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Sample records for cancer signature identified

  1. Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

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    Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.

    2016-01-01

    Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680

  2. A basal stem cell signature identifies aggressive prostate cancer phenotypes

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    Smith, Bryan A.; Sokolov, Artem; Uzunangelov, Vladislav; Baertsch, Robert; Newton, Yulia; Graim, Kiley; Mathis, Colleen; Cheng, Donghui; Stuart, Joshua M.; Witte, Owen N.

    2015-01-01

    Evidence from numerous cancers suggests that increased aggressiveness is accompanied by up-regulation of signaling pathways and acquisition of properties common to stem cells. It is unclear if different subtypes of late-stage cancer vary in stemness properties and whether or not these subtypes are transcriptionally similar to normal tissue stem cells. We report a gene signature specific for human prostate basal cells that is differentially enriched in various phenotypes of late-stage metastatic prostate cancer. We FACS-purified and transcriptionally profiled basal and luminal epithelial populations from the benign and cancerous regions of primary human prostates. High-throughput RNA sequencing showed the basal population to be defined by genes associated with stem cell signaling programs and invasiveness. Application of a 91-gene basal signature to gene expression datasets from patients with organ-confined or hormone-refractory metastatic prostate cancer revealed that metastatic small cell neuroendocrine carcinoma was molecularly more stem-like than either metastatic adenocarcinoma or organ-confined adenocarcinoma. Bioinformatic analysis of the basal cell and two human small cell gene signatures identified a set of E2F target genes common between prostate small cell neuroendocrine carcinoma and primary prostate basal cells. Taken together, our data suggest that aggressive prostate cancer shares a conserved transcriptional program with normal adult prostate basal stem cells. PMID:26460041

  3. Ensemble of gene signatures identifies novel biomarkers in colorectal cancer activated through PPARγ and TNFα signaling.

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    Stefano Maria Pagnotta

    Full Text Available We describe a novel bioinformatic and translational pathology approach, gene Signature Finder Algorithm (gSFA to identify biomarkers associated with Colorectal Cancer (CRC survival. Here a robust set of CRC markers is selected by an ensemble method. By using a dataset of 232 gene expression profiles, gSFA discovers 16 highly significant small gene signatures. Analysis of dichotomies generated by the signatures results in a set of 133 samples stably classified in good prognosis group and 56 samples in poor prognosis group, whereas 43 remain unreliably classified. AKAP12, DCBLD2, NT5E and SPON1 are particularly represented in the signatures and selected for validation in vivo on two independent patients cohorts comprising 140 tumor tissues and 60 matched normal tissues. Their expression and regulatory programs are investigated in vitro. We show that the coupled expression of NT5E and DCBLD2 robustly stratifies our patients in two groups (one of which with 100% survival at five years. We show that NT5E is a target of the TNF-α signaling in vitro; the tumor suppressor PPARγ acts as a novel NT5E antagonist that positively and concomitantly regulates DCBLD2 in a cancer cell context-dependent manner.

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

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    Sofie Claerhout

    Full Text Available 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.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.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. Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer

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    Choi, Woonyoung; Park, Yun-Yong; Kim, KyoungHyun; Kim, Sang-Bae; Lee, Ju-Seog; Mills, Gordon B.; Cho, Jae Yong

    2011-01-01

    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. PMID:21931799

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

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    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

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

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    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

  8. Expression profiling of cervical cancers in Indian women at different stages to identify gene signatures during progression of the disease

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    Thomas, Asha; Mahantshetty, Umesh; Kannan, Sadhana; Deodhar, Kedar; Shrivastava, Shyam K; Kumar-Sinha, Chandan; Mulherkar, Rita

    2013-01-01

    Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from Indian women, spanning International Federation of Gynaecology and Obstetrics (FIGO) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA–B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine–cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP1, proliferating cell nuclear antigen (PCNA), STK17A, and DUSP1 among others that were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression

  9. An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

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    Liang Yu

    2008-12-01

    Full Text Available Abstract Background Patients diagnosed with lung adenocarcinoma (AD and squamous cell carcinoma (SCC, two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy. Methods MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays. Results Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively. Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette

  10. 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

    2013-04-05

    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. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

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    Li He

    2014-01-01

    Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

  12. Utilization of genomic signatures to identify phenotype-specific drugs.

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    Seiichi Mori

    2009-08-01

    Full Text Available Genetic and genomic studies highlight the substantial complexity and heterogeneity of human cancers and emphasize the general lack of therapeutics that can match this complexity. With the goal of expanding opportunities for drug discovery, we describe an approach that makes use of a phenotype-based screen combined with the use of multiple cancer cell lines. In particular, we have used the NCI-60 cancer cell line panel that includes drug sensitivity measures for over 40,000 compounds assayed on 59 independent cells lines. Targets are cancer-relevant phenotypes represented as gene expression signatures that are used to identify cells within the NCI-60 panel reflecting the signature phenotype and then connect to compounds that are selectively active against those cells. As a proof-of-concept, we show that this strategy effectively identifies compounds with selectivity to the RAS or PI3K pathways. We have then extended this strategy to identify compounds that have activity towards cells exhibiting the basal phenotype of breast cancer, a clinically-important breast cancer characterized as ER-, PR-, and Her2- that lacks viable therapeutic options. One of these compounds, Simvastatin, has previously been shown to inhibit breast cancer cell growth in vitro and importantly, has been associated with a reduction in ER-, PR- breast cancer in a clinical study. We suggest that this approach provides a novel strategy towards identification of therapeutic agents based on clinically relevant phenotypes that can augment the conventional strategies of target-based screens.

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

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    Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

    2014-01-01

    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. 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. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  14. 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 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.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.Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

  15. Real time gamma-ray signature identifier

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    Rowland, Mark [Alamo, CA; Gosnell, Tom B [Moraga, CA; Ham, Cheryl [Livermore, CA; Perkins, Dwight [Livermore, CA; Wong, James [Dublin, CA

    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.

  16. N-glycan signatures identified in tumor interstitial fluid and serum of breast cancer patients - association with tumor biology and clinical outcome.

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    Terkelsen, Thilde; Haakensen, Vilde D; Saldova, Radka; Gromov, Pavel; Hansen, Merete Kjaer; Stöckmann, Henning; Lingjaerde, Ole Christian; Børresen-Dale, Anne-Lise; Papaleo, Elena; Helland, Åslaug; Rudd, Pauline M; Gromova, Irina

    2018-04-26

    Particular N-glycan structures are known to be associated with breast malignancies by coordinating various regulatory events within the tumor and corresponding microenvironment, thus implying that N-glycan patterns may be used for cancer stratification and as predictive or prognostic biomarkers. However, the association between N-glycans secreted by breast tumor and corresponding clinical relevance remain to be elucidated. We profiled N-glycans by HILIC UPLC across a discovery dataset composed of tumor interstitial fluids (TIF, n=85), paired normal interstitial fluids (NIF, n=54) and serum samples (n=28) followed by independent evaluation, with the ultimate goal of identifying tumor-related N-glycan patterns in blood of breast cancer patients. The segregation of N-linked oligosaccharides revealed 33 compositions, which exhibited differential abundances between TIF and NIF. TIFs were depleted of bisecting N-glycans, which are known to play essential roles in tumor suppression. An increased level of simple high mannose N-glycans in TIF strongly correlated with the presence of tumor infiltrating lymphocytes within tumor. At the same time, a low level of highly complex N-glycans in TIF inversely correlated with the presence of infiltrating lymphocytes within tumor. Survival analysis showed that patients exhibiting increased TIF abundance of GP24 had better outcomes, whereas low levels of GP10, GP23, GP38, and coreF were associated with poor prognosis. Levels of GP1, GP8, GP9, GP14, GP23, GP28, GP37, GP38, and coreF were significantly correlated between TIF and paired serum samples. Cross-validation analysis using an independent serum dataset supported the observed correlation between TIF and serum, for five out of nine N-glycan groups: GP8, GP9, GP14, GP23, and coreF. Collectively, our results imply that profiling of N-glycans from proximal breast tumor fluids is a promising strategy for determining tumor-derived glyco-signature(s) in the blood. N-glycans structures

  17. 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.

  18. Signatures of mutational processes in human cancer

    NARCIS (Netherlands)

    Alexandrov, L.B.; Nik-Zainal, S.; Wedge, D.C.; Aparicio, S.A.; Behjati, S.; Biankin, A.V.; Bignell, G.R.; Bolli, N.; Borg, A.; Borresen-Dale, A.L.; Boyault, S.; Burkhardt, B.; Butler, A.P.; Caldas, C.; Davies, H.R.; Desmedt, C.; Eils, R.; Eyfjord, J.E.; Foekens, J.A.; Greaves, M.; Hosoda, F.; Hutter, B.; Ilicic, T.; Imbeaud, S.; Imielinsk, M.; Jager, N.; Jones, D.T.; Knappskog, S.; Kool, M.; Lakhani, S.R.; Lopez-Otin, C.; Martin, S.; Munshi, N.C.; Nakamura, H.; Northcott, P.A.; Pajic, M.; Papaemmanuil, E.; Paradiso, A.; Pearson, J.V.; Puente, X.S.; Raine, K.; Ramakrishna, M.; Richardson, A.L.; Richter, J.; Rosenstiel, P.; Schlesner, M.; Schumacher, T.N.; Span, P.N.; Teague, J.W.; Totoki, Y.; Tutt, A.N.; Valdes-Mas, R.; Buuren, M.M. van; Veer, L. van 't; Vincent-Salomon, A.; Waddell, N.; Yates, L.R.; Zucman-Rossi, J.; Futreal, P.A.; McDermott, U.; Lichter, P.; Meyerson, M.; Grimmond, S.M.; Siebert, R.; Campo, E.; Shibata, T.; Pfister, S.M.; Campbell, P.J.; Stratton, M.R.; Schlooz-Vries, M.S.; Tol, J.J. van; Laarhoven, H.W. van; Sweep, F.C.; Bult, P.; et al.,

    2013-01-01

    All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362

  19. Protein signature of lung cancer tissues.

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    Michael R Mehan

    Full Text Available Lung cancer remains the most common cause of cancer-related mortality. We applied a highly multiplexed proteomic technology (SOMAscan to compare protein expression signatures of non small-cell lung cancer (NSCLC tissues with healthy adjacent and distant tissues from surgical resections. In this first report of SOMAscan applied to tissues, we highlight 36 proteins that exhibit the largest expression differences between matched tumor and non-tumor tissues. The concentrations of twenty proteins increased and sixteen decreased in tumor tissue, thirteen of which are novel for NSCLC. NSCLC tissue biomarkers identified here overlap with a core set identified in a large serum-based NSCLC study with SOMAscan. We show that large-scale comparative analysis of protein expression can be used to develop novel histochemical probes. As expected, relative differences in protein expression are greater in tissues than in serum. The combined results from tissue and serum present the most extensive view to date of the complex changes in NSCLC protein expression and provide important implications for diagnosis and treatment.

  20. Identifying Breast Cancer Oncogenes

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    2011-10-01

    cells we observed that it promoted transformation of HMLE cells, suggesting a tumor suppressive role of Merlin in breast cancer (Figure 4B). A...08-1-0767 TITLE: Identifying Breast Cancer Oncogenes PRINCIPAL INVESTIGATOR: Yashaswi Shrestha...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 W81XWH-08-1-0767 Identifying Breast Cancer Oncogenes Yashaswi Shrestha Dana-Farber

  1. HPV status, cancer stem cell marker expression, hypoxia gene signatures and tumour volume identify good prognosis subgroups in patients with HNSCC after primary radiochemotherapy: A multicentre retrospective study of the German Cancer Consortium Radiation Oncology Group (DKTK-ROG)

    DEFF Research Database (Denmark)

    Linge, Annett; Lohaus, Fabian; Löck, Steffen

    2016-01-01

    OBJECTIVE: To investigate the impact of the tumour volume, HPV status, cancer stem cell (CSC) marker expression and hypoxia gene signatures, as potential markers of radiobiological mechanisms of radioresistance, in a contemporary cohort of patients with locally advanced head and neck squamous cell...

  2. Can specific transcriptional regulators assemble a universal cancer signature?

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    Roy, Janine; Isik, Zerrin; Pilarsky, Christian; Schroeder, Michael

    2013-10-01

    Recently, there is a lot of interest in using biomarker signatures derived from gene expression data to predict cancer progression. We assembled signatures of 25 published datasets covering 13 types of cancers. How do these signatures compare with each other? On one hand signatures answering the same biological question should overlap, whereas signatures predicting different cancer types should differ. On the other hand, there could also be a Universal Cancer Signature that is predictive independently of the cancer type. Initially, we generate signatures for all datasets using classical approaches such as t-test and fold change and then, we explore signatures resulting from a network-based method, that applies the random surfer model of Google's PageRank algorithm. We show that the signatures as published by the authors and the signatures generated with classical methods do not overlap - not even for the same cancer type - whereas the network-based signatures strongly overlap. Selecting 10 out of 37 universal cancer genes gives the optimal prediction for all cancers thus taking a first step towards a Universal Cancer Signature. We furthermore analyze and discuss the involved genes in terms of the Hallmarks of cancer and in particular single out SP1, JUN/FOS and NFKB1 and examine their specific role in cancer progression.

  3. 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.

  4. Identification of miRNA Signatures Associated with Epithelial Ovarian Cancer Chemoresistance with Further Biological and Functional Validation of Identified Key miRNAS

    Science.gov (United States)

    2016-04-01

    chemoresistant cancer cells can sensitize chemoresistant ovarian tumors to cisplatin treatment and inhibit ovarian cancer dissemination in a pre...determine the mechanism by which miR-181a was regulating the emergence of these CICs. What opportunities for training and professional development has...also perform data analysis to correlate those miRNAs expression with patient response to cisplatin and other clinicopathological parameters. She

  5. Identification of miRNA Signatures Associated with Epithelial Ovarian Cancer Chemoresistance with Further Biological and Functional Validation of Identified Key miRNAs

    Science.gov (United States)

    2012-08-01

    separated on 12% SDS PAGE gels and transferred to nitrocellulose membranes. After blocking with 5% non- fat milk (Labscientific, Inc) in TBS-Tween buffer... Raw mass spectrometric data were processed and analyzed for variations in the spectral counts of peptides between sample sets and bioinformatics was...accomplished using Ingenuity Pathways Analysis (IPA). Results: The total numbers of proteins and peptides identified are listed in the table

  6. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    Science.gov (United States)

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    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 prediction of breast

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

    Directory of Open Access Journals (Sweden)

    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

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

    Science.gov (United States)

    2011-01-01

    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 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. PMID:21492432

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

    Directory of Open Access Journals (Sweden)

    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.

  10. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Ning Ye

    2015-01-01

    Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  11. 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.

  12. A genomic copy number signature predicts radiation exposure in post-Chernobyl breast cancer.

    Science.gov (United States)

    Wilke, Christina M; Braselmann, Herbert; Hess, Julia; Klymenko, Sergiy V; Chumak, Vadim V; Zakhartseva, Liubov M; Bakhanova, Elena V; Walch, Axel K; Selmansberger, Martin; Samaga, Daniel; Weber, Peter; Schneider, Ludmila; Fend, Falko; Bösmüller, Hans C; Zitzelsberger, Horst; Unger, Kristian

    2018-04-16

    Breast cancer is the second leading cause of cancer death among women worldwide and besides life style, age and genetic risk factors, exposure to ionizing radiation is known to increase the risk for breast cancer. Further, DNA copy number alterations (CNAs), which can result from radiation-induced double-strand breaks, are frequently occurring in breast cancer cells. We set out to identify a signature of CNAs discriminating breast cancers from radiation-exposed and non-exposed female patients. We analyzed resected breast cancer tissues from 68 exposed female Chernobyl clean-up workers and evacuees and 68 matched non-exposed control patients for CNAs by array comparative genomic hybridization analysis (aCGH). Using a stepwise forward-backward selection approach a non-complex CNA signature, that is, less than ten features, was identified in the training data set, which could be subsequently validated in the validation data set (p value < 0.05). The signature consisted of nine copy number regions located on chromosomal bands 7q11.22-11.23, 7q21.3, 16q24.3, 17q21.31, 20p11.23-11.21, 1p21.1, 2q35, 2q35, 6p22.2. The signature was independent of any clinical characteristics of the patients. In all, we identified a CNA signature that has the potential to allow identification of radiation-associated breast cancer at the individual level. © 2018 UICC.

