improve Oral Cancer Screening Uptake: A Qualitative Study

    OpenAIRE

    Fatemeh Vida Zohoori; Kamini Shah; Julie Mason; Janet Shucksmith

    2012-01-01

    AIMS: To engage with high risk groups to identify knowledge and awareness of oral cancer signs and symptoms and the factors likely to contribute to improved screening uptake. METHODS: Focus group discussions were undertaken with 18 males; 40+ years of age; smokers and/or drinkers (15+ cigarettes per day and/or 15+ units of alcohol per week), irregular dental attenders living in economically deprived areas of Teesside. RESULTS: There was a striking reported lack of knowledge and awareness of o...

  14. Integrated genome and transcriptome sequencing identifies a novel form of hybrid and aggressive prostate cancer.

    Science.gov (United States)

    Wu, Chunxiao; Wyatt, Alexander W; Lapuk, Anna V; McPherson, Andrew; McConeghy, Brian J; Bell, Robert H; Anderson, Shawn; Haegert, Anne; Brahmbhatt, Sonal; Shukin, Robert; Mo, Fan; Li, Estelle; Fazli, Ladan; Hurtado-Coll, Antonio; Jones, Edward C; Butterfield, Yaron S; Hach, Faraz; Hormozdiari, Fereydoun; Hajirasouliha, Iman; Boutros, Paul C; Bristow, Robert G; Jones, Steven Jm; Hirst, Martin; Marra, Marco A; Maher, Christopher A; Chinnaiyan, Arul M; Sahinalp, S Cenk; Gleave, Martin E; Volik, Stanislav V; Collins, Colin C

    2012-05-01

    Next-generation sequencing is making sequence-based molecular pathology and personalized oncology viable. We selected an individual initially diagnosed with conventional but aggressive prostate adenocarcinoma and sequenced the genome and transcriptome from primary and metastatic tissues collected prior to hormone therapy. The histology-pathology and copy number profiles were remarkably homogeneous, yet it was possible to propose the quadrant of the prostate tumour that likely seeded the metastatic diaspora. Despite a homogeneous cell type, our transcriptome analysis revealed signatures of both luminal and neuroendocrine cell types. Remarkably, the repertoire of expressed but apparently private gene fusions, including C15orf21:MYC, recapitulated this biology. We hypothesize that the amplification and over-expression of the stem cell gene MSI2 may have contributed to the stable hybrid cellular identity. This hybrid luminal-neuroendocrine tumour appears to represent a novel and highly aggressive case of prostate cancer with unique biological features and, conceivably, a propensity for rapid progression to castrate-resistance. Overall, this work highlights the importance of integrated analyses of genome, exome and transcriptome sequences for basic tumour biology, sequence-based molecular pathology and personalized oncology.

  15. DRUG-REPOSITIONING SCREENING IDENTIFIED PIPERLONGUMINE AS A DIRECT STAT3 INHIBITOR WITH POTENT ACTIVITY AGAINST BREAST CANCER

    OpenAIRE

    Bharadwaj, Uddalak; Eckols, T. Kris; Kolosov, Mikhail; Kasembeli, Moses M.; Adam, Abel; Torres, David; Zhang, Xiaomei; Lacey E Dobrolecki; Wei, Wei; Lewis, Michael T; Dave, Bhuvanesh; Chang, Jenny C.; Landis, Melissa D.; Creighton, Chad J.; Mancini, Michael A.

    2014-01-01

    Signal transducer and activator of transcription (STAT) 3 regulates many cardinal features of cancer including cancer cell growth, apoptosis resistance, DNA damage response, metastasis, immune escape, tumor angiogenesis, the Warburg effect, and oncogene addiction and has been validated as a drug target for cancer therapy. Several strategies have been employed to identify agents that target Stat3 in breast cancer but none has yet entered into clinical use. We used a high-throughput fluorescenc...

  16. Characterization of novel tumor stroma markers identified by gene expression profiling of human cancer tissues and 3D co-culture models

    International Nuclear Information System (INIS)

    The tumor stroma plays an important role in tumorigenesis. During cancer progression it undergoes changes in architecture, gene expression and secretion of proteolytic enzymes that are essential for the invasive and metastatic phenotype of malignant tumors. Cancer associated fibroblasts (Cafes) represent the major cellular component of the stroma and recent studies demonstrated the prognostic and therapeutic significance of CaF-related molecular signatures. The identification and characterization of genes and signaling pathways involved in the molecular interactions between tumor and stromal cells has been the focus of this study. For that purpose we have used two complementary approaches: the identification of novel tumor stroma targets in human colon cancer samples using whole genome Affymetrix GeneChip analysis and the validation of theses targets in a newly established of 3D co-culture model that mimics the cellular and molecular heterogeneity of human cancers. We have demonstrated increased expression of gene sets related to hypoxia, epithelial-to-mesenchymal transition (EMT) and TGFβ pathway activation in CAFs vs their normal counterparts in both systems. The putative TGFβ target IGFBP7 (insulin-like growth factor binding protein 7) was identified as a tumor stroma marker of epithelial cancers and as a tumor antigen in mesenchyme-derived sarcomas. IGFPB7 was shown to promote anchorage-independent growth in malignant mesenchymal cells and malignant epithelial cells with an EMT-phenotype, whereas a tumor suppressor function was observed in tumor epithelial cells. In summary, we have demonstrated that a number of important signaling pathways involved in cancer progression and metastasis are specifically dysregulated in the tumor stroma both in our in vivo screen and in the in vitro 3D model, illustrating the value of these approaches for the identification and characterization of novel stromal markers. (author)

  17. Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

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    Matthew Ruffalo

    2015-12-01

    Full Text Available Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these "silent players". For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.

  18. Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation.

    Science.gov (United States)

    Hira, Zena M; Gillies, Duncan F

    2016-01-01

    In order to provide the most effective therapy for cancer, it is important to be able to diagnose whether a patient's cancer will respond to a proposed treatment. Methylation profiling could contain information from which such predictions could be made. Currently, hypothesis testing is used to determine whether possible biomarkers for cancer progression produce statistically significant results. However, this approach requires the identification of individual genes, or sets of genes, as candidate hypotheses, and with the increasing size of modern microarrays, this task is becoming progressively harder. Exhaustive testing of small sets of genes is computationally infeasible, and so hypothesis generation depends either on the use of established biological knowledge or on heuristic methods. As an alternative machine learning, methods can be used to identify groups of genes that are acting together within sets of cancer data and associate their behaviors with cancer progression. These methods have the advantage of being multivariate and unbiased but unfortunately also rapidly become computationally infeasible as the number of gene probes and datasets increases. To address this problem, we have investigated a way of utilizing prior knowledge to segment microarray datasets in such a way that machine learning can be used to identify candidate sets of genes for hypothesis testing. A methylation dataset is divided into subsets, where each subset contains only the probes that relate to a known gene pathway. Each of these pathway subsets is used independently for classification. The classification method is AdaBoost with decision trees as weak classifiers. Since each pathway subset contains a relatively small number of gene probes, it is possible to train and test its classification accuracy quickly and determine whether it has valuable diagnostic information. Finally, genes from successful pathway subsets can be combined to create a classifier of high accuracy. PMID:27688706

  19. Immunohistochemical detection of ROS1 is useful for identifying ROS1 rearrangements in lung cancers.

    Science.gov (United States)

    Yoshida, Akihiko; Tsuta, Koji; Wakai, Susumu; Arai, Yasuhito; Asamura, Hisao; Shibata, Tatsuhiro; Furuta, Koh; Kohno, Takashi; Kushima, Ryoji

    2014-05-01

    The recent discovery and characterization of an oncogenic ROS1 gene fusion in a subset of lung cancers has raised significant clinical interest because small molecule inhibitors may be effective to these tumors. As lung cancers with ROS1 rearrangements comprise only 1-3% of lung adenocarcinomas, patients with such tumors must be identified to gain optimal benefit from molecular therapy. Recently, immunohistochemical analyses using a novel anti-ROS1 rabbit monoclonal antibody (D4D6) have shown promise for accurate identification of ROS1-rearranged cancers. To validate this finding, we compared the immunostaining results of tissue microarrays (TMAs) containing 17 ROS1-rearranged and 253 ROS1-non-rearranged lung carcinomas. All 17 ROS1-rearranged cancers showed ROS1 immunoreactivity mostly in a diffuse and moderate-to-strong manner with an H-score range of 5-300 (median, 260). In contrast, 69% of ROS1-non-rearranged cancers lacked detectable immunoreactivity, whereas the remaining 31% showed reactivity mainly in a weak or focal manner. The H-score for the entire ROS1-non-rearranged group ranged from 0 to 240 (median, 0). The difference in H-score between the two cohorts was statistically significant, and the H-score cutoff (≥150) allowed optimal discrimination (94% sensitivity and 98% specificity). Similar but slightly less-specific performance was achieved using the extent of diffuse (≥75%) staining or ≥2+ staining intensity as cutoffs. CD74-ROS1 and EZR-ROS1 fusions were significantly associated with at least focal globular immunoreactivity and plasma membranous accentuation, respectively, and these patterns were specific to ROS1-rearranged cases. Although full-length ROS1 is expressed in some ROS1-non-rearranged cases, we showed that establishment of an optimal set of interpretative criteria makes ROS1 immunohistochemistry a valuable method to rapidly and accurately screen lung cancer patients for appropriate molecular therapy. PMID:24186139

  20. Tim-3 identifies exhausted follicular helper T cells in breast cancer patients.

    Science.gov (United States)

    Zhu, Shiguang; Lin, Jun; Qiao, Guangdong; Wang, Xingmiao; Xu, Yanping

    2016-09-01

    Breast cancer is the most common cancer diagnosed in women worldwide. Although a series of treatment options have improved the overall 5-year survival rate to 90%, individual responses still vary from patient to patient. New evidence suggested that the infiltration of CXCL13-expressing CD4(+) follicular helper cells (Tfh) in breast tumor predicted better survival. Here, we examined the regulation of Tfh function in breast cancer patients in depth. We found that the frequencies of circulating Tfh cells were not altered in breast cancer patients compared to healthy controls. However, the expression of PD-1 and Tim-3 in Tfh cells was significantly elevated in breast cancer patients. Interestingly, we observed a preferential upregulation of PD-1 in Tim-3(+) Tfh cells compared to Tim-3(-) Tfh cells. Coexpression of PD-1 and Tim-3 is typically a hallmark of functional exhaustion in chronic virus infections and tumor. To examine whether Tim-3(+) identifies exhausted Tfh cells, we stimulated Tfh cells with anti-CD3/CD28, and found that Tim-3(+) T cells expressed reduced frequencies of chemokine CXCL13 and cytokine interleukin 21 (IL-21), and contained fewer proliferating cells, than Tim-3(-) Tfh cells. Compared to those cocultured with Tim-3(-) Tfh cells, naive B cells cocultured with Tim-3(+) Tfh cells resulted in significantly less IgM, IgG and IgA production after 12 day incubation, demonstrating a reduction in Tim-3(+) Tfh-mediated B cell help. Moreover, the frequencies of Tim-3(+) Tfh cells in resected breast tumor were further upregulated than autologous blood, suggesting a participation of Tim-3(+) Tfh cells in tumor physiology. Overall, the data presented here provided new insight in the regulation of Tfh cells in breast cancer patients. PMID:27156907

  1. Androgen receptors and serum testosterone levels identify different subsets of postmenopausal breast cancers

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    Secreto Giorgio

    2012-12-01

    Full Text Available Abstract Background Androgen receptors (AR are frequently expressed in breast cancers, but their implication in cancer growth is still controversial. In the present study, we further investigated the role of the androgen/AR pathway in breast cancer development. Methods AR expression was evaluated by immunochemistry in a cohort of 528 postmenopausal breast cancer patients previously examined for the association of serum testosterone levels with patient and tumor characteristics. AR expression was classified according to the percentage of stained cells: AR-absent (0% and AR-poorly (1%-30%, AR-moderately (>30%-60%, and AR-highly (>60% positive. Results Statistical analysis was performed in 451 patients who experienced natural menopause. AR-high expression was significantly related with low histologic grade and estrogen receptor (ER- and progesterone receptor (PR-positive status (P trendP=0.022, although a trend across the AR expression categories was not present. When women defined by ER status were analyzed separately, regression analysis in the ER-positive group showed a significant association of high testosterone levels with AR-highly-positive expression (OR 1.86; 95% CI, 1.10-3.16, but the association was essentially due to patients greater than or equal to 65 years (OR 2.42; 95% CI, 1.22-4.82. In ER-positive group, elevated testosterone levels appeared also associated with AR-absent expression, although the small number of patients in this category limited the appearance of significant effects (OR 1.92; 95% CI, 0.73–5.02: the association was present in both age groups ( Conclusions The findings in the present study confirm that testosterone levels are a marker of hormone-dependent breast cancer and suggest that the contemporary evaluation of ER status, AR expression, and circulating testosterone levels may identify different subsets of cancers whose growth may be influenced by androgens.

  2. A Specific miRNA Signature Correlates With Complete Pathological Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

    International Nuclear Information System (INIS)

    Purpose: MicroRNAs (miRNAs) are small, noncoding RNA molecules that can be down- or upregulated in colorectal cancer and have been associated to prognosis and response to treatment. We studied miRNA expression in tumor biopsies of patients with rectal cancer to identify a specific “signature” correlating with pathological complete response (pCR) after neoadjuvant chemoradiotherapy. Methods and Materials: A total of 38 T3–4/N+ rectal cancer patients received capecitabine-oxaliplatin and radiotherapy followed by surgery. Pathologic response was scored according to the Mandard TRG scale. MiRNA expression was analyzed by microarray and confirmed by real-time Reverse Transcription Polymerase Chain Reaction (qRT-PCR) on frozen biopsies obtained before treatment. The correlation between miRNA expression and TRG, coded as TRG1 (pCR) vs. TRG >1 (no pCR), was assessed by methods specifically designed for this study. Results: Microarray analysis selected 14 miRNAs as being differentially expressed in TRG1 patients, and 13 were confirmed by qRT-PCR: 11 miRNAs (miR-1183, miR-483-5p, miR-622, miR-125a-3p, miR-1224-5p, miR-188-5p, miR-1471, miR-671-5p, miR-1909∗, miR-630, miR-765) were significantly upregulated in TRG1 patients, 2 (miR-1274b, miR-720) were downexpressed. MiR-622 and miR-630 had a 100% sensitivity and specificity in selecting TRG1 cases. Conclusions: A set of 13 miRNAs is strongly associated with pCR and may represent a specific predictor of response to chemoradiotherapy in rectal cancer patients.

  3. Identifying Gender-Preferred Communication Styles within Online Cancer Communities: A Retrospective, Longitudinal Analysis

    Science.gov (United States)

    Durant, Kathleen T.; McCray, Alexa T.; Safran, Charles

    2012-01-01

    Background The goal of this research is to determine if different gender-preferred social styles can be observed within the user interactions at an online cancer community. To achieve this goal, we identify and measure variables that pertain to each gender-specific social style. Methods and Findings We perform social network and statistical analysis on the communication flow of 8,388 members at six different cancer forums over eight years. Kruskal-Wallis tests were conducted to measure the difference between the number of intimate (and highly intimate) dyads, relationship length, and number of communications. We determine that two patients are more likely to form an intimate bond on a gender-specific cancer forum (ovarian P = <0.0001, breast P = 0.0089, prostate P = 0.0021). Two female patients are more likely to form a highly intimate bond on a female-specific cancer forum (Ovarian P<0.0001, Breast P<0.01). Typically a male patient communicates with more members than a female patient (Ovarian forum P = 0.0406, Breast forum P = 0.0013). A relationship between two patients is longer on the gender-specific cancer forums than a connection between two members not identified as patients (ovarian forum P = 0.00406, breast forum P = 0.00013, prostate forum P = .0.0003). Conclusion The high level of interconnectedness among the prostate patients supports the hypothesis that men prefer to socialize in large, interconnected, less-intimate groups. A female patient is more likely to form a highly intimate connection with another female patient; this finding is consistent with the hypothesis that woman prefer fewer, more intimate connections. The relationships of same-gender cancer patients last longer than other relationships; this finding demonstrates homophily within these online communities. Our findings regarding online communication preferences are in agreement with research findings from person-to-person communication preference studies

  4. Identifying gender-preferred communication styles within online cancer communities: a retrospective, longitudinal analysis.

    Directory of Open Access Journals (Sweden)

    Kathleen T Durant

    Full Text Available BACKGROUND: The goal of this research is to determine if different gender-preferred social styles can be observed within the user interactions at an online cancer community. To achieve this goal, we identify and measure variables that pertain to each gender-specific social style. METHODS AND FINDINGS: We perform social network and statistical analysis on the communication flow of 8,388 members at six different cancer forums over eight years. Kruskal-Wallis tests were conducted to measure the difference between the number of intimate (and highly intimate dyads, relationship length, and number of communications. We determine that two patients are more likely to form an intimate bond on a gender-specific cancer forum (ovarian P = <0.0001, breast P = 0.0089, prostate P = 0.0021. Two female patients are more likely to form a highly intimate bond on a female-specific cancer forum (Ovarian P<0.0001, Breast P<0.01. Typically a male patient communicates with more members than a female patient (Ovarian forum P = 0.0406, Breast forum P = 0.0013. A relationship between two patients is longer on the gender-specific cancer forums than a connection between two members not identified as patients (ovarian forum P = 0.00406, breast forum P = 0.00013, prostate forum P = .0.0003. CONCLUSION: The high level of interconnectedness among the prostate patients supports the hypothesis that men prefer to socialize in large, interconnected, less-intimate groups. A female patient is more likely to form a highly intimate connection with another female patient; this finding is consistent with the hypothesis that woman prefer fewer, more intimate connections. The relationships of same-gender cancer patients last longer than other relationships; this finding demonstrates homophily within these online communities. Our findings regarding online communication preferences are in agreement with research findings from person-to-person communication

  5. Large-scale evaluation of candidate genes identifies associations between VEGF polymorphisms and bladder cancer risk.

    Directory of Open Access Journals (Sweden)

    Montserrat García-Closas

    2007-02-01

    Full Text Available Common genetic variation could alter the risk for developing bladder cancer. We conducted a large-scale evaluation of single nucleotide polymorphisms (SNPs in candidate genes for cancer to identify common variants that influence bladder cancer risk. An Illumina GoldenGate assay was used to genotype 1,433 SNPs within or near 386 genes in 1,086 cases and 1,033 controls in Spain. The most significant finding was in the 5' UTR of VEGF (rs25648, p for likelihood ratio test, 2 degrees of freedom = 1 x 10(-5. To further investigate the region, we analyzed 29 additional SNPs in VEGF, selected to saturate the promoter and 5' UTR and to tag common genetic variation in this gene. Three additional SNPs in the promoter region (rs833052, rs1109324, and rs1547651 were associated with increased risk for bladder cancer: odds ratio (95% confidence interval: 2.52 (1.06-5.97, 2.74 (1.26-5.98, and 3.02 (1.36-6.63, respectively; and a polymorphism in intron 2 (rs3024994 was associated with reduced risk: 0.65 (0.46-0.91. Two of the promoter SNPs and the intron 2 SNP showed linkage disequilibrium with rs25648. Haplotype analyses revealed three blocks of linkage disequilibrium with significant associations for two blocks including the promoter and 5' UTR (global p = 0.02 and 0.009, respectively. These findings are biologically plausible since VEGF is critical in angiogenesis, which is important for tumor growth, its elevated expression in bladder tumors correlates with tumor progression, and specific 5' UTR haplotypes have been shown to influence promoter activity. Associations between bladder cancer risk and other genes in this report were not robust based on false discovery rate calculations. In conclusion, this large-scale evaluation of candidate cancer genes has identified common genetic variants in the regulatory regions of VEGF that could be associated with bladder cancer risk.

  6. Genome-wide association studies identify four ER negative–specific breast cancer risk loci

    Science.gov (United States)

    Garcia-Closas, Montserrat; Couch, Fergus J; Lindstrom, Sara; Michailidou, Kyriaki; Schmidt, Marjanka K; Brook, Mark N; orr, Nick; Rhie, Suhn Kyong; Riboli, Elio; Feigelson, Heather s; Le Marchand, Loic; Buring, Julie E; Eccles, Diana; Miron, Penelope; Fasching, Peter A; Brauch, Hiltrud; Chang-Claude, Jenny; Carpenter, Jane; Godwin, Andrew K; Nevanlinna, Heli; Giles, Graham G; Cox, Angela; Hopper, John L; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dicks, Ed; Howat, Will J; Schoof, Nils; Bojesen, Stig E; Lambrechts, Diether; Broeks, Annegien; Andrulis, Irene L; Guénel, Pascal; Burwinkel, Barbara; Sawyer, Elinor J; Hollestelle, Antoinette; Fletcher, Olivia; Winqvist, Robert; Brenner, Hermann; Mannermaa, Arto; Hamann, Ute; Meindl, Alfons; Lindblom, Annika; Zheng, Wei; Devillee, Peter; Goldberg, Mark S; Lubinski, Jan; Kristensen, Vessela; Swerdlow, Anthony; Anton-Culver, Hoda; Dörk, Thilo; Muir, Kenneth; Matsuo, Keitaro; Wu, Anna H; Radice, Paolo; Teo, Soo Hwang; Shu, Xiao-Ou; Blot, William; Kang, Daehee; Hartman, Mikael; Sangrajrang, Suleeporn; Shen, Chen-Yang; Southey, Melissa C; Park, Daniel J; Hammet, Fleur; Stone, Jennifer; Veer, Laura J Van’t; Rutgers, Emiel J; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Peto, Julian; Schrauder, Michael G; Ekici, Arif B; Beckmann, Matthias W; Silva, Isabel dos Santos; Johnson, Nichola; Warren, Helen; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Marme, Federick; Schneeweiss, Andreas; Sohn, Christof; Truong, Therese; Laurent-Puig, Pierre; Kerbrat, Pierre; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Lichtner, Peter; Lochmann, Magdalena; Justenhoven, Christina; Ko, Yon-Dschun; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Greco, Dario; Heikkinen, Tuomas; Ito, Hidemi; Iwata, Hiroji; Yatabe, Yasushi; Antonenkova, Natalia N; Margolin, Sara; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Balleine, Rosemary; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Neven, Patrick; Dieudonné, Anne-Sophie; Leunen, Karin; Rudolph, Anja; Nickels, Stefan; Flesch-Janys, Dieter; Peterlongo, Paolo; Peissel, Bernard; Bernard, Loris; Olson, Janet E; Wang, Xianshu; Stevens, Kristen; Severi, Gianluca; Baglietto, Laura; Mclean, Catriona; Coetzee, Gerhard A; Feng, Ye; Henderson, Brian E; Schumacher, Fredrick; Bogdanova, Natalia V; Labrèche, France; Dumont, Martine; Yip, Cheng Har; Taib, Nur Aishah Mohd; Cheng, Ching-Yu; Shrubsole, Martha; Long, Jirong; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Tollenaar, Robertus A E M; Seynaeve, Caroline M; Kriege, Mieke; Hooning, Maartje J; Van den Ouweland, Ans M W; Van Deurzen, Carolien H M; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Balasubramanian, Sabapathy P; Cross, Simon S; Reed, Malcolm W R; Signorello, Lisa; Cai, Qiuyin; Shah, Mitul; Miao, Hui; Chan, Ching Wan; Chia, Kee Seng; Jakubowska, Anna; Jaworska, Katarzyna; Durda, Katarzyna; Hsiung, Chia-Ni; Wu, Pei-Ei; Yu, Jyh-Cherng; Ashworth, Alan; Jones, Michael; Tessier, Daniel C; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Vincent, Daniel; Bacot, Francois; Ambrosone, Christine B; Bandera, Elisa V; John, Esther M; Chen, Gary K; Hu, Jennifer J; Rodriguez-gil, Jorge L; Bernstein, Leslie; Press, Michael F; Ziegler, Regina G; Millikan, Robert M; Deming-Halverson, Sandra L; Nyante, Sarah; Ingles, Sue A; Waisfisz, Quinten; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Gibson, Lorna; Müller-Myhsok, Bertram; Schmutzler, Rita K; Hein, Rebecca; Dahmen, Norbert; Beckmann, Lars; Aaltonen, Kirsimari; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Turnbull, Clare; Rahman, Nazneen; Meijers-Heijboer, Hanne; Uitterlinden, Andre G; Rivadeneira, Fernando; Olswold, Curtis; Slager, Susan; Pilarski, Robert; Ademuyiwa, Foluso; Konstantopoulou, Irene; Martin, Nicholas G; Montgomery, Grant W; Slamon, Dennis J; Rauh, Claudia; Lux, Michael P; Jud, Sebastian M; Bruning, Thomas; Weaver, Joellen; Sharma, Priyanka; Pathak, Harsh; Tapper, Will; Gerty, Sue; Durcan, Lorraine; Trichopoulos, Dimitrios; Tumino, Rosario; Peeters, Petra H; Kaaks, Rudolf; Campa, Daniele; Canzian, Federico; Weiderpass, Elisabete; Johansson, Mattias; Khaw, Kay-Tee; Travis, Ruth; Clavel-Chapelon, Françoise; Kolonel, Laurence N; Chen, Constance; Beck, Andy; Hankinson, Susan E; Berg, Christine D; Hoover, Robert N; Lissowska, Jolanta; Figueroa, Jonine D; Chasman, Daniel I; Gaudet, Mia M; Diver, W Ryan

    2013-01-01

    Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10−12 and LGR6, P = 1.4 × 10−8), 2p24.1 (P = 4.6 × 10−8) and 16q12.2 (FTO, P = 4.0 × 10−8), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers. PMID:23535733

  7. Five endometrial cancer risk loci identified through genome-wide association analysis.

    Science.gov (United States)

    Cheng, Timothy H T; Thompson, Deborah J; O'Mara, Tracy A; Painter, Jodie N; Glubb, Dylan M; Flach, Susanne; Lewis, Annabelle; French, Juliet D; Freeman-Mills, Luke; Church, David; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Webb, Penelope M; Attia, John; Holliday, Elizabeth G; McEvoy, Mark; Scott, Rodney J; Henders, Anjali K; Martin, Nicholas G; Montgomery, Grant W; Nyholt, Dale R; Ahmed, Shahana; Healey, Catherine S; Shah, Mitul; Dennis, Joe; Fasching, Peter A; Beckmann, Matthias W; Hein, Alexander; Ekici, Arif B; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo; Amant, Frederic; Schrauwen, Stefanie; Zhao, Hui; Lambrechts, Diether; Depreeuw, Jeroen; Dowdy, Sean C; Goode, Ellen L; Fridley, Brooke L; Winham, Stacey J; Njølstad, Tormund S; Salvesen, Helga B; Trovik, Jone; Werner, Henrica M J; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Liu, Tao; Mints, Miriam; Tham, Emma; Li, Mulin Jun; Yip, Shun H; Wang, Junwen; Bolla, Manjeet K; Michailidou, Kyriaki; Wang, Qin; Tyrer, Jonathan P; Dunlop, Malcolm; Houlston, Richard; Palles, Claire; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Cunningham, Julie M; Pharoah, Paul D P; Dunning, Alison M; Edwards, Stacey L; Easton, Douglas F; Tomlinson, Ian; Spurdle, Amanda B

    2016-06-01

    We conducted a meta-analysis of three endometrial cancer genome-wide association studies (GWAS) and two follow-up phases totaling 7,737 endometrial cancer cases and 37,144 controls of European ancestry. Genome-wide imputation and meta-analysis identified five new risk loci of genome-wide significance at likely regulatory regions on chromosomes 13q22.1 (rs11841589, near KLF5), 6q22.31 (rs13328298, in LOC643623 and near HEY2 and NCOA7), 8q24.21 (rs4733613, telomeric to MYC), 15q15.1 (rs937213, in EIF2AK4, near BMF) and 14q32.33 (rs2498796, in AKT1, near SIVA1). We also found a second independent 8q24.21 signal (rs17232730). Functional studies of the 13q22.1 locus showed that rs9600103 (pairwise r(2) = 0.98 with rs11841589) is located in a region of active chromatin that interacts with the KLF5 promoter region. The rs9600103[T] allele that is protective in endometrial cancer suppressed gene expression in vitro, suggesting that regulation of the expression of KLF5, a gene linked to uterine development, is implicated in tumorigenesis. These findings provide enhanced insight into the genetic and biological basis of endometrial cancer. PMID:27135401

  8. Follow-up Care Education and Information: Identifying Cancer Survivors in Need of More Guidance.

    Science.gov (United States)

    O'Malley, Denalee M; Hudson, Shawna V; Ohman-Strickland, Pamela A; Bator, Alicja; Lee, Heather S; Gundersen, Daniel A; Miller, Suzanne M

    2016-03-01

    Cancer survivors engage in cancer screenings and protective health behaviors at suboptimal rates despite their increased risk for future illness. Survivorship care plans and other educational strategies to prepare cancer survivors to adopt engaged roles in managing long-term follow-up care and health risks are needed. In a sample of cancer survivors, we identified patient characteristics and psychosocial predictors associated with increased follow-up care informational needs. Cross-sectional surveys were administered to early-stage breast and prostate survivors (N = 278; 68 % breast) at least 2 years post treatment from four community hospital programs in New Jersey between May 2012 and July 2013. Patient demographics, medical history, psychosocial characteristics (i.e., worries about the future, fear of disease recurrence, and patient activation), and perceptions of oncology and primary care were assessed. African-American survivors (AOR = 2.69, 95 % confidence interval [CI] 1.27-5.68) and survivors with higher comorbidity (AOR =1.16, CI 1.01-1.33) were more likely to want additional information to guide follow-up care. Adjusting for race and comorbidities, survivors who wanted more information to guide their follow-up care reported greater worries about the future (p educational strategies that are both responsive to the needs of specific populations (e.g., African-American survivors and patients with multiple comorbidities) and the psychosocial profiles that motivate requests for more extensive follow-up guidance. PMID:25524391

  9. Oligonucleotide microarray identifies genes differentially expressed during tumorigenesis of DMBA-induced pancreatic cancer in rats.

    Directory of Open Access Journals (Sweden)

    Jun-Chao Guo

    Full Text Available The extremely dismal prognosis of pancreatic cancer (PC is attributed, at least in part, to lack of early diagnosis. Therefore, identifying differentially expressed genes in multiple steps of tumorigenesis of PC is of great interest. In the present study, a 7,12-dimethylbenzanthraene (DMBA-induced PC model was established in male Sprague-Dawley rats. The gene expression profile was screened using an oligonucleotide microarray, followed by real-time quantitative polymerase chain reaction (qRT-PCR and immunohistochemical staining validation. A total of 661 differentially expressed genes were identified in stages of pancreatic carcinogenesis. According to GO classification, these genes were involved in multiple molecular pathways. Using two-way hierarchical clustering analysis, normal pancreas, acute and chronic pancreatitis, PanIN, early and advanced pancreatic cancer were completely discriminated. Furthermore, 11 upregulated and 142 downregulated genes (probes were found by Mann-Kendall trend Monotone test, indicating homologous genes of rat and human. The qRT-PCR and immunohistochemistry analysis of CXCR7 and UBe2c, two of the identified genes, confirmed the microarray results. In human PC cell lines, knockdown of CXCR7 resulted in decreased migration and invasion. Collectively, our data identified several promising markers and therapeutic targets of PC based on a comprehensive screening and systemic validation.

  10. Genomic Copy Number Signatures Uncovered a Genetically Distinct Group from Adenocarcinoma and Squamous Cell Carcinoma in Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Lee, Eunjung; Moon, Ji Wook; Wang, Xianfu; Kim, Chungyeul; Li, Shibo; Shin, Bong Kyung; Jung, Wonkyung; Kim, Hyun Koo; Kim, Han Kyeom; Lee, Ji-Yun

    2015-08-01

    Adenocarcinoma (AC) and squamous cell carcinoma (SCC) of non-small cell lung carcinoma (NSCLC) have different clinical presentations, morphologies, treatments, and prognoses. Recent studies suggested that fundamental genetic alterations related to carcinogenesis of each tumor type may be different. In this study, we investigated the genomic alterations of 47 primary NSCLC samples (22 ACs and 25 SCCs) as well as the corresponding normal tissue using array comparative genomic hybridization. Frequent copy number alterations (CNAs), which were identified in more than 68% of all of the cases, were evaluated in each subtype (SCC and AC), and a CNA signature was established. Among these CNAs, 37 genes from the SCCs and 15 genes from the ACs were located in a region of gain, and 4 genes from the SCCs and 13 genes from the ACs were located in a region of loss. The most frequent gain was located on 3q26-29 including the gene TP63 in SCCs and 7q11.23 and 7q36.3 in ACs. Moreover, we identified 3 genetically distinct groups (group I [16 SCC] with CNA signature of SCC; group II [7 SCC + 8 AC], which has a genetically distinctive CNA signature from SCC and AC; and group III [2 SCC + 14 AC] with CNA signature of AC) by gene clustering extracted from CNAs, which are associated with a prognosis. The present study contributed to the molecular characterization of AC and SCC of NSCLC and showed a subtype of tumor that has a unique genetic CNA signature. However, further study about the significance of these 3 distinct groups and their usefulness as a diagnostic marker of identified CNAs is necessary.

  11. Oncogene Mutations in Colorectal Polyps Identified in the Norwegian Colorectal Cancer Prevention (NORCCAP) Screening Study

    Science.gov (United States)

    Lorentzen, Jon A.; Grzyb, Krzysztof; De Angelis, Paula M.; Hoff, Geir; Eide, Tor J.; Andresen, Per Arne

    2016-01-01

    Data are limited on oncogene mutation frequencies in polyps from principally asymptomatic participants of population-based colorectal cancer screening studies. In this study, DNA from 204 polyps, 5 mm or larger, were collected from 176 participants of the NORCCAP screening study and analyzed for mutations in KRAS, BRAF, and PIK3CA including the rarely studied KRAS exons 3 and 4 mutations. KRAS mutations were identified in 23.0% of the lesions and were significantly associated with tubulovillous adenomas and large size. A significantly higher frequency of KRAS mutations in females was associated with mutations in codon 12. The KRAS exon 3 and 4 mutations constituted 23.4% of the KRAS positive lesions, which is a larger proportion compared to previous observations in colorectal cancer. BRAF mutations were identified in 11.3% and were associated with serrated polyps. None of the individuals were diagnosed with de novo or recurrent colorectal cancer during the follow-up time (median 11.2 years). Revealing differences in mutation-spectra according to gender and stages in tumorigenesis might be important for optimal use of oncogenes as therapeutic targets and biomarkers. PMID:27656095

  12. GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer.

    Science.gov (United States)

    Pharoah, Paul D P; Tsai, Ya-Yu; Ramus, Susan J; Phelan, Catherine M; Goode, Ellen L; Lawrenson, Kate; Buckley, Melissa; Fridley, Brooke L; Tyrer, Jonathan P; Shen, Howard; Weber, Rachel; Karevan, Rod; Larson, Melissa C; Song, Honglin; Tessier, Daniel C; Bacot, François; Vincent, Daniel; Cunningham, Julie M; Dennis, Joe; Dicks, Ed; Aben, Katja K; Anton-Culver, Hoda; Antonenkova, Natalia; Armasu, Sebastian M; Baglietto, Laura; Bandera, Elisa V; Beckmann, Matthias W; Birrer, Michael J; Bloom, Greg; Bogdanova, Natalia; Brenton, James D; Brinton, Louise A; Brooks-Wilson, Angela; Brown, Robert; Butzow, Ralf; Campbell, Ian; Carney, Michael E; Carvalho, Renato S; Chang-Claude, Jenny; Chen, Y Anne; Chen, Zhihua; Chow, Wong-Ho; Cicek, Mine S; Coetzee, Gerhard; Cook, Linda S; Cramer, Daniel W; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Despierre, Evelyn; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Edwards, Robert; Ekici, Arif B; Fasching, Peter A; Fenstermacher, David; Flanagan, James; Gao, Yu-Tang; Garcia-Closas, Montserrat; Gentry-Maharaj, Aleksandra; Giles, Graham; Gjyshi, Anxhela; Gore, Martin; Gronwald, Jacek; Guo, Qi; Halle, Mari K; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hillemanns, Peter; Hoatlin, Maureen; Høgdall, Estrid; Høgdall, Claus K; Hosono, Satoyo; Jakubowska, Anna; Jensen, Allan; Kalli, Kimberly R; Karlan, Beth Y; Kelemen, Linda E; Kiemeney, Lambertus A; Kjaer, Susanne Krüger; Konecny, Gottfried E; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Nathan; Lee, Janet; Leminen, Arto; Lim, Boon Kiong; Lissowska, Jolanta; Lubiński, Jan; Lundvall, Lene; Lurie, Galina; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Nakanishi, Toru; Narod, Steven A; Ness, Roberta B; Nevanlinna, Heli; Nickels, Stefan; Noushmehr, Houtan; Odunsi, Kunle; Olson, Sara; Orlow, Irene; Paul, James; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jenny; Pike, Malcolm C; Poole, Elizabeth M; Qu, Xiaotao; Risch, Harvey A; Rodriguez-Rodriguez, Lorna; Rossing, Mary Anne; Rudolph, Anja; Runnebaum, Ingo; Rzepecka, Iwona K; Salvesen, Helga B; Schwaab, Ira; Severi, Gianluca; Shen, Hui; Shridhar, Vijayalakshmi; Shu, Xiao-Ou; Sieh, Weiva; Southey, Melissa C; Spellman, Paul; Tajima, Kazuo; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S; van Altena, Anne M; van den Berg, David; Vergote, Ignace; Vierkant, Robert A; Vitonis, Allison F; Wang-Gohrke, Shan; Wentzensen, Nicolas; Whittemore, Alice S; Wik, Elisabeth; Winterhoff, Boris; Woo, Yin Ling; Wu, Anna H; Yang, Hannah P; Zheng, Wei; Ziogas, Argyrios; Zulkifli, Famida; Goodman, Marc T; Hall, Per; Easton, Douglas F; Pearce, Celeste L; Berchuck, Andrew; Chenevix-Trench, Georgia; Iversen, Edwin; Monteiro, Alvaro N A; Gayther, Simon A; Schildkraut, Joellen M; Sellers, Thomas A

    2013-04-01

    Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10(-9)) and 10p12 (rs1243180, P = 1.8 × 10(-8)) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10(-10)). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility and implicated CHMP4C in the pathogenesis of ovarian cancer. PMID:23535730

  13. GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer

    Science.gov (United States)

    Pharoah, Paul D. P.; Tsai, Ya-Yu; Ramus, Susan J.; Phelan, Catherine M.; Goode, Ellen L.; Lawrenson, Kate; Price, Melissa; Fridley, Brooke L.; Tyrer, Jonathan P.; Shen, Howard; Weber, Rachel; Karevan, Rod; Larson, Melissa C.; Song, Honglin; Tessier, Daniel C.; Bacot, François; Vincent, Daniel; Cunningham, Julie M.; Dennis, Joe; Dicks, Ed; Aben, Katja K.; Anton-Culver, Hoda; Antonenkova, Natalia; Armasu, Sebastian M.; Baglietto, Laura; Bandera, Elisa V.; Beckmann, Matthias W.; Birrer, Michael J.; Bloom, Greg; Bogdanova, Natalia; Brenton, James D.; Brinton, Louise A.; Brooks-Wilson, Angela; Brown, Robert; Butzow, Ralf; Campbell, Ian; Carney, Michael E; Carvalho, Renato S.; Chang-Claude, Jenny; Chen, Y. Anne; Chen, Zhihua; Chow, Wong-Ho; Cicek, Mine S.; Coetzee, Gerhard; Cook, Linda S.; Cramer, Daniel W.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Despierre, Evelyn; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Edwards, Robert; Ekici, Arif B.; Fasching, Peter A.; Fenstermacher, David; Flanagan, James; Gao, Yu-Tang; Garcia-Closas, Montserrat; Gentry-Maharaj, Aleksandra; Giles, Graham; Gjyshi, Anxhela; Gore, Martin; Gronwald, Jacek; Guo, Qi; Halle, Mari K; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hillemanns, Peter; Hoatlin, Maureen; Høgdall, Estrid; Høgdall, Claus K.; Hosono, Satoyo; Jakubowska, Anna; Jensen, Allan; Kalli, Kimberly R.; Karlan, Beth Y.; Kelemen, Linda E.; Kiemeney, Lambertus A.; Kjaer, Susanne Krüger; Konecny, Gottfried E.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Nathan; Lee, Janet; Leminen, Arto; Lim, Boon Kiong; Lissowska, Jolanta; Lubiński, Jan; Lundvall, Lene; Lurie, Galina; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Nakanishi, Toru; Narod, Steven A.; Ness, Roberta B.; Nevanlinna, Heli; Nickels, Stefan; Noushmehr, Houtan; Odunsi, Kunle; Olson, Sara; Orlow, Irene; Paul, James; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jenny; Pike, Malcolm C; Poole, Elizabeth M; Qu, Xiaotao; Risch, Harvey A.; Rodriguez-Rodriguez, Lorna; Rossing, Mary Anne; Rudolph, Anja; Runnebaum, Ingo; Rzepecka, Iwona K; Salvesen, Helga B.; Schwaab, Ira; Severi, Gianluca; Shen, Hui; Shridhar, Vijayalakshmi; Shu, Xiao-Ou; Sieh, Weiva; Southey, Melissa C.; Spellman, Paul; Tajima, Kazuo; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S.; van Altena, Anne M.; Berg, David Van Den; Vergote, Ignace; Vierkant, Robert A.; Vitonis, Allison F.; Wang-Gohrke, Shan; Wentzensen, Nicolas; Whittemore, Alice S.; Wik, Elisabeth; Winterhoff, Boris; Woo, Yin Ling; Wu, Anna H; Yang, Hannah P.; Zheng, Wei; Ziogas, Argyrios; Zulkifli, Famida; Goodman, Marc T.; Hall, Per; Easton, Douglas F; Pearce, Celeste L; Berchuck, Andrew; Chenevix-Trench, Georgia; Iversen, Edwin; Monteiro, Alvaro N.A.; Gayther, Simon A.; Schildkraut, Joellen M.; Sellers, Thomas A.

    2013-01-01

    Genome wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC) with another two loci being close to genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the United Kingdom. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. Follow-up genotyping was carried out in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 previously near genome-wide significance and identified three novel loci associated with risk; two loci associated with all EOC subtypes, at 8q21 (rs11782652, P=5.5×10-9) and 10p12 (rs1243180; P=1.8×10-8), and another locus specific to the serous subtype at 17q12 (rs757210; P=8.1×10-10). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility that implicates CHMP4C in the pathogenesis of ovarian cancer. PMID:23535730

  14. Comparative analysis of methods for identifying recurrent copy number alterations in cancer.

    Directory of Open Access Journals (Sweden)

    Xiguo Yuan

    Full Text Available Recurrent copy number alterations (CNAs play an important role in cancer genesis. While a number of computational methods have been proposed for identifying such CNAs, their relative merits remain largely unknown in practice since very few efforts have been focused on comparative analysis of the methods. To facilitate studies of recurrent CNA identification in cancer genome, it is imperative to conduct a comprehensive comparison of performance and limitations among existing methods. In this paper, six representative methods proposed in the latest six years are compared. These include one-stage and two-stage approaches, working with raw intensity ratio data and discretized data respectively. They are based on various techniques such as kernel regression, correlation matrix diagonal segmentation, semi-parametric permutation and cyclic permutation schemes. We explore multiple criteria including type I error rate, detection power, Receiver Operating Characteristics (ROC curve and the area under curve (AUC, and computational complexity, to evaluate performance of the methods under multiple simulation scenarios. We also characterize their abilities on applications to two real datasets obtained from cancers with lung adenocarcinoma and glioblastoma. This comparison study reveals general characteristics of the existing methods for identifying recurrent CNAs, and further provides new insights into their strengths and weaknesses. It is believed helpful to accelerate the development of novel and improved methods.

  15. A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer

    Science.gov (United States)

    Al Olama, Ali Amin; Kote-Jarai, Zsofia; Berndt, Sonja I.; Conti, David V.; Schumacher, Fredrick; Han, Ying; Benlloch, Sara; Hazelett, Dennis J.; Wang, Zhaoming; Saunders, Ed; Leongamornlert, Daniel; Lindstrom, Sara; Jugurnauth-Little, Sara; Dadaev, Tokhir; Tymrakiewicz, Malgorzata; Stram, Daniel O.; Rand, Kristin; Wan, Peggy; Stram, Alex; Sheng, Xin; Pooler, Loreall C.; Park, Karen; Xia, Lucy; Tyrer, Jonathan; Kolonel, Laurence N.; Le Marchand, Loic; Hoover, Robert N.; Machiela, Mitchell J.; Yeager, Merideth; Burdette, Laurie; Chung, Charles C.; Hutchinson, Amy; Yu, Kai; Goh, Chee; Ahmed, Mahbubl; Govindasami, Koveela; Guy, Michelle; Tammela, Teuvo L.J.; Auvinen, Anssi; Wahlfors, Tiina; Schleutker, Johanna; Visakorpi, Tapio; Leinonen, Katri A.; Xu, Jianfeng; Aly, Markus; Donovan, Jenny; Travis, Ruth C.; Key, Tim J.; Siddiq, Afshan; Canzian, Federico; Khaw, Kay-Tee; Takahashi, Atsushi; Kubo, Michiaki; Pharoah, Paul; Pashayan, Nora; Weischer, Maren; Nordestgaard, Borge G.; Nielsen, Sune F.; Klarskov, Peter; Røder, Martin Andreas; Iversen, Peter; Thibodeau, Stephen N.; McDonnell, Shannon K; Schaid, Daniel J; Stanford, Janet L.; Kolb, Suzanne; Holt, Sarah; Knudsen, Beatrice; Coll, Antonio Hurtado; Gapstur, Susan M.; Diver, W. Ryan; Stevens, Victoria L.; Maier, Christiane; Luedeke, Manuel; Herkommer, Kathleen; Rinckleb, Antje E.; Strom, Sara S.; Pettaway, Curtis; Yeboah, Edward D.; Tettey, Yao; Biritwum, Richard B.; Adjei, Andrew A.; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P.; Cannon-Albright, Lisa; Cybulski, Cezary; Wokołorczyk, Dominika; Kluźniak, Wojciech; Park, Jong; Sellers, Thomas; Lin, Hui-Yi; Isaacs, William B.; Partin, Alan W.; Brenner, Hermann; Dieffenbach, Aida Karina; Stegmaier, Christa; Chen, Constance; Giovannucci, Edward L.; Ma, Jing; Stampfer, Meir; Penney, Kathryn L.; Mucci, Lorelei; John, Esther M.; Ingles, Sue A.; Kittles, Rick A.; Murphy, Adam B.; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej M.; Blot, William; Signorello, Lisa B.; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, Cristina; Wu, Suh-Yuh; Hennis, Anselm; Kibel, Adam S.; Rybicki, Benjamin A.; Neslund-Dudas, Christine; Hsing, Ann W.; Chu, Lisa; Goodman, Phyllis J.; Klein, Eric A; Zheng, S. Lilly; Batra, Jyotsna; Clements, Judith; Spurdle, Amanda; Teixeira, Manuel R.; Paulo, Paula; Maia, Sofia; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Witte, John S.; Casey, Graham; Gillanders, Elizabeth M.; Seminara, Daniella; Riboli, Elio; Hamdy, Freddie C.; Coetzee, Gerhard A.; Li, Qiyuan; Freedman, Matthew L.; Hunter, David J.; Muir, Kenneth; Gronberg, Henrik; Neal, David E.; Southey, Melissa; Giles, Graham G.; Severi, Gianluca; Cook, Michael B.; Nakagawa, Hidewaki; Wiklund, Fredrik; Kraft, Peter; Chanock, Stephen J.; Henderson, Brian E.; Easton, Douglas F.; Eeles, Rosalind A.; Haiman, Christopher A.