  13. Identifying Breast Cancer Oncogenes

    Science.gov (United States)

    2010-10-01

    tyrosine kinases with an SH3, SH2 and catalytic domain, it lacks a native myristylation signal shared by most members of this class [14], [38]. The...therapeutics and consequently, improve clinical outcomes. We aim to identify novel drivers of breast oncogenesis. We hypothesize that a kinase gain-of...human mammary epithelial cells. A pBabe-Puro-Myr-Flag kinase open reading frame (ORF) library was screened in immortalized human mammary epithelial

  14. Signature of genetic associations in oral cancer.

    Science.gov (United States)

    Sharma, Vishwas; Nandan, Amrita; Sharma, Amitesh Kumar; Singh, Harpreet; Bharadwaj, Mausumi; Sinha, Dhirendra Narain; Mehrotra, Ravi

    2017-10-01

    Oral cancer etiology is complex and controlled by multi-factorial events including genetic events. Candidate gene studies, genome-wide association studies, and next-generation sequencing identified various chromosomal loci to be associated with oral cancer. There is no available review that could give us the comprehensive picture of genetic loci identified to be associated with oral cancer by candidate gene studies-based, genome-wide association studies-based, and next-generation sequencing-based approaches. A systematic literature search was performed in the PubMed database to identify the loci associated with oral cancer by exclusive candidate gene studies-based, genome-wide association studies-based, and next-generation sequencing-based study approaches. The information of loci associated with oral cancer is made online through the resource "ORNATE." Next, screening of the loci validated by candidate gene studies and next-generation sequencing approach or by two independent studies within candidate gene studies or next-generation sequencing approaches were performed. A total of 264 loci were identified to be associated with oral cancer by candidate gene studies, genome-wide association studies, and next-generation sequencing approaches. In total, 28 loci, that is, 14q32.33 (AKT1), 5q22.2 (APC), 11q22.3 (ATM), 2q33.1 (CASP8), 11q13.3 (CCND1), 16q22.1 (CDH1), 9p21.3 (CDKN2A), 1q31.1 (COX-2), 7p11.2 (EGFR), 22q13.2 (EP300), 4q35.2 (FAT1), 4q31.3 (FBXW7), 4p16.3 (FGFR3), 1p13.3 (GSTM1-GSTT1), 11q13.2 (GSTP1), 11p15.5 (H-RAS), 3p25.3 (hOGG1), 1q32.1 (IL-10), 4q13.3 (IL-8), 12p12.1 (KRAS), 12q15 (MDM2), 12q13.12 (MLL2), 9q34.3 (NOTCH1), 17p13.1 (p53), 3q26.32 (PIK3CA), 10q23.31 (PTEN), 13q14.2 (RB1), and 5q14.2 (XRCC4), were validated to be associated with oral cancer. "ORNATE" gives a snapshot of genetic loci associated with oral cancer. All 28 loci were validated to be linked to oral cancer for which further fine-mapping followed by gene-by-gene and gene

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

    DEFF Research Database (Denmark)

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

    2005-01-01

    The majority of microsatellite instable (MSI) colorectal cancers are sporadic, but a subset belongs to the syndrome hereditary non-polyposis colorectal cancer (HNPCC). Microsatellite instability is caused by dysfunction of the mismatch repair (MMR) system that leads to a mutator phenotype, and MSI...... of 101 stage II and III colorectal cancers (34 MSI, 67 microsatellite stable (MSS)) using high-density oligonucleotide microarrays. From these data, we constructed a nine-gene signature capable of separating the mismatch repair proficient and deficient tumours. Subsequently, we demonstrated...... 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...

  16. lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis

    Directory of Open Access Journals (Sweden)

    Silu Zhang

    2018-01-01

    Full Text Available Background: Breast cancer is intrinsically heterogeneous and is commonly classified into four main subtypes associated with distinct biological features and clinical outcomes. However, currently available data resources and methods are limited in identifying molecular subtyping on protein-coding genes, and little is known about the roles of long non-coding RNAs (lncRNAs, which occupies 98% of the whole genome. lncRNAs may also play important roles in subgrouping cancer patients and are associated with clinical phenotypes. Methods: The purpose of this project was to identify lncRNA gene signatures that are associated with breast cancer subtypes and clinical outcomes. We identified lncRNA gene signatures from The Cancer Genome Atlas (TCGA RNAseq data that are associated with breast cancer subtypes by an optimized 1-Norm SVM feature selection algorithm. We evaluated the prognostic performance of these gene signatures with a semi-supervised principal component (superPC method. Results: Although lncRNAs can independently predict breast cancer subtypes with satisfactory accuracy, a combined gene signature including both coding and non-coding genes will give the best clinically relevant prediction performance. We highlighted eight potential biomarkers (three from coding genes and five from non-coding genes that are significantly associated with survival outcomes. Conclusion: Our proposed methods are a novel means of identifying subtype-specific coding and non-coding potential biomarkers that are both clinically relevant and biologically significant.

  17. A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.

    Science.gov (United States)

    Lee, Unjin; Frankenberger, Casey; Yun, Jieun; Bevilacqua, Elena; Caldas, Carlos; Chin, Suet-Feung; Rueda, Oscar M; Reinitz, John; Rosner, Marsha Rich

    2013-01-01

    Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.

  18. *K-means and Cluster Models for Cancer Signatures

    OpenAIRE

    Kakushadze, Zura; Yu, Willie

    2017-01-01

    We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means’ computational cost is a fraction of NMF’s. Using 1389 published samples for 14 cancer types, we find that 3 cancer...

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

    International Nuclear Information System (INIS)

    Anastassiou, Dimitris; Rumjantseva, Viktoria; Cheng, Weiyi; Huang, Jianzhong; Canoll, Peter D; Yamashiro, Darrell J; Kandel, Jessica J

    2011-01-01

    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). 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. 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. 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

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

    International Nuclear Information System (INIS)

    Yu, Jack X; Sieuwerts, Anieta M; Zhang, Yi; Martens, John WM; Smid, Marcel; Klijn, Jan GM; Wang, Yixin; Foekens, John A

    2007-01-01

    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

  1. Validation of a radiosensitivity molecular signature in breast cancer

    NARCIS (Netherlands)

    S.A. Eschrich (Steven); C. Fulp (Carl); Y. Pawitan (Yudi); J.A. Foekens (John); M. Smid (Marcel); J.W.M. Martens (John); M. Echevarria (Michelle); P.S. Kamath (Patrick); J.-H. Lee (Ji-Hyun); E.E. Harris (Eleanor); J. Bergh (Jonas); J.F. Torres-Roca (Javier)

    2012-01-01

    textabstractPurpose: Previously, we developed a radiosensitivity molecular signature [radiosensitivity index (RSI)] that was clinically validated in 3 independent datasets (rectal, esophageal, and head and neck) in 118 patients. Here, we test RSI in radiotherapy (RT)-treated breast cancer patients.

  2. DNA methylation–based immune response signature improves patient diagnosis in multiple cancers

    Science.gov (United States)

    Jeschke, Jana; Bizet, Martin; Calonne, Emilie; Dedeurwaerder, Sarah; Garaud, Soizic; Koch, Alexander; Larsimont, Denis; Salgado, Roberto; Van den Eynden, Gert; Willard Gallo, Karen; Defrance, Matthieu; Sotiriou, Christos

    2017-01-01

    BACKGROUND. The tumor immune response is increasingly associated with better clinical outcomes in breast and other cancers. However, the evaluation of tumor-infiltrating lymphocytes (TILs) relies on histopathological measurements with limited accuracy and reproducibility. Here, we profiled DNA methylation markers to identify a methylation of TIL (MeTIL) signature that recapitulates TIL evaluations and their prognostic value for long-term outcomes in breast cancer (BC). METHODS. MeTIL signature scores were correlated with clinical endpoints reflecting overall or disease-free survival and a pathologic complete response to preoperative anthracycline therapy in 3 BC cohorts from the Jules Bordet Institute in Brussels and in other cancer types from The Cancer Genome Atlas. RESULTS. The MeTIL signature measured TIL distributions in a sensitive manner and predicted survival and response to chemotherapy in BC better than did histopathological assessment of TILs or gene expression–based immune markers, respectively. The MeTIL signature also improved the prediction of survival in other malignancies, including melanoma and lung cancer. Furthermore, the MeTIL signature predicted differences in survival for malignancies in which TILs were not known to have a prognostic value. Finally, we showed that MeTIL markers can be determined by bisulfite pyrosequencing of small amounts of DNA from formalin-fixed, paraffin-embedded tumor tissue, supporting clinical applications for this methodology. CONCLUSIONS. This study highlights the power of DNA methylation to evaluate tumor immune responses and the potential of this approach to improve the diagnosis and treatment of breast and other cancers. FUNDING. This work was funded by the Fonds National de la Recherche Scientifique (FNRS) and Télévie, the INNOVIRIS Brussels Region BRUBREAST Project, the IUAP P7/03 program, the Belgian “Foundation against Cancer,” the Breast Cancer Research Foundation (BCRF), and the Fonds Gaston Ithier

  3. Identifying developmental vascular disruptor compounds using a predictive signature and alternative toxicity models

    Science.gov (United States)

    Identifying Developmental Vascular Disruptor Compounds Using a Predictive Signature and Alternative Toxicity Models Presenting Author: Tamara Tal Affiliation: U.S. EPA/ORD/ISTD, RTP, NC, USA Chemically induced vascular toxicity during embryonic development can result in a wide...

  4. *K-means and cluster models for cancer signatures.

    Science.gov (United States)

    Kakushadze, Zura; Yu, Willie

    2017-09-01

    We present *K-means clustering algorithm and source code by expanding statistical clustering methods applied in https://ssrn.com/abstract=2802753 to quantitative finance. *K-means is statistically deterministic without specifying initial centers, etc. We apply *K-means to extracting cancer signatures from genome data without using nonnegative matrix factorization (NMF). *K-means' computational cost is a fraction of NMF's. Using 1389 published samples for 14 cancer types, we find that 3 cancers (liver cancer, lung cancer and renal cell carcinoma) stand out and do not have cluster-like structures. Two clusters have especially high within-cluster correlations with 11 other cancers indicating common underlying structures. Our approach opens a novel avenue for studying such structures. *K-means is universal and can be applied in other fields. We discuss some potential applications in quantitative finance.

  5. 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.

  6. 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.

  7. Toward a comprehensive and systematic methylome signature in colorectal cancers

    OpenAIRE

    Ashktorab, Hassan; Rahi, Hamed; Wansley, Daniel; Varma, Sudhir; Shokrani, Babak; Lee, Edward; Daremipouran, Mohammad; Laiyemo, Adeyinka; Goel, Ajay; Carethers, John M; Brim, Hassan

    2013-01-01

    CpG Island Methylator Phenotype (CIMP) is one of the underlying mechanisms in colorectal cancer (CRC). This study aimed to define a methylome signature in CRC through a methylation microarray analysis and a compilation of promising CIMP markers from the literature. Illumina HumanMethylation27 (IHM27) array data was generated and analyzed based on statistical differences in methylation data (1st approach) or based on overall differences in methylation percentages using lower 95% CI (2nd approa...

  8. A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.

    Directory of Open Access Journals (Sweden)

    Unjin Lee

    Full Text Available Although triple negative breast cancers (TNBC are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS, based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP. We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.

  9. Toward a comprehensive and systematic methylome signature in colorectal cancers.

    Science.gov (United States)

    Ashktorab, Hassan; Rahi, Hamed; Wansley, Daniel; Varma, Sudhir; Shokrani, Babak; Lee, Edward; Daremipouran, Mohammad; Laiyemo, Adeyinka; Goel, Ajay; Carethers, John M; Brim, Hassan

    2013-08-01

    CpG Island Methylator Phenotype (CIMP) is one of the underlying mechanisms in colorectal cancer (CRC). This study aimed to define a methylome signature in CRC through a methylation microarray analysis and a compilation of promising CIMP markers from the literature. Illumina HumanMethylation27 (IHM27) array data was generated and analyzed based on statistical differences in methylation data (1st approach) or based on overall differences in methylation percentages using lower 95% CI (2nd approach). Pyrosequencing was performed for the validation of nine genes. A meta-analysis was used to identify CIMP and non-CIMP markers that were hypermethylated in CRC but did not yet make it to the CIMP genes' list. Our 1st approach for array data analysis demonstrated the limitations in selecting genes for further validation, highlighting the need for the 2nd bioinformatics approach to adequately select genes with differential aberrant methylation. A more comprehensive list, which included non-CIMP genes, such as APC, EVL, CD109, PTEN, TWIST1, DCC, PTPRD, SFRP1, ICAM5, RASSF1A, EYA4, 30ST2, LAMA1, KCNQ5, ADHEF1, and TFPI2, was established. Array data are useful to categorize and cluster colonic lesions based on their global methylation profiles; however, its usefulness in identifying robust methylation markers is limited and rely on the data analysis method. We have identified 16 non-CIMP-panel genes for which we provide rationale for inclusion in a more comprehensive characterization of CIMP+ CRCs. The identification of a definitive list for methylome specific genes in CRC will contribute to better clinical management of CRC patients.

  10. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

    Science.gov (United States)

    Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2014-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544

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

    International Nuclear Information System (INIS)

    Starmans, Maud H.W.; Chu, Kenneth C.; Haider, Syed; Nguyen, Francis; Seigneuric, Renaud; Magagnin, Michael G.; Koritzinsky, Marianne; Kasprzyk, Arek; Boutros, Paul C.; Wouters, Bradly G.

    2012-01-01

    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

  12. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

    Science.gov (United States)

    Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-06

    Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

  13. 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

  14. Liver regeneration signature in hepatitis B virus (HBV-associated acute liver failure identified by gene expression profiling.

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    Oriel Nissim

    Full Text Available The liver has inherent regenerative capacity via mitotic division of mature hepatocytes or, when the hepatic loss is massive or hepatocyte proliferation is impaired, through activation of hepatic stem/progenitor cells (HSPC. The dramatic clinical course of acute liver failure (ALF has posed major limitations to investigating the molecular mechanisms of liver regeneration and the role of HSPC in this setting. We investigated the molecular mechanisms of liver regeneration in 4 patients who underwent liver transplantation for hepatitis B virus (HBV-associated ALF.Gene expression profiling of 17 liver specimens from the 4 ALF cases and individual specimens from 10 liver donors documented a distinct gene signature for ALF. However, unsupervised multidimensional scaling and hierarchical clustering identified two clusters of ALF that segregated according to histopathological severity massive hepatic necrosis (MHN; 2 patients and submassive hepatic necrosis (SHN; 2 patients. We found that ALF is characterized by a strong HSPC gene signature, along with ductular reaction, both of which are more prominent in MHN. Interestingly, no evidence of further lineage differentiation was seen in MHN, whereas in SHN we detected cells with hepatocyte-like morphology. Strikingly, ALF was associated with a strong tumorigenesis gene signature. MHN had the greatest upregulation of stem cell genes (EpCAM, CK19, CK7, whereas the most up-regulated genes in SHN were related to cellular growth and proliferation. The extent of liver necrosis correlated with an overriding fibrogenesis gene signature, reflecting the wound-healing process.Our data provide evidence for a distinct gene signature in HBV-associated ALF whose intensity is directly correlated with the histopathological severity. HSPC activation and fibrogenesis positively correlated with the extent of liver necrosis. Moreover, we detected a tumorigenesis gene signature in ALF, emphasizing the close relationship between

  15. Autoantibody signatures as biomarkers to distinguish prostate cancer from benign prostatic hyperplasia in patients with increased serum prostate specific antigen.