    2014-01-01

    Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of >10 million SNPs in 43,303prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three novel susceptibility loci were revealed at P<5×10-8; 15 variants were identified among men of European ancestry, 7 from multiethnic analyses and one was associated with early-onset prostate cancer. These 23 variants, in combination with the known prostate cancer risk variants, explain 33% of the familial risk of the disease in European ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the utility of combining ancestrally diverse populations to discover risk loci for disease. PMID:25217961

  16. Candidate cancer-targeting agents identified by expression-profiling arrays

    Directory of Open Access Journals (Sweden)

    Termglinchan V

    2013-04-01

    Full Text Available Vittavat Termglinchan,1 Wachiraporn Wanichnopparat,1 Kulachanya Suwanwongse,1 Chunhakarn Teeyapant,1 Kanticha Chatpermporn,1 Kanchana Leerunyakul,1 Khwanruthai Chuadpia,1 Onpailin Sirimaneethum,1 Parinya Wijitworawong,1 Wattanakitch Mutirangura,1 Chatchawit Aporntewan,2 Chanida Vinayanuwattikun,3 Apiwat Mutirangura4 1Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; 2Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Bangkok, Thailand; 3Division of Medical Oncology, Department of Medicine, Faculty of Medicine, Chulalongkorn University and The King Chulalongkorn Memorial Hospital, Bangkok, Thailand; 4Center of Excellence in Molecular Genetics of Cancer and Human Diseases, Department of Anatomy, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand Background: One particularly promising component of personalized medicine in cancer treatment is targeted therapy, which aims to maximize therapeutic efficacy while minimizing toxicity. However, the number of approved targeted agents remains limited. Expression microarray data for different types of cancer are resources to identify genes that were upregulated. The genes are candidate targets for cancer-targeting agents for future anticancer research and targeted treatments. Methods and findings: The gene expression profiles of 48 types of cancer from 2,141 microarrays reported in the Gene Expression Omnibus were analyzed. These data were organized into 78 experimental groups, on which we performed comprehensive analyses using two-tailed Student's t-tests with significance set at P < 0.01 to identify genes that were upregulated compared with normal cells in each cancer type. The resulting list of significantly upregulated genes was cross-referenced with three categories of protein inhibitor targets, categorized by inhibitor type ('Targets of US Food and Drug Administration (FDA-approved anticancer drugs', 'Targets of FDA

  17. Identifying and assessing the risk of opioid abuse in patients with cancer: an integrative review

    Directory of Open Access Journals (Sweden)

    Carmichael AN

    2016-06-01

    Full Text Available Ashley-Nicole Carmichael,1 Laura Morgan,1 Egidio Del Fabbro2 1School of Pharmacy, 2Division of Hematology, Oncology, and Palliative Care, Virginia Commonwealth University, Richmond, VA, USA Background: The misuse and abuse of opioid medications in many developed nations is a health crisis, leading to increased health-system utilization, emergency department visits, and overdose deaths. There are also increasing concerns about opioid abuse and diversion in patients with cancer, even at the end of life. Aims: To evaluate the current literature on opioid misuse and abuse, and more specifically the identification and assessment of opioid-abuse risk in patients with cancer. Our secondary aim is to offer the most current evidence of best clinical practice and suggest future directions for research. Materials and methods: Our integrative review included a literature search using the key terms “identification and assessment of opioid abuse in cancer”, “advanced cancer and opioid abuse”, “hospice and opioid abuse”, and “palliative care and opioid abuse”. PubMed, PsycInfo, and Embase were supplemented by a manual search. Results: We found 691 articles and eliminated 657, because they were predominantly noncancer populations or specifically excluded cancer patients. A total of 34 articles met our criteria, including case studies, case series, retrospective observational studies, and narrative reviews. The studies were categorized into screening questionnaires for opioid abuse or alcohol, urine drug screens to identify opioid misuse or abuse, prescription drug-monitoring programs, and the use of universal precautions. Conclusion: Screening questionnaires and urine drug screens indicated at least one in five patients with cancer may be at risk of opioid-use disorder. Several studies demonstrated associations between high-risk patients and clinical outcomes, such as aberrant behavior, prolonged opioid use, higher morphine-equivalent daily dose

  18. HLA ligandomics identifies histone deacetylase 1 as target for ovarian cancer immunotherapy.

    Science.gov (United States)

    Peper, Janet Kerstin; Bösmüller, Hans-Christian; Schuster, Heiko; Gückel, Brigitte; Hörzer, Helen; Roehle, Kevin; Schäfer, Richard; Wagner, Philipp; Rammensee, Hans-Georg; Stevanović, Stefan; Fend, Falko; Staebler, Annette

    2016-05-01

    The recent approval of clincially effective immune checkpoint inhibitors illustrates the potential of cancer immunotherapy. A challenging task remains the identification of specific targets guiding immunotherapy. Facilitated by technical advances, the direct identification of physiologically relevant targets is enabled by analyzing the HLA ligandome of cancer cells. Since recent publications demonstrate the immunogenicity of ovarian cancer (OvCa), immunotherapies, including peptide-based cancer vaccines, represent a promising treatment approach. To identify vaccine peptides, we employed a combined strategy of HLA ligandomics in high-grade serous OvCa samples and immunogenicity analysis. Only few proteins were naturally presented as HLA ligands on all samples analyzed, including histone deacetylase (HDAC) 1 and 2. In vitro priming of CD8(+) T cells demonstrated that two HDAC1/2-derived HLA ligands can induce T-cell responses, capable of killing HLA-matched tumor cells. High HDAC1 expression shown by immunohistochemistry in 136 high-grade serous OvCa patients associated with significantly reduced overall survival (OS), whereas patients with high numbers of CD3(+) tumor-infiltrating lymphocytes (TILs) in the tumor epithelium and CD8(+) TILs in the tumor stroma showed improved OS. However, correlating HDAC1 expression with TILs, high levels of TILs abrogated the impact of HDAC1 on OS. This study strengthens the role of HDAC1/2 as an important tumor antigen in OvCa, demonstrating its impact on OS in a large cohort of OvCa patients. We further identified two immunogenic HDAC1-derived peptides, which frequently induce multi-functional T-cell responses in many donors, suitable for future multi-peptide vaccine trials in OvCa patients.

  19. Transposon activation mutagenesis as a screening tool for identifying resistance to cancer therapeutics

    International Nuclear Information System (INIS)

    The development of resistance to chemotherapies represents a significant barrier to successful cancer treatment. Resistance mechanisms are complex, can involve diverse and often unexpected cellular processes, and can vary with both the underlying genetic lesion and the origin or type of tumor. For these reasons developing experimental strategies that could be used to understand, identify and predict mechanisms of resistance in different malignant cells would be a major advance. Here we describe a gain-of-function forward genetic approach for identifying mechanisms of resistance. This approach uses a modified piggyBac transposon to generate libraries of mutagenized cells, each containing transposon insertions that randomly activate nearby gene expression. Genes of interest are identified using next-gen high-throughput sequencing and barcode multiplexing is used to reduce experimental cost. Using this approach we successfully identify genes involved in paclitaxel resistance in a variety of cancer cell lines, including the multidrug transporter ABCB1, a previously identified major paclitaxel resistance gene. Analysis of co-occurring transposons integration sites in single cell clone allows for the identification of genes that might act cooperatively to produce drug resistance a level of information not accessible using RNAi or ORF expression screening approaches. We have developed a powerful pipeline to systematically discover drug resistance in mammalian cells in vitro. This cost-effective approach can be readily applied to different cell lines, to identify canonical or context specific resistance mechanisms. Its ability to probe complex genetic context and non-coding genomic elements as well as cooperative resistance events makes it a good complement to RNAi or ORF expression based screens

  20. An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

    Directory of Open Access Journals (Sweden)

    Lockwood William W

    2010-05-01

    Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

  1. Germline DNA copy number aberrations identified as potential prognostic factors for breast cancer recurrence.

    Directory of Open Access Journals (Sweden)

    Yadav Sapkota

    Full Text Available Breast cancer recurrence (BCR is a common treatment outcome despite curative-intent primary treatment of non-metastatic breast cancer. Currently used prognostic and predictive factors utilize tumor-based markers, and are not optimal determinants of risk of BCR. Germline-based copy number aberrations (CNAs have not been evaluated as determinants of predisposition to experience BCR. In this study, we accessed germline DNA from 369 female breast cancer subjects who received curative-intent primary treatment following diagnosis. Of these, 155 experienced BCR and 214 did not, after a median duration of follow up after breast cancer diagnosis of 6.35 years (range = 0.60-21.78 and 8.60 years (range = 3.08-13.57, respectively. Whole genome CNA genotyping was performed on the Affymetrix SNP array 6.0 platform. CNAs were identified using the SNP-Fast Adaptive States Segmentation Technique 2 algorithm implemented in Nexus Copy Number 6.0. Six samples were removed due to poor quality scores, leaving 363 samples for further analysis. We identified 18,561 CNAs with ≥1 kb as a predefined cut-off for observed aberrations. Univariate survival analyses (log-rank tests identified seven CNAs (two copy number gains and five copy neutral-loss of heterozygosities, CN-LOHs showing significant differences (P<2.01×10(-5 in recurrence-free survival (RFS probabilities with and without CNAs.We also observed three additional but distinct CN-LOHs showing significant differences in RFS probabilities (P<2.86×10(-5 when analyses were restricted to stratified cases (luminal A, n = 208 only. After adjusting for tumor stage and grade in multivariate analyses (Cox proportional hazards models, all the CNAs remained strongly associated with the phenotype of BCR. Of these, we confirmed three CNAs at 17q11.2, 11q13.1 and 6q24.1 in representative samples using independent genotyping platforms. Our results suggest further investigations on the potential use of germline DNA

  2. Differential analysis of ovarian and endometrial cancers identifies a methylator phenotype.

    Directory of Open Access Journals (Sweden)

    Diana L Kolbe

    Full Text Available Despite improved outcomes in the past 30 years, less than half of all women diagnosed with epithelial ovarian cancer live five years beyond their diagnosis. Although typically treated as a single disease, epithelial ovarian cancer includes several distinct histological subtypes, such as papillary serous and endometrioid carcinomas. To address whether the morphological differences seen in these carcinomas represent distinct characteristics at the molecular level we analyzed DNA methylation patterns in 11 papillary serous tumors, 9 endometrioid ovarian tumors, 4 normal fallopian tube samples and 6 normal endometrial tissues, plus 8 normal fallopian tube and 4 serous samples from TCGA. For comparison within the endometrioid subtype we added 6 primary uterine endometrioid tumors and 5 endometrioid metastases from uterus to ovary. Data was obtained from 27,578 CpG dinucleotides occurring in or near promoter regions of 14,495 genes. We identified 36 locations with significant increases or decreases in methylation in comparisons of serous tumors and normal fallopian tube samples. Moreover, unsupervised clustering techniques applied to all samples showed three major profiles comprising mostly normal samples, serous tumors, and endometrioid tumors including ovarian, uterine and metastatic origins. The clustering analysis identified 60 differentially methylated sites between the serous group and the normal group. An unrelated set of 25 serous tumors validated the reproducibility of the methylation patterns. In contrast, >1,000 genes were differentially methylated between endometrioid tumors and normal samples. This finding is consistent with a generalized regulatory disruption caused by a methylator phenotype. Through DNA methylation analyses we have identified genes with known roles in ovarian carcinoma etiology, whereas pathway analyses provided biological insight to the role of novel genes. Our finding of differences between serous and endometrioid

  3. Overexpression screens identify conserved dosage chromosome instability genes in yeast and human cancer.

    Science.gov (United States)

    Duffy, Supipi; Fam, Hok Khim; Wang, Yi Kan; Styles, Erin B; Kim, Jung-Hyun; Ang, J Sidney; Singh, Tejomayee; Larionov, Vladimir; Shah, Sohrab P; Andrews, Brenda; Boerkoel, Cornelius F; Hieter, Philip

    2016-09-01

    Somatic copy number amplification and gene overexpression are common features of many cancers. To determine the role of gene overexpression on chromosome instability (CIN), we performed genome-wide screens in the budding yeast for yeast genes that cause CIN when overexpressed, a phenotype we refer to as dosage CIN (dCIN), and identified 245 dCIN genes. This catalog of genes reveals human orthologs known to be recurrently overexpressed and/or amplified in tumors. We show that two genes, TDP1, a tyrosyl-DNA-phosphdiesterase, and TAF12, an RNA polymerase II TATA-box binding factor, cause CIN when overexpressed in human cells. Rhabdomyosarcoma lines with elevated human Tdp1 levels also exhibit CIN that can be partially rescued by siRNA-mediated knockdown of TDP1 Overexpression of dCIN genes represents a genetic vulnerability that could be leveraged for selective killing of cancer cells through targeting of an unlinked synthetic dosage lethal (SDL) partner. Using SDL screens in yeast, we identified a set of genes that when deleted specifically kill cells with high levels of Tdp1. One gene was the histone deacetylase RPD3, for which there are known inhibitors. Both HT1080 cells overexpressing hTDP1 and rhabdomyosarcoma cells with elevated levels of hTdp1 were more sensitive to histone deacetylase inhibitors valproic acid (VPA) and trichostatin A (TSA), recapitulating the SDL interaction in human cells and suggesting VPA and TSA as potential therapeutic agents for tumors with elevated levels of hTdp1. The catalog of dCIN genes presented here provides a candidate list to identify genes that cause CIN when overexpressed in cancer, which can then be leveraged through SDL to selectively target tumors. PMID:27551064

  4. The Bimodality Index: A Criterion for Discovering and Ranking Bimodal Signatures from Cancer Gene Expression Profiling Data

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2009-01-01

    Full Text Available Motivation: Identifying genes with bimodal expression patterns from large-scale expression profiling data is an important analytical task. Model-based clustering is popular for this purpose. That technique commonly uses the Bayesian information criterion (BIC for model selection. In practice, however, BIC appears to be overly sensitive and may lead to the identification of bimodally expressed genes that are unreliable or not clinically useful. We propose using a novel criterion, the bimodality index, not only to identify but also to rank meaningful and reliable bimodal patterns. The bimodality index can be computed using either a mixture model-based algorithm or Markov chain Monte Carlo techniques.Results: We carried out simulation studies and applied the method to real data from a cancer gene expression profiling study. Our findings suggest that BIC behaves like a lax cutoff based on the bimodality index, and that the bimodality index provides an objective measure to identify and rank meaningful and reliable bimodal patterns from large-scale gene expression datasets. R code to compute the bimodality index is included in the ClassDiscovery package of the Object-Oriented Microarray and Proteomic Analysis (OOMPA suite available at the web site http://bioinformatics.mdanderson.org/Software/OOMPA.

  5. Genome-wide association studies identify four ER negative–specific breast cancer risk loci

    OpenAIRE

    Garcia-Closas, Montserrat; Couch, Fergus J.; Lindstrom, Sara; Michailidou, Kyriaki; Schmidt, Marjanka K.; Brook, Mark N.; Orr, Nick; Rhie, Suhn Kyong; Riboli, Elio; Feigelson, Heather s; Le Marchand, Loic; Buring, Julie E.; Eccles, Diana; Miron, Penelope; Fasching, Peter A.

    2013-01-01

    Estrogen receptor (ER)-negative tumors represent 20–30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry1. The etiology2 and clinical behavior3 of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition4. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast can...

  6. A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci

    Science.gov (United States)

    Rothman, Nathaniel; Garcia-Closas, Montserrat; Chatterjee, Nilanjan; Malats, Nuria; Wu, Xifeng; Figueroa, Jonine; Real, Francisco X; Van Den Berg, David; Matullo, Giuseppe; Baris, Dalsu; Thun, Michael; Kiemeney, Lambertus A; Vineis, Paolo; De Vivo, Immaculata; Albanes, Demetrius; Purdue, Mark P; Rafnar, Thorunn; Hildebrandt, Michelle A T; Kiltie, Anne E; Cussenot, Olivier; Golka, Klaus; Kumar, Rajiv; Taylor, Jack A; Mayordomo, Jose I; Jacobs, Kevin B; Kogevinas, Manolis; Hutchinson, Amy; Wang, Zhaoming; Fu, Yi-Ping; Prokunina-Olsson, Ludmila; Burdette, Laurie; Yeager, Meredith; Wheeler, William; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Johnson, Alison; Schwenn, Molly; Karagas, Margaret R; Schned, Alan; Andriole, Gerald; Grubb, Robert; Black, Amanda; Jacobs, Eric J; Diver, W Ryan; Gapstur, Susan M; Weinstein, Stephanie J; Virtamo, Jarmo; Cortessis, Victoria K; Gago-Dominguez, Manuela; Pike, Malcolm C; Stern, Mariana C; Yuan, Jian-Min; Hunter, David; McGrath, Monica; Dinney, Colin P; Czerniak, Bogdan; Chen, Meng; Yang, Hushan; Vermeulen, Sita H; Aben, Katja K; Witjes, J Alfred; Makkinje, Remco R; Sulem, Patrick; Besenbacher, Soren; Stefansson, Kari; Riboli, Elio; Brennan, Paul; Panico, Salvatore; Navarro, Carmen; Allen, Naomi E; Bueno-de-Mesquita, H Bas; Trichopoulos, Dimitrios; Caporaso, Neil; Landi, Maria Teresa; Canzian, Federico; Ljungberg, Borje; Tjonneland, Anne; Clavel-Chapelon, Francoise; Bishop, David T; Teo, Mark T W; Knowles, Margaret A; Guarrera, Simonetta; Polidoro, Silvia; Ricceri, Fulvio; Sacerdote, Carlotta; Allione, Alessandra; Cancel-Tassin, Geraldine; Selinski, Silvia; Hengstler, Jan G; Dietrich, Holger; Fletcher, Tony; Rudnai, Peter; Gurzau, Eugen; Koppova, Kvetoslava; Bolick, Sophia C E; Godfrey, Ashley; Xu, Zongli; Sanz-Velez, José I; García-Prats, María D; Sanchez, Manuel; Valdivia, Gabriel; Porru, Stefano; Benhamou, Simone; Hoover, Robert N; Fraumeni, Joseph F; Silverman, Debra T; Chanock, Stephen J

    2010-01-01

    We conducted a multi-stage, genome-wide association study (GWAS) of bladder cancer with a primary scan of 589,299 single nucleotide polymorphisms (SNPs) in 3,532 cases and 5,120 controls of European descent (5 studies) followed by a replication strategy, which included 8,381 cases and 48,275 controls (16 studies). In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1; rs1014971, (P=8×10−12) maps to a non-genic region of chromosome 22q13.1; rs8102137 (P=2×10−11) on 19q12 maps to CCNE1; and rs11892031 (P=1×10−7) maps to the UGT1A cluster on 2q37.1. We confirmed four previous GWAS associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P=4×10−11) and a tag SNP for NAT2 acetylation status (P=4×10−11), as well as demonstrated smoking interactions with both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into mechanisms of carcinogenesis. PMID:20972438

  7. Systematically identify key genes in inflammatory and non-inflammatory breast cancer.

    Science.gov (United States)

    Chai, Fan; Liang, Yan; Zhang, Fan; Wang, Minghao; Zhong, Ling; Jiang, Jun

    2016-01-10

    Although the gene expression in breast tumor stroma, playing a critical role in determining inflammatory breast cancer (IBC) phenotype, has been proved to be significantly different between IBC and non-inflammatory breast cancer (non-IBC), more effort needs to systematically investigate the gene expression profiles between tumor epithelium and stroma and to efficiently uncover the potential molecular networks and critical genes for IBC and non-IBC. Here, we comprehensively analyzed and compared the transcriptional profiles from IBC and non-IBC patients using hierarchical clustering, protein-protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database analyses, and identified PDGFRβ, SUMO1, COL1A1, FYN, CAV1, COL5A1 and MMP2 to be the key genes for breast cancer. Interestingly, PDGFRβ was found to be the hub gene in both IBC and non-IBC; SUMO1 and COL1A1 were respectively the key genes for IBC and non-IBC. These analysis results indicated that those key genes might play important role in IBC and non-IBC and provided some clues for future studies. PMID:26403314

  8. Gene expression signatures that predict outcome of tamoxifen-treated estrogen receptor-positive, high-risk, primary breast cancer patients

    DEFF Research Database (Denmark)

    Lyng, Maria B; Lænkholm, Anne-Vibeke; Tan, Qihua;

    2013-01-01

    BACKGROUND: Tamoxifen significantly improves outcome for estrogen receptor-positive (ER+) breast cancer, but the 15-year recurrence rate remains 30%. The aim of this study was to identify gene profiles that accurately predicted the outcome of ER+ breast cancer patients who received adjuvant Tamox...

  9. Fine-mapping identifies two additional breast cancer susceptibility loci at 9q31.2

    Science.gov (United States)

    Orr, Nick; Dudbridge, Frank; Dryden, Nicola; Maguire, Sarah; Novo, Daniela; Perrakis, Eleni; Johnson, Nichola; Ghoussaini, Maya; Hopper, John L.; Southey, Melissa C.; Apicella, Carmel; Stone, Jennifer; Schmidt, Marjanka K.; Broeks, Annegien; Van't Veer, Laura J.; Hogervorst, Frans B.; Fasching, Peter A.; Haeberle, Lothar; Ekici, Arif B.; Beckmann, Matthias W.; Gibson, Lorna; Aitken, Zoe; Warren, Helen; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Burwinkel, Barbara; Marme, Frederik; Schneeweiss, Andreas; Sohn, Chistof; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Sanchez, Marie; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Benitez, Javier; Zamora, Maria Pilar; Arias Perez, Jose Ignacio; Menéndez, Primitiva; Anton-Culver, Hoda; Neuhausen, Susan L.; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Hamann, Ute; Brauch, Hiltrud; Justenhoven, Christina; Brüning, Thomas; Ko, Yon-Dschun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Bogdanova, Natalia; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Chenevix-Trench, Georgia; Beesley, Jonathan; Lambrechts, Diether; Moisse, Matthieu; Floris, Guiseppe; Beuselinck, Benoit; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Radice, Paolo; Peterlongo, Paolo; Peissel, Bernard; Pensotti, Valeria; Couch, Fergus J.; Olson, Janet E.; Slettedahl, Seth; Vachon, Celine; Giles, Graham G.; Milne, Roger L.; McLean, Catriona; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Kristensen, Vessela; Alnæs, Grethe Grenaker; Nord, Silje; Borresen-Dale, Anne-Lise; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robertus A. E. M.; Seynaeve, Caroline M.; Van Asperen, Christi J.; Garcia-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J.; Lissowska, Jolanta; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Klevebring, Daniel; Hooning, Maartje J.; Hollestelle, Antoinette; van Deurzen, Carolien H. M.; Kriege, Mieke; Hall, Per; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Cox, Angela; Cross, Simon S.; Reed, Malcolm W. R.; Pharoah, Paul D. P.; Dunning, Alison M.; Shah, Mitul; Perkins, Barbara J.; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katarzyna; Ashworth, Alan; Swerdlow, Anthony; Jones, Michael; Schoemaker, Minouk J.; Meindl, Alfons; Schmutzler, Rita K.; Olswold, Curtis; Slager, Susan; Toland, Amanda E.; Yannoukakos, Drakoulis; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Matsuo, Keitaro; Ito, Hidema; Iwata, Hiroji; Ishiguro, Junko; Wu, Anna H.; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O.; Teo, Soo Hwang; Yip, Cheng Har; Kang, Peter; Ikram, Mohammad Kamran; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Noh, Dong-Young; Hartman, Mikael; Miao, Hui; Lim, Wei Yen; Lee, Soo Chin; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; Mckay, James; Wu, Pei-Ei; Hou, Ming-Feng; Yu, Jyh-Cherng; Shen, Chen-Yang; Blot, William; Cai, Qiuyin; Signorello, Lisa B.; Luccarini, Craig; Bayes, Caroline; Ahmed, Shahana; Maranian, Mel; Healey, Catherine S.; González-Neira, Anna; Pita, Guillermo; Alonso, M. Rosario; Álvarez, Nuria; Herrero, Daniel; Tessier, Daniel C.; Vincent, Daniel; Bacot, Francois; Hunter, David J.; Lindstrom, Sara; Dennis, Joe; Michailidou, Kyriaki; Bolla, Manjeet K.; Easton, Douglas F.; dos Santos Silva, Isabel; Fletcher, Olivia; Peto, Julian

    2015-01-01

    We recently identified a novel susceptibility variant, rs865686, for estrogen-receptor positive breast cancer at 9q31.2. Here, we report a fine-mapping analysis of the 9q31.2 susceptibility locus using 43 160 cases and 42 600 controls of European ancestry ascertained from 52 studies and a further 5795 cases and 6624 controls of Asian ancestry from nine studies. Single nucleotide polymorphism (SNP) rs676256 was most strongly associated with risk in Europeans (odds ratios [OR] = 0.90 [0.88–0.92]; P-value = 1.58 × 10−25). This SNP is one of a cluster of highly correlated variants, including rs865686, that spans ∼14.5 kb. We identified two additional independent association signals demarcated by SNPs rs10816625 (OR = 1.12 [1.08–1.17]; P-value = 7.89 × 10−09) and rs13294895 (OR = 1.09 [1.06–1.12]; P-value = 2.97 × 10−11). SNP rs10816625, but not rs13294895, was also associated with risk of breast cancer in Asian individuals (OR = 1.12 [1.06–1.18]; P-value = 2.77 × 10−05). Functional genomic annotation using data derived from breast cancer cell-line models indicates that these SNPs localise to putative enhancer elements that bind known drivers of hormone-dependent breast cancer, including ER-α, FOXA1 and GATA-3. In vitro analyses indicate that rs10816625 and rs13294895 have allele-specific effects on enhancer activity and suggest chromatin interactions with the KLF4 gene locus. These results demonstrate the power of dense genotyping in large studies to identify independent susceptibility variants. Analysis of associations using subjects with different ancestry, combined with bioinformatic and genomic characterisation, can provide strong evidence for the likely causative alleles and their functional basis. PMID:25652398

  10. Evaluation of the prognostic benefit of identifying the probable primary site in cancer of unknown primary

    Directory of Open Access Journals (Sweden)

    Das Joyutpal

    2015-09-01

    Full Text Available With the development of site-specific cancer therapy, identifying the primary origin allows the oncologist to personalise therapy for patients with the cancer of unknown primaries (CUPs. At present, immunohistochemistry (IHC screening is the standard method used to postulate the primary site in CUP. In this retrospective study, we evaluated the prognostic benefit of identifying the primary site in CUP. All 84 patients who presented with suspected CUP to the Royal Stoke University Hospital between 2011 and 2012 were included in our study. Forty-eight percent (40/84 of these patients were unable to undergo necessary investigations to identify primary sites because of poor performance status. IHC screening was able to postulate the primary site in 59% (26/44 of the remaining patients with confirmed CUP. Therefore, the primary site was not identified in a significant proportion of patients with CUP. The median survival of confirmed CUP with probable primary site was 2.0 months (95% confidence interval (CI: 1.2 to 2.9 months, whereas the median survival of confirmed CUP with no probable primary site was 4.1 months (95% CI: 1.5 to 9.7 months. This difference in survival time was statistically significant. In addition, using the Cox regression model, we found that patients with confirmed CUP with primary sites had prognostically unfavourable diseases with a shorter median survival, regardless of the age of disease onset, gender, sites of metastases or number of metastases. One approach to improve the survival would be to start systemic therapy at the earliest possible opportunity rather than waiting for all investigation results, such as IHC.