    Science.gov (United States)

    O'Rourke, Dennis J; DiJohnson, Daniel A; Caiazzo, Robert J; Nelson, James C; Ure, David; O'Leary, Michael P; Richie, Jerome P; Liu, Brian C-S

    2012-03-22

    Serum prostate specific antigen (PSA) concentrations lack the specificity to differentiate prostate cancer from benign prostate hyperplasia (BPH), resulting in unnecessary biopsies. We identified 5 autoantibody signatures to specific cancer targets which might be able to differentiate prostate cancer from BPH in patients with increased serum PSA. To identify autoantibody signatures as biomarkers, a native antigen reverse capture microarray platform was used. Briefly, well-characterized monoclonal antibodies were arrayed onto nanoparticle slides to capture native antigens from prostate cancer cells. Prostate cancer patient serum samples (n=41) and BPH patient samples (collected starting at the time of initial diagnosis) with a mean follow-up of 6.56 y without the diagnosis of cancer (n=39) were obtained. One hundred micrograms of IgGs were purified and labeled with a Cy3 dye and incubated on the arrays. The arrays were scanned for fluorescence and the intensity was quantified. Receiver operating characteristic curves were produced and the area under the curve (AUC) was determined. Using our microarray platform, we identified autoantibody signatures capable of distinguishing between prostate cancer and BPH. The top 5 autoantibody signatures were TARDBP, TLN1, PARK7, LEDGF/PSIP1, and CALD1. Combining these signatures resulted in an AUC of 0.95 (sensitivity of 95% at 80% specificity) compared to AUC of 0.5 for serum concentration PSA (sensitivity of 12.2% at 80% specificity). Our preliminary results showed that we were able to identify specific autoantibody signatures that can differentiate prostate cancer from BPH, and may result in the reduction of unnecessary biopsies in patients with increased serum PSA. Copyright © 2011 Elsevier B.V. All rights reserved.

  16. Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

    Science.gov (United States)

    Borrebaeck, Carl A K

    2017-03-01

    Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

  17. Single-gene prognostic signatures for advanced stage serous ovarian cancer based on 1257 patient samples.

    Science.gov (United States)

    Zhang, Fan; Yang, Kai; Deng, Kui; Zhang, Yuanyuan; Zhao, Weiwei; Xu, Huan; Rong, Zhiwei; Li, Kang

    2018-04-16

    We sought to identify stable single-gene prognostic signatures based on a large collection of advanced stage serous ovarian cancer (AS-OvCa) gene expression data and explore their functions. The empirical Bayes (EB) method was used to remove the batch effect and integrate 8 ovarian cancer datasets. Univariate Cox regression was used to evaluate the association between gene and overall survival (OS). The Database for Annotation, Visualization and Integrated Discovery (DAVID) tool was used for the functional annotation of genes for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The batch effect was removed by the EB method, and 1257 patient samples were used for further analysis. We selected 341 single-gene prognostic signatures with FDR matrix organization, focal adhesion and DNA replication which are closely associated with cancer. We used the EB method to remove the batch effect of 8 datasets, integrated these datasets and identified stable prognosis signatures for AS-OvCa.

  18. Radiation Gene-expression Signatures in Primary Breast Cancer Cells.

    Science.gov (United States)

    Minafra, Luigi; Bravatà, Valentina; Cammarata, Francesco P; Russo, Giorgio; Gilardi, Maria C; Forte, Giusi I

    2018-05-01

    In breast cancer (BC) care, radiation therapy (RT) is an efficient treatment to control localized tumor. Radiobiological research is needed to understand molecular differences that affect radiosensitivity of different tumor subtypes and the response variability. The aim of this study was to analyze gene expression profiling (GEP) in primary BC cells following irradiation with doses of 9 Gy and 23 Gy delivered by intraoperative electron radiation therapy (IOERT) in order to define gene signatures of response to high doses of ionizing radiation. We performed GEP by cDNA microarrays and evaluated cell survival after IOERT treatment in primary BC cell cultures. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate candidate genes. We showed, for the first time, a 4-gene and a 6-gene signature, as new molecular biomarkers, in two primary BC cell cultures after exposure at 9 Gy and 23 Gy respectively, for which we observed a significantly high survival rate. Gene signatures activated by different doses of ionizing radiation may predict response to RT and contribute to defining a personalized biological-driven treatment plan. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  19. Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses.

    Science.gov (United States)

    Eng, Christine L P; Tong, Joo Chuan; Tan, Tin Wee

    2016-01-01

    Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.

  20. Polyphenols as Promising Drugs against Main Breast Cancer Signatures

    Directory of Open Access Journals (Sweden)

    María Losada-Echeberría

    2017-11-01

    Full Text Available Breast cancer is one of the most common neoplasms worldwide, and in spite of clinical and pharmacological advances, it is still a clinical problem, causing morbidity and mortality. On the one hand, breast cancer shares with other neoplasms some molecular signatures such as an imbalanced redox state, cell cycle alterations, increased proliferation and an inflammatory status. On the other hand, breast cancer shows differential molecular subtypes that determine its prognosis and treatment. These are characterized mainly by hormone receptors especially estrogen receptors (ERs and epidermal growth factor receptor 2 (HER2. Tumors with none of these receptors are classified as triple negative breast cancer (TNBC and are associated with a worse prognosis. The success of treatments partially depends on their specificity and the adequate molecular classification of tumors. New advances in anticancer drug discovery using natural compounds have been made in the last few decades, and polyphenols have emerged as promising molecules. They may act on various molecular targets because of their promiscuous behavior, presenting several physiological effects, some of which confer antitumor activity. This review analyzes the accumulated evidence of the antitumor effects of plant polyphenols on breast cancer, with special attention to their activity on ERs and HER2 targets and also covering different aspects such as redox balance, uncontrolled proliferation and chronic inflammation.

  1. Polyphenols as Promising Drugs against Main Breast Cancer Signatures

    Science.gov (United States)

    Herranz-López, María; Micol, Vicente

    2017-01-01

    Breast cancer is one of the most common neoplasms worldwide, and in spite of clinical and pharmacological advances, it is still a clinical problem, causing morbidity and mortality. On the one hand, breast cancer shares with other neoplasms some molecular signatures such as an imbalanced redox state, cell cycle alterations, increased proliferation and an inflammatory status. On the other hand, breast cancer shows differential molecular subtypes that determine its prognosis and treatment. These are characterized mainly by hormone receptors especially estrogen receptors (ERs) and epidermal growth factor receptor 2 (HER2). Tumors with none of these receptors are classified as triple negative breast cancer (TNBC) and are associated with a worse prognosis. The success of treatments partially depends on their specificity and the adequate molecular classification of tumors. New advances in anticancer drug discovery using natural compounds have been made in the last few decades, and polyphenols have emerged as promising molecules. They may act on various molecular targets because of their promiscuous behavior, presenting several physiological effects, some of which confer antitumor activity. This review analyzes the accumulated evidence of the antitumor effects of plant polyphenols on breast cancer, with special attention to their activity on ERs and HER2 targets and also covering different aspects such as redox balance, uncontrolled proliferation and chronic inflammation. PMID:29112149

  2. Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.

    Science.gov (United States)

    Cascione, Luciano; Gasparini, Pierluigi; Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M; Shapiro, Charles L; Huebner, Kay

    2013-01-01

    Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

  3. Validation of a Radiosensitivity Molecular Signature in Breast Cancer

    Science.gov (United States)

    Eschrich, Steven A.; Fulp, William J.; Pawitan, Yudi; Foekens, John A.; Smid, Marcel; Martens, John W. M.; Echevarria, Michelle; Kamath, Vidya; Lee, Ji-Hyun; Harris, Eleanor E.; Bergh, Jonas; Torres-Roca, Javier F.

    2014-01-01

    Purpose Previously, we developed a radiosensitivity molecular signature (RSI) that was clinically-validated in three independent datasets (rectal, esophageal, head and neck) in 118 patients. Here, we test RSI in radiotherapy (RT) treated breast cancer patients. Experimental Design RSI was tested in two previously published breast cancer datasets. Patients were treated at the Karolinska University Hospital (n=159) and Erasmus Medical Center (n=344). RSI was applied as previously described. Results We tested RSI in RT-treated patients (Karolinska). Patients predicted to be radiosensitive (RS) had an improved 5 yr relapse-free survival when compared with radioresistant (RR) patients (95% vs. 75%, p=0.0212) but there was no difference between RS/RR patients treated without RT (71% vs. 77%, p=0.6744), consistent with RSI being RT-specific (interaction term RSIxRT, p=0.05). Similarly, in the Erasmus dataset RT-treated RS patients had an improved 5-year distant-metastasis-free survival over RR patients (77% vs. 64%, p=0.0409) but no difference was observed in patients treated without RT (RS vs. RR, 80% vs. 81%, p=0.9425). Multivariable analysis showed RSI is the strongest variable in RT-treated patients (Karolinska, HR=5.53, p=0.0987, Erasmus, HR=1.64, p=0.0758) and in backward selection (removal alpha of 0.10) RSI was the only variable remaining in the final model. Finally, RSI is an independent predictor of outcome in RT-treated ER+ patients (Erasmus, multivariable analysis, HR=2.64, p=0.0085). Conclusions RSI is validated in two independent breast cancer datasets totaling 503 patients. Including prior data, RSI is validated in five independent cohorts (621 patients) and represents, to our knowledge, the most extensively validated molecular signature in radiation oncology. PMID:22832933

  4. The rapamycin-regulated gene expression signature determines prognosis for breast cancer

    Directory of Open Access Journals (Sweden)

    Tsavachidis Spiridon

    2009-09-01

    Full Text Available Abstract Background Mammalian target of rapamycin (mTOR is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes may also be used to simulate a biologic process or effects of a drug treatment. In this study, we tested the hypothesis that the gene-expression signature regulated by rapamycin could predict disease outcome for patients with breast cancer. Results Colony formation and sulforhodamine B (IC50 in vitro and in vivo gene expression data identified a signature, termed rapamycin metagene index (RMI, of 31 genes upregulated by rapamycin treatment in vitro as well as in vivo (false discovery rate of 10%. In the Miller dataset, RMI did not correlate with tumor size or lymph node status. High (>75th percentile RMI was significantly associated with longer survival (P = 0.015. On multivariate analysis, RMI (P = 0.029, tumor size (P = 0.015 and lymph node status (P = 0.001 were prognostic. In van 't Veer study, RMI was not associated with the time to develop distant metastasis (P = 0.41. In the Wang dataset, RMI predicted time to disease relapse (P = 0.009. Conclusion Rapamycin-regulated gene expression signature predicts clinical outcome in breast cancer. This supports the central role of mTOR signaling in breast cancer biology and provides further impetus to pursue mTOR-targeted therapies for breast cancer treatment.

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

    Directory of Open Access Journals (Sweden)

    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

  6. Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival

    NARCIS (Netherlands)

    Chang, Howard Y.; Nuyten, Dimitry S. A.; Sneddon, Julie B.; Hastie, Trevor; Tibshirani, Robert; Sørlie, Therese; Dai, Hongyue; He, Yudong D.; van't Veer, Laura J.; Bartelink, Harry; van de Rijn, Matt; Brown, Patrick O.; van de Vijver, Marc J.

    2005-01-01

    Based on the hypothesis that features of the molecular program of normal wound healing might play an important role in cancer metastasis, we previously identified consistent features in the transcriptional response of normal fibroblasts to serum, and used this "wound-response signature" to reveal

  7. MicroRNA meta-signature of oral cancer: evidence from a meta-analysis.

    Science.gov (United States)

    Zeljic, Katarina; Jovanovic, Ivan; Jovanovic, Jasmina; Magic, Zvonko; Stankovic, Aleksandra; Supic, Gordana

    2018-03-01

    It was the aim of the study to identify commonly deregulated miRNAs in oral cancer patients by performing a meta-analysis of previously published miRNA expression profiles in cancer and matched normal non-cancerous tissue in such patients. Meta-analysis included seven independent studies analyzed by a vote-counting method followed by bioinformatic enrichment analysis. Amongst seven independent studies included in the meta-analysis, 20 miRNAs were found to be deregulated in oral cancer when compared with non-cancerous tissue. Eleven miRNAs were consistently up-regulated in three or more studies (miR-21-5p, miR-31-5p, miR-135b-5p, miR-31-3p, miR-93-5p, miR-34b-5p, miR-424-5p, miR-18a-5p, miR-455-3p, miR-450a-5p, miR-21-3p), and nine were down-regulated (miR-139-5p, miR-30a-3p, miR-376c-3p, miR-885-5p, miR-375, miR-486-5p, miR-411-5p, miR-133a-3p, miR-30a-5p). The meta-signature of identified miRNAs was functionally characterized by KEGG enrichment analysis. Twenty-four KEGG pathways were significantly enriched, and TGF-beta signaling was the most enriched signaling pathway. The highest number of meta-signature miRNAs was involved in the sphingolipid signaling pathway. Natural killer cell-mediated cytotoxicity was the pathway with most genes regulated by identified miRNAs. The rest of the enriched pathways in our miRNA list describe different malignancies and signaling. The identified miRNA meta-signature might be considered as a potential battery of biomarkers when distinguishing oral cancer tissue from normal, non-cancerous tissue. Further mechanistic studies are warranted in order to confirm and fully elucidate the role of deregulated miRNAs in oral cancer.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. MicroRNA Expression Profiling Identifies Molecular Diagnostic Signatures for Anaplastic Large Cell Lymphoma

    DEFF Research Database (Denmark)

    Liu, Cuiling; Iqbal, Javeed; Teruya-Feldstein, Julie

    2013-01-01

    distinct clustering of ALCL, PTCL-NOS, and the AITL subtype of PTCL. Cases of ALK(+) ALCL and ALK(-) ALCL were interspersed in unsupervised analysis, suggesting a close relationship at the molecular level. We identified an miRNA signature of 7 miRNAs (5 upregulated: miR-512-3p, miR-886-5p, miR-886-3p, mi...

  10. 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

    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...

  11. Functional heterogeneity of cancer-associated fibroblasts from human colon tumors shows specific prognostic gene expression signature.

    Science.gov (United States)

    Herrera, Mercedes; Islam, Abul B M M K; Herrera, Alberto; Martín, Paloma; García, Vanesa; Silva, Javier; Garcia, Jose M; Salas, Clara; Casal, Ignacio; de Herreros, Antonio García; Bonilla, Félix; Peña, Cristina

    2013-11-01

    Cancer-associated fibroblasts (CAF) actively participate in reciprocal communication with tumor cells and with other cell types in the microenvironment, contributing to a tumor-permissive neighborhood and promoting tumor progression. The aim of this study is the characterization of how CAFs from primary human colon tumors promote migration of colon cancer cells. Primary CAF cultures from 15 primary human colon tumors were established. Their enrichment in CAFs was evaluated by the expression of various epithelial and myofibroblast specific markers. Coculture assays of primary CAFs with different colon tumor cells were performed to evaluate promigratory CAF-derived effects on cancer cells. Gene expression profiles were developed to further investigate CAF characteristics. Coculture assays showed significant differences in fibroblast-derived paracrine promigratory effects on cancer cells. Moreover, the association between CAFs' promigratory effects on cancer cells and classic fibroblast activation or stemness markers was observed. CAF gene expression profiles were analyzed by microarray to identify deregulated genes in different promigratory CAFs. The gene expression signature, derived from the most protumorogenic CAFs, was identified. Interestingly, this "CAF signature" showed a remarkable prognostic value for the clinical outcome of patients with colon cancer. Moreover, this prognostic value was validated in an independent series of 142 patients with colon cancer, by quantitative real-time PCR (qRT-PCR), with a set of four genes included in the "CAF signature." In summary, these studies show for the first time the heterogeneity of primary CAFs' effect on colon cancer cell migration. A CAF gene expression signature able to classify patients with colon cancer into high- and low-risk groups was identified.

  12. Hormone-induced protection against mammary tumorigenesis is conserved in multiple rat strains and identifies a core gene expression signature induced by pregnancy.

    Science.gov (United States)

    Blakely, Collin M; Stoddard, Alexander J; Belka, George K; Dugan, Katherine D; Notarfrancesco, Kathleen L; Moody, Susan E; D'Cruz, Celina M; Chodosh, Lewis A

    2006-06-15

    Women who have their first child early in life have a substantially lower lifetime risk of breast cancer. The mechanism for this is unknown. Similar to humans, rats exhibit parity-induced protection against mammary tumorigenesis. To explore the basis for this phenomenon, we identified persistent pregnancy-induced changes in mammary gene expression that are tightly associated with protection against tumorigenesis in multiple inbred rat strains. Four inbred rat strains that exhibit marked differences in their intrinsic susceptibilities to carcinogen-induced mammary tumorigenesis were each shown to display significant protection against methylnitrosourea-induced mammary tumorigenesis following treatment with pregnancy levels of estradiol and progesterone. Microarray expression profiling of parous and nulliparous mammary tissue from these four strains yielded a common 70-gene signature. Examination of the genes constituting this signature implicated alterations in transforming growth factor-beta signaling, the extracellular matrix, amphiregulin expression, and the growth hormone/insulin-like growth factor I axis in pregnancy-induced alterations in breast cancer risk. Notably, related molecular changes have been associated with decreased mammographic density, which itself is strongly associated with decreased breast cancer risk. Our findings show that hormone-induced protection against mammary tumorigenesis is widely conserved among divergent rat strains and define a gene expression signature that is tightly correlated with reduced mammary tumor susceptibility as a consequence of a normal developmental event. Given the conservation of this signature, these pathways may contribute to pregnancy-induced protection against breast cancer.

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

    Directory of Open Access Journals (Sweden)

    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

  14. Developing a PTEN-ERG Signature to Improve Molecular Risk Stratification in Prostate Cancer

    Science.gov (United States)

    2017-10-01

    AWARD NUMBER: W81XWH-16-1-0737 TITLE: Developing a PTEN-ERG Signature to Improve Molecular Risk Stratification in Prostate Cancer PRINCIPAL...AND SUBTITLE 5a. CONTRACT NUMBER Developing a PTEN-ERG Signature to Improve Molecular Risk Stratification in Prostate Cancer 5b. GRANT NUMBER W81XWH...that there exist distinctive molecular correlates of PTEN loss in the context of ETS-negative versus ETS-positive human prostate cancers and that

  15. Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer.

    Science.gov (United States)

    Francavilla, Chiara; Lupia, Michela; Tsafou, Kalliopi; Villa, Alessandra; Kowalczyk, Katarzyna; Rakownikow Jersie-Christensen, Rosa; Bertalot, Giovanni; Confalonieri, Stefano; Brunak, Søren; Jensen, Lars J; Cavallaro, Ugo; Olsen, Jesper V

    2017-03-28

    Our understanding of the molecular determinants of cancer is still inadequate because of cancer heterogeneity. Here, using epithelial ovarian cancer (EOC) as a model system, we analyzed a minute amount of patient-derived epithelial cells from either healthy or cancerous tissues by single-shot mass-spectrometry-based phosphoproteomics. Using a multi-disciplinary approach, we demonstrated that primary cells recapitulate tissue complexity and represent a valuable source of differentially expressed proteins and phosphorylation sites that discriminate cancer from healthy cells. Furthermore, we uncovered kinase signatures associated with EOC. In particular, CDK7 targets were characterized in both EOC primary cells and ovarian cancer cell lines. We showed that CDK7 controls cell proliferation and that pharmacological inhibition of CDK7 selectively represses EOC cell proliferation. Our approach defines the molecular landscape of EOC, paving the way for efficient therapeutic approaches for patients. Finally, we highlight the potential of phosphoproteomics to identify clinically relevant and druggable pathways in cancer. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  16. Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer

    Directory of Open Access Journals (Sweden)

    Chiara Francavilla

    2017-03-01

    Full Text Available Our understanding of the molecular determinants of cancer is still inadequate because of cancer heterogeneity. Here, using epithelial ovarian cancer (EOC as a model system, we analyzed a minute amount of patient-derived epithelial cells from either healthy or cancerous tissues by single-shot mass-spectrometry-based phosphoproteomics. Using a multi-disciplinary approach, we demonstrated that primary cells recapitulate tissue complexity and represent a valuable source of differentially expressed proteins and phosphorylation sites that discriminate cancer from healthy cells. Furthermore, we uncovered kinase signatures associated with EOC. In particular, CDK7 targets were characterized in both EOC primary cells and ovarian cancer cell lines. We showed that CDK7 controls cell proliferation and that pharmacological inhibition of CDK7 selectively represses EOC cell proliferation. Our approach defines the molecular landscape of EOC, paving the way for efficient therapeutic approaches for patients. Finally, we highlight the potential of phosphoproteomics to identify clinically relevant and druggable pathways in cancer.

  17. 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

  18. 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

  19. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data

    OpenAIRE

    REN, ZHONGLU; WANG, WENHUI; LI, JINMING

    2015-01-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristi...

  20. Pancreatic cancer circulating tumour cells express a cell motility gene signature that predicts survival after surgery

    International Nuclear Information System (INIS)

    Sergeant, Gregory; Eijsden, Rudy van; Roskams, Tania; Van Duppen, Victor; Topal, Baki

    2012-01-01

    Most cancer deaths are caused by metastases, resulting from circulating tumor cells (CTC) that detach from the primary cancer and survive in distant organs. The aim of the present study was to develop a CTC gene signature and to assess its prognostic relevance after surgery for pancreatic ductal adenocarcinoma (PDAC). Negative depletion fluorescence activated cell sorting (FACS) was developed and validated with spiking experiments using cancer cell lines in whole human blood samples. This FACS-based method was used to enrich for CTC from the blood of 10 patients who underwent surgery for PDAC. Total RNA was isolated from 4 subgroup samples, i.e. CTC, haematological cells (G), original tumour (T), and non-tumoural pancreatic control tissue (P). After RNA quality control, samples of 6 patients were eligible for further analysis. Whole genome microarray analysis was performed after double linear amplification of RNA. ‘Ingenuity Pathway Analysis’ software and AmiGO were used for functional data analyses. A CTC gene signature was developed and validated with the nCounter system on expression data of 78 primary PDAC using Cox regression analysis for disease-free (DFS) and overall survival (OS). Using stringent statistical analysis, we retained 8,152 genes to compare expression profiles of CTC vs. other subgroups, and found 1,059 genes to be differentially expressed. The pathway with the highest expression ratio in CTC was p38 mitogen-activated protein kinase (p38 MAPK) signaling, known to be involved in cancer cell migration. In the p38 MAPK pathway, TGF-β1, cPLA2, and MAX were significantly upregulated. In addition, 9 other genes associated with both p38 MAPK signaling and cell motility were overexpressed in CTC. High co-expression of TGF-β1 and our cell motility panel (≥ 4 out of 9 genes for DFS and ≥ 6 out of 9 genes for OS) in primary PDAC was identified as an independent predictor of DFS (p=0.041, HR (95% CI) = 1.885 (1.025 – 3.559)) and OS (p=0.047, HR

  1. Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.

    Science.gov (United States)

    Godec, Jernej; Tan, Yan; Liberzon, Arthur; Tamayo, Pablo; Bhattacharya, Sanchita; Butte, Atul J; Mesirov, Jill P; Haining, W Nicholas

    2016-01-19

    Gene-expression profiling has become a mainstay in immunology, but subtle changes in gene networks related to biological processes are hard to discern when comparing various datasets. For instance, conservation of the transcriptional response to sepsis in mouse models and human disease remains controversial. To improve transcriptional analysis in immunology, we created ImmuneSigDB: a manually annotated compendium of ∼5,000 gene-sets from diverse cell states, experimental manipulations, and genetic perturbations in immunology. Analysis using ImmuneSigDB identified signatures induced in activated myeloid cells and differentiating lymphocytes that were highly conserved between humans and mice. Sepsis triggered conserved patterns of gene expression in humans and mouse models. However, we also identified species-specific biological processes in the sepsis transcriptional response: although both species upregulated phagocytosis-related genes, a mitosis signature was specific to humans. ImmuneSigDB enables granular analysis of transcriptomic data to improve biological understanding of immune processes of the human and mouse immune systems. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. 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...... into low- and high-methylation subgroups, was trained in cohort 1 (HR, 1.91; 95% CI, 1.26 to 2.90) and validated in cohort 2 (HR, 2.33; 95% CI, 1.31 to 4.13). Conclusion We identified six novel candidate DNA methylation markers for PC. C1orf114 hypermethylation and a three-gene methylation signature were...

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Molecular Signature for Lymphatic Invasion Associated with Survival of Epithelial Ovarian Cancer.

    Science.gov (United States)

    Paik, E Sun; Choi, Hyun Jin; Kim, Tae-Joong; Lee, Jeong-Won; Kim, Byoung-Gie; Bae, Duk-Soo; Choi, Chel Hun

    2018-04-01

    We aimed to develop molecular classifier that can predict lymphatic invasion and their clinical significance in epithelial ovarian cancer (EOC) patients. We analyzed gene expression (mRNA, methylated DNA) in data from The Cancer Genome Atlas. To identify molecular signatures for lymphatic invasion, we found differentially expressed genes. The performance of classifier was validated by receiver operating characteristics analysis, logistic regression, linear discriminant analysis (LDA), and support vector machine (SVM). We assessed prognostic role of classifier using random survival forest (RSF) model and pathway deregulation score (PDS). For external validation,we analyzed microarray data from 26 EOC samples of Samsung Medical Center and curatedOvarianData database. We identified 21 mRNAs, and seven methylated DNAs from primary EOC tissues that predicted lymphatic invasion and created prognostic models. The classifier predicted lymphatic invasion well, which was validated by logistic regression, LDA, and SVM algorithm (C-index of 0.90, 0.71, and 0.74 for mRNA and C-index of 0.64, 0.68, and 0.69 for DNA methylation). Using RSF model, incorporating molecular data with clinical variables improved prediction of progression-free survival compared with using only clinical variables (p < 0.001 and p=0.008). Similarly, PDS enabled us to classify patients into high-risk and low-risk group, which resulted in survival difference in mRNA profiles (log-rank p-value=0.011). In external validation, gene signature was well correlated with prediction of lymphatic invasion and patients' survival. Molecular signature model predicting lymphatic invasion was well performed and also associated with survival of EOC patients.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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

  7. Prediction of the prognosis of breast cancer in routine histologic specimens using a simplified, low-cost gene expression signature

    DEFF Research Database (Denmark)

    Marcell, S.A.; Balazs, A.; Emese, A.

    2013-01-01

    Prediction of the prognosis of breast cancer in routine histologic specimens using a simplified, low-cost gene expression signature Background: Grade 2 breast carcinomas do not form a uniform prognostic group. Aim: To extend the number of patients and the investigated genes of a previously...... grade 2 breast carcinomas into prognostic groups. Gene expression was investigated by polymerase chain reaction in 249 formalin-fixed, paraffin-embedded breast tumors. The results were correlated with relapse-free survival. Results: Histologically grade 2 carcinomas were split into good and a poor...... identified prognostic signature described by the authors that reflect chromosomal instability in order to refine characterization of grade 2 breast cancers and identify driver genes. Methods: Using publicly available databases, the authors selected 9 target and 3 housekeeping genes that are capable to divide...

  8. Identifying pathways affected by cancer mutations.

    Science.gov (United States)

    Iengar, Prathima

    2017-12-16

    Mutations in 15 cancers, sourced from the COSMIC Whole Genomes database, and 297 human pathways, arranged into pathway groups based on the processes they orchestrate, and sourced from the KEGG pathway database, have together been used to identify pathways affected by cancer mutations. Genes studied in ≥15, and mutated in ≥10 samples of a cancer have been considered recurrently mutated, and pathways with recurrently mutated genes have been considered affected in the cancer. Novel doughnut plots have been presented which enable visualization of the extent to which pathways and genes, in each pathway group, are targeted, in each cancer. The 'organismal systems' pathway group (including organism-level pathways; e.g., nervous system) is the most targeted, more than even the well-recognized signal transduction, cell-cycle and apoptosis, and DNA repair pathway groups. The important, yet poorly-recognized, role played by the group merits attention. Pathways affected in ≥7 cancers yielded insights into processes affected. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Utilizing Biomarker Signature Pairs To Develop Gene Therapeutic Viral Delivery Platforms For Treating Prostate Cancer

    Science.gov (United States)

    Dr. Tamaro Hudson is currently an Assistant Professor at Howard University in the Department of Pharmacology and holds an appointment as a Health Research Specialist at the Washington VA Medical Center. Dr. Hudson received his Bachelor of Science from Iowa State University in Biology in 1994 and went on to receive a Master of Science in Preventive Medicine from Ohio State University in 2007. Afterwards, he received a Ph.D. from Ohio State University in 2002 where he focused on evaluating the functional differences among isothiocyanates in the rat esophageal tumor model. Following his Ph.D., Dr. Hudson was selected to complete a prestigious Cancer Prevention Fellowship Program at the National Institute of Health, National Cancer Institute, where he focused on utilizing in vitro and in vivo cancer models to assess the biological activity of bioactive compounds on prostate cancer molecular pathways. Concurrently, he completed a Master of Public Health degree from George Washington University in 2003 where he focused on assessing the degree of agreement between a food frequency questionnaire and a 4-day food record as it related to dietary fiber intake. Upon completion of his MPH and Fellowship, he was recruited by Howard University Cancer Center in 2007 as an Assistant Professor. Since joining the Howard faculty, Dr. Hudson has integrated his research focus by identifying novel signature biomarkers – that could have a significant impact on both the diagnosis and targeted treatment of prostate cancer – with the evaluation of new chemopreventive strategies, which have been evaluated in Phase I and Phase II clinical trials. Dr. Hudson received the first five-year VA-HBCU Research, Scientist, and Training grant that focuses on developing a biomarker-based risk prediction model for prostate cancer. Dr. Hudson serves on several Howard University committees and has many peer-reviewed publications. Dr. Hudson's research interests continue to expand as he tries to build

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

    Directory of Open Access Journals (Sweden)

    Byungwoo Ryu

    2007-07-01

    Full Text Available 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.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 specific genes identified within each class

  11. A mutational signature reveals alterations underlying deficient homologous recombination repair in breast cancer.

    Science.gov (United States)

    Polak, Paz; Kim, Jaegil; Braunstein, Lior Z; Karlic, Rosa; Haradhavala, Nicholas J; Tiao, Grace; Rosebrock, Daniel; Livitz, Dimitri; Kübler, Kirsten; Mouw, Kent W; Kamburov, Atanas; Maruvka, Yosef E; Leshchiner, Ignaty; Lander, Eric S; Golub, Todd R; Zick, Aviad; Orthwein, Alexandre; Lawrence, Michael S; Batra, Rajbir N; Caldas, Carlos; Haber, Daniel A; Laird, Peter W; Shen, Hui; Ellisen, Leif W; D'Andrea, Alan D; Chanock, Stephen J; Foulkes, William D; Getz, Gad

    2017-10-01

    Biallelic inactivation of BRCA1 or BRCA2 is associated with a pattern of genome-wide mutations known as signature 3. By analyzing ∼1,000 breast cancer samples, we confirmed this association and established that germline nonsense and frameshift variants in PALB2, but not in ATM or CHEK2, can also give rise to the same signature. We were able to accurately classify missense BRCA1 or BRCA2 variants known to impair homologous recombination (HR) on the basis of this signature. Finally, we show that epigenetic silencing of RAD51C and BRCA1 by promoter methylation is strongly associated with signature 3 and, in our data set, was highly enriched in basal-like breast cancers in young individuals of African descent.