  11. Identifying unproven cancer treatments on the health web: addressing accuracy, generalizability and scalability.

    Science.gov (United States)

    Aphinyanaphongs, Yin; Fu, Lawrence D; Aliferis, Constantin F

    2013-01-01

    Building machine learning models that identify unproven cancer treatments on the Health Web is a promising approach for dealing with the dissemination of false and dangerous information to vulnerable health consumers. Aside from the obvious requirement of accuracy, two issues are of practical importance in deploying these models in real world applications. (a) Generalizability: The models must generalize to all treatments (not just the ones used in the training of the models). (b) Scalability: The models can be applied efficiently to billions of documents on the Health Web. First, we provide methods and related empirical data demonstrating strong accuracy and generalizability. Second, by combining the MapReduce distributed architecture and high dimensionality compression via Markov Boundary feature selection, we show how to scale the application of the models to WWW-scale corpora. The present work provides evidence that (a) a very small subset of unproven cancer treatments is sufficient to build a model to identify unproven treatments on the web; (b) unproven treatments use distinct language to market their claims and this language is learnable; (c) through distributed parallelization and state of the art feature selection, it is possible to prepare the corpora and build and apply models with large scalability. PMID:23920640

  12. Genetic mapping in mice identifies DMBT1 as a candidate modifier of mammary tumors and breast cancer risk

    DEFF Research Database (Denmark)

    Blackburn, Anneke C; Hill, Linda Z; Roberts, Amy L;

    2007-01-01

    Low-penetrance breast cancer susceptibility alleles seem to play a significant role in breast cancer risk but are difficult to identify in human cohorts. A genetic screen of 176 N2 backcross progeny of two Trp53(+/-) strains, BALB/c and C57BL/6, which differ in their susceptibility to mammary tum...

  13. Microcell-mediated chromosome transfer identifies EPB41L3 as a functional suppressor of epithelial ovarian cancers

    DEFF Research Database (Denmark)

    Dafou, Dimitra; Grun, Barbara; Sinclair, John;

    2010-01-01

    We used a functional complementation approach to identify tumor-suppressor genes and putative therapeutic targets for ovarian cancer. Microcell-mediated transfer of chromosome 18 in the ovarian cancer cell line TOV21G induced in vitro and in vivo neoplastic suppression. Gene expression microarray...

  14. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    DEFF Research Database (Denmark)

    Rudolph, Anja; Milne, Roger L; Truong, Thérèse;

    2015-01-01

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estro...

  15. Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients

    DEFF Research Database (Denmark)

    Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan;

    2014-01-01

    Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in...... hematopoietic hierarchy, using expression profiles from normal stem/progenitor cells, and next mapped the AML patient samples to this landscape. This allowed us to identify the closest normal counterpart of individual AML samples and determine gene expression changes between cancer and normal. We find the...... cancer vs normal method (CvN method) to be superior to conventional methods in stratifying AML patients with aberrant karyotype and in identifying common aberrant transcriptional programs with potential importance for AML etiology. Moreover, the CvN method uncovered a novel poor-outcome subtype of normal...

  16. Repositioning "old" drugs for new causes: identifying new inhibitors of prostate cancer cell migration and invasion.

    Science.gov (United States)

    Shah, Esha T; Upadhyaya, Akanksha; Philp, Lisa K; Tang, Tiffany; Skalamera, Dubravka; Gunter, Jennifer; Nelson, Colleen C; Williams, Elizabeth D; Hollier, Brett G

    2016-04-01

    The majority of prostate cancer (PCa) deaths occur due to the metastatic spread of tumor cells to distant organs. Currently, there is a lack of effective therapies once tumor cells have spread outside the prostate. It is therefore imperative to rapidly develop therapeutics to inhibit the metastatic spread of tumor cells. Gain of cell motility and invasive properties is the first step of metastasis and by inhibiting motility one can potentially inhibit metastasis. Using the drug repositioning strategy, we developed a cell-based multi-parameter primary screening assay to identify drugs that inhibit the migratory and invasive properties of metastatic PC-3 PCa cells. Following the completion of the primary screening assay, 33 drugs were identified from an FDA approved drug library that either inhibited migration or were cytotoxic to the PC-3 cells. Based on the data obtained from the subsequent validation studies, mitoxantrone hydrochloride, simvastatin, fluvastatin and vandetanib were identified as strong candidates that can inhibit both the migration and invasion of PC-3 cells without significantly affecting cell viability. By employing the drug repositioning strategy instead of a de novo drug discovery and development strategy, the identified drug candidates have the potential to be rapidly translated into the clinic for the management of men with aggressive forms of PCa.

  17. Microcell-Mediated Chromosome Transfer Identifies EPB41L3 as a Functional Suppressor of Epithelial Ovarian Cancers

    OpenAIRE

    Dimitra Dafou; Barbara Grun; John Sinclair; Kate Lawrenson; Benjamin, Elizabeth C; Estrid Hogdall; Susanne Kruger-Kjaer; Lise Christensen; Sowter, Heidi M.; Ahmed Al-Attar; Richard Edmondson; Stephen Darby; Andrew Berchuck; Laird, Peter W; C. Leigh Pearce

    2010-01-01

    We used a functional complementation approach to identify tumor-suppressor genes and putative therapeutic targets for ovarian cancer. Microcell-mediated transfer of chromosome 18 in the ovarian cancer cell line TOV21 G induced in vitro and in vivo neoplastic suppression. Gene expression microarray profiling in TOV21 +19 hybrids identified 14 candidate genes on chromosome 18 that were significantly overexpressed and therefore associated with neoplastic suppression. Further analysis of messenge...

  18. DNA methylation changes in ovarian cancer are cumulative with disease progression and identify tumor stage

    Directory of Open Access Journals (Sweden)

    DeGeest Koen

    2008-09-01

    Full Text Available Abstract Background Hypermethylation of promoter CpG islands with associated loss of gene expression, and hypomethylation of CpG-rich repetitive elements that may destabilize the genome are common events in most, if not all, epithelial cancers. Methods The methylation of 6,502 CpG-rich sequences spanning the genome was analyzed in 137 ovarian samples (ten normal, 23 low malignant potential, 18 stage I, 16 stage II, 54 stage III, and 16 stage IV ranging from normal tissue through to stage IV cancer using a sequence-validated human CpG island microarray. The microarray contained 5' promoter-associated CpG islands as well as CpG-rich satellite and Alu repetitive elements. Results Results showed a progressive de-evolution of normal CpG methylation patterns with disease progression; 659 CpG islands showed significant loss or gain of methylation. Satellite and Alu sequences were primarily associated with loss of methylation, while promoter CpG islands composed the majority of sequences with gains in methylation. Since the majority of ovarian tumors are late stage when diagnosed, we tested whether DNA methylation profiles could differentiate between normal and low malignant potential (LMP compared to stage III ovarian samples. We developed a class predictor consisting of three CpG-rich sequences that was 100% sensitive and 89% specific when used to predict an independent set of normal and LMP samples versus stage III samples. Bisulfite sequencing confirmed the NKX-2-3 promoter CpG island was hypermethylated with disease progression. In addition, 5-aza-2'-deoxycytidine treatment of the ES2 and OVCAR ovarian cancer cell lines re-expressed NKX-2-3. Finally, we merged our CpG methylation results with previously published ovarian expression microarray data and identified correlated expression changes. Conclusion Our results show that changes in CpG methylation are cumulative with ovarian cancer progression in a sequence-type dependent manner, and that Cp

  19. Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes

    Directory of Open Access Journals (Sweden)

    Moreau Thierry

    2010-03-01

    Full Text Available Abstract Background With the growing number of public repositories for high-throughput genomic data, it is of great interest to combine the results produced by independent research groups. Such a combination allows the identification of common genomic factors across multiple cancer types and provides new insights into the disease process. In the framework of the proportional hazards model, classical procedures, which consist of ranking genes according to the estimated hazard ratio or the p-value obtained from a test statistic of no association between survival and gene expression level, are not suitable for gene selection across multiple genomic datasets with different sample sizes. We propose a novel index for identifying genes with a common effect across heterogeneous genomic studies designed to remain stable whatever the sample size and which has a straightforward interpretation in terms of the percentage of separability between patients according to their survival times and gene expression measurements. Results The simulations results show that the proposed index is not substantially affected by the sample size of the study and the censoring. They also show that its separability performance is higher than indices of predictive accuracy relying on the likelihood function. A simulated example illustrates the good operating characteristics of our index. In addition, we demonstrate that it is linked to the score statistic and possesses a biologically relevant interpretation. The practical use of the index is illustrated for identifying genes with common effects across eight independent genomic cancer studies of different sample sizes. The meta-selection allows the identification of four genes (ESPL1, KIF4A, HJURP, LRIG1 that are biologically relevant to the carcinogenesis process and have a prognostic impact on survival outcome across various solid tumors. Conclusion The proposed index is a promising tool for identifying factors having a

  20. Operator dependent choice of prostate cancer biopsy has limited impact on a gene signature analysis for the highly expressed genes IGFBP3 and F3 in prostate cancer epithelial cells.

    Directory of Open Access Journals (Sweden)

    Zhuochun Peng

    Full Text Available BACKGROUND: Predicting the prognosis of prostate cancer disease through gene expression analysis is receiving increasing interest. In many cases, such analyses are based on formalin-fixed, paraffin embedded (FFPE core needle biopsy material on which Gleason grading for diagnosis has been conducted. Since each patient typically has multiple biopsy samples, and since Gleason grading is an operator dependent procedure known to be difficult, the impact of the operator's choice of biopsy was evaluated. METHODS: Multiple biopsy samples from 43 patients were evaluated using a previously reported gene signature of IGFBP3, F3 and VGLL3 with potential prognostic value in estimating overall survival at diagnosis of prostate cancer. A four multiplex one-step qRT-PCR test kit, designed and optimized for measuring the signature in FFPE core needle biopsy samples was used. Concordance of gene expression levels between primary and secondary Gleason tumor patterns, as well as benign tissue specimens, was analyzed. RESULTS: The gene expression levels of IGFBP3 and F3 in prostate cancer epithelial cell-containing tissue representing the primary and secondary Gleason patterns were high and consistent, while the low expressed VGLL3 showed more variation in its expression levels. CONCLUSION: The assessment of IGFBP3 and F3 gene expression levels in prostate cancer tissue is independent of Gleason patterns, meaning that the impact of operator's choice of biopsy is low.

  1. CERTIFICATELESS SIGNATURE AND BLIND SIGNATURE

    Institute of Scientific and Technical Information of China (English)

    Zhang Lei; Zhang Futai

    2008-01-01

    Certificateless public key cryptography is a new paradigm introduced by AI-Riyami and Paterson. It eliminates the need of the certificates in traditional public key cryptosystems and the key escrow problem in IDentity-based Public Key Cryptography (ID-PKC). Due to the advantages of the certificateless public key cryptography,a new efficient certificateless pairing-based signature scheme is presented,which has some advantages over previous constructions in computational cost. Based on this new signature scheme,a certificateless blind signature scheme is proposed. The security of our schemes is proven based on the hardness of computational Diffie-Hellman problem.

  2. A conditional piggyBac transposition system for genetic screening in mice identifies oncogenic networks in pancreatic cancer.

    Science.gov (United States)

    Rad, Roland; Rad, Lena; Wang, Wei; Strong, Alexander; Ponstingl, Hannes; Bronner, Iraad F; Mayho, Matthew; Steiger, Katja; Weber, Julia; Hieber, Maren; Veltkamp, Christian; Eser, Stefan; Geumann, Ulf; Öllinger, Rupert; Zukowska, Magdalena; Barenboim, Maxim; Maresch, Roman; Cadiñanos, Juan; Friedrich, Mathias; Varela, Ignacio; Constantino-Casas, Fernando; Sarver, Aaron; Ten Hoeve, Jelle; Prosser, Haydn; Seidler, Barbara; Bauer, Judith; Heikenwälder, Mathias; Metzakopian, Emmanouil; Krug, Anne; Ehmer, Ursula; Schneider, Günter; Knösel, Thomas; Rümmele, Petra; Aust, Daniela; Grützmann, Robert; Pilarsky, Christian; Ning, Zemin; Wessels, Lodewyk; Schmid, Roland M; Quail, Michael A; Vassiliou, George; Esposito, Irene; Liu, Pentao; Saur, Dieter; Bradley, Allan

    2015-01-01

    Here we describe a conditional piggyBac transposition system in mice and report the discovery of large sets of new cancer genes through a pancreatic insertional mutagenesis screen. We identify Foxp1 as an oncogenic transcription factor that drives pancreatic cancer invasion and spread in a mouse model and correlates with lymph node metastasis in human patients with pancreatic cancer. The propensity of piggyBac for open chromatin also enabled genome-wide screening for cancer-relevant noncoding DNA, which pinpointed a Cdkn2a cis-regulatory region. Histologically, we observed different tumor subentities and discovered associated genetic events, including Fign insertions in hepatoid pancreatic cancer. Our studies demonstrate the power of genetic screening to discover cancer drivers that are difficult to identify by other approaches to cancer genome analysis, such as downstream targets of commonly mutated human cancer genes. These piggyBac resources are universally applicable in any tissue context and provide unique experimental access to the genetic complexity of cancer.

  3. Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia

    OpenAIRE

    Lan, Qing; Hsiung, Chao A.; Matsuo, Keitaro; Hong, Yun-Chul; Seow, Adeline; Wang, Zhaoming; Hosgood, H Dean; Chen, Kexin; Wang, Jiu-Cun; Chatterjee, Nilanjan; Hu, Wei; Wong, Maria Pik; Zheng, Wei; Caporaso, Neil; PARK, JAE YONG

    2012-01-01

    To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland China, South Korea, Japan, Singapore, Taiwan, and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10-6) in an additional 1,099 cases and 2,913 controls. We identified three...

  4. A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures.

    Directory of Open Access Journals (Sweden)

    Maud H W Starmans

    Full Text Available BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited.

  5. A combined approach to data mining of textual and structured data to identify cancer-related targets

    Directory of Open Access Journals (Sweden)

    Adelstein S James

    2006-07-01

    Full Text Available Abstract Background We present an effective, rapid, systematic data mining approach for identifying genes or proteins related to a particular interest. A selected combination of programs exploring PubMed abstracts, universal gene/protein databases (UniProt, InterPro, NCBI Entrez, and state-of-the-art pathway knowledge bases (LSGraph and Ingenuity Pathway Analysis was assembled to distinguish enzymes with hydrolytic activities that are expressed in the extracellular space of cancer cells. Proteins were identified with respect to six types of cancer occurring in the prostate, breast, lung, colon, ovary, and pancreas. Results The data mining method identified previously undetected targets. Our combined strategy applied to each cancer type identified a minimum of 375 proteins expressed within the extracellular space and/or attached to the plasma membrane. The method led to the recognition of human cancer-related hydrolases (on average, ~35 per cancer type, among which were prostatic acid phosphatase, prostate-specific antigen, and sulfatase 1. Conclusion The combined data mining of several databases overcame many of the limitations of querying a single database and enabled the facile identification of gene products. In the case of cancer-related targets, it produced a list of putative extracellular, hydrolytic enzymes that merit additional study as candidates for cancer radioimaging and radiotherapy. The proposed data mining strategy is of a general nature and can be applied to other biological databases for understanding biological functions and diseases.

  6. Deep sequencing and in silico analyses identify MYB-regulated gene networks and signaling pathways in pancreatic cancer.

    Science.gov (United States)

    Azim, Shafquat; Zubair, Haseeb; Srivastava, Sanjeev K; Bhardwaj, Arun; Zubair, Asif; Ahmad, Aamir; Singh, Seema; Khushman, Moh'd; Singh, Ajay P

    2016-01-01

    We have recently demonstrated that the transcription factor MYB can modulate several cancer-associated phenotypes in pancreatic cancer. In order to understand the molecular basis of these MYB-associated changes, we conducted deep-sequencing of transcriptome of MYB-overexpressing and -silenced pancreatic cancer cells, followed by in silico pathway analysis. We identified significant modulation of 774 genes upon MYB-silencing (p RELA was validated by both qPCR and immunoblotting and they were both shown to be under direct transcriptional control of MYB. These observations were further confirmed in a converse approach wherein MYB was overexpressed ectopically in a MYB-null pancreatic cancer cell line. Our findings thus suggest that MYB potentially regulates growth and genomic stability of pancreatic cancer cells via targeting complex gene networks and signaling pathways. Further in-depth functional studies are warranted to fully understand MYB signaling in pancreatic cancer. PMID:27354262

  7. Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

    International Nuclear Information System (INIS)

    Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

  8. Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

    DEFF Research Database (Denmark)

    Permuth, Jennifer B; Pirie, Ailith; Ann Chen, Y;

    2016-01-01

    Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from...... that is in LD (r(2 )=( )0.90) with a previously identified 'best hit' (rs7651446) mapping to an intron of TIPARP. Suggestive associations (5.0 × 10 (-)  (5 )>( )P≥5.0 ×10 (-)  (7)) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391.......67 × 10 (-)  (4); PSKAT-o = 1.07 × 10 (-)  (5)), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology...

  9. Vessel Architectural Imaging Identifies Cancer Patient Responders to Anti-angiogenic Therapy

    Science.gov (United States)

    Emblem, Kyrre E.; Mouridsen, Kim; Bjornerud, Atle; Farrar, Christian T.; Jennings, Dominique; Borra, Ronald J. H.; Wen, Patrick Y.; Ivy, Percy; Batchelor, Tracy T.; Rosen, Bruce R.; Jain, Rakesh K.; Sorensen, A. Gregory

    2013-01-01

    Measurement of vessel caliber by Magnetic Resonance Imaging (MRI) is a valuable technique for in vivo monitoring of hemodynamic status and vascular development, especially in the brain. Here, we introduce a new paradigm in MRI coined as Vessel Architectural Imaging (VAI) that exploits an intriguing and overlooked temporal shift in the MR signal forming the basis for vessel caliber estimation and show how this phenomenon can reveal new information on vessel type and function not assessed by any other non-invasive imaging technique. We also show how this biomarker can provide novel biological insights into the treatment of cancer patients. As an example, we demonstrate using VAI that anti-angiogenic therapy can improve microcirculation and oxygen saturation levels and reduce vessel calibers in patients with recurrent glioblastomas, and more crucially, that patients with these responses have prolonged survival. Thus, VAI has the potential to identify patients who would benefit from therapies. PMID:23955713

  10. GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer

    DEFF Research Database (Denmark)

    Pharoah, Paul D P; Tsai, Ya-Yu; Ramus, Susan J;

    2013-01-01

    ,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have...... associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10−9) and 10p12 (rs1243180, P = 1.8 × 10−8) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10...

  11. MRI anatomy of parametrial extension to better identify local pathways of disease spread in cervical cancer

    Science.gov (United States)

    Valentini, Anna Lia; Gui, Benedetta; Miccò, Maura; Giuliani, Michela; Rodolfino, Elena; Ninivaggi, Valeria; Iacobucci, Marta; Marino, Marzia; Gambacorta, Maria Antonietta; Testa, Antonia Carla; Zannoni, Gian Franco; Bonomo, Lorenzo

    2016-01-01

    This paper highlights an updated anatomy of parametrial extension with emphasis on magnetic resonance imaging (MRI) assessment of disease spread in the parametrium in patients with locally advanced cervical cancer. Pelvic landmarks were identified to assess the anterior and posterior extensions of the parametria, besides the lateral extension, as defined in a previous anatomical study. A series of schematic drawings and MRI images are shown to document the anatomical delineation of disease on MRI, which is crucial not only for correct image-based three-dimensional radiotherapy but also for the surgical oncologist, since neoadjuvant chemoradiotherapy followed by radical surgery is emerging in Europe as a valid alternative to standard chemoradiation. PMID:27165471

  12. TCPs: privileged scaffolds for identifying potent LSD1 inhibitors for cancer therapy.

    Science.gov (United States)

    Zheng, Yi-Chao; Yu, Bin; Chen, Zhe-Sheng; Liu, Ying; Liu, Hong-Min

    2016-05-01

    Since the first lysine-specific demethylase (KDM), lysine-specific demethylase 1 (LSD1), was characterized in 2004, several families of KDMs have been identified. LSD1 can specifically demethylate H3K4me1/2, H3K9me1/2 as well as some nonhistone substrates. It has been demonstrated to be an oncogene as well as a drug target. Hence, tens of small-molecule LSD1 inhibitors have been designed, synthesized and applied for cancer treatment. However, the two LSD1 inhibitors that have been advanced into early phase clinical trials are trans-2-phenylcyclopropylamine (TCP) derivatives, which indicate that TCP is a druggable scaffold for LSD1 inhibitor. Here, we review the design, synthesis and properties of reported TCP-based LSD1 inhibitors as well as their biological roles. PMID:27102879

  13. Identifying the common interaction networks of amoeboid motility and cancer cell metastasis

    Directory of Open Access Journals (Sweden)

    Ahmed H. Zeitoun

    2012-06-01

    Full Text Available The recently analyzed genome of Naegleria gruberi, a free-living amoeboflagellate of the Heterolobosea clade, revealed a remarkably complex ancestral eukaryote with a rich repertoire of cytoskeletal-, motility- and signaling-genes. This protist, which diverged from other eukaryotic lineages over a billion years ago, possesses the ability for both amoeboid and flagellar motility. In a phylogenomic comparison of two free living eukaryotes with large proteomic datasets of three metastatic tumour entities (malignant melanoma, breast- and prostate-carcinoma, we find common proteins with potential importance for cell motility and cancer cell metastasis. To identify the underlying signaling modules, we constructed for each tumour type a protein-protein interaction network including these common proteins. The connectivity within this interactome revealed specific interactions and pathways which constitute prospective points of intervention for novel anti-metastatic tumour therapies.

  14. Genome-wide profiling identifies a DNA methylation signature that associates with TET2 mutations in diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Asmar, Fazila; Punj, Vasu; Christensen, Jesper Aagaard;

    2013-01-01

    The discovery that the Ten-Eleven Translocation (TET) hydroxylases cause DNA demethylation has fundamentally changed the notion of how DNA methylation is regulated. Clonal analysis of the hematopoetic stem cell compartment suggests that TET2 mutations can be early events in hematologic cancers...

  15. UTSW Researchers Identify Potential Therapeutic Targets for High-grade Neuroendocrine Lung Cancers | Office of Cancer Genomics

    Science.gov (United States)

    Neuroendocrine specific lung cancers comprise about 10% of non-small cell lung cancer (NSCLC) cases and all small cell lung cancer (SCLC) cases. Studies have previously shown that the transcription factor achaete-scute homolog 1 (ASCL1) is a cancer “lineage” factor required for the development and survival of SCLC, and is highly expressed in neuroendocrine-specific NSCLC (NE-NSCLC).

  16. Functional screening identifies miRNAs influencing apoptosis and proliferation in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Lise Lotte Christensen

    Full Text Available MicroRNAs (miRNAs play a critical role in many biological processes and are aberrantly expressed in human cancers. Particular miRNAs function either as tumor suppressors or oncogenes and appear to have diagnostic and prognostic significance. Although numerous miRNAs are dys-regulated in colorectal cancer (CRC only a small fraction has been characterized functionally. Using high-throughput functional screening and miRNA profiling of clinical samples the present study aims at identifying miRNAs important for the control of cellular growth and/or apoptosis in CRC. The high-throughput functional screening was carried out in six CRC cell lines transfected with a pre-miR library including 319 synthetic human pre-miRs. Phenotypic alterations were evaluated by immunostaining of cleaved cPARP (apoptosis or MKI67 (proliferation. Additionally, TaqMan Human MicroRNA Array Set v2.0 was used to profile the expression of 667 miRNAs in 14 normal colon mucosa and 46 microsatellite stable stage II CRC patients. Among the miRNAs that induced growth arrest and apoptosis in the CRC cell lines, and at same time were dys-regulated in the clinical samples, miR-375 was selected for further analysis. Independent in vitro analysis of transient and stable transfected CRC cell lines confirmed that miR-375 reduces cell viability through the induction of apoptotic death. We identified YAP1 as a direct miR-375 target in CRC and show that HELLS and NOLC1 are down-stream targets. Knock-down of YAP1 mimicked the phenotype induced by miR-375 over-expression indicating that miR-375 most likely exerts its pro-apoptotic role through YAP1 and its anti-apoptotic down-stream targets BIRC5 and BCL2L1. Finally, in vivo analysis of mouse xenograft tumors showed that miR-375 expression significantly reduced tumor growth. We conclude that the high-throughput screening successfully identified miRNAs that induce apoptosis and/or inhibit proliferation in CRC cells. Finally, combining the

  17. Genome-wide analysis identifies novel loci associated with ovarian cancer outcomes: findings from the Ovarian Cancer Association Consortium

    Science.gov (United States)

    Johnatty, Sharon E.; Tyrer, Jonathan P.; Kar, Siddhartha; Beesley, Jonathan; Lu, Yi; Gao, Bo; Fasching, Peter A.; Hein, Alexander; Ekici, Arif B.; Beckmann, Matthias W.; Lambrechts, Diether; Nieuwenhuysen, Els Van; Vergote, Ignace; Lambrechts, Sandrina; Rossing, Mary Anne; Doherty, Jennifer A.; Chang-Claude, Jenny; Modugno, Francesmary; Ness, Roberta B.; Moysich, Kirsten B.; Levine, Douglas A.; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; Gronwald, Jacek; Lubiński, Jan; Jakubowska, Anna; Cybulski, Cezary; Brinton, Louise; Lissowska, Jolanta; Wentzensen, Nicolas; Song, Honglin; Rhenius, Valerie; Campbell, Ian; Eccles, Diana; Sieh, Weiva; Whittemore, Alice S.; McGuire, Valerie; Rothstein, Joseph H.; Sutphen, Rebecca; Anton-Culver, Hoda; Ziogas, Argyrios; Gayther, Simon A.; Gentry-Maharaj, Aleksandra; Menon, Usha; Ramus, Susan J.; Pearce, Celeste L; Pike, Malcolm C; Stram, Daniel O.; Wu, Anna H.; Kupryjanczyk, Jolanta; Dansonka-Mieszkowska, Agnieszka; Rzepecka, Iwona K.; Spiewankiewicz, Beata; Goodman, Marc T.; Wilkens, Lynne R.; Carney, Michael E.; Thompson, Pamela J; Heitz, Florian; du Bois, Andreas; Schwaab, Ira; Harter, Philipp; Pisterer, Jacobus; Hillemanns, Peter; Karlan, Beth Y.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Winham, Stacey J; Earp, Madalene; Larson, Melissa C.; Fogarty, Zachary C.; Høgdall, Estrid; Jensen, Allan; Kjaer, Susanne Kruger; Fridley, Brooke L.; Cunningham, Julie M.; Vierkant, Robert A.; Schildkraut, Joellen M.; Iversen, Edwin S.; Terry, Kathryn L.; Cramer, Daniel W.; Bandera, Elisa V.; Orlow, Irene; Pejovic, Tanja; Bean, Yukie; Høgdall, Claus; Lundvall, Lene; McNeish, Ian; Paul, James; Carty, Karen; Siddiqui, Nadeem; Glasspool, Rosalind; Sellers, Thomas; Kennedy, Catherine; Chiew, Yoke-Eng; Berchuck, Andrew; MacGregor, Stuart; deFazio, Anna; Pharoah, Paul D.P.; Goode, Ellen L.; deFazio, Anna; Webb, Penelope M.; Chenevix-Trench, Georgia

    2015-01-01

    Purpose Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design We analyzed ~2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent firstline treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients including patients from The Cancer Genome Atlas. Additionally we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results Five SNPs were significantly associated (p≤1.0x10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23) and rs6674079 (1q22) were located in long non-coding RNAs (lncRNAs) RP11–179A10.1, RP11–314O13.1 and RP11–284F21.8 respectively (p≤7.1x10−6). ENCODE ChIP-seq data at 1q22 for normal ovary shows evidence of histone modification around RP11–284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression, and HDL-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA≤6x10−3). Conclusion We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. PMID:26152742

  18. Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Suzanne Miyamoto

    2015-04-01

    Full Text Available Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05. Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection.

  19. Parallel screening of FDA-approved antineoplastic drugs for identifying sensitizers of TRAIL-induced apoptosis in cancer cells

    Directory of Open Access Journals (Sweden)

    Taylor David J

    2011-11-01

    Full Text Available Abstract Background Tumor Necrosis Factor-α Related Apoptosis Inducing Ligand (TRAIL and agonistic antibodies to death receptor 4 and 5 are promising candidates for cancer therapy due to their ability to induce apoptosis selectively in a variety of human cancer cells, while demonstrating little cytotoxicity in normal cells. Although TRAIL and agonistic antibodies to DR4 and DR5 are considered safe and promising candidates in cancer therapy, many malignant cells are resistant to DR-mediated, TRAIL-induced apoptosis. In the current work, we screened a small library of fifty-five FDA and foreign-approved anti-neoplastic drugs in order to identify candidates that sensitized resistant prostate and pancreatic cancer cells to TRAIL-induced apoptosis. Methods FDA-approved drugs were screened for their ability to sensitize TRAIL resistant prostate cancer cells to TRAIL using an MTT assay for cell viability. Analysis of variance was used to identify drugs that exhibited synergy with TRAIL. Drugs demonstrating the highest synergy were selected as leads and tested in different prostate and pancreatic cancer cell lines, and one immortalized human pancreatic epithelial cell line. Sequential and simultaneous dosing modalities were investigated and the annexin V/propidium iodide assay, in concert with fluorescence microscopy, was employed to visualize cells undergoing apoptosis. Results Fourteen drugs were identified as having synergy with TRAIL, including those whose TRAIL sensitization activities were previously unknown in either prostate or pancreatic cancer cells or both. Five leads were tested in additional cancer cell lines of which, doxorubicin, mitoxantrone, and mithramycin demonstrated synergy in all lines. In particular, mitoxantrone and mithramycin demonstrated significant synergy with TRAIL and led to reduction of cancer cell viability at concentrations lower than 1 μM. At these low concentrations, mitoxantrone demonstrated selectivity toward

  20. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    DEFF Research Database (Denmark)

    Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara;

    2015-01-01

    Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748...

  1. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

    NARCIS (Netherlands)

    K. Michailidou (Kyriaki); J. Beesley (Jonathan); S. Lindstrom (Stephen); S. Canisius (Sander); J. Dennis (Joe); M. Lush (Michael); M. Maranian (Melanie); M.K. Bolla (Manjeet); Q. Wang (Qing); M. Shah (Mitul); B. Perkins (Barbara); K. Czene (Kamila); M. Eriksson (Mikael); H. Darabi (Hatef); J.S. Brand (Judith S.); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); H. Flyger (Henrik); S.F. Nielsen (Sune); N. Rahman (Nazneen); C. Turnbull (Clare); O. Fletcher (Olivia); J. Peto (Julian); L.J. Gibson (Lorna); I. dos Santos Silva (Isabel); J. Chang-Claude (Jenny); D. Flesch-Janys (Dieter); A. Rudolph (Anja); U. Eilber (Ursula); T.W. Behrens (Timothy); H. Nevanlinna (Heli); T.A. Muranen (Taru); K. Aittomäki (Kristiina); C. Blomqvist (Carl); S. Khan (Sofia); K. Aaltonen (Kirsimari); H. Ahsan (Habibul); M.G. Kibriya (Muhammad); A.S. Whittemore (Alice S.); E.M. John (Esther M.); K.E. Malone (Kathleen E.); M.D. Gammon (Marilie); R.M. Santella (Regina M.); G. Ursin (Giske); E. Makalic (Enes); D.F. Schmidt (Daniel); G. Casey (Graham); D.J. Hunter (David J.); S.M. Gapstur (Susan M.); M.M. Gaudet (Mia); W.R. Diver (Ryan); C.A. Haiman (Christopher A.); F.R. Schumacher (Fredrick); B.E. Henderson (Brian); L. Le Marchand (Loic); C.D. Berg (Christine); S.J. Chanock (Stephen); J.D. Figueroa (Jonine); R.N. Hoover (Robert N.); D. Lambrechts (Diether); P. Neven (Patrick); H. Wildiers (Hans); E. van Limbergen (Erik); M.K. Schmidt (Marjanka); A. Broeks (Annegien); S. Verhoef; S. Cornelissen (Sten); F.J. Couch (Fergus); J.E. Olson (Janet); B. Hallberg (Boubou); C. Vachon (Celine); Q. Waisfisz (Quinten); E.J. Meijers-Heijboer (Hanne); M.A. Adank (Muriel); R.B. van der Luijt (Rob); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); D. Kang (Daehee); J.-Y. Choi (Ji-Yeob); S.K. Park (Sue K.); K.Y. Yoo; K. Matsuo (Keitaro); H. Ito (Hidemi); H. Iwata (Hiroji); K. Tajima (Kazuo); P. Guénel (Pascal); T. Truong (Thérèse); C. Mulot (Claire); M. Sanchez (Marie); B. Burwinkel (Barbara); F. Marme (Federick); H. Surowy (Harald); C. Sohn (Christof); A.H. Wu (Anna H); C.-C. Tseng (Chiu-chen); D. Van Den Berg (David); D.O. Stram (Daniel O.); A. González-Neira (Anna); J. Benítez (Javier); M.P. Zamora (Pilar); J.I.A. Perez (Jose Ignacio Arias); X.-O. Shu (Xiao-Ou); W. Lu (Wei); Y. Gao; H. Cai (Hui); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); A.-M. Mulligan (Anna-Marie); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); A. Lindblom (Annika); S. Margolin (Sara); S.H. Teo (Soo Hwang); C.H. Yip (Cheng Har); N.A.M. Taib (Nur Aishah Mohd); G.-H. Tan (Gie-Hooi); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); J.W.M. Martens (John); J. Margriet Collée; W.J. Blot (William); L.B. Signorello (Lisa B.); Q. Cai (Qiuyin); J. Hopper (John); M.C. Southey (Melissa); H. Tsimiklis (Helen); C. Apicella (Carmel); C-Y. Shen (Chen-Yang); C.-N. Hsiung (Chia-Ni); P.-E. Wu (Pei-Ei); M.-F. Hou (Ming-Feng); V. Kristensen (Vessela); S. Nord (Silje); G.G. Alnæs (Grethe Grenaker); G.G. Giles (Graham G.); R.L. Milne (Roger); C.A. McLean (Catriona Ann); F. Canzian (Federico); D. Trichopoulos (Dimitrios); P.H.M. Peeters; E. Lund (Eiliv); R. Sund (Reijo); K.T. Khaw; M.J. Gunter (Marc J.); D. Palli (Domenico); L.M. Mortensen (Lotte Maxild); L. Dossus (Laure); J.-M. Huerta (Jose-Maria); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Sutter (Christian); R. Yang (Rongxi); K. Muir (Kenneth); A. Lophatananon (Artitaya); S. Stewart-Brown (Sarah); P. Siriwanarangsan (Pornthep); J.M. Hartman (Joost); X. Miao; K.S. Chia (Kee Seng); C.W. Chan (Ching Wan); P.A. Fasching (Peter); R. Hein (Rebecca); M.W. Beckmann (Matthias W.); L. Haeberle (Lothar); H. Brenner (Hermann); A.K. Dieffenbach (Aida Karina); V. Arndt (Volker); C. Stegmaier (Christa); A. Ashworth (Alan); N. Orr (Nick); M. Schoemaker (Minouk); A.J. Swerdlow (Anthony ); L.A. Brinton (Louise); M. García-Closas (Montserrat); W. Zheng (Wei); S.L. Halverson (Sandra L.); M. Shrubsole (Martha); J. Long (Jirong); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); H. Brauch (Hiltrud); U. Hamann (Ute); T. Brüning (Thomas); P. Radice (Paolo); P. Peterlongo (Paolo); S. Manoukian (Siranoush); L. Bernard (Loris); N.V. Bogdanova (Natalia); T. Dörk (Thilo); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti)

    2015-01-01

    textabstractGenome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprisi

  2. Patient Derived Cancer Cell Lines in Identifying Molecular Changes in Patients With Previously Untreated Pancreatic Cancer Receiving Gemcitabine Hydrochloride-Based Chemotherapy

    Science.gov (United States)

    2016-10-18

    Pancreatic Ductal Adenocarcinoma; Stage IA Pancreatic Cancer; Stage IB Pancreatic Cancer; Stage IIA Pancreatic Cancer; Stage IIB Pancreatic Cancer; Stage III Pancreatic Cancer; Stage IV Pancreatic Cancer

  3. A Novel WRN Frameshift Mutation Identified by Multiplex Genetic Testing in a Family with Multiple Cases of Cancer.

    Science.gov (United States)

    Yang, Liu; Wang, Guosheng; Zhao, Xinyi; Ye, Song; Shen, Peng; Wang, Weilin; Zheng, Shusen

    2015-01-01

    Next-generation sequencing technology allows simultaneous analysis of multiple susceptibility genes for clinical cancer genetics. In this study, multiplex genetic testing was conducted in a Chinese family with multiple cases of cancer to determine the variations in cancer predisposition genes. The family comprises a mother and her five daughters, of whom the mother and the eldest daughter have cancer and the secondary daughter died of cancer. We conducted multiplex genetic testing of 90 cancer susceptibility genes using the peripheral blood DNA of the mother and all five daughters. WRN frameshift mutation is considered a potential pathogenic variation according to the guidelines of the American College of Medical Genetics. A novel WRN frameshift mutation (p.N1370Tfs*23) was identified in the three cancer patients and in the youngest unaffected daughter. Other rare non-synonymous germline mutations were also detected in DICER and ELAC2. Functional mutations in WRN cause Werner syndrome, a human autosomal recessive disease characterized by premature aging and associated with genetic instability and increased cancer risk. Our results suggest that the WRN frameshift mutation is important in the surveillance of other members of this family, especially the youngest daughter, but the pathogenicity of the novel WRN frameshift mutation needs to be investigated further. Given its extensive use in clinical genetic screening, multiplex genetic testing is a promising tool in clinical cancer surveillance.

  4. The characterization of an intestine-like genomic signature maintained during Barrett’s-associated adenocarcinogenesis reveals an NR5A2-mediated promotion of cancer cell survival

    Science.gov (United States)

    Duggan, Shane P.; Behan, Fiona M.; Kirca, Murat; Zaheer, Abdul; McGarrigle, Sarah A.; Reynolds, John V.; Vaz, Gisela M. F.; Senge, Mathias O.; Kelleher, Dermot

    2016-09-01

    Barrett’s oesophagus (BO), an intestinal-type metaplasia (IM), typically arising in conjunction with gastro-oesophageal reflux disease, is a prominent risk factor for the development of oesophageal adenocarcinoma (OAC). The molecular similarities between IM and normal intestinal tissues are ill-defined. Consequently, the contribution of intestine-enriched factors expressed within BO to oncogenesis is unclear. Herein, using transcriptomics we define the intestine-enriched genes expressed in meta-profiles of BO and OAC. Interestingly, 77% of the genes differentially expressed in a meta-profile of BO were similarly expressed in intestinal tissues. Furthermore, 85% of this intestine-like signature was maintained upon transition to OAC. Gene networking analysis of transcription factors within this signature revealed a network centred upon NR5A2, GATA6 and FOXA2, whose over-expression was determined in a cohort of BO and OAC patients. Simulated acid reflux was observed to induce the expression of both NR5A2 and GATA6. Using siRNA-mediated silencing and an NR5A2 antagonist we demonstrate that NR5A2-mediated cancer cell survival is facilitated through augmentation of GATA6 and anti-apoptotic factor BCL-XL levels. Abrogation of NR5A2-GATA6 expression in conjunction with BCL-XL co-silencing resulted in synergistically increased sensitivity to chemotherapeutics and photo-dynamic therapeutics. These findings characterize the intestine-like signature associated with IM which may have important consequences to adenocarcinogenesis.

  5. Low ANXA10 expression is associated with disease aggressiveness in bladder cancer

    DEFF Research Database (Denmark)

    Munksgaard, P P; Mansilla, F; Brems Eskildsen, A-S;

    2011-01-01

    Markers for outcome prediction in bladder cancer are urgently needed. We have previously identified a molecular signature for predicting progression in non-muscle-invasive bladder cancer. ANXA10 was one of the markers included in the signature and we now validated the prognostic relevance of ANXA...

  6. Colon Cancer Biomarkers To Identify Patients Suitable For Therapeutic Intervention | NCI Technology Transfer Center | TTC

    Science.gov (United States)

    The National Cancer Institute's Laboratory of Human Carcinogenesis is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize cancer biomarkers and therapeutic targets.

  7. Metabolomic profile in pancreatic cancer patients: a consensus-based approach to identify highly discriminating metabolites

    OpenAIRE

    Di Gangi, Iole Maria; Mazza, Tommaso; Fontana, Andrea; Copetti, Massimiliano; Fusilli, Caterina; Ippolito, Antonio; Mattivi, Fulvio; Latiano, Anna; Andriulli, Angelo; Vrhovsek, Urska; Pazienza, Valerio

    2016-01-01

    Purpose pancreatic adenocarcinoma is the fourth leading cause of cancer related deaths due to its aggressive behavior and poor clinical outcome. There is a considerable variability in the frequency of serum tumor markers in cancer' patients. We performed a metabolomics screening in patients diagnosed with pancreatic cancer. Experimental Design Two targeted metabolomic assays were conducted on 40 serum samples of patients diagnosed with pancreatic cancer and 40 healthy controls. Multivariate m...

  8. Genome-wide association study identifies new prostate cancer susceptibility loci

    DEFF Research Database (Denmark)

    Schumacher, Fredrick R.; Berndt, Sonja I.; Siddiq, Afshan;

    2011-01-01

    Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have iden...

  9. Comparative evaluation of genetic assays to identify oral pre-cancerous fields

    NARCIS (Netherlands)

    J.F. Bremmer; B.J. Braakhuis; A. Brink; M.A. Broeckaert; J.A.M. Beliën; G.A. Meijer; D.J. Kuik; C.R. Leemans; E. Bloemena; I. van der Waal; R.H. Brakenhoff

    2008-01-01

    Background: Oral squamous cell carcinomas often develop in a pre-cancerous field, defined as mucosal epithelium with cancer-related genetic alterations, and which may appear as a clinically visible lesion. The test characteristics of three genetic assays that were developed to detect pre-cancerous f

  10. Integrative analyses identify osteopontin, LAMB3 and ITGB1 as critical pro-metastatic genes for lung cancer.

    Directory of Open Access Journals (Sweden)

    Xiao-Min Wang

    Full Text Available OBJECTIVE: To explore the key regulatory genes associated with lung cancer in order to reduce its occurrence and progress through silencing these key genes. METHODS: To identify the key regulatory genes involved in lung cancer, we performed a combination of gene array and bioinformatics analyses to compare gene transcription profiles in 3 monoclonal cell strains with high, medium or low metastatic abilities, which were separated from the SPC-A-1sci and SPC-A-1 cell lines by limiting dilution monoclone assay. We then analyzed those genes' biological activities by knocking down their expression in SPC-A-1sci cells using siRNA and lenti-viral shRNA vectors, followed by determinations of the invasion and migration capabilities of the resulting cell lines in vitro as well as their potential for inducing occurrence and metastasis of lung cancer in vivo. To examine the clinical relevance of these findings, we analyzed the expression levels of the identified genes in human lung cancer tissues (n = 135 and matched adjacent normal tissues by immunohistochemical (IHC staining. RESULTS: Three monoclonal cell strains characterized with high, medium or low metastatic abilities were successfully selected. Gene array and bioinformatics analyses implied that osteopontin, LAMB3 and ITGB1 were key genes involved in lung cancer. Knockdown of these genes suppressed human lung cancer cell invasion and metastasis in vitro and in vivo. Clinical sample analyses indicated that osteopontin, LAMB3 and ITGB1 protein expression levels were higher in lung cancer patients, compared to non-cancerous adjacent tissues, and correlated with lymphatic metastasis. CONCLUSIONS: We confirmed that osteopontin, LAMB3 and ITGB1 played important roles in the occurrence and metastasis of lung cancer, thus provided important clues to understanding the molecular mechanism of metastasis and contributing to the therapeutic treatment of lung cancer.

  11. Identifying important breast cancer control strategies in Asia, Latin America and the Middle East/North Africa

    Directory of Open Access Journals (Sweden)

    Niessen Louis W

    2011-09-01

    Full Text Available Abstract Background Breast cancer is the most frequent cause of cancer death in women worldwide, but global disparities in breast cancer control persist, due to a lack of a comprehensive breast cancer control strategy in many countries. Objectives To identify and compare the need for breast cancer control strategies in Asia, Latin America and the Middle East/North Africa and to develop a common framework to guide the development of national breast cancer control strategies. Methods Data were derived from open-ended, semi-structured interviews conducted in 2007 with 221 clinicians, policy makers, and patient advocates; stratified across Asia (n = 97, Latin America (n = 46, the Middle East/North Africa (ME/NA (n = 39 and Australia and Canada (n = 39. Respondents were identified using purposive and snowballing sampling. Interpretation of the data utilized interpretive phenomenological analysis where transcripts and field notes were coded and analyzed and common themes were identified. Analysis of regional variation was conducted based on the frequency of discussion and the writing of the manuscript followed the RATS guidelines. Results Analysis revealed four major themes that form the foundation for developing national breast cancer control strategies: 1 building capacity; 2 developing evidence; 3 removing barriers; and 4 promoting advocacy - each specified across five sub-ordinate dimensions. The propensity to discuss most dimensions was similar across regions, but managing advocacy was discussed more frequently (p = 0.004 and organized advocacy was discussed less frequently (p Conclusions This unique research identified common themes for the development of breast cancer control strategies, grounded in the experience of local practitioners, policy makers and advocacy leaders across diverse regions. Future research should be aimed at gathering a wider array of experiences, including those of patients.