  12. Meta-analysis of gene expression signatures defining the epithelial to mesenchymal transition during cancer progression.

    Directory of Open Access Journals (Sweden)

    Christian J Gröger

    Full Text Available The epithelial to mesenchymal transition (EMT represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression.

  13. 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 iden......-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients....

  14. Identification of a Genomic Signature Predicting for Recurrence in Early Stage Ovarian Cancer

    Science.gov (United States)

    2015-12-01

    do it. Thus, instead of simply sequencing all the FFPE samples, we used 10 tumor samples (5 recurrent and 5 non recurrent ) to test sequencing and...Award Number: W81XWH-12-1-0521 TITLE: Identification of a Genomic Signature Predicting for Recurrence in Early-Stage Ovarian Cancer PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-12-1-0521 Identification of a Genomic Signature Predicting for Recurrence in

  15. Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

    Science.gov (United States)

    Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

    2016-01-01

    The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

  16. Phosphopeptide derivatization signatures to identify serine and threonine phosphorylated peptides by mass spectrometry.

    Science.gov (United States)

    Molloy, M P; Andrews, P C

    2001-11-15

    The development of rapid, global methods for monitoring states of protein phosphorylation would provide greater insight for understanding many fundamental biological processes. Current best practices use mass spectrometry (MS) to profile digests of purified proteins for evidence of phosphorylation. However, this approach is beset by inherent difficulties in both identifying phosphopeptides from within a complex mixture containing many other unmodified peptides and ionizing phosphopeptides in positive-ion MS. We have modified an approach that uses barium hydroxide to rapidly eliminate the phosphoryl group of serine and threonine modified amino acids, creating dehydroamino acids that are susceptible to nucleophilic derivatization. By derivatizing a protein digest with a mixture of two different alkanethiols, phosphopeptide-specific derivatives were readily distinguished by MS due to their characteristic ion-pair signature. The resulting tagged ion pairs accommodate simple and rapid screening for phosphopeptides in a protein digest, obviating the use of isotopically labeled samples for qualitative phosphopeptide detection. MALDI-MS is used in a first pass manner to detect derivatized phosphopeptides, while the remaining sample is available for tandem MS to reveal the site of derivatization and, thus, phosphorylation. We demonstrated the technique by identifying phosphopeptides from beta-casein and ovalbumin. The approach was further used to examine in vitro phosphorylation of recombinant human HSP22 by protein kinase C, revealing phosphorylation of Thr-63.

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

    Directory of Open Access Journals (Sweden)

    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

  18. The high cancer incidence in young people in Italy: do genetic signatures reveal their environmental causes?

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    Ruggero Ridolfi

    2016-03-01

    Full Text Available The increased incidence of cancer in children and adolescents registered in Italy in the last few decades is one of the highest amongst Western countries. The causes are difficult to identify, but recent daily news and some epidemiological surveys, such as the ‘Sentieri’ study, suggest that environmental pollution has an important role. In the past 20 years, epigenetic studies have described how the changes induced by the cell microenvironment on the non-coding parts of the genome can heavily influence gene function, contributing to the carcinogenesis process. Connecting links amongst the external environment, cellular microenvironment and functional epigenetic and genetic mutations promote carcinogenesis. Today, the whole genome sequencing techniques for human cancers can help to formulate a map of mutational signatures in individual tumours, and a list of mutational fingerprints showing exposure to specific environmental mutagens is being developed. Determining the ethical, legal and economic consequences of known cancer causative agents in young people will be a crucial step for a serious reconsideration of primary prevention.

  19. Metformin induces a Senescence-associated gene Signature in Breast Cancer Cells

    Science.gov (United States)

    Williams, Christopher C.; Singleton, Brittany A.; Llopis, Shawn D.; Skripnikova, Elena V.

    2013-01-01

    Diabetic patients taking metformin have lower incidence of breast cancer than those taking other anti-diabetic medications. Additionally, triple negative breast cancer (TNBC), a form of breast cancer disproportionately afflicting premenopausal African American women, shows atypical susceptibility to metformin’s antiproliferative effect. The mechanisms involved in metformin’s function in TNBC has not yet been fully elucidated. Therefore, we sought to identify pathways regulated by metformin in using the MDA-MB-468 TNBC cell model. Metformin dose-dependently caused apoptosis, decreased cell viability, and induced cell morphology/chromatin condensation consistent with the permanent proliferative arrest. Furthermore, gene expression arrays revealed that metformin caused expression of stress markers DDIT3, CYP1A1, and GDF-15 and a concomitant reduction in PTGS1 expression. Our findings show that metformin may affect the viability and proliferative capacity of TNBC by inducing an antiproliferative gene signature, and that metformin may be effective in the treatment/prevention of TNBC. PMID:23395946

  20. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

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    Mingguang Shi

    Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network

  1. Expression profiling feline peripheral blood monocytes identifies a transcriptional signature associated with type two diabetes mellitus.

    Science.gov (United States)

    O'Leary, Caroline A; Sedhom, Mamdouh; Reeve-Johnson, Mia; Mallyon, John; Irvine, Katharine M

    2017-04-01

    Diabetes mellitus is a common disease of cats and is similar to type 2 diabetes (T2D) in humans, especially with respect to the role of obesity-induced insulin resistance, glucose toxicity, decreased number of pancreatic β-cells and pancreatic amyloid deposition. Cats have thus been proposed as a valuable translational model of T2D. In humans, inflammation associated with adipose tissue is believed to be central to T2D development, and peripheral blood monocytes (PBM) are important in the inflammatory cascade which leads to insulin resistance and β-cell failure. PBM may thus provide a useful window to study the pathogenesis of diabetes mellitus in cats, however feline monocytes are poorly characterised. In this study, we used the Affymetrix Feline 1.0ST array to profile peripheral blood monocytes from 3 domestic cats with T2D and 3 cats with normal glucose tolerance. Feline monocytes were enriched for genes expressed in human monocytes, and, despite heterogeneous gene expression, we identified a T2D-associated expression signature associated with cell cycle perturbations, DNA repair and the unfolded protein response, oxidative phosphorylation and inflammatory responses. Our data provide novel insights into the feline monocyte transcriptome, and support the hypothesis that inflammatory monocytes contribute to T2D pathogenesis in cats as well as in humans. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. 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

  3. Strong Signature of Natural Selection within an FHIT Intron Implicated in Prostate Cancer Risk

    Science.gov (United States)

    Ding, Yan; Larson, Garrett; Rivas, Guillermo; Lundberg, Cathryn; Geller, Louis; Ouyang, Ching; Weitzel, Jeffrey; Archambeau, John; Slater, Jerry; Daly, Mary B.; Benson, Al B.; Kirkwood, John M.; O'Dwyer, Peter J.; Sutphen, Rebecca; Stewart, James A.; Johnson, David; Nordborg, Magnus; Krontiris, Theodore G.

    2008-01-01

    Previously, a candidate gene linkage approach on brother pairs affected with prostate cancer identified a locus of prostate cancer susceptibility at D3S1234 within the fragile histidine triad gene (FHIT), a tumor suppressor that induces apoptosis. Subsequent association tests on 16 SNPs spanning approximately 381 kb surrounding D3S1234 in Americans of European descent revealed significant evidence of association for a single SNP within intron 5 of FHIT. In the current study, re-sequencing and genotyping within a 28.5 kb region surrounding this SNP further delineated the association with prostate cancer risk to a 15 kb region. Multiple SNPs in sequences under evolutionary constraint within intron 5 of FHIT defined several related haplotypes with an increased risk of prostate cancer in European-Americans. Strong associations were detected for a risk haplotype defined by SNPs 138543, 142413, and 152494 in all cases (Pearson's χ2 = 12.34, df 1, P = 0.00045) and for the homozygous risk haplotype defined by SNPs 144716, 142413, and 148444 in cases that shared 2 alleles identical by descent with their affected brothers (Pearson's χ2 = 11.50, df 1, P = 0.00070). In addition to highly conserved sequences encompassing SNPs 148444 and 152413, population studies revealed strong signatures of natural selection for a 1 kb window covering the SNP 144716 in two human populations, the European American (π = 0.0072, Tajima's D = 3.31, 14 SNPs) and the Japanese (π = 0.0049, Fay & Wu's H = 8.05, 14 SNPs), as well as in chimpanzees (Fay & Wu's H = 8.62, 12 SNPs). These results strongly support the involvement of the FHIT intronic region in an increased risk of prostate cancer. PMID:18953408

  4. Population genomics identifies the origin and signatures of selection of Korean weedy rice

    OpenAIRE

    He, Qiang; Kim, Kyu?Won; Park, Yong?Jin

    2016-01-01

    Summary Weedy rice is the same biological species as cultivated rice (Oryza sativa); it is also a noxious weed infesting rice fields worldwide. Its formation and population?selective or ?adaptive signatures are poorly understood. In this study, we investigated the phylogenetics, population structure and signatures of selection of Korean weedy rice by determining the whole genomes of 30 weedy rice, 30 landrace rice and ten wild rice samples. The phylogenetic tree and results of ancestry infere...

  5. Methylation signature of lymph node metastases in breast cancer patients

    International Nuclear Information System (INIS)

    Barekati, Zeinab; Radpour, Ramin; Lu, Qing; Bitzer, Johannes; Zheng, Hong; Toniolo, Paolo; Lenner, Per; Zhong, Xiao Yan

    2012-01-01

    Invasion and metastasis are two important hallmarks of malignant tumors caused by complex genetic and epigenetic alterations. The present study investigated the contribution of aberrant methylation profiles of cancer related genes, APC, BIN1, BMP6, BRCA1, CST6, ESR-b, GSTP1, P14 (ARF), P16 (CDKN2A), P21 (CDKN1A), PTEN, and TIMP3, in the matched axillary lymph node metastasis in comparison to the primary tumor tissue and the adjacent normal tissue from the same breast cancer patients to identify the potential of candidate genes methylation as metastatic markers. The quantitative methylation analysis was performed using the SEQUENOM’s EpiTYPER™ assay which relies on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The quantitative DNA methylation analysis of the candidate genes showed higher methylation proportion in the primary tumor tissue than that of the matched normal tissue and the differences were significant for the APC, BIN1, BMP6, BRCA1, CST6, ESR-b, P16, PTEN and TIMP3 promoter regions (P<0.05). Among those candidate methylated genes, APC, BMP6, BRCA1 and P16 displayed higher methylation proportion in the matched lymph node metastasis than that found in the normal tissue (P<0.05). The pathway analysis revealed that BMP6, BRCA1 and P16 have a role in prevention of neoplasm metastasis. The results of the present study showed methylation heterogeneity between primary tumors and metastatic lesion. The contribution of aberrant methylation alterations of BMP6, BRCA1 and P16 genes in lymph node metastasis might provide a further clue to establish useful biomarkers for screening metastasis

  6. Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers.

    Science.gov (United States)

    Klimov, Sergey; Rida, Padmashree Cg; Aleskandarany, Mohammed A; Green, Andrew R; Ellis, Ian O; Janssen, Emiel Am; Rakha, Emad A; Aneja, Ritu

    2017-09-05

    Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC. A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses. Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status. Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

  7. Identifying microRNA/mRNA dysregulations in ovarian cancer.

    Science.gov (United States)

    Miles, Gregory D; Seiler, Michael; Rodriguez, Lorna; Rajagopal, Gunaretnam; Bhanot, Gyan

    2012-03-27

    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). 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. 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 indirect regulatory mechanisms. Our findings identify

  8. CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

    Science.gov (United States)

    Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

    2015-10-13

    Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

  9. 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.

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

    Science.gov (United States)

    Handkiewicz-Junak, Daria; Swierniak, Michal; Rusinek, Dagmara; Oczko-Wojciechowska, Małgorzata; Dom, Genevieve; Maenhaut, Carine; Unger, Kristian; Detours, Vincent; Bogdanova, Tetiana; Thomas, Geraldine; Likhtarov, Ilya; Jaksik, Roman; Kowalska, Malgorzata; Chmielik, Ewa; Jarzab, Michal; Swierniak, Andrzej; Jarzab, Barbara

    2016-07-01

    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 Chernobyl PTC are associated with previous low-dose radiation exposure.

  11. Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS) Severity.

    Science.gov (United States)

    Bosch-Bayard, Jorge; Galán-García, Lídice; Fernandez, Thalia; Lirio, Rolando B; Bringas-Vega, Maria L; Roca-Stappung, Milene; Ricardo-Garcell, Josefina; Harmony, Thalía; Valdes-Sosa, Pedro A

    2017-01-01

    In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven) regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to) different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS) disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia), Mathematics (Dyscalculia), or Writing (Dysgraphia). By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

  12. The metabolomic approach identifies a biological signature of low-dose chronic exposure to Cesium 137

    International Nuclear Information System (INIS)

    Grison, S.; Grandcolas, L.; Martin, J.C.

    2012-01-01

    Reports have described apparent biological effects of 137 Cs (the most persistent dispersed radionuclide) irradiation in people living in Chernobyl-contaminated territory. The sensitive analytical technology described here should now help assess the relation of this contamination to the observed effects. A rat model chronically exposed to 137 Cs through drinking water was developed to identify biomarkers of radiation-induced metabolic disorders, and the biological impact was evaluated by a metabolomic approach that allowed us to detect several hundred metabolites in biofluids and assess their association with disease states. After collection of plasma and urine from contaminated and non-contaminated rats at the end of the 9-months contamination period, analysis with a liquid chromatography coupled to mass spectrometry (LC-MS) system detected 742 features in urine and 1309 in plasma. Biostatistical discriminant analysis extracted a subset of 26 metabolite signals (2 urinary, 4 plasma non-polar, and 19 plasma polar metabolites) that in combination were able to predict from 68 up to 94% of the contaminated rats, depending on the prediction method used, with a misclassification rate as low as 5.3%. The difference in this metabolic score between the contaminated and non-contaminated rats was highly significant (P=0.019 after ANOVA cross-validation). In conclusion, our proof-of-principle study demonstrated for the first time the usefulness of a metabolomic approach for addressing biological effects of chronic low-dose contamination. We can conclude that a metabolomic signature discriminated 137 Cs-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators. (author)

  13. Stable Sparse Classifiers Identify qEEG Signatures that Predict Learning Disabilities (NOS Severity

    Directory of Open Access Journals (Sweden)

    Jorge Bosch-Bayard

    2018-01-01

    Full Text Available In this paper, we present a novel methodology to solve the classification problem, based on sparse (data-driven regressions, combined with techniques for ensuring stability, especially useful for high-dimensional datasets and small samples number. The sensitivity and specificity of the classifiers are assessed by a stable ROC procedure, which uses a non-parametric algorithm for estimating the area under the ROC curve. This method allows assessing the performance of the classification by the ROC technique, when more than two groups are involved in the classification problem, i.e., when the gold standard is not binary. We apply this methodology to the EEG spectral signatures to find biomarkers that allow discriminating between (and predicting pertinence to different subgroups of children diagnosed as Not Otherwise Specified Learning Disabilities (LD-NOS disorder. Children with LD-NOS have notable learning difficulties, which affect education but are not able to be put into some specific category as reading (Dyslexia, Mathematics (Dyscalculia, or Writing (Dysgraphia. By using the EEG spectra, we aim to identify EEG patterns that may be related to specific learning disabilities in an individual case. This could be useful to develop subject-based methods of therapy, based on information provided by the EEG. Here we study 85 LD-NOS children, divided in three subgroups previously selected by a clustering technique over the scores of cognitive tests. The classification equation produced stable marginal areas under the ROC of 0.71 for discrimination between Group 1 vs. Group 2; 0.91 for Group 1 vs. Group 3; and 0.75 for Group 2 vs. Group1. A discussion of the EEG characteristics of each group related to the cognitive scores is also presented.