  12. Genome-wide sequencing to identify the cause of hereditary cancer syndromes: with examples from familial pancreatic cancer

    OpenAIRE

    Roberts, Nicholas J.; Klein, Alison P.

    2012-01-01

    Advances in our understanding of the human genome and next-generation technologies have facilitated the use of genome-wide sequencing to decipher the genetic basis of Mendelian disease and hereditary cancer syndromes. The application of genome-wide sequencing in hereditary cancer syndromes has had mixed success, in part, due to complex nature of the underlying genetic architecture. In this review we discuss the use of genome-wide sequencing in both Mendelian diseases and hereditary cancer syn...

  13. Genome-wide sequencing to identify the cause of hereditary cancer syndromes: with examples from familial pancreatic cancer.

    Science.gov (United States)

    Roberts, Nicholas J; Klein, Alison P

    2013-11-01

    Advances in our understanding of the human genome and next-generation technologies have facilitated the use of genome-wide sequencing to decipher the genetic basis of Mendelian disease and hereditary cancer syndromes. However, the application of genome-wide sequencing in hereditary cancer syndromes has had mixed success, in part, due to complex nature of the underlying genetic architecture. In this review we discuss the use of genome-wide sequencing in both Mendelian diseases and hereditary cancer syndromes, highlighting the potential and challenges of this approach using familial pancreatic cancer as an example. PMID:23196058

  14. A cohort analysis to identify eligible patients for intraoperative radiotherapy (IORT) of early breast cancer

    International Nuclear Information System (INIS)

    Since the results from the randomized TARGIT A trial were published, intraoperative radiotherapy (IORT) is used more often. IORT can be provided as accelerated partial breast irradiation (APBI) or as a boost. The definition of suitable patients for IORT as APBI differs between different national societies (e.g. ESTRO and ASTRO) and different inclusion criteria of trials and so does the eligibility of patients. This analysis identifies eligible patients for IORT according to available consensus statements and inclusion criteria of the ongoing TARGIT trials. Between 01/03 – 12/09, 1505 breast cancer cases were treated at the breast cancer center at the University Medical Center Mannheim. Complete data sets for age, stage (T, N, and M), histology and hormone receptor status were available in 1108 cases. Parameters to identify eligible patients are as follows: ESTRO: >50 years, invasive ductal carcinoma/other favorable histology (IDC), T1-2 (≤3 cm), N0, any hormone receptor status, M0; ASTRO: ≥60 years, IDC, T1, N0, positive estrogen hormone receptor status, M0; TARGIT E “elderly”, risk adapted radiotherapy with IORT followed by external beam radiotherapy in case of risk factors in final histopathology, phase II: ≥70 years, IDC, T1, N0, any hormone receptor status, M0; TARGIT C “consolidation”, risk adapted radiotherapy, phase IV: ≥50 years, IDC, T1, N0, positive hormone receptor status, M0; TARGIT BQR “boost quality registry”: every age, every histology, T1-2 (max. 3.5 cm), any hormone receptor status, N0/+, M0/+. Out of the 1108 cases, 379 cases (34.2%) were suitable for IORT as APBI regarding the ESTRO and 175 (15.8%) regarding the ASTRO consensus statements. 82 (7.4%) patients were eligible for the TARGIT E trial, 258 (23.3%) for the TARGIT C trial and 671 (60.6%) for the TARGIT BQR registry. According to the consensus statements of ASTRO (45.1%) and ESTRO (41.4%) about half of the eligible patients were treated with IORT as APBI. From the

  15. Identifying Temporal Changes and Topics that Promote Growth Within Online Communities: A Prospective Study of Six Online Cancer Forums

    Science.gov (United States)

    Durant, Kathleen T.; McCray, Alexa T.; Safran, Charles

    2011-01-01

    In this paper the authors have extended the methodology for temporal analysis of online forums and applied the methodology to six online cancer forums (melanoma, prostate cancer, testicular cancer, ovarian cancer and breast cancer). The goal was to develop, apply and improve methods that quantify the responsiveness of the interactions in online forums in order to identify the users and topics that promote use and usefulness of these online medical communities. The evolutional stages that gauge when a forum is expanding, contracting, or in a state of equilibrium were considered. The response function was thought to be an approximation of a discussion group’s utility to its members. By applying the evolutionary phase algorithm, it was determined that two out of six of the forums are in contracting phases, while four are in their largest growth phase. By analyzing the topics of the influential threads, the authors conclude that cancer treatment discussions as well as stage IV cancer discussions promote growth in the forums. It is observed that the discussion of treatment rather than diagnosis is important to help a cancer forum thrive. PMID:22022636

  16. Screening of 1331 Danish breast and/or ovarian cancer families identified 40 novel BRCA1 and BRCA2 mutations

    DEFF Research Database (Denmark)

    Hansen, Thomas V O; Jønson, Lars; Steffensen, Ane Y;

    2011-01-01

    Germ-line mutations in the tumour suppressor genes BRCA1 and BRCA2 predispose to breast and ovarian cancer. Since 1999 we have performed mutational screening of breast and/or ovarian cancer patients in East Denmark. During this period we have identified 40 novel sequence variations in BRCA1...... and BRCA2 in high risk breast and/or ovarian cancer families. The mutations were detected via pre-screening using dHPLC or high-resolution melting and direct sequencing. We identified 16 variants in BRCA1, including 9 deleterious frame-shift mutations, 2 intronic variants, 4 missense mutations, and 1...... interpreted as pathogenic, 3 missense mutations were suggested to be pathogenic based on in silico analysis, 6 mutations were suggested to be benign since they were identified in patients together with a well-known disease-causing BRCA1/BRCA2 mutation, while 12 were variants of unknown significance....

  17. Drug-repositioning screening identified piperlongumine as a direct STAT3 inhibitor with potent activity against breast cancer.

    Science.gov (United States)

    Bharadwaj, U; Eckols, T K; Kolosov, M; Kasembeli, M M; Adam, A; Torres, D; Zhang, X; Dobrolecki, L E; Wei, W; Lewis, M T; Dave, B; Chang, J C; Landis, M D; Creighton, C J; Mancini, M A; Tweardy, D J

    2015-03-12

    Signal transducer and activator of transcription (STAT) 3 regulates many cardinal features of cancer including cancer cell growth, apoptosis resistance, DNA damage response, metastasis, immune escape, tumor angiogenesis, the Warburg effect and oncogene addiction and has been validated as a drug target for cancer therapy. Several strategies have been used to identify agents that target Stat3 in breast cancer but none has yet entered into clinical use. We used a high-throughput fluorescence microscopy search strategy to identify compounds in a drug-repositioning library (Prestwick library) that block ligand-induced nuclear translocation of Stat3 and identified piperlongumine (PL), a natural product isolated from the fruit of the pepper Piper longum. PL inhibited Stat3 nuclear translocation, inhibited ligand-induced and constitutive Stat3 phosphorylation, and modulated expression of multiple Stat3-regulated genes. Surface plasmon resonance assay revealed that PL directly inhibited binding of Stat3 to its phosphotyrosyl peptide ligand. Phosphoprotein antibody array analysis revealed that PL does not modulate kinases known to activate Stat3 such as Janus kinases, Src kinase family members or receptor tyrosine kinases. PL inhibited anchorage-independent and anchorage-dependent growth of multiple breast cancer cell lines having increased pStat3 or total Stat3, and induced apoptosis. PL also inhibited mammosphere formation by tumor cells from patient-derived xenografts. PL's antitumorigenic function was causally linked to its Stat3-inhibitory effect. PL was non-toxic in mice up to a dose of 30 mg/kg/day for 14 days and caused regression of breast cancer cell line xenografts in nude mice. Thus, PL represents a promising new agent for rapid entry into the clinic for use in treating breast cancer, as well as other cancers in which Stat3 has a role. PMID:24681959

  18. Whole-genome sequencing identifies genomic heterogeneity at a nucleotide and chromosomal level in bladder cancer

    Science.gov (United States)

    Morrison, Carl D.; Liu, Pengyuan; Woloszynska-Read, Anna; Zhang, Jianmin; Luo, Wei; Qin, Maochun; Bshara, Wiam; Conroy, Jeffrey M.; Sabatini, Linda; Vedell, Peter; Xiong, Donghai; Liu, Song; Wang, Jianmin; Shen, He; Li, Yinwei; Omilian, Angela R.; Hill, Annette; Head, Karen; Guru, Khurshid; Kunnev, Dimiter; Leach, Robert; Eng, Kevin H.; Darlak, Christopher; Hoeflich, Christopher; Veeranki, Srividya; Glenn, Sean; You, Ming; Pruitt, Steven C.; Johnson, Candace S.; Trump, Donald L.

    2014-01-01

    Using complete genome analysis, we sequenced five bladder tumors accrued from patients with muscle-invasive transitional cell carcinoma of the urinary bladder (TCC-UB) and identified a spectrum of genomic aberrations. In three tumors, complex genotype changes were noted. All three had tumor protein p53 mutations and a relatively large number of single-nucleotide variants (SNVs; average of 11.2 per megabase), structural variants (SVs; average of 46), or both. This group was best characterized by chromothripsis and the presence of subclonal populations of neoplastic cells or intratumoral mutational heterogeneity. Here, we provide evidence that the process of chromothripsis in TCC-UB is mediated by nonhomologous end-joining using kilobase, rather than megabase, fragments of DNA, which we refer to as “stitchers,” to repair this process. We postulate that a potential unifying theme among tumors with the more complex genotype group is a defective replication–licensing complex. A second group (two bladder tumors) had no chromothripsis, and a simpler genotype, WT tumor protein p53, had relatively few SNVs (average of 5.9 per megabase) and only a single SV. There was no evidence of a subclonal population of neoplastic cells. In this group, we used a preclinical model of bladder carcinoma cell lines to study a unique SV (translocation and amplification) of the gene glutamate receptor ionotropic N-methyl D-aspertate as a potential new therapeutic target in bladder cancer. PMID:24469795

  19. The signature package on Witt spaces, II. Higher signatures

    CERN Document Server

    Albin, Pierre; Mazzeo, Rafe; Piazza, Paolo

    2009-01-01

    This is a sequel to the paper "The signature package on Witt spaces, I. Index classes" by the same authors. In the first part we investigated, via a parametrix construction, the regularity properties of the signature operator on a stratified Witt pseudomanifold, proving, in particular, that one can define a K-homology signature class. We also established the existence of an analytic index class for the signature operator twisted by a C^*_r\\Gamma Mischenko bundle and proved that the K-homology signature class is mapped to the signature index class by the assembly map. In this paper we continue our study, showing that the signature index class is invariant under rational Witt bordisms and stratified homotopies. We are also able to identify this analytic class with the topological analogue of the Mischenko symmetric signature recently defined by Banagl. Finally, we define Witt-Novikov higher signatures and show that our analytic results imply a purely topological theorem, namely that the Witt-Novikov higher sign...

  20. Somatic mutation profiles of MSI and MSS colorectal cancer identified by whole exome next generation sequencing and bioinformatics analysis.

    Directory of Open Access Journals (Sweden)

    Bernd Timmermann

    Full Text Available BACKGROUND: Colorectal cancer (CRC is with approximately 1 million cases the third most common cancer worldwide. Extensive research is ongoing to decipher the underlying genetic patterns with the hope to improve early cancer diagnosis and treatment. In this direction, the recent progress in next generation sequencing technologies has revolutionized the field of cancer genomics. However, one caveat of these studies remains the large amount of genetic variations identified and their interpretation. METHODOLOGY/PRINCIPAL FINDINGS: Here we present the first work on whole exome NGS of primary colon cancers. We performed 454 whole exome pyrosequencing of tumor as well as adjacent not affected normal colonic tissue from microsatellite stable (MSS and microsatellite instable (MSI colon cancer patients and identified more than 50,000 small nucleotide variations for each tissue. According to predictions based on MSS and MSI pathomechanisms we identified eight times more somatic non-synonymous variations in MSI cancers than in MSS and we were able to reproduce the result in four additional CRCs. Our bioinformatics filtering approach narrowed down the rate of most significant mutations to 359 for MSI and 45 for MSS CRCs with predicted altered protein functions. In both CRCs, MSI and MSS, we found somatic mutations in the intracellular kinase domain of bone morphogenetic protein receptor 1A, BMPR1A, a gene where so far germline mutations are associated with juvenile polyposis syndrome, and show that the mutations functionally impair the protein function. CONCLUSIONS/SIGNIFICANCE: We conclude that with deep sequencing of tumor exomes one may be able to predict the microsatellite status of CRC and in addition identify potentially clinically relevant mutations.

  1. Identifying association model for single-nucleotide polymorphisms of ORAI1 gene for breast cancer

    OpenAIRE

    Chang, Wei-Chiao; Fang, Yong-Yuan; Chang, Hsueh-Wei; Chuang, Li-Yeh; Lin, Yu-Da; Hou, Ming-Feng; Yang, Cheng-Hong

    2014-01-01

    Background ORAI1 channels play an important role for breast cancer progression and metastasis. Previous studies indicated the strong correlation between breast cancer and individual single nucleotide polymorphisms (SNPs) of ORAI1 gene. However, the possible SNP-SNP interaction of ORAI1 gene was not investigated. Results To develop the complex analyses of SNP-SNP interaction, we propose a genetic algorithm (GA) to detect the model of breast cancer association between five SNPs (rs12320939, rs1...

  2. Next generation sequencing approaches to identify novel susceptibility genes for epithelial ovarian cancer

    OpenAIRE

    Hayward, J. D.

    2014-01-01

    Ovarian cancer is the fifth most common cancer in women in developed countries and is associated with poor survival due to late diagnoses. Strategies focusing on detecting the disease in the earliest stages and/or improving risk prediction may represent effective clinical intervention reducing disease burden. Women at the greatest risk of epithelial ovarian cancer (EOC) can be offered prophylactic risk-reducing salpingo-oopherectomy (RRSO), which is currently only offered to women with mutati...

  3. STAT3-Mediated Autophagy Dependence Identifies Subtypes of Breast Cancer where Autophagy Inhibition can be Efficacious

    OpenAIRE

    Maycotte, Paola; Gearheart, Christy M.; Barnard, Rebecca; Aryal, Suraj; Mulcahy Levy, Jean M.; Fosmire, Susan P.; Hansen, Ryan J.; Morgan, Michael J.; Christopher C Porter; Gustafson, Daniel L.; Thorburn, Andrew

    2014-01-01

    Autophagy is a protein and organelle degradation pathway that is involved in diverse diseases including cancer. Recent evidence suggests that autophagy is a cell survival mechanism in tumor cells and that its inhibition especially in combination with other therapy could be beneficial but it remains unclear if all cancer cells behave the same way when autophagy is inhibited. We inhibited autophagy in a panel of breast cancer cell lines and found that some of them are dependent on autophagy for...

  4. Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer

    OpenAIRE

    Kwei, KA; Kim, YH; Girard, L; Kao, J; Pacyna-Gengelbach, M; Salari, K; Lee, J.; Choi, Y-L; Sato, M.; Wang, P.; Hernandez-Boussard, T; Gazdar, AF; Petersen, I. (Inga); Minna, JD; Pollack, JR

    2008-01-01

    Lung cancer is a leading cause of cancer death, where the amplification of oncogenes contributes to tumorigenesis. Genomic profiling of 128 lung cancer cell lines and tumors revealed frequent focal DNA amplification at cytoband 14q13.3, a locus not amplified in other tumor types. The smallest region of recurrent amplification spanned the homeobox transcription factor TITF1 (thyroid transcription factor 1; also called NKX2-1), previously linked to normal lung development and function. When amp...

  5. The lung cancer breath signature: a comparative analysis of exhaled breath and air sampled from inside the lungs

    Science.gov (United States)

    Capuano, Rosamaria; Santonico, Marco; Pennazza, Giorgio; Ghezzi, Silvia; Martinelli, Eugenio; Roscioni, Claudio; Lucantoni, Gabriele; Galluccio, Giovanni; Paolesse, Roberto; di Natale, Corrado; D'Amico, Arnaldo

    2015-11-01

    Results collected in more than 20 years of studies suggest a relationship between the volatile organic compounds exhaled in breath and lung cancer. However, the origin of these compounds is still not completely elucidated. In spite of the simplistic vision that cancerous tissues in lungs directly emit the volatile metabolites into the airways, some papers point out that metabolites are collected by the blood and then exchanged at the air-blood interface in the lung. To shed light on this subject we performed an experiment collecting both the breath and the air inside both the lungs with a modified bronchoscopic probe. The samples were measured with a gas chromatography-mass spectrometer (GC-MS) and an electronic nose. We found that the diagnostic capability of the electronic nose does not depend on the presence of cancer in the sampled lung, reaching in both cases an above 90% correct classification rate between cancer and non-cancer samples. On the other hand, multivariate analysis of GC-MS achieved a correct classification rate between the two lungs of only 76%. GC-MS analysis of breath and air sampled from the lungs demonstrates a substantial preservation of the VOCs pattern from inside the lung to the exhaled breath.

  6. Module network inference from a cancer gene expression data set identifies microRNA regulated modules.

    Directory of Open Access Journals (Sweden)

    Eric Bonnet

    Full Text Available BACKGROUND: MicroRNAs (miRNAs are small RNAs that recognize and regulate mRNA target genes. Multiple lines of evidence indicate that they are key regulators of numerous critical functions in development and disease, including cancer. However, defining the place and function of miRNAs in complex regulatory networks is not straightforward. Systems approaches, like the inference of a module network from expression data, can help to achieve this goal. METHODOLOGY/PRINCIPAL FINDINGS: During the last decade, much progress has been made in the development of robust and powerful module network inference algorithms. In this study, we analyze and assess experimentally a module network inferred from both miRNA and mRNA expression data, using our recently developed module network inference algorithm based on probabilistic optimization techniques. We show that several miRNAs are predicted as statistically significant regulators for various modules of tightly co-expressed genes. A detailed analysis of three of those modules demonstrates that the specific assignment of miRNAs is functionally coherent and supported by literature. We further designed a set of experiments to test the assignment of miR-200a as the top regulator of a small module of nine genes. The results strongly suggest that miR-200a is regulating the module genes via the transcription factor ZEB1. Interestingly, this module is most likely involved in epithelial homeostasis and its dysregulation might contribute to the malignant process in cancer cells. CONCLUSIONS/SIGNIFICANCE: Our results show that a robust module network analysis of expression data can provide novel insights of miRNA function in important cellular processes. Such a computational approach, starting from expression data alone, can be helpful in the process of identifying the function of miRNAs by suggesting modules of co-expressed genes in which they play a regulatory role. As shown in this study, those modules can then be

  7. Developing a prognostic micro-RNA signature for human cervical carcinoma.

    Directory of Open Access Journals (Sweden)

    Christine How

    Full Text Available Cervical cancer remains the third most frequently diagnosed and fourth leading cause of cancer death in women worldwide. We sought to develop a micro-RNA signature that was prognostic for disease-free survival, which could potentially allow tailoring of treatment for cervical cancer patients. A candidate prognostic 9-micro-RNA signature set was identified in the training set of 79 frozen specimens. However, three different approaches to validate this signature in an independent cohort of 87 patients with formalin-fixed paraffin-embedded (FFPE specimens, were unsuccessful. There are several challenges and considerations associated with developing a prognostic micro-RNA signature for cervical cancer, namely: tumour heterogeneity, lack of concordance between frozen and FFPE specimens, and platform selection for global micro-RNA expression profiling in this disease. Our observations provide an important cautionary tale for future miRNA signature studies for cervical cancer, which can also be potentially applicable to miRNA profiling studies involving other types of human malignancies.

  8. High-throughput genomic technology in research and clinical management of breast cancer. Molecular signatures of progression from benign epithelium to metastatic breast cancer

    OpenAIRE

    Rennstam, Karin; Hedenfalk, Ingrid

    2006-01-01

    It is generally accepted that early detection of breast cancer has great impact on patient survival, emphasizing the importance of early diagnosis. In a widely recognized model of breast cancer development, tumor cells progress through chronological and well defined stages. However, the molecular basis of disease progression in breast cancer remains poorly understood. High-throughput molecular profiling techniques are excellent tools for the study of complex molecular alterations. By accurate...

  9. Characterizing associations and SNP-environment interactions for GWAS-identified prostate cancer risk markers--results from BPC3.

    Directory of Open Access Journals (Sweden)

    Sara Lindstrom

    Full Text Available Genome-wide association studies (GWAS have identified multiple single nucleotide polymorphisms (SNPs associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3. We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10⁻²⁸. Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test, where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade < 8 tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.

  10. Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

    Science.gov (United States)

    Wang, Xianshu; McGuffog, Lesley; Lee, Andrew; Olswold, Curtis; Kuchenbaecker, Karoline B.; Soucy, Penny; Fredericksen, Zachary; Barrowdale, Daniel; Dennis, Joe; Gaudet, Mia M.; Dicks, Ed; Kosel, Matthew; Healey, Sue; Sinilnikova, Olga M.; Lee, Adam; Bacot, François; Vincent, Daniel; Hogervorst, Frans B. L.; Peock, Susan; Stoppa-Lyonnet, Dominique; Jakubowska, Anna; Investigators, kConFab; Radice, Paolo; Schmutzler, Rita Katharina; Domchek, Susan M.; Piedmonte, Marion; Singer, Christian F.; Friedman, Eitan; Thomassen, Mads; Hansen, Thomas V. O.; Neuhausen, Susan L.; Szabo, Csilla I.; Blanco, Ignacio; Greene, Mark H.; Karlan, Beth Y.; Garber, Judy; Phelan, Catherine M.; Weitzel, Jeffrey N.; Montagna, Marco; Olah, Edith; Andrulis, Irene L.; Godwin, Andrew K.; Yannoukakos, Drakoulis; Goldgar, David E.; Caldes, Trinidad; Nevanlinna, Heli; Osorio, Ana; Terry, Mary Beth; Daly, Mary B.; van Rensburg, Elizabeth J.; Hamann, Ute; Ramus, Susan J.; Ewart Toland, Amanda; Caligo, Maria A.; Olopade, Olufunmilayo I.; Tung, Nadine; Claes, Kathleen; Beattie, Mary S.; Southey, Melissa C.; Imyanitov, Evgeny N.; Tischkowitz, Marc; Janavicius, Ramunas; John, Esther M.; Kwong, Ava; Diez, Orland; Balmaña, Judith; Barkardottir, Rosa B.; Arun, Banu K.; Rennert, Gad; Teo, Soo-Hwang; Ganz, Patricia A.; Campbell, Ian; van der Hout, Annemarie H.; van Deurzen, Carolien H. M.; Seynaeve, Caroline; Gómez Garcia, Encarna B.; van Leeuwen, Flora E.; Meijers-Heijboer, Hanne E. J.; Gille, Johannes J. P.; Ausems, Margreet G. E. M.; Blok, Marinus J.; Ligtenberg, Marjolijn J. L.; Rookus, Matti A.; Devilee, Peter; Verhoef, Senno; van Os, Theo A. M.; Wijnen, Juul T.; Frost, Debra; Ellis, Steve; Fineberg, Elena; Platte, Radka; Evans, D. Gareth; Izatt, Louise; Eeles, Rosalind A.; Adlard, Julian; Eccles, Diana M.; Cook, Jackie; Brewer, Carole; Douglas, Fiona; Hodgson, Shirley; Morrison, Patrick J.; Side, Lucy E.; Donaldson, Alan; Houghton, Catherine; Rogers, Mark T.; Dorkins, Huw; Eason, Jacqueline; Gregory, Helen; McCann, Emma; Murray, Alex; Calender, Alain; Hardouin, Agnès; Berthet, Pascaline; Delnatte, Capucine; Nogues, Catherine; Lasset, Christine; Houdayer, Claude; Leroux, Dominique; Rouleau, Etienne; Prieur, Fabienne; Damiola, Francesca; Sobol, Hagay; Coupier, Isabelle; Venat-Bouvet, Laurence; Castera, Laurent; Gauthier-Villars, Marion; Léoné, Mélanie; Pujol, Pascal; Mazoyer, Sylvie; Bignon, Yves-Jean; Złowocka-Perłowska, Elżbieta; Gronwald, Jacek; Lubinski, Jan; Durda, Katarzyna; Jaworska, Katarzyna; Huzarski, Tomasz; Spurdle, Amanda B.; Viel, Alessandra; Peissel, Bernard; Bonanni, Bernardo; Melloni, Giulia; Ottini, Laura; Papi, Laura; Varesco, Liliana; Tibiletti, Maria Grazia; Peterlongo, Paolo; Volorio, Sara; Manoukian, Siranoush; Pensotti, Valeria; Arnold, Norbert; Engel, Christoph; Deissler, Helmut; Gadzicki, Dorothea; Gehrig, Andrea; Kast, Karin; Rhiem, Kerstin; Meindl, Alfons; Niederacher, Dieter; Ditsch, Nina; Plendl, Hansjoerg; Preisler-Adams, Sabine; Engert, Stefanie; Sutter, Christian; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Weber, Bernhard H. F.; Arver, Brita; Stenmark-Askmalm, Marie; Loman, Niklas; Rosenquist, Richard; Einbeigi, Zakaria; Nathanson, Katherine L.; Rebbeck, Timothy R.; Blank, Stephanie V.; Cohn, David E.; Rodriguez, Gustavo C.; Small, Laurie; Friedlander, Michael; Bae-Jump, Victoria L.; Fink-Retter, Anneliese; Rappaport, Christine; Gschwantler-Kaulich, Daphne; Pfeiler, Georg; Tea, Muy-Kheng; Lindor, Noralane M.; Kaufman, Bella; Shimon Paluch, Shani; Laitman, Yael; Skytte, Anne-Bine; Gerdes, Anne-Marie; Pedersen, Inge Sokilde; Moeller, Sanne Traasdahl; Kruse, Torben A.; Jensen, Uffe Birk; Vijai, Joseph; Sarrel, Kara; Robson, Mark; Kauff, Noah; Mulligan, Anna Marie; Glendon, Gord; Ozcelik, Hilmi; Ejlertsen, Bent; Nielsen, Finn C.; Jønson, Lars; Andersen, Mette K.; Ding, Yuan Chun; Steele, Linda; Foretova, Lenka; Teulé, Alex; Lazaro, Conxi; Brunet, Joan; Pujana, Miquel Angel; Mai, Phuong L.; Loud, Jennifer T.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Narod, Steven A.; Herzog, Josef; Sand, Sharon R.; Tognazzo, Silvia; Agata, Simona; Vaszko, Tibor; Weaver, Joellen; Stavropoulou, Alexandra V.; Buys, Saundra S.; Romero, Atocha; de la Hoya, Miguel; Aittomäki, Kristiina; Muranen, Taru A.; Duran, Mercedes; Chung, Wendy K.; Lasa, Adriana; Dorfling, Cecilia M.; Miron, Alexander; Benitez, Javier; Senter, Leigha; Huo, Dezheng; Chan, Salina B.; Sokolenko, Anna P.; Chiquette, Jocelyne; Tihomirova, Laima; Friebel, Tara M.; Agnarsson, Bjarni A.; Lu, Karen H.; Lejbkowicz, Flavio; James, Paul A.; Hall, Per

    2013-01-01

    BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10−8, HR = 1.14, 95% CI: 1.09–1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10−8, HR = 1.27, 95% CI: 1.17–1.38) and 4q32.3 (rs4691139, P = 3.4×10−8, HR = 1.20, 95% CI: 1.17–1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10−4). These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%–50% compared to 81%–100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers. PMID:23544013

  11. Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk.

    Directory of Open Access Journals (Sweden)

    Fergus J Couch

    Full Text Available BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer, with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7 × 10(-8, HR = 1.14, 95% CI: 1.09-1.20. In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4 × 10(-8, HR = 1.27, 95% CI: 1.17-1.38 and 4q32.3 (rs4691139, P = 3.4 × 10(-8, HR = 1.20, 95% CI: 1.17-1.38. The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific association. The 17q21.31 locus was also associated with ovarian cancer risk in 8,211 BRCA2 carriers (P = 2×10(-4. These loci may lead to an improved understanding of the etiology of breast and ovarian tumors in BRCA1 carriers. Based on the joint distribution of the known BRCA1 breast cancer risk-modifying loci, we estimated that the breast cancer lifetime risks for the 5% of BRCA1 carriers at lowest risk are 28%-50% compared to 81%-100% for the 5% at highest risk. Similarly, based on the known ovarian cancer risk-modifying loci, the 5% of BRCA1 carriers at lowest risk have an estimated lifetime risk of developing ovarian cancer of 28% or lower, whereas the 5% at highest risk will have a risk of 63% or higher. Such differences in risk may have important implications for risk prediction and clinical management for BRCA1 carriers.

  12. Deep sequencing and in silico analyses identify MYB-regulated gene networks and signaling pathways in pancreatic cancer.

    Science.gov (United States)

    Azim, Shafquat; Zubair, Haseeb; Srivastava, Sanjeev K; Bhardwaj, Arun; Zubair, Asif; Ahmad, Aamir; Singh, Seema; Khushman, Moh'd; Singh, Ajay P

    2016-06-29

    We have recently demonstrated that the transcription factor MYB can modulate several cancer-associated phenotypes in pancreatic cancer. In order to understand the molecular basis of these MYB-associated changes, we conducted deep-sequencing of transcriptome of MYB-overexpressing and -silenced pancreatic cancer cells, followed by in silico pathway analysis. We identified significant modulation of 774 genes upon MYB-silencing (p networks by in silico analysis. Further analyses placed genes in our RNA sequencing-generated dataset to several canonical signalling pathways, such as cell-cycle control, DNA-damage and -repair responses, p53 and HIF1α. Importantly, we observed downregulation of the pancreatic adenocarcinoma signaling pathway in MYB-silenced pancreatic cancer cells exhibiting suppression of EGFR and NF-κB. Decreased expression of EGFR and RELA was validated by both qPCR and immunoblotting and they were both shown to be under direct transcriptional control of MYB. These observations were further confirmed in a converse approach wherein MYB was overexpressed ectopically in a MYB-null pancreatic cancer cell line. Our findings thus suggest that MYB potentially regulates growth and genomic stability of pancreatic cancer cells via targeting complex gene networks and signaling pathways. Further in-depth functional studies are warranted to fully understand MYB signaling in pancreatic cancer.

  13. Primary breast cancer stem-like cells metastasise to bone, switch phenotype and acquire a bone tropism signature

    OpenAIRE

    D′Amico, L; Patanè, S; Grange, C.; Bussolati, B; Isella, C.; Fontani, L; Godio, L; Cilli, M; D′Amelio, P; Isaia, G; Medico, E; Ferracini, R; Roato, I

    2013-01-01

    Background: Bone metastases represent a common and severe complication in breast cancer, and the involvement of cancer stem cells (CSCs) in the promotion of bone metastasis is currently under discussion. Here, we used a human-in-mice model to study bone metastasis formation due to primary breast CSCs-like colonisation. Methods: Primary CD44+CD24− breast CSCs-like were transduced by a luciferase-lentiviral vector and injected through subcutaneous and intracardiac (IC) routes in non-obese/sever...

  14. Metastasis-related plasma membrane proteins of human breast cancer cells identified by comparative quantitative mass spectrometry

    DEFF Research Database (Denmark)

    Leth-Larsen, Rikke; Lund, Rikke; Hansen, Helle V;

    2009-01-01

    '-nucleotidase (ecto-5'-NT, CD73), Ndrg1, integrin beta1, CD44, CD74 and MHC class II proteins. The altered expression levels of proteins identified by LC-MS/MS were validated using flow cytometry, Western blotting, immunocyto- and immunohisto-chemistry. Analysis of clinical breast cancer biopsies demonstrated......The spread of cancer cells from a primary tumor to form metastasis at distant sites is a complex multi-step process. The cancer cell proteins, and plasma membrane proteins in particular, involved in this process are poorly defined and a study of the very early events of the metastatic process using...... clinical samples or in vitro assays is not feasible. We have used a unique model system consisting of two isogenic human breast cancer cell lines that are equally tumorigenic in mice, but while one gives rise to metastasis, the other disseminates single cells that remain dormant at distant organs. Membrane...

  15. Using functional genetics to identify components of cancer relevant signaling pathways

    NARCIS (Netherlands)

    Heynen, G.J.J.E.

    2015-01-01

    The clinical introduction of the so-called ‘targeted therapies’ some 15 years ago has started a new era in the treatment of cancer patients. These drugs hugely increase the possibilities to treat patients based on the genetic mutations of their cancer and therefore hold the promise of ‘personalized

  16. Reasons for failure to identify positive sentinel nodes in breast cancer patients with significant nodal involvement

    NARCIS (Netherlands)

    de Kanter, A. Y.; Menke-Pluijmers, M. B. E.; Henzen-Logmans, S. C.; van Geel, A. N.; van Eijck, C. J. H.; Wiggers, T.; Eggermont, A. M. M.

    2006-01-01

    Aim: To analyse causes of failure of sentinel node (SN) procedures in breast cancer patients and assess the role of pre-operative ultrasound examination of the axilla. Methods: In 138 consecutive clinically node negative breast cancer patients with the primary turnout in situ a SN procedure with rad

  17. Big screens with small RNAs : loss of function genetic screens to identify novel cancer genes

    NARCIS (Netherlands)

    Mullenders, J.

    2009-01-01

    This thesis described the construction and screening of one of the first large scale RNAi libraries for use in human cells. Functional genetic screens with this library have led to the identification of novel cancer genes. These cancer genes function in several pathways including the p53 tumor suppr

  18. Using Concept Mapping to Identify Action Steps for Physical Activity Promotion in Cancer Treatment

    Science.gov (United States)

    Fitzpatrick, Sean Joseph; Zizzi, Sam J.

    2014-01-01

    Background: The benefits of exercise during and after cancer treatment represent research areas that have received increased attention throughout the past 2 decades. Numerous benefits have been observed for cancer survivors who are physically active, yet oncologists have been slow to incorporate exercise counseling into practice. Purpose: The…

  19. Comparative survival analysis of breast cancer microarray studies identifies important prognostic genetic pathways

    Directory of Open Access Journals (Sweden)

    Liu Song

    2010-10-01

    Full Text Available Abstract Background An estimated 12% of females in the United States will develop breast cancer in their lifetime. Although, there are advances in treatment options including surgery and chemotherapy, breast cancer is still the second most lethal cancer in women. Thus, there is a clear need for better methods to predict prognosis for each breast cancer patient. With the advent of large genetic databases and the reduction in cost for the experiments, researchers are faced with choosing from a large pool of potential prognostic markers from numerous breast cancer gene expression profile studies. Methods Five microarray datasets related to breast cancer were examined using gene set analysis and the cancers were categorized into different subtypes using a scoring system based on genetic pathway activity. Results We have observed that significant genes in the individual studies show little reproducibility across the datasets. From our comparative analysis, using gene pathways with clinical variables is more reliable across studies and shows promise in assessing a patient's prognosis. Conclusions This study concludes that, in light of clinical variables, there are significant gene pathways in common across the datasets. Specifically, several pathways can further significantly stratify patients for survival. These candidate pathways should help to develop a panel of significant biomarkers for the prognosis of breast cancer patients in a clinical setting.

  20. Three LIF-dependent signatures and gene clusters with atypical expression profiles, identified by transcriptome studies in mouse ES cells and early derivatives

    Directory of Open Access Journals (Sweden)

    Hummel Oliver

    2009-02-01

    Full Text Available Abstract Background Mouse embryonic stem (ES cells remain pluripotent in vitro when grown in the presence of the cytokine Leukaemia Inhibitory Factor (LIF. Identification of LIF targets and of genes regulating the transition between pluripotent and early differentiated cells is a critical step for understanding the control of ES cell pluripotency. Results By gene profiling studies carried out with mRNAs from ES cells and their early derivatives treated or not with LIF, we have identified i LIF-dependent genes, highly expressed in pluripotent cells, whose expression level decreases sharply upon LIF withdrawal [Pluri genes], ii LIF induced genes [Lifind genes] whose expression is differentially regulated depending upon cell context and iii genes specific to the reversible or irreversible committed states. In addition, by hierarchical gene clustering, we have identified, among eight independent gene clusters, two atypical groups of genes, whose expression level was highly modulated in committed cells only. Computer based analyses led to the characterization of different sub-types of Pluri and Lifind genes, and revealed their differential modulation by Oct4 or Nanog master genes. Individual knock down of a selection of Pluri and Lifind genes leads to weak changes in the expression of early differentiation markers, in cell growth conditions in which these master genes are still expressed. Conclusion We have identified different sets of LIF-regulated genes depending upon the cell state (reversible or irreversible commitment, which allowed us to present a novel global view of LIF responses. We are also reporting on the identification of genes whose expression is strictly regulated during the commitment step. Furthermore, our studies identify sub-networks of genes with a restricted expression in pluripotent ES cells, whose down regulation occurs while the master knot (composed of OCT4, SOX2 and NANOG is still expressed and which might be down

  1. Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium

    OpenAIRE

    Birse, Charles E; Lagier, Robert J.; Fitzhugh, William; Harvey I Pass; Rom, William N.; Eric S. Edell; Aaron O. Bungum; Maldonado, Fabien; Jett, James R.; Mesri, Mehdi; Sult, Erin; Joseloff, Elizabeth; Li, Aiqun; Heidbrink, Jenny; Dhariwal, Gulshan

    2015-01-01

    Background Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making the...

  2. Identifying Liver Cancer-Related Enhancer SNPs by Integrating GWAS and Histone Modification ChIP-seq Data

    Directory of Open Access Journals (Sweden)

    Tianjiao Zhang

    2016-01-01

    Full Text Available Many disease-related single nucleotide polymorphisms (SNPs have been inferred from genome-wide association studies (GWAS in recent years. Numerous studies have shown that some SNPs located in protein-coding regions are associated with numerous diseases by affecting gene expression. However, in noncoding regions, the mechanism of how SNPs contribute to disease susceptibility remains unclear. Enhancer elements are functional segments of DNA located in noncoding regions that play an important role in regulating gene expression. The SNPs located in enhancer elements may affect gene expression and lead to disease. We presented a method for identifying liver cancer-related enhancer SNPs through integrating GWAS and histone modification ChIP-seq data. We identified 22 liver cancer-related enhancer SNPs, 9 of which were regulatory SNPs involved in distal transcriptional regulation. The results highlight that these enhancer SNPs may play important roles in liver cancer.

  3. Identifying Liver Cancer-Related Enhancer SNPs by Integrating GWAS and Histone Modification ChIP-seq Data

    Science.gov (United States)

    Hu, Yang; Wu, Xiaoliang; Ma, Rui

    2016-01-01

    Many disease-related single nucleotide polymorphisms (SNPs) have been inferred from genome-wide association studies (GWAS) in recent years. Numerous studies have shown that some SNPs located in protein-coding regions are associated with numerous diseases by affecting gene expression. However, in noncoding regions, the mechanism of how SNPs contribute to disease susceptibility remains unclear. Enhancer elements are functional segments of DNA located in noncoding regions that play an important role in regulating gene expression. The SNPs located in enhancer elements may affect gene expression and lead to disease. We presented a method for identifying liver cancer-related enhancer SNPs through integrating GWAS and histone modification ChIP-seq data. We identified 22 liver cancer-related enhancer SNPs, 9 of which were regulatory SNPs involved in distal transcriptional regulation. The results highlight that these enhancer SNPs may play important roles in liver cancer. PMID:27429976

  4. Identifying Liver Cancer-Related Enhancer SNPs by Integrating GWAS and Histone Modification ChIP-seq Data

    Science.gov (United States)

    Hu, Yang; Wu, Xiaoliang; Ma, Rui

    2016-01-01

    Many disease-related single nucleotide polymorphisms (SNPs) have been inferred from genome-wide association studies (GWAS) in recent years. Numerous studies have shown that some SNPs located in protein-coding regions are associated with numerous diseases by affecting gene expression. However, in noncoding regions, the mechanism of how SNPs contribute to disease susceptibility remains unclear. Enhancer elements are functional segments of DNA located in noncoding regions that play an important role in regulating gene expression. The SNPs located in enhancer elements may affect gene expression and lead to disease. We presented a method for identifying liver cancer-related enhancer SNPs through integrating GWAS and histone modification ChIP-seq data. We identified 22 liver cancer-related enhancer SNPs, 9 of which were regulatory SNPs involved in distal transcriptional regulation. The results highlight that these enhancer SNPs may play important roles in liver cancer.

  5. Case-control study for colorectal cancer genetic susceptibility in EPICOLON: previously identified variants and mucins

    Directory of Open Access Journals (Sweden)

    Moreno Victor

    2011-08-01

    Full Text Available Abstract Background Colorectal cancer (CRC is the second leading cause of cancer death in developed countries. Familial aggregation in CRC is also important outside syndromic forms and, in this case, a polygenic model with several common low-penetrance alleles contributing to CRC genetic predisposition could be hypothesized. Mucins and GALNTs (N-acetylgalactosaminyltransferase are interesting candidates for CRC genetic susceptibility and have not been previously evaluated. We present results for ten genetic variants linked to CRC risk in previous studies (previously identified category and 18 selected variants from the mucin gene family in a case-control association study from the Spanish EPICOLON consortium. Methods CRC cases and matched controls were from EPICOLON, a prospective, multicenter, nationwide Spanish initiative, comprised of two independent stages. Stage 1 corresponded to 515 CRC cases and 515 controls, whereas stage 2 consisted of 901 CRC cases and 909 controls. Also, an independent cohort of 549 CRC cases and 599 controls outside EPICOLON was available for additional replication. Genotyping was performed for ten previously identified SNPs in ADH1C, APC, CCDN1, IL6, IL8, IRS1, MTHFR, PPARG, VDR and ARL11, and 18 selected variants in the mucin gene family. Results None of the 28 SNPs analyzed in our study was found to be associated with CRC risk. Although four SNPs were significant with a P-value ADH1C (OR = 1.63, 95% CI = 1.06-2.50, P-value = 0.02, recessive, rs1800795 in IL6 (OR = 1.62, 95% CI = 1.10-2.37, P-value = 0.01, recessive, rs3803185 in ARL11 (OR = 1.58, 95% CI = 1.17-2.15, P-value = 0.007, codominant, and rs2102302 in GALNTL2 (OR = 1.20, 95% CI = 1.00-1.44, P-value = 0.04, log-additive 0, 1, 2 alleles], only rs3803185 achieved statistical significance in EPICOLON stage 2 (OR = 1.34, 95% CI = 1.06-1.69, P-value = 0.01, recessive. In the joint analysis for both stages, results were only significant for rs3803185 (OR = 1

  6. Case-control study for colorectal cancer genetic susceptibility in EPICOLON: previously identified variants and mucins

    International Nuclear Information System (INIS)

    Colorectal cancer (CRC) is the second leading cause of cancer death in developed countries. Familial aggregation in CRC is also important outside syndromic forms and, in this case, a polygenic model with several common low-penetrance alleles contributing to CRC genetic predisposition could be hypothesized. Mucins and GALNTs (N-acetylgalactosaminyltransferase) are interesting candidates for CRC genetic susceptibility and have not been previously evaluated. We present results for ten genetic variants linked to CRC risk in previous studies (previously identified category) and 18 selected variants from the mucin gene family in a case-control association study from the Spanish EPICOLON consortium. CRC cases and matched controls were from EPICOLON, a prospective, multicenter, nationwide Spanish initiative, comprised of two independent stages. Stage 1 corresponded to 515 CRC cases and 515 controls, whereas stage 2 consisted of 901 CRC cases and 909 controls. Also, an independent cohort of 549 CRC cases and 599 controls outside EPICOLON was available for additional replication. Genotyping was performed for ten previously identified SNPs in ADH1C, APC, CCDN1, IL6, IL8, IRS1, MTHFR, PPARG, VDR and ARL11, and 18 selected variants in the mucin gene family. None of the 28 SNPs analyzed in our study was found to be associated with CRC risk. Although four SNPs were significant with a P-value < 0.05 in EPICOLON stage 1 [rs698 in ADH1C (OR = 1.63, 95% CI = 1.06-2.50, P-value = 0.02, recessive), rs1800795 in IL6 (OR = 1.62, 95% CI = 1.10-2.37, P-value = 0.01, recessive), rs3803185 in ARL11 (OR = 1.58, 95% CI = 1.17-2.15, P-value = 0.007, codominant), and rs2102302 in GALNTL2 (OR = 1.20, 95% CI = 1.00-1.44, P-value = 0.04, log-additive 0, 1, 2 alleles], only rs3803185 achieved statistical significance in EPICOLON stage 2 (OR = 1.34, 95% CI = 1.06-1.69, P-value = 0.01, recessive). In the joint analysis for both stages, results were only significant for rs3803185 (OR = 1.12, 95% CI = 1

  7. Apples to origins: Identifying brain tumor stem cell genes by comparing transcriptomes of normal and cancer stem cells

    OpenAIRE

    Wortham, Matthew; Yan, Hai

    2012-01-01

    The mechanisms whereby medulloblastoma stem cells coordinate tumor propagation are poorly understood. Utilizing microarray analysis, Corno and colleagues draw parallels and distinctions between medulloblastoma stem cells from the Ptch+/− mouse and normal neural stem cells, identifying Ebf3 as a cancer stem cell-specific transcript critical for tumor growth.

  8. PS1-08: Genetic Service Providers Identify Barriers Related to Referral, Counseling and Testing for Familial Cancer

    OpenAIRE

    Jackson, Jody; Rolnick, Cheri; Rahm, Alanna; Nekhlyudov, Larissa; Goddard, Katrina; Field, Terry; McCarty, Catherine; Nakasato, Cynthia; ROBLIN, DOUGLAS; Anderson, Christopher; Valdez, Rodolfo

    2010-01-01

    Background and Aims: Little of what we know about the use of family history and genetic risk assessment services has been gathered from those engaged in counseling. To fill this gap, we conducted a survey to understand the processes of identifying and referring high-risk patients for genetic counseling and testing for familial cancer from the perspective of genetic service providers.

  9. Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer

    OpenAIRE

    Deodutta Roy; Marisa Morgan; Changwon Yoo; Alok Deoraj; Sandhya Roy; Vijay Kumar Yadav; Mohannad Garoub; Hamza Assaggaf; Mayur Doke

    2015-01-01

    We present a combined environmental epidemiologic, genomic, and bioinformatics approach to identify: exposure of environmental chemicals with estrogenic activity; epidemiologic association between endocrine disrupting chemical (EDC) and health effects, such as, breast cancer or endometriosis; and gene-EDC interactions and disease associations. Human exposure measurement and modeling confirmed estrogenic activity of three selected class of environmental chemicals, polychlorinated biphenyls (PC...