  14. Did Shakespeare write double falsehood? Identifying individuals by creating psychological signatures with text analysis.

    Science.gov (United States)

    Boyd, Ryan L; Pennebaker, James W

    2015-05-01

    More than 100 years after Shakespeare's death, Lewis Theobald published Double Falsehood, a play supposedly sourced from a lost play by Shakespeare and John Fletcher. Since its release, scholars have attempted to determine its true authorship. Using new approaches to language and psychological analysis, we examined Double Falsehood and the works of Theobald, Shakespeare, and Fletcher. Specifically, we created a psychological signature from each author's language and statistically compared the features of each signature with those of Double Falsehood's signature. Multiple analytic approaches converged in suggesting that Double Falsehood's psychological style and content architecture predominantly resemble those of Shakespeare, showing some similarity with Fletcher's signature and only traces of Theobald's. Closer inspection revealed that Shakespeare's influence is most apparent early in the play, whereas Fletcher's is most apparent in later acts. Double Falsehood has a psychological signature consistent with that expected to be present in the long-lost play The History of Cardenio, cowritten by Shakespeare and Fletcher. © The Author(s) 2015.

  15. A core invasiveness gene signature reflects epithelial-to-mesenchymal transition but not metastatic potential in breast cancer cell lines and tissue samples.

    Directory of Open Access Journals (Sweden)

    Melike Marsan

    Full Text Available INTRODUCTION: Metastases remain the primary cause of cancer-related death. The acquisition of invasive tumour cell behaviour is thought to be a cornerstone of the metastatic cascade. Therefore, gene signatures related to invasiveness could aid in stratifying patients according to their prognostic profile. In the present study we aimed at identifying an invasiveness gene signature and investigated its biological relevance in breast cancer. METHODS & RESULTS: We collected a set of published gene signatures related to cell motility and invasion. Using this collection, we identified 16 genes that were represented at a higher frequency than observed by coincidence, hereafter named the core invasiveness gene signature. Principal component analysis showed that these overrepresented genes were able to segregate invasive and non-invasive breast cancer cell lines, outperforming sets of 16 randomly selected genes (all P<0.001. When applied onto additional data sets, the expression of the core invasiveness gene signature was significantly elevated in cell lines forced to undergo epithelial-mesenchymal transition. The link between core invasiveness gene expression and epithelial-mesenchymal transition was also confirmed in a dataset consisting of 2420 human breast cancer samples. Univariate and multivariate Cox regression analysis demonstrated that CIG expression is not associated with a shorter distant metastasis free survival interval (HR = 0.956, 95%C.I. = 0.896-1.019, P = 0.186. DISCUSSION: These data demonstrate that we have identified a set of core invasiveness genes, the expression of which is associated with epithelial-mesenchymal transition in breast cancer cell lines and in human tissue samples. Despite the connection between epithelial-mesenchymal transition and invasive tumour cell behaviour, we were unable to demonstrate a link between the core invasiveness gene signature and enhanced metastatic potential.

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

    Science.gov (United States)

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

    2014-01-01

    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 distributions that signal the presence of sewer, fecal, and human fecal pollution. The sequences classified to three sewer infrastructure-associated bacterial genera, Acinetobacter, Arcobacter, and Trichococcus, and five fecal-associated bacterial families, Bacteroidaceae, Porphyromonadaceae, Clostridiaceae, Lachnospiraceae, and Ruminococcaceae, served as signatures of sewer and fecal contamination, respectively. The human fecal signature was determined with the Bayesian source estimation program SourceTracker, which we applied to a set of 40 sewage influent samples collected in Milwaukee, WI, USA to identify operational taxonomic units (≥97 % identity) that were most likely of human fecal origin. During periods of dry weather, the magnitudes of all three signatures were relatively low in Milwaukee's urban rivers and harbor and nearly zero in Lake Michigan. However, the relative contribution of the sewer and fecal signature frequently increased to >2 % of the measured surface water communities following sewer overflows. Also during combined sewer overflows, the ratio of the human fecal pollution signature to the fecal pollution signature in surface waters was generally close to that of sewage, but this ratio decreased dramatically during dry weather and rain events, suggesting that nonhuman fecal pollution was the dominant source during these weather-driven scenarios. The qPCR detection of two human fecal indicators, human Bacteroides and Lachno2, confirmed the urban fecal footprint in

  17. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

    Science.gov (United States)

    Ren, Zhonglu; Wang, Wenhui; Li, Jinming

    2016-02-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

  18. The predictive value of the 70-gene signature for adjuvant chemotherapy in early breast cancer

    NARCIS (Netherlands)

    Knauer, Michael; Mook, Stella; Rutgers, Emiel J. T.; Bender, Richard A.; Hauptmann, Michael; van de Vijver, Marc J.; Koornstra, Rutger H. T.; Bueno-de-Mesquita, Jolien M.; Linn, Sabine C.; van 't Veer, Laura J.

    2010-01-01

    Multigene assays have been developed and validated to determine the prognosis of breast cancer. In this study, we assessed the additional predictive value of the 70-gene MammaPrint signature for chemotherapy (CT) benefit in addition to endocrine therapy (ET) from pooled study series. For 541

  19. Pathway-Enriched Gene Signature Associated with 53BP1 Response to PARP Inhibition in Triple-Negative Breast Cancer.

    Science.gov (United States)

    Hassan, Saima; Esch, Amanda; Liby, Tiera; Gray, Joe W; Heiser, Laura M

    2017-12-01

    Effective treatment of patients with triple-negative (ER-negative, PR-negative, HER2-negative) breast cancer remains a challenge. Although PARP inhibitors are being evaluated in clinical trials, biomarkers are needed to identify patients who will most benefit from anti-PARP therapy. We determined the responses of three PARP inhibitors (veliparib, olaparib, and talazoparib) in a panel of eight triple-negative breast cancer cell lines. Therapeutic responses and cellular phenotypes were elucidated using high-content imaging and quantitative immunofluorescence to assess markers of DNA damage (53BP1) and apoptosis (cleaved PARP). We determined the pharmacodynamic changes as percentage of cells positive for 53BP1, mean number of 53BP1 foci per cell, and percentage of cells positive for cleaved PARP. Inspired by traditional dose-response measures of cell viability, an EC 50 value was calculated for each cellular phenotype and each PARP inhibitor. The EC 50 values for both 53BP1 metrics strongly correlated with IC 50 values for each PARP inhibitor. Pathway enrichment analysis identified a set of DNA repair and cell cycle-associated genes that were associated with 53BP1 response following PARP inhibition. The overall accuracy of our 63 gene set in predicting response to olaparib in seven breast cancer patient-derived xenograft tumors was 86%. In triple-negative breast cancer patients who had not received anti-PARP therapy, the predicted response rate of our gene signature was 45%. These results indicate that 53BP1 is a biomarker of response to anti-PARP therapy in the laboratory, and our DNA damage response gene signature may be used to identify patients who are most likely to respond to PARP inhibition. Mol Cancer Ther; 16(12); 2892-901. ©2017 AACR . ©2017 American Association for Cancer Research.

  20. 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.)

  1. A signature of epithelial-mesenchymal plasticity and stromal activation in primary tumor modulates late recurrence in breast cancer independent of disease subtype.

    Science.gov (United States)

    Cheng, Qing; Chang, Jeffrey T; Gwin, William R; Zhu, Jun; Ambs, Stefan; Geradts, Joseph; Lyerly, H Kim

    2014-07-25

    Despite improvements in adjuvant therapy, late systemic recurrences remain a lethal consequence of both early- and late-stage breast cancer. A delayed recurrence is thought to arise from a state of tumor dormancy, but the mechanisms that govern tumor dormancy remain poorly understood. To address the features of breast tumors associated with late recurrence, but not confounded by variations in systemic treatment, we compiled breast tumor gene expression data from 4,767 patients and established a discovery cohort consisting of 743 lymph node-negative patients who did not receive systemic neoadjuvant or adjuvant therapy. We interrogated the gene expression profiles of the 743 tumors and identified gene expression patterns that were associated with early and late disease recurrence among these patients. We applied this classification to a subset of 46 patients for whom expression data from microdissected tumor epithelium and stroma was available, and identified a distinct gene signature in the stroma and also a corresponding tumor epithelium signature that predicted disease recurrence in the discovery cohort. This tumor epithelium signature was then validated as a predictor for late disease recurrence in the entire cohort of 4,767 patients. We identified a novel 51-gene signature from microdissected tumor epithelium associated with late disease recurrence in breast cancer independent of the molecular disease subtype. This signature correlated with gene expression alterations in the adjacent tumor stroma and describes a process of epithelial to mesenchymal transition (EMT) and tumor-stroma interactions. Our findings suggest that an EMT-related gene signature in the tumor epithelium is related to both stromal activation and escape from disease dormancy in breast cancer. The presence of a late recurrence gene signature in the primary tumor also suggests that intrinsic features of this tumor regulate the transition of disseminated tumor cells into a dormant phenotype with

  2. Calorimetric signatures of human cancer cells and their nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Todinova, S. [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria); Stoyanova, E. [Department of Molecular Immunology, Institute of Biology and Immunology of Reproduction, Bulgarian Academy of Sciences, Tzarigradsko shose Blvd. 73, Sofia 1113 (Bulgaria); Krumova, S., E-mail: sakrumo@gmail.com [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria); Iliev, I. [Institute of Experimental Morphology, Pathology and Anthropology with Museum, Acad. G. Bonchev Str., Bl. 25, Sofia 1113 (Bulgaria); Taneva, S.G. [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria)

    2016-01-10

    Graphical abstract: - Highlights: • Two temperature ranges are distinguished in the thermograms of cells/nuclei. • Different thermodynamic properties of cancer and normal human cells/nuclei. • Dramatic reduction of the enthalpy of the low-temperature range in cancer cells. • Oxaliplatin and 5-FU affect the nuclear matrix proteins and the DNA stability. - Abstract: The human cancer cell lines HeLa, JEG-3, Hep G2, SSC-9, PC-3, HT-29, MCF7 and their isolated nuclei were characterized by differential scanning calorimetry. The calorimetric profiles differed from normal human fibroblast (BJ) cells in the two well distinguished temperature ranges—the high-temperature range (H{sub T}, due to DNA-containing structures) and the low-temperature range (L{sub T}, assigned to the nuclear matrix and cellular proteins). The enthalpy of the L{sub T} range, and, respectively the ratio of the enthalpies of the L{sub T}- vs. H{sub T}-range, ΔH{sub L}/ΔH{sub H}, is strongly reduced for all cancer cells compared to normal fibroblasts. On the contrary, for most of the cancer nuclei this ratio is higher compared to normal nuclei. The HT-29 human colorectal cancer cells/nuclei differed most drastically from normal human fibroblast cells/nuclei. Our data also reveal that the treatment of HT-29 cancer cells with cytostatic drugs affects not only the DNA replication but also the cellular proteome.

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

    International Nuclear Information System (INIS)

    Gonzalez-Perez, Ruben Rene; Lanier, Viola; Newman, Gale

    2013-01-01

    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

  4. Adaptation of a RAS pathway activation signature from FF to FFPE tissues in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Bernard Omolo

    2016-10-01

    Full Text Available Abstract Background The KRAS gene is mutated in about 40 % of colorectal cancer (CRC cases, which has been clinically validated as a predictive mutational marker of intrinsic resistance to anti-EGFR inhibitor (EGFRi therapy. Since nearly 60 % of patients with a wild type KRAS fail to respond to EGFRi combination therapies, there is a need to develop more reliable molecular signatures to better predict response. Here we address the challenge of adapting a gene expression signature predictive of RAS pathway activation, created using fresh frozen (FF tissues, for use with more widely available formalin fixed paraffin-embedded (FFPE tissues. Methods In this study, we evaluated the translation of an 18-gene RAS pathway signature score from FF to FFPE in 54 CRC cases, using a head-to-head comparison of five technology platforms. FFPE-based technologies included the Affymetrix GeneChip (Affy, NanoString nCounter™ (NanoS, Illumina whole genome RNASeq (RNA-Acc, Illumina targeted RNASeq (t-RNA, and Illumina stranded Total RNA-rRNA-depletion (rRNA. Results Using Affy_FF as the “gold” standard, initial analysis of the 18-gene RAS scores on all 54 samples shows varying pairwise Spearman correlations, with (1 Affy_FFPE (r = 0.233, p = 0.090; (2 NanoS_FFPE (r = 0.608, p < 0.0001; (3 RNA-Acc_FFPE (r = 0.175, p = 0.21; (4 t-RNA_FFPE (r = −0.237, p = 0.085; (5 and t-RNA (r = −0.012, p = 0.93. These results suggest that only NanoString has successful FF to FFPE translation. The subsequent removal of identified “problematic” samples (n = 15 and genes (n = 2 further improves the correlations of Affy_FF with three of the five technologies: Affy_FFPE (r = 0.672, p < 0.0001; NanoS_FFPE (r = 0.738, p < 0.0001; and RNA-Acc_FFPE (r = 0.483, p = 0.002. Conclusions Of the five technology platforms tested, NanoString technology provides a more faithful translation of the RAS pathway gene

  5. A breast cancer gene signature for indolent disease

    NARCIS (Netherlands)

    Delahaye, Leonie J. M. J.; Drukker, Caroline A.; Dreezen, Christa; Witteveen, Anke; Chan, Bob; Snel, Mireille; Beumer, Inès J.; Bernards, Rene; Audeh, M. William; van't Veer, Laura J.; Glas, Annuska M.

    2017-01-01

    Early-stage hormone-receptor positive breast cancer is treated with endocrine therapy and the recommended duration of these treatments has increased over time. While endocrine therapy is considered less of a burden to patients compared to chemotherapy, long-term adherence may be low due to potential

  6. Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes

    Directory of Open Access Journals (Sweden)

    Amanda M. Ackermann

    2016-03-01

    Conclusions: We have determined the genetic landscape of human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

  7. 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, nois...... patterns of mutual exclusivity. These techniques, coupled with advances in high-throughput DNA sequencing, are enabling precision medicine approaches to the diagnosis and treatment of cancer....

  8. 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

  9. Molecular characterization of circulating colorectal tumor cells defines genetic signatures for individualized cancer care

    Science.gov (United States)

    Kong, Say Li; Liu, Xingliang; Suhaimi, Nur-Afidah Mohamed; Koh, Kenneth Jia Hao; Hu, Min; Lee, Daniel Yoke San; Cima, Igor; Phyo, Wai Min; Lee, Esther Xing Wei; Tai, Joyce A.; Foong, Yu Miin; Vo, Jess Honganh; Koh, Poh Koon; Zhang, Tong; Ying, Jackie Y.; Lim, Bing; Tan, Min-Han; Hillmer, Axel M.