  10. Fine-scale mapping of the 4q24 locus identifies & pr two Independent loci associated with breast cancer risk

    NARCIS (Netherlands)

    X. Guo (Xingyi); J. Long (Jirong); C. Zeng (Chenjie); K. Michailidou (Kyriaki); M. Ghoussaini (Maya); M.K. Bolla (Manjeet); Q. Wang (Qing); R.L. Milne (Roger L.); X.-O. Shu (Xiao-Ou); Q. Cai (Qiuyin); J. Beesley (Jonathan); S. Kar (Siddhartha); I.L. Andrulis (Irene); H. Anton-Culver (Hoda); V. Arndt (Volker); M.W. Beckmann (Matthias W.); A. Beeghly-Fadiel (Alicia); J. Benítez (Javier); W.J. Blot (William); N.V. Bogdanova (Natalia); S.E. Bojesen (Stig); H. Brauch (Hiltrud); H. Brenner (Hermann); L.A. Brinton (Louise); A. Broekss (Annegien); T. Brüning (Thomas); B. Burwinkel (Barbara); H. Cai (Hui); S. Canisius (Sander); J. Chang-Claude (Jenny); J.-Y. Choi (J.); F.J. Couch (Fergus); A. Cox (Angela); S.S. Cross (Simon); K. Czene (Kamila); H. Darabi (Hatef); P. Devilee (Peter); A. Droit (Arnaud); T. Dörk (Thilo); P.A. Fasching (Peter); O. Fletcher (Olivia); H. Flyger (Henrik); F. Fostira (Florentia); V. Gaborieau (Valerie); M. García-Closas (Montserrat); G.G. Giles (Graham G.); M. Grip (Mervi); P. Guénel (Pascal); C.A. Haiman (Christopher A.); U. Hamann (Ute); J.M. Hartman (Joost); A. Hollestelle (Antoinette); J.L. Hopper (John L.); C.-N. Hsiung (Chia-Ni); H. Ito (Hidemi); A. Jakubowska (Anna); N. Johnson (Nichola); M. Kabisch (Maria); D. Kang (Daehee); S. Khan (Sofia); J.A. Knight (Julia); V-M. Kosma (Veli-Matti); D. Lambrechts (Diether); L. Le Marchand (Loic); J. Li (Jingmei); A. Lindblom (Annika); A. Lophatananon (Artitaya); J. Lubinski (Jan); A. Mannermaa (Arto); S. Manoukian (Siranoush); S. Margolin (Sara); F. Marme (Federick); K. Matsuo (Keitaro); C.A. McLean (Catriona Ann); A. Meindl (Alfons); K. Muir (Kenneth); S.L. Neuhausen (Susan); H. Nevanlinna (Heli); S. Nord (Silje); J.E. Olson (Janet); N. Orr (Nick); P. Peterlongo (Paolo); T.C. Putti (Thomas Choudary); A. Rudolph (Anja); S. Sangrajrang (Suleeporn); E.J. Sawyer (Elinor); M.K. Schmidt (Marjanka); R.K. Schmutzler (Rita); C-Y. Shen (Chen-Yang); J. Shi (Jiajun); M. Shrubsole (Martha); M.C. Southey (Melissa); A.J. Swerdlow (Anthony ); S.H. Teo (Soo Hwang); B. Thienpont (Bernard); A.E. Toland (Amanda); R.A.E.M. Tollenaar (Rob); I. Tomlinson (Ian); T. Truong (Thérèse); C.-C. Tseng (Chiu-chen); A.M.W. van den Ouweland (Ans); W. Wen (Wanqing); R. Winqvist (Robert); A. Wu (Anna); C.H. Yip (Cheng Har); M.P. Zamora (Pilar); Y. Zheng (Ying); P. Hall (Per); P.D.P. Pharoah (Paul); J. Simard (Jacques); G. Chenevix-Trench (Georgia); A.M. Dunning (Alison); D.F. Easton (Douglas F.); W. Zheng (Wei); R. Eeles (Rosalind); A.A. Al Olama (Ali Amin); Z. Kote-Jarai; S. Benlloch (Sara); A.C. Antoniou (Antonis C.); L. McGuffog (Lesley); K. Offit (Kenneth); A. Lee (Andrew); E. Dicks (Ed); C. Luccarini (Craig); D.C. Tessier (Daniel C.); F. Bacot (Francois); D. Vincent (Daniel); S. La Boissière (Sylvie); F. Robidoux (Frederic); S.F. Nielsen (Sune); J.M. Cunningham (Julie); S.A. Windebank (Sharon A.); C.A. Hilker (Christopher A.); J. Meyer (Jeffrey); M. Angelakos (Maggie); J. Maskiell (Judi); E.J. Rutgers (Emiel J.); S. Verhoef; F.B.L. Hogervorst (Frans); P. Boonyawongviroj (Prat); P. Siriwanarungsan (Pornthep); A. Schrauder (André); M. Rübner (Matthias); S. Oeser (Sonja); S. Landrith (Silke); E. Williams (Eileen); E. Ryder-Mills (Elaine); K. Sargus (Kara); N. McInerney (Niall); G. Colleran (Gabrielle); A. Rowan (Andrew); A. Jones (Angela); C. Sohn (Christof); A. Schneeweiß (Andeas); P. Bugert (Peter); N. Álvarez (Nuria); L. Bernstein (Leslie); J. Lacey (James); S. Wang (Sophia); H. Ma (Huiyan); Y. Lu (Yani); J. Clague De Hart (Jessica); D. Deapen (Dennis); R. Pinder (Rich); E. Lee (Eunjung); F.R. Schumacher (Fredrick); P. Horn-Ross (Pam); P. Reynolds (Peggy); D. Nelson (David); H. Park (Hannah); H. Ziegler (Hartwig); S. Wolf (Sonja); V. Hermann (Volker); W.-Y. Lo (Wing-Yee); C. Justenhoven (Christina); Y.-D. Ko (Yon-Dschun); C. Baisch (Christian); H.-P. Fischer (Hans-Peter); B. Pesch (Beate); S. Rabstein (Sylvia); A. Lotz (Anne); V. Harth (Volker); T. Heikkinen (Tuomas); I. Erkkilä (Irja); K. Aaltonen (Kirsimari); K. von Smitten (Karl); N.N. Antonenkova (Natalia); P. Hillemanns (Peter); H. Christiansen (Hans); E. Myöhänen (Eija); H. Kemiläinen (Helena); H. Thorne (Heather); E. Niedermayr (Eveline); D. Bowtell; G. Chenevix-Trench (Georgia); A. De Fazio (Anna); D. Gertig; A. Green; P. Webb (Penny); A. Green; P. Parsons; N. Hayward; P.M. Webb (P.); D. Whiteman; A. Fung (Annie); J. Yashiki (June); G. Peuteman (Gilian); D. Smeets (Dominiek); T. Van Brussel (Thomas); K. Corthouts (Kathleen); N. Obi (Nadia); J. Heinz (Judith); T.W. Behrens (Timothy); U. Eilber (Ursula); M. Celik (Muhabbet); T. Olchers (Til); B. Peissel (Bernard); G. Scuvera (Giulietta); D. Zaffaroni (Daniela); B. Bonnani (Bernardo); I. Feroce (Irene); A. Maniscalco (Angela); A. Rossi (Alessandra); L. Bernard (Loris); M. Tranchant (Martine); M.-F. Valois (Marie-France); A. Turgeon (Annie); L. Heguy (Lea); P.S. Yee (Phuah Sze); P. Kang (Peter); K.I. Nee (Kang In); S. Mariapun (Shivaani); Y. Sook-Yee (Yoon); D.S.C. Lee (Daphne S.C.); T.Y. Ching (Teh Yew); N.A.M. Taib (Nur Aishah Mohd); M. Otsukka (Meeri); K. Mononen (Kari); T. Selander (Teresa); N. Weerasooriya (Nayana); E.M.M. Krol-Warmerdam (Elly); J. Molenaar; J. Blom; N. Szeszenia-Dabrowska (Neonilia); B. Peplonska (Beata); W. Zatonski (Witold); P. Chao (Pei); M. Stagner (Michael); P. Bos (Petra); J. Blom (Jannet); E. Crepin (Ellen); A. Nieuwlaat (Anja); A. Heemskerk (Annette); S. Higham (Sue); H.E. Cramp (Helen); D. Connley (Daniel); S. Balasubramanian (Sabapathy); I.W. Brock (Ian); M. Kerin (Michael); N. Miller (Nicola); P. Kerbrat (Pierre); P. Arveux (Patrick); R. Le Scodan (Romuald); Y. Raoul (Yves); P. Laurent-Puig (Pierre); C. Mulot (Claire); C. Stegmaier (Christa); K. Butterbach (Katja); J.H. Karstens (Johann); D. Flesch-Janys (Dieter); P. Seibold (Petra); A. Vrieling (Alina); S. Nickels (Stefan); P. Radice (Paolo); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); S. Kauppila (Saila); D. Conroy (Don); C. Baynes (Caroline); K. Chua (Kimberley); R. Pilarski (Robert)

    2015-01-01

    textabstractBackground: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540

  11. Fine-scale mapping of the 4q24 locus identifies two independent loci associated with breast cancer risk

    DEFF Research Database (Denmark)

    Guo, Xingyi; Long, Jirong; Zeng, Chenjie;

    2015-01-01

    BACKGROUND: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. METHODS: We conducted a fine-mapping analysis in 55,540 breast c...

  12. Identifying subgroups among poor prognosis patients with nonseminomatous germ cell cancer by tree modelling: a validation study.

    NARCIS (Netherlands)

    M.R. van Dijk (Merel); E.W. Steyerberg (Ewout); S.P. Stenning; J.D.F. Habbema (Dik)

    2004-01-01

    textabstractBACKGROUND: In order to target intensive treatment strategies for poor prognosis patients with non-seminomatous germ cell cancer, those with the poorest prognosis should be identified. These patients might profit most from more intensive treatment strategies. For this p

  13. A novel method for identifying settings for well-motivated ecologic studies of cancer.

    Science.gov (United States)

    Stang, Andreas; Kowall, Bernd; Rusner, Carsten; Trabert, Britton; Bray, Freddie; Schüz, Joachim; McGlynn, Katherine A; Kuss, Oliver

    2016-04-15

    A low within-country variability and a large between-country variability in cancer incidence may indicate that ecologic factors are involved in the etiology of the disease. The aim of this study is to explore the within- and between-country variability of cancer incidence to motivate high-quality ecologic studies. We extracted age-standardized incidence rate estimates (world standard population) from 135 regions for the ten most frequent invasive cancers in Europe for non-Hispanic white populations from Cancer Incidence in Five Continents, Volume X. We fitted weighted multilevel Poisson regression models with random country effects for each cancer and sex. We estimated intraclass correlation coefficients (ICCs) and 95% confidence intervals (95% CIs). A high ICC indicates a low within- and a high between-country variability of rates. The two cancer sites with the highest ICC among men were prostate cancer (0.96, 95% CI: 0.92-0.99) and skin melanoma (0.78, 0.64-0.93). Among women, high ICCs were observed for lung cancer (0.84, 0.73-0.95) and breast cancer (0.80, 0.69-0.91). The two most prominent sex differences for ICC occurred for cancers of the head and neck (men: 0.70, 0.55-0.85, women: 0.19, 0.08-0.30) and breast cancer (men: 0.04, 0.01-0.07, women: 0.80, 0.69-0.91). ICCs were relatively low for pancreatic cancer (men: 0.23, 0.10-0.35; women: 0.13, 0.04-0.21) and leukemia (men: 0.12, 0.04-0.21; women: 0.08, 0.02-0.14). For cancers with high ICC for which systematic factors of the health care system, screening and diagnostic activities are not plausible explanations for between-country variations in incidence, cross-country sex-specific ecologic studies may be especially promising.

  14. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    Directory of Open Access Journals (Sweden)

    Jun Yao

    Full Text Available Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT, recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  15. Identification of common prognostic gene expression signatures with biological meanings from microarray gene expression datasets.

    Science.gov (United States)

    Yao, Jun; Zhao, Qi; Yuan, Ying; Zhang, Li; Liu, Xiaoming; Yung, W K Alfred; Weinstein, John N

    2012-01-01

    Numerous prognostic gene expression signatures for breast cancer were generated previously with few overlap and limited insight into the biology of the disease. Here we introduce a novel algorithm named SCoR (Survival analysis using Cox proportional hazard regression and Random resampling) to apply random resampling and clustering methods in identifying gene features correlated with time to event data. This is shown to reduce overfitting noises involved in microarray data analysis and discover functional gene sets linked to patient survival. SCoR independently identified a common poor prognostic signature composed of cell proliferation genes from six out of eight breast cancer datasets. Furthermore, a sequential SCoR analysis on highly proliferative breast cancers repeatedly identified T/B cell markers as favorable prognosis factors. In glioblastoma, SCoR identified a common good prognostic signature of chromosome 10 genes from two gene expression datasets (TCGA and REMBRANDT), recapitulating the fact that loss of one copy of chromosome 10 (which harbors the tumor suppressor PTEN) is linked to poor survival in glioblastoma patients. SCoR also identified prognostic genes on sex chromosomes in lung adenocarcinomas, suggesting patient gender might be used to predict outcome in this disease. These results demonstrate the power of SCoR to identify common and biologically meaningful prognostic gene expression signatures.

  16. Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

    DEFF Research Database (Denmark)

    Bothwell, H.; Bisbing, S.; Therkildsen, Nina Overgaard;

    2013-01-01

    loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi...... variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major......-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R adj 2 > 0.5). 2) Models including PCNM...

  17. Genome-Wide Transcriptome Analysis of Cotton (Gossypium hirsutum L. Identifies Candidate Gene Signatures in Response to Aflatoxin Producing Fungus Aspergillus flavus.

    Directory of Open Access Journals (Sweden)

    Renesh Bedre

    Full Text Available Aflatoxins are toxic and potent carcinogenic metabolites produced from the fungi Aspergillus flavus and A. parasiticus. Aflatoxins can contaminate cottonseed under conducive preharvest and postharvest conditions. United States federal regulations restrict the use of aflatoxin contaminated cottonseed at >20 ppb for animal feed. Several strategies have been proposed for controlling aflatoxin contamination, and much success has been achieved by the application of an atoxigenic strain of A. flavus in cotton, peanut and maize fields. Development of cultivars resistant to aflatoxin through overexpression of resistance associated genes and/or knocking down aflatoxin biosynthesis of A. flavus will be an effective strategy for controlling aflatoxin contamination in cotton. In this study, genome-wide transcriptome profiling was performed to identify differentially expressed genes in response to infection with both toxigenic and atoxigenic strains of A. flavus on cotton (Gossypium hirsutum L. pericarp and seed. The genes involved in antifungal response, oxidative burst, transcription factors, defense signaling pathways and stress response were highly differentially expressed in pericarp and seed tissues in response to A. flavus infection. The cell-wall modifying genes and genes involved in the production of antimicrobial substances were more active in pericarp as compared to seed. The genes involved in auxin and cytokinin signaling were also induced. Most of the genes involved in defense response in cotton were highly induced in pericarp than in seed. The global gene expression analysis in response to fungal invasion in cotton will serve as a source for identifying biomarkers for breeding, potential candidate genes for transgenic manipulation, and will help in understanding complex plant-fungal interaction for future downstream research.

  18. Genome-Wide Transcriptome Analysis of Cotton (Gossypium hirsutum L.) Identifies Candidate Gene Signatures in Response to Aflatoxin Producing Fungus Aspergillus flavus.

    Science.gov (United States)

    Bedre, Renesh; Rajasekaran, Kanniah; Mangu, Venkata Ramanarao; Sanchez Timm, Luis Eduardo; Bhatnagar, Deepak; Baisakh, Niranjan

    2015-01-01

    Aflatoxins are toxic and potent carcinogenic metabolites produced from the fungi Aspergillus flavus and A. parasiticus. Aflatoxins can contaminate cottonseed under conducive preharvest and postharvest conditions. United States federal regulations restrict the use of aflatoxin contaminated cottonseed at >20 ppb for animal feed. Several strategies have been proposed for controlling aflatoxin contamination, and much success has been achieved by the application of an atoxigenic strain of A. flavus in cotton, peanut and maize fields. Development of cultivars resistant to aflatoxin through overexpression of resistance associated genes and/or knocking down aflatoxin biosynthesis of A. flavus will be an effective strategy for controlling aflatoxin contamination in cotton. In this study, genome-wide transcriptome profiling was performed to identify differentially expressed genes in response to infection with both toxigenic and atoxigenic strains of A. flavus on cotton (Gossypium hirsutum L.) pericarp and seed. The genes involved in antifungal response, oxidative burst, transcription factors, defense signaling pathways and stress response were highly differentially expressed in pericarp and seed tissues in response to A. flavus infection. The cell-wall modifying genes and genes involved in the production of antimicrobial substances were more active in pericarp as compared to seed. The genes involved in auxin and cytokinin signaling were also induced. Most of the genes involved in defense response in cotton were highly induced in pericarp than in seed. The global gene expression analysis in response to fungal invasion in cotton will serve as a source for identifying biomarkers for breeding, potential candidate genes for transgenic manipulation, and will help in understanding complex plant-fungal interaction for future downstream research. PMID:26366857

  19. Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia

    Science.gov (United States)

    Lan, Qing; Hsiung, Chao A; Matsuo, Keitaro; Hong, Yun-Chul; Seow, Adeline; Wang, Zhaoming; Hosgood, H Dean; Chen, Kexin; Wang, Jiu-Cun; Chatterjee, Nilanjan; Hu, Wei; Wong, Maria Pik; Zheng, Wei; Caporaso, Neil; Park, Jae Yong; Chen, Chien-Jen; Kim, Yeul Hong; Kim, Young Tae; Landi, Maria Teresa; Shen, Hongbing; Lawrence, Charles; Burdett, Laurie; Yeager, Meredith; Yuenger, Jeffrey; Jacobs, Kevin B; Chang, I-Shou; Mitsudomi, Tetsuya; Kim, Hee Nam; Chang, Gee-Chen; Bassig, Bryan A; Tucker, Margaret; Wei, Fusheng; Yin, Zhihua; Wu, Chen; An, She-Juan; Qian, Biyun; Lee, Victor Ho Fun; Lu, Daru; Liu, Jianjun; Jeon, Hyo-Sung; Hsiao, Chin-Fu; Sung, Jae Sook; Kim, Jin Hee; Gao, Yu-Tang; Tsai, Ying-Huang; Jung, Yoo Jin; Guo, Huan; Hu, Zhibin; Hutchinson, Amy; Wang, Wen-Chang; Klein, Robert; Chung, Charles C; Oh, In-Jae; Chen, Kuan-Yu; Berndt, Sonja I; He, Xingzhou; Wu, Wei; Chang, Jiang; Zhang, Xu-Chao; Huang, Ming-Shyan; Zheng, Hong; Wang, Junwen; Zhao, Xueying; Li, Yuqing; Choi, Jin Eun; Su, Wu-Chou; Park, Kyong Hwa; Sung, Sook Whan; Shu, Xiao-Ou; Chen, Yuh-Min; Liu, Li; Kang, Chang Hyun; Hu, Lingmin; Chen, Chung-Hsing; Pao, William; Kim, Young-Chul; Yang, Tsung-Ying; Xu, Jun; Guan, Peng; Tan, Wen; Su, Jian; Wang, Chih-Liang; Li, Haixin; Sihoe, Alan Dart Loon; Zhao, Zhenhong; Chen, Ying; Choi, Yi Young; Hung, Jen-Yu; Kim, Jun Suk; Yoon, Ho-Il; Cai, Qiuyin; Lin, Chien-Chung; Park, In Kyu; Xu, Ping; Dong, Jing; Kim, Christopher; He, Qincheng; Perng, Reury-Perng; Kohno, Takashi; Kweon, Sun-Seog; Chen, Chih-Yi; Vermeulen, Roel; Wu, Junjie; Lim, Wei-Yen; Chen, Kun-Chieh; Chow, Wong-Ho; Ji, Bu-Tian; Chan, John K C; Chu, Minjie; Li1, Yao-Jen; Yokota, Jun; Li, Jihua; Chen, Hongyan; Xiang, Yong-Bing; Yu, Chong-Jen; Kunitoh, Hideo; Wu, Guoping; Jin, Li; Lo, Yen-Li; Shiraishi, Kouya; Chen, Ying-Hsiang; Lin, Hsien-Chih; Wu, Tangchun; Wu, Yi-Long; Yang, Pan-Chyr; Zhou, Baosen; Shin, Min-Ho; Fraumeni, Joseph F; Lin, Dongxin; Chanock, Stephen J; Rothman, Nathaniel

    2014-01-01

    To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland China, South Korea, Japan, Singapore, Taiwan, and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10-6) in an additional 1,099 cases and 2,913 controls. We identified three new susceptibility loci at 10q25.2 (rs7086803, P = 3.54 × 10-18), 6q22.2 (rs9387478, P = 4.14 × 10-10) and 6p21.32 (rs2395185, P = 9.51 × 10-9). We also confirmed associations reported for loci at 5p15.33 and 3q28 and a recently reported finding at 17q24.3. We observed no evidence of association for lung cancer at 15q25 in never-smoking women in Asia, providing strong evidence that this locus is not associated with lung cancer independent of smoking. PMID:23143601

  20. Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia.

    Science.gov (United States)

    Lan, Qing; Hsiung, Chao A; Matsuo, Keitaro; Hong, Yun-Chul; Seow, Adeline; Wang, Zhaoming; Hosgood, H Dean; Chen, Kexin; Wang, Jiu-Cun; Chatterjee, Nilanjan; Hu, Wei; Wong, Maria Pik; Zheng, Wei; Caporaso, Neil; Park, Jae Yong; Chen, Chien-Jen; Kim, Yeul Hong; Kim, Young Tae; Landi, Maria Teresa; Shen, Hongbing; Lawrence, Charles; Burdett, Laurie; Yeager, Meredith; Yuenger, Jeffrey; Jacobs, Kevin B; Chang, I-Shou; Mitsudomi, Tetsuya; Kim, Hee Nam; Chang, Gee-Chen; Bassig, Bryan A; Tucker, Margaret; Wei, Fusheng; Yin, Zhihua; Wu, Chen; An, She-Juan; Qian, Biyun; Lee, Victor Ho Fun; Lu, Daru; Liu, Jianjun; Jeon, Hyo-Sung; Hsiao, Chin-Fu; Sung, Jae Sook; Kim, Jin Hee; Gao, Yu-Tang; Tsai, Ying-Huang; Jung, Yoo Jin; Guo, Huan; Hu, Zhibin; Hutchinson, Amy; Wang, Wen-Chang; Klein, Robert; Chung, Charles C; Oh, In-Jae; Chen, Kuan-Yu; Berndt, Sonja I; He, Xingzhou; Wu, Wei; Chang, Jiang; Zhang, Xu-Chao; Huang, Ming-Shyan; Zheng, Hong; Wang, Junwen; Zhao, Xueying; Li, Yuqing; Choi, Jin Eun; Su, Wu-Chou; Park, Kyong Hwa; Sung, Sook Whan; Shu, Xiao-Ou; Chen, Yuh-Min; Liu, Li; Kang, Chang Hyun; Hu, Lingmin; Chen, Chung-Hsing; Pao, William; Kim, Young-Chul; Yang, Tsung-Ying; Xu, Jun; Guan, Peng; Tan, Wen; Su, Jian; Wang, Chih-Liang; Li, Haixin; Sihoe, Alan Dart Loon; Zhao, Zhenhong; Chen, Ying; Choi, Yi Young; Hung, Jen-Yu; Kim, Jun Suk; Yoon, Ho-Il; Cai, Qiuyin; Lin, Chien-Chung; Park, In Kyu; Xu, Ping; Dong, Jing; Kim, Christopher; He, Qincheng; Perng, Reury-Perng; Kohno, Takashi; Kweon, Sun-Seog; Chen, Chih-Yi; Vermeulen, Roel; Wu, Junjie; Lim, Wei-Yen; Chen, Kun-Chieh; Chow, Wong-Ho; Ji, Bu-Tian; Chan, John K C; Chu, Minjie; Li, Yao-Jen; Yokota, Jun; Li, Jihua; Chen, Hongyan; Xiang, Yong-Bing; Yu, Chong-Jen; Kunitoh, Hideo; Wu, Guoping; Jin, Li; Lo, Yen-Li; Shiraishi, Kouya; Chen, Ying-Hsiang; Lin, Hsien-Chih; Wu, Tangchun; Wu, Yi-Long; Yang, Pan-Chyr; Zhou, Baosen; Shin, Min-Ho; Fraumeni, Joseph F; Lin, Dongxin; Chanock, Stephen J; Rothman, Nathaniel

    2012-12-01

    To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland China, South Korea, Japan, Singapore, Taiwan and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10(-6)) in an additional 1,099 cases and 2,913 controls. We identified three new susceptibility loci at 10q25.2 (rs7086803, P = 3.54 × 10(-18)), 6q22.2 (rs9387478, P = 4.14 × 10(-10)) and 6p21.32 (rs2395185, P = 9.51 × 10(-9)). We also confirmed associations reported for loci at 5p15.33 and 3q28 and a recently reported finding at 17q24.3. We observed no evidence of association for lung cancer at 15q25 in never-smoking women in Asia, providing strong evidence that this locus is not associated with lung cancer independent of smoking. PMID:23143601