    2017-01-01

    Studies on circulating tumor cells (CTCs) have largely focused on platform development and CTC enumeration rather than on the genomic characterization of CTCs. To address this, we performed targeted sequencing of CTCs of colorectal cancer patients and compared the mutations with the matched primary tumors. We collected preoperative blood and matched primary tumor samples from 48 colorectal cancer patients. CTCs were isolated using a label-free microfiltration device on a silicon microsieve. Upon whole genome amplification, we performed amplicon-based targeted sequencing on a panel of 39 druggable and frequently mutated genes on both CTCs and fresh-frozen tumor samples. We developed an analysis pipeline to minimize false-positive detection of somatic mutations in amplified DNA. In 60% of the CTC-enriched blood samples, we detected primary tumor matching mutations. We found a significant positive correlation between the allele frequencies of somatic mutations detected in CTCs and abnormal CEA serum level. Strikingly, we found driver mutations and amplifications in cancer and druggable genes such as APC, KRAS, TP53, ERBB3, FBXW7 and ERBB2. In addition, we found that CTCs carried mutation signatures that resembled the signatures of their primary tumors. Cumulatively, our study defined genetic signatures and somatic mutation frequency of colorectal CTCs. The identification of druggable mutations in CTCs of preoperative colorectal cancer patients could lead to more timely and focused therapeutic interventions. PMID:28978093

  10. A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

    Science.gov (United States)

    Cao, Bangrong; Luo, Liping; Feng, Lin; Ma, Shiqi; Chen, Tingqing; Ren, Yuan; Zha, Xiao; Cheng, Shujun; Zhang, Kaitai; Chen, Changmin

    2017-12-13

    The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC. Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study. In the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells. Only a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as

  11. TCGA study identifies genomic features of cervical cancer

    Science.gov (United States)

    Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.

  12. 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

    2015-12-08

    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.

  13. Value of a gene signature assay in patients with early breast cancer and intermediate risk: a single institution retrospective study.

    Science.gov (United States)

    Bonneterre, Jacques; Prat, Aleix; Galván, Patricia; Morel, Pascale; Giard, Sylvia

    2016-05-01

    Purpose In daily clinical practice, the indication for adjuvant chemotherapy (CT) is relatively easy to make in patients with early hormone-receptor-positive (HR+) breast cancer with either very poor or very good clinicopathological prognostic variables. However, this decision is much more difficult in patients with intermediate clinicopathological prognostic variables. Here, we evaluate the value of a gene-expression profile identified by the Prosigna gene signature assay in guiding treatment decision-making in patients with these intermediate features. Methods A consecutive cohort of 577 HR + breast cancer patients surgically treated in a single institution between January 2012 and December 2012 was evaluated. From this population, pre- and post-menopausal patients with intermediate prognosis clinicopathological variables were identified and indication of adjuvant CT in these patients was recorded. The gene signature assay was performed retrospectively in this intermediate risk group. Descriptive statistics are presented. Results Among 96 intermediate-risk patients, 64 postmenopausal patients underwent gene signature testing. Subtype distribution was as follows: Luminal A (N = 33; 51.6%), Luminal B (N = 31; 48.4%). Risk of recurrence (ROR) distribution was as follows: ROR-low (n = 16; 25%); ROR-intermediate (N = 26; 40.6%); and ROR-high (N = 22; 34.4%). CT was subsequently administered in 18.7%, 53.8% and 59.0% of the ROR-low, ROR-intermediate and ROR-high groups, respectively. With the use of the gene signature assay, 59.4% of the intermediate cases were re-classified to either ROR-low or ROR-high risk categories. In the ROR-intermediate group, 11/26 patients (42.3%) had Luminal A and 15/26 (57.7%) had Luminal B. Due to follow-up time constraints, no patient outcome results were evaluated. Conclusion The gene signature assay provides clinically useful information and improved treatment decision-making in patients with intermediate risk based on

  14. 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.

  15. Transcriptional blood signatures distinguish pulmonary tuberculosis, pulmonary sarcoidosis, pneumonias and lung cancers.

    Science.gov (United States)

    Bloom, Chloe I; Graham, Christine M; Berry, Matthew P R; Rozakeas, Fotini; Redford, Paul S; Wang, Yuanyuan; Xu, Zhaohui; Wilkinson, Katalin A; Wilkinson, Robert J; Kendrick, Yvonne; Devouassoux, Gilles; Ferry, Tristan; Miyara, Makoto; Bouvry, Diane; Valeyre, Dominique; Dominique, Valeyre; Gorochov, Guy; Blankenship, Derek; Saadatian, Mitra; Vanhems, Phillip; Beynon, Huw; Vancheeswaran, Rama; Wickremasinghe, Melissa; Chaussabel, Damien; Banchereau, Jacques; Pascual, Virginia; Ho, Ling-Pei; Lipman, Marc; O'Garra, Anne

    2013-01-01

    New approaches to define factors underlying the immunopathogenesis of pulmonary diseases including sarcoidosis and tuberculosis are needed to develop new treatments and biomarkers. Comparing the blood transcriptional response of tuberculosis to other similar pulmonary diseases will advance knowledge of disease pathways and help distinguish diseases with similar clinical presentations. To determine the factors underlying the immunopathogenesis of the granulomatous diseases, sarcoidosis and tuberculosis, by comparing the blood transcriptional responses in these and other pulmonary diseases. We compared whole blood genome-wide transcriptional profiles in pulmonary sarcoidosis, pulmonary tuberculosis, to community acquired pneumonia and primary lung cancer and healthy controls, before and after treatment, and in purified leucocyte populations. An Interferon-inducible neutrophil-driven blood transcriptional signature was present in both sarcoidosis and tuberculosis, with a higher abundance and expression in tuberculosis. Heterogeneity of the sarcoidosis signature correlated significantly with disease activity. Transcriptional profiles in pneumonia and lung cancer revealed an over-abundance of inflammatory transcripts. After successful treatment the transcriptional activity in tuberculosis and pneumonia patients was significantly reduced. However the glucocorticoid-responsive sarcoidosis patients showed a significant increase in transcriptional activity. 144-blood transcripts were able to distinguish tuberculosis from other lung diseases and controls. Tuberculosis and sarcoidosis revealed similar blood transcriptional profiles, dominated by interferon-inducible transcripts, while pneumonia and lung cancer showed distinct signatures, dominated by inflammatory genes. There were also significant differences between tuberculosis and sarcoidosis in the degree of their transcriptional activity, the heterogeneity of their profiles and their transcriptional response to treatment.

  16. Establishment of a 12-gene expression signature to predict colon cancer prognosis

    Directory of Open Access Journals (Sweden)

    Dalong Sun

    2018-06-01

    Full Text Available A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA. The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS: Kaplan Meier (KM Log Rank p = 0.0034; overall survival (OS: KM Log Rank p = 0.0336 in GSE17538. For patients with proficient mismatch repair system (pMMR in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS: KM Log Rank p = 0.022. Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003. After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01 and stage II & III (Log Rank p = 0.017 in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041. Among stage II/III pMMR patients

  17. Multifunctional imaging signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in colorectal cancer.

    Science.gov (United States)

    Miles, Kenneth A; Ganeshan, Balaji; Rodriguez-Justo, Manuel; Goh, Vicky J; Ziauddin, Zia; Engledow, Alec; Meagher, Marie; Endozo, Raymondo; Taylor, Stuart A; Halligan, Stephen; Ell, Peter J; Groves, Ashley M

    2014-03-01

    This study explores the potential for multifunctional imaging to provide a signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutations in colorectal cancer. This prospective study approved by the institutional review board comprised 33 patients undergoing PET/CT before surgery for proven primary colorectal cancer. Tumor tissue was examined histologically for presence of the KRAS mutations and for expression of hypoxia-inducible factor-1 (HIF-1) and minichromosome maintenance protein 2 (mcm2). The following imaging parameters were derived for each tumor: (18)F-FDG uptake ((18)F-FDG maximum standardized uptake value [SUVmax]), CT texture (expressed as mean of positive pixels [MPP]), and blood flow measured by dynamic contrast-enhanced CT. A recursive decision tree was developed in which the imaging investigations were applied sequentially to identify tumors with KRAS mutations. Monte Carlo analysis provided mean values and 95% confidence intervals for sensitivity, specificity, and accuracy. The final decision tree comprised 4 decision nodes and 5 terminal nodes, 2 of which identified KRAS mutants. The true-positive rate, false-positive rate, and accuracy (95% confidence intervals) of the decision tree were 82.4% (63.9%-93.9%), 0% (0%-10.4%), and 90.1% (79.2%-96.0%), respectively. KRAS mutants with high (18)F-FDG SUVmax and low MPP showed greater frequency of HIF-1 expression (P = 0.032). KRAS mutants with low (18)F-FDG SUV(max), high MPP, and high blood flow expressed mcm2 (P = 0.036). Multifunctional imaging with PET/CT and recursive decision-tree analysis to combine measurements of tumor (18)F-FDG uptake, CT texture, and perfusion has the potential to identify imaging signatures for colorectal cancers with KRAS mutations exhibiting hypoxic or proliferative phenotypes.

  18. Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer.

    Science.gov (United States)

    Namani, Akhileshwar; Matiur Rahaman, Md; Chen, Ming; Tang, Xiuwen

    2018-01-06

    NRF2 is the key regulator of oxidative stress in normal cells and aberrant expression of the NRF2 pathway due to genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NRF2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) axis leads to tumorigenesis and drug resistance in many cancers including head and neck squamous cell cancer (HNSCC). The main goal of this study was to identify specific genes regulated by the KEAP1-NRF2-CUL3 axis in HNSCC patients, to assess the prognostic value of this gene signature in different cohorts, and to reveal potential biomarkers. RNA-Seq V2 level 3 data from 279 tumor samples along with 37 adjacent normal samples from patients enrolled in the The Cancer Genome Atlas (TCGA)-HNSCC study were used to identify upregulated genes using two methods (altered KEAP1-NRF2-CUL3 versus normal, and altered KEAP1-NRF2-CUL3 versus wild-type). We then used a new approach to identify the combined gene signature by integrating both datasets and subsequently tested this signature in 4 independent HNSCC datasets to assess its prognostic value. In addition, functional annotation using the DAVID v6.8 database and protein-protein interaction (PPI) analysis using the STRING v10 database were performed on the signature. A signature composed of a subset of 17 genes regulated by the KEAP1-NRF2-CUL3 axis was identified by overlapping both the upregulated genes of altered versus normal (251 genes) and altered versus wild-type (25 genes) datasets. We showed that increased expression was significantly associated with poor survival in 4 independent HNSCC datasets, including the TCGA-HNSCC dataset. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PPI analysis revealed that most of the genes in this signature are associated with drug metabolism and glutathione metabolic pathways. Altogether, our study emphasizes the discovery of a gene signature regulated by the KEAP1-NRF2-CUL3 axis which is strongly associated with

  19. Nuclear proliferomics: A new field of study to identify signatures of nuclear materials as demonstrated on alpha-UO3.

    Science.gov (United States)

    Schwerdt, Ian J; Brenkmann, Alexandria; Martinson, Sean; Albrecht, Brent D; Heffernan, Sean; Klosterman, Michael R; Kirkham, Trenton; Tasdizen, Tolga; McDonald Iv, Luther W

    2018-08-15

    The use of a limited set of signatures in nuclear forensics and nuclear safeguards may reduce the discriminating power for identifying unknown nuclear materials, or for verifying processing at existing facilities. Nuclear proliferomics is a proposed new field of study that advocates for the acquisition of large databases of nuclear material properties from a variety of analytical techniques. As demonstrated on a common uranium trioxide polymorph, α-UO 3 , in this paper, nuclear proliferomics increases the ability to improve confidence in identifying the processing history of nuclear materials. Specifically, α-UO 3 was investigated from the calcination of unwashed uranyl peroxide at 350, 400, 450, 500, and 550 °C in air. Scanning electron microscopy (SEM) images were acquired of the surface morphology, and distinct qualitative differences are presented between unwashed and washed uranyl peroxide, as well as the calcination products from the unwashed uranyl peroxide at the investigated temperatures. Differential scanning calorimetry (DSC), UV-Vis spectrophotometry, powder X-ray diffraction (p-XRD), and thermogravimetric analysis-mass spectrometry (TGA-MS) were used to understand the source of these morphological differences as a function of calcination temperature. Additionally, the SEM images were manually segmented using Morphological Analysis for MAterials (MAMA) software to identify quantifiable differences in morphology for three different surface features present on the unwashed uranyl peroxide calcination products. No single quantifiable signature was sufficient to discern all calcination temperatures with a high degree of confidence; therefore, advanced statistical analysis was performed to allow the combination of a number of quantitative signatures, with their associated uncertainties, to allow for complete discernment by calcination history. Furthermore, machine learning was applied to the acquired SEM images to demonstrate automated discernment with

  20. Exploring gene expression signatures for predicting disease free survival after resection of colorectal cancer liver metastases.

    Directory of Open Access Journals (Sweden)

    Nikol Snoeren

    Full Text Available BACKGROUND AND OBJECTIVES: This study was designed to identify and validate gene signatures that can predict disease free survival (DFS in patients undergoing a radical resection for their colorectal liver metastases (CRLM. METHODS: Tumor gene expression profiles were collected from 119 patients undergoing surgery for their CRLM in the Paul Brousse Hospital (France and the University Medical Center Utrecht (The Netherlands. Patients were divided into high and low risk groups. A randomly selected training set was used to find predictive gene signatures. The ability of these gene signatures to predict DFS was tested in an independent validation set comprising the remaining patients. Furthermore, 5 known clinical risk scores were tested in our complete patient cohort. RESULT: No gene signature was found that significantly predicted DFS in the validation set. In contrast, three out of five clinical risk scores were able to predict DFS in our patient cohort. CONCLUSIONS: No gene signature was found that could predict DFS in patients undergoing CRLM resection. Three out of five clinical risk scores were able to predict DFS in our patient cohort. These results emphasize the need for validating risk scores in independent patient groups and suggest improved designs for future studies.

  1. Integration of a Radiosensitivity Molecular Signature Into the Assessment of Local Recurrence Risk in Breast Cancer

    International Nuclear Information System (INIS)

    Torres-Roca, Javier F.; Fulp, William J.; Caudell, Jimmy J.; Servant, Nicolas; Bollet, Marc A.; Vijver, Marc van de; Naghavi, Arash O.; Harris, Eleanor E.; Eschrich, Steven A.

    2015-01-01

    Purpose: Recently, we developed radiosensitivity (RSI), a clinically validated molecular signature that estimates tumor radiosensitivity. In the present study, we tested whether integrating RSI with the molecular subtype refines the classification of local recurrence (LR) risk in breast cancer. Methods and Materials: RSI and molecular subtype were evaluated in 343 patients treated with breast-conserving therapy that included whole-breast radiation therapy with or without a tumor bed boost (dose range 45-72 Gy). The follow-up period for patients without recurrence was 10 years. The clinical endpoint was LR-free survival. Results: Although RSI did not uniformly predict for LR across the entire cohort, combining RSI and the molecular subtype identified a subpopulation with an increased risk of LR: triple negative (TN) and radioresistant (reference TN-radioresistant, hazard ratio [HR] 0.37, 95% confidence interval [CI] 0.15-0.92, P=.02). TN patients who were RSI-sensitive/intermediate had LR rates similar to those of luminal (LUM) patients (HR 0.86, 95% CI 0.47-1.57, P=.63). On multivariate analysis, combined RSI and molecular subtype (P=.004) and age (P=.001) were the most significant predictors of LR. In contrast, integrating RSI into the LUM subtype did not identify additional risk groups. We hypothesized that radiation dose escalation was affecting radioresistance in the LUM subtype and serving as a confounder. An increased radiation dose decreased LR only in the luminal-resistant (LUM-R) subset (HR 0.23, 95% CI 0.05-0.98, P=.03). On multivariate analysis, the radiation dose was an independent variable only in the LUMA/B-RR subset (HR 0.025, 95% CI 0.001-0.946, P=.046), along with age (P=.008), T stage (P=.004), and chemotherapy (P=.008). Conclusions: The combined molecular subtype–RSI identified a novel molecular subpopulation (TN and radioresistant) with an increased risk of LR after breast-conserving therapy. We propose that the combination of RSI and

  2. Integration of a Radiosensitivity Molecular Signature Into the Assessment of Local Recurrence Risk in Breast Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Torres-Roca, Javier F., E-mail: javier.torresroca@moffitt.org [Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida (United States); Department of Chemical Biology and Molecular Medicine, Moffitt Cancer Center, Tampa, Florida (United States); Fulp, William J. [Department of Bioinformatics, Moffitt Cancer Center, Tampa, Florida (United States); Department of Biostatistics, Moffitt Cancer Center, Tampa, Florida (United States); Caudell, Jimmy J. [Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida (United States); Servant, Nicolas [Institut Curie, INSERM U900, Paris (France); Mines ParisTech, Paris (France); Bollet, Marc A. [Institut Curie, INSERM U900, Paris (France); Vijver, Marc van de [Netherlands Cancer Institute, Amsterdam (Netherlands); Naghavi, Arash O. [Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida (United States); Harris, Eleanor E. [East Carolina University, Greensborough, North Carolina (United States); Eschrich, Steven A. [Department of Bioinformatics, Moffitt Cancer Center, Tampa, Florida (United States)

    2015-11-01

    Purpose: Recently, we developed radiosensitivity (RSI), a clinically validated molecular signature that estimates tumor radiosensitivity. In the present study, we tested whether integrating RSI with the molecular subtype refines the classification of local recurrence (LR) risk in breast cancer. Methods and Materials: RSI and molecular subtype were evaluated in 343 patients treated with breast-conserving therapy that included whole-breast radiation therapy with or without a tumor bed boost (dose range 45-72 Gy). The follow-up period for patients without recurrence was 10 years. The clinical endpoint was LR-free survival. Results: Although RSI did not uniformly predict for LR across the entire cohort, combining RSI and the molecular subtype identified a subpopulation with an increased risk of LR: triple negative (TN) and radioresistant (reference TN-radioresistant, hazard ratio [HR] 0.37, 95% confidence interval [CI] 0.15-0.92, P=.02). TN patients who were RSI-sensitive/intermediate had LR rates similar to those of luminal (LUM) patients (HR 0.86, 95% CI 0.47-1.57, P=.63). On multivariate analysis, combined RSI and molecular subtype (P=.004) and age (P=.001) were the most significant predictors of LR. In contrast, integrating RSI into the LUM subtype did not identify additional risk groups. We hypothesized that radiation dose escalation was affecting radioresistance in the LUM subtype and serving as a confounder. An increased radiation dose decreased LR only in the luminal-resistant (LUM-R) subset (HR 0.23, 95% CI 0.05-0.98, P=.03). On multivariate analysis, the radiation dose was an independent variable only in the LUMA/B-RR subset (HR 0.025, 95% CI 0.001-0.946, P=.046), along with age (P=.008), T stage (P=.004), and chemotherapy (P=.008). Conclusions: The combined molecular subtype–RSI identified a novel molecular subpopulation (TN and radioresistant) with an increased risk of LR after breast-conserving therapy. We propose that the combination of RSI and

  3. Two microRNA signatures for malignancy and immune infiltration predict overall survival in advanced epithelial ovarian cancer.

    Science.gov (United States)

    Korsunsky, Ilya; Parameswaran, Janaki; Shapira, Iuliana; Lovecchio, John; Menzin, Andrew; Whyte, Jill; Dos Santos, Lisa; Liang, Sharon; Bhuiya, Tawfiqul; Keogh, Mary; Khalili, Houman; Pond, Cassandra; Liew, Anthony; Shih, Andrew; Gregersen, Peter K; Lee, Annette T

    2017-10-01

    MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their co-localized gene targets in primary tumor tissue of 20 patients with advanced EOC in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy-related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune-related functions, was strongly correlated with imputed intratumoral immune infiltrates of T cells, natural killer cells, cytotoxic lymphocytes, and macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publicly available The Cancer Genome Atlas data set. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival. © American Federation for Medical Research (unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  4. The biochemical, nanomechanical and chemometric signatures of brain cancer

    Science.gov (United States)

    Abramczyk, Halina; Imiela, Anna

    2018-01-01

    % for cross-validation, respectively. The high sensitivity and specificity demonstrates usefulness for a proper decision for a Raman diagnostic test on biochemical alterations monitored by Raman spectroscopy related to brain cancer development.

  5. Signatures in vibrational and UV-visible absorption spectra for identifying cyclic hydrocarbons by graphene fragments.

    Science.gov (United States)

    Meng, Yan; Wu, Qi; Chen, Lei; Wangmo, Sonam; Gao, Yang; Wang, Zhigang; Zhang, Rui-Qin; Ding, Dajun; Niehaus, Thomas A; Frauenheim, Thomas

    2013-12-21

    To promote possible applications of graphene in molecular identification based on stacking effects, in particular in recognizing aromatic amino acids and even sequencing nucleobases in life sciences, we comprehensively study the interaction between graphene segments and different cyclic organic hydrocarbons including benzene (C6H6), cyclohexane (C6H12), benzyne (C6H4), cyclohexene (C6H10), 1,3-cyclohexadiene (C6H8(1)) and 1,4-cyclohexadiene (C6H8(2)), using the density-functional tight-binding (DFTB) method. Interestingly, we find obviously different characteristics in Raman vibrational and ultraviolet visible absorption spectra of the small molecules adsorbed on the graphene sheet. Specifically, we find that both spectra involve clearly different characteristic peaks, belonging to the different small molecules upon adsorption, with the ones of ionized molecules being more substantial. Further analysis shows that the adsorptions are almost all due to the presence of dispersion energy in neutral cases and involve charge transfer from the graphene to the small molecules. In contrast, the main binding force in the ionic adsorption systems is the electronic interaction. The results present clear signatures that can be used to recognize different kinds of aromatic hydrocarbon rings on graphene sheets. We expect that our findings will be helpful for designing molecular recognition devices using graphene.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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

  8. Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia

    Science.gov (United States)

    Lequerré, Thierry; Bansard, Carine; Vittecoq, Olivier; Derambure, Céline; Hiron, Martine; Daveau, Maryvonne; Tron, François; Ayral, Xavier; Biga, Norman; Auquit-Auckbur, Isabelle; Chiocchia, Gilles; Le Loët, Xavier; Salier, Jean-Philippe

    2009-01-01

    Introduction Rheumatoid arthritis (RA) is a heterogeneous disease and its underlying molecular mechanisms are still poorly understood. Because previous microarray studies have only focused on long-standing (LS) RA compared to osteoarthritis, we aimed to compare the molecular profiles of early and LS RA versus control synovia. Methods Synovial biopsies were obtained by arthroscopy from 15 patients (4 early untreated RA, 4 treated LS RA and 7 controls, who had traumatic or mechanical lesions). Extracted mRNAs were used for large-scale gene-expression profiling. The different gene-expression combinations identified by comparison of profiles of early, LS RA and healthy synovia were linked to the biological processes involved in each situation. Results Three combinations of 719, 116 and 52 transcripts discriminated, respectively, early from LS RA, and early or LS RA from healthy synovia. We identified several gene clusters and distinct molecular signatures specifically expressed during early or LS RA, thereby suggesting the involvement of different pathophysiological mechanisms during the course of RA. Conclusions Early and LS RA have distinct molecular signatures with different biological processes participating at different times during the course of the disease. These results suggest that better knowledge of the main biological processes involved at a given RA stage might help to choose the most appropriate treatment. PMID:19563633

  9. Radiation signatures in childhood thyroid cancers after the Chernobyl accident: Possible roles of radiation in carcinogenesis

    Science.gov (United States)

    Suzuki, Keiji; Mitsutake, Norisato; Saenko, Vladimir; Yamashita, Shunichi

    2015-01-01

    After the Tokyo Electric Power Company Fukushima Daiichi nuclear power plant accident, cancer risk from low-dose radiation exposure has been deeply concerning. The linear no-threshold model is applied for the purpose of radiation protection, but it is a model based on the concept that ionizing radiation induces stochastic oncogenic alterations in the target cells. As the elucidation of the mechanism of radiation-induced carcinogenesis is indispensable to justify the concept, studies aimed at the determination of molecular changes associated with thyroid cancers among children who suffered effects from the Chernobyl nuclear accident will be overviewed. We intend to discuss whether any radiation signatures are associated with radiation-induced childhood thyroid cancers. PMID:25483826

  10. 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...... signatures of 102 fresh-frozen patient samples during PCa progression by miRNA microarrays. Both platforms were cross-validated by quantitative reverse transcriptase-PCR. Besides the altered expression of several miRNAs, our deep sequencing analyses revealed strong differential expression of small nucleolar...... 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...

  11. Systematic assessment of prognostic gene signatures for breast cancer shows distinct influence of time and ER status

    International Nuclear Information System (INIS)

    Zhao, Xi; Rødland, Einar Andreas; Sørlie, Therese; Vollan, Hans Kristian Moen; Russnes, Hege G; Kristensen, Vessela N; Lingjærde, Ole Christian; Børresen-Dale, Anne-Lise

    2014-01-01

    The aim was to assess and compare prognostic power of nine breast cancer gene signatures (Intrinsic, PAM50, 70-gene, 76-gene, Genomic-Grade-Index, 21-gene-Recurrence-Score, EndoPredict, Wound-Response and Hypoxia) in relation to ER status and follow-up time. A gene expression dataset from 947 breast tumors was used to evaluate the signatures for prediction of Distant Metastasis Free Survival (DMFS). A total of 912 patients had available DMFS status. The recently published METABRIC cohort was used as an additional validation set. Survival predictions were fairly concordant across most signatures. Prognostic power declined with follow-up time. During the first 5 years of followup, all signatures except for Hypoxia were predictive for DMFS in ER-positive disease, and 76-gene, Hypoxia and Wound-Response were prognostic in ER-negative disease. After 5 years, the signatures had little prognostic power. Gene signatures provide significant prognostic information beyond tumor size, node status and histological grade. Generally, these signatures performed better for ER-positive disease, indicating that risk within each ER stratum is driven by distinct underlying biology. Most of the signatures were strong risk predictors for DMFS during the first 5 years of follow-up. Combining gene signatures with histological grade or tumor size, could improve the prognostic power, perhaps also of long-term survival

  12. DNA polymerase η mutational signatures are found in a variety of different types of cancer.

    Science.gov (United States)

    Rogozin, Igor B; Goncearenco, Alexander; Lada, Artem G; De, Subhajyoti; Yurchenko, Vyacheslav; Nudelman, German; Panchenko, Anna R; Cooper, David N; Pavlov, Youri I

    2018-01-01

    DNA polymerase (pol) η is a specialized error-prone polymerase with at least two quite different and contrasting cellular roles: to mitigate the genetic consequences of solar UV irradiation, and promote somatic hypermutation in the variable regions of immunoglobulin genes. Misregulation and mistargeting of pol η can compromise genome integrity. We explored whether the mutational signature of pol η could be found in datasets of human somatic mutations derived from normal and cancer cells. A substantial excess of single and tandem somatic mutations within known pol η mutable motifs was noted in skin cancer as well as in many other types of human cancer, suggesting that somatic mutations in A:T bases generated by DNA polymerase η are a common feature of tumorigenesis. Another peculiarity of pol ηmutational signatures, mutations in YCG motifs, led us to speculate that error-prone DNA synthesis opposite methylated CpG dinucleotides by misregulated pol η in tumors might constitute an additional mechanism of cytosine demethylation in this hypermutable dinucleotide.

  13. A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

    Directory of Open Access Journals (Sweden)

    Fardin Paolo

    2010-07-01

    Full Text Available Abstract Background Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome. Results We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification. Conclusions Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

  14. Identification and Construction of Combinatory Cancer Hallmark-Based Gene Signature Sets to Predict Recurrence and Chemotherapy Benefit in Stage II Colorectal Cancer.

    Science.gov (United States)

    Gao, Shanwu; Tibiche, Chabane; Zou, Jinfeng; Zaman, Naif; Trifiro, Mark; O'Connor-McCourt, Maureen; Wang, Edwin

    2016-01-01

    Decisions regarding adjuvant therapy in patients with stage II colorectal cancer (CRC) have been among the most challenging and controversial in oncology over the past 20 years. To develop robust combinatory cancer hallmark-based gene signature sets (CSS sets) that more accurately predict prognosis and identify a subset of patients with stage II CRC who could gain survival benefits from adjuvant chemotherapy. Thirteen retrospective studies of patients with stage II CRC who had clinical follow-up and adjuvant chemotherapy were analyzed. Respective totals of 162 and 843 patients from 2 and 11 independent cohorts were used as the discovery and validation cohorts, respectively. A total of 1005 patients with stage II CRC were included in the 13 cohorts. Among them, 84 of 416 patients in 3 independent cohorts received fluorouracil-based adjuvant chemotherapy. Identification of CSS sets to predict relapse-free survival and identify a subset of patients with stage II CRC who could gain substantial survival benefits from fluorouracil-based adjuvant chemotherapy. Eight cancer hallmark-based gene signatures (30 genes each) were identified and used to construct CSS sets for determining prognosis. The CSS sets were validated in 11 independent cohorts of 767 patients with stage II CRC who did not receive adjuvant chemotherapy. The CSS sets accurately stratified patients into low-, intermediate-, and high-risk groups. Five-year relapse-free survival rates were 94%, 78%, and 45%, respectively, representing 60%, 28%, and 12% of patients with stage II disease. The 416 patients with CSS set-defined high-risk stage II CRC who received fluorouracil-based adjuvant chemotherapy showed a substantial gain in survival benefits from the treatment (ie, recurrence reduced by 30%-40% in 5 years). The CSS sets substantially outperformed other prognostic predictors of stage 2 CRC. They are more accurate and robust for prognostic predictions and facilitate the identification of patients with stage

  15. 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.

  16. 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

  17. Identifying Genetic Signatures of Natural Selection Using Pooled Population Sequencing in Picea abies.

    Science.gov (United States)

    Chen, Jun; Källman, Thomas; Ma, Xiao-Fei; Zaina, Giusi; Morgante, Michele; Lascoux, Martin

    2016-07-07

    The joint inference of selection and past demography remain a costly and demanding task. We used next generation sequencing of two pools of 48 Norway spruce mother trees, one corresponding to the Fennoscandian domain, and the other to the Alpine domain, to assess nucleotide polymorphism at 88 nuclear genes. These genes are candidate genes for phenological traits, and most belong to the photoperiod pathway. Estimates of population genetic summary statistics from the pooled data are similar to previous estimates, suggesting that pooled sequencing is reliable. The nonsynonymous SNPs tended to have both lower frequency differences and lower FST values between the two domains than silent ones. These results suggest the presence of purifying selection. The divergence between the two domains based on synonymous changes was around 5 million yr, a time similar to a recent phylogenetic estimate of 6 million yr, but much larger than earlier estimates based on isozymes. Two approaches, one of them novel and that considers both FST and difference in allele frequencies between the two domains, were used to identify SNPs potentially under diversifying selection. SNPs from around 20 genes were detected, including genes previously identified as main target for selection, such as PaPRR3 and PaGI. Copyright © 2016 Chen et al.

  18. A model-based approach for identifying signatures of ancient balancing selection in genetic data.

    Science.gov (United States)

    DeGiorgio, Michael; Lohmueller, Kirk E; Nielsen, Rasmus

    2014-08-01

    While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

  19. A model-based approach for identifying signatures of ancient balancing selection in genetic data.

    Directory of Open Access Journals (Sweden)

    Michael DeGiorgio

    2014-08-01

    Full Text Available While much effort has focused on detecting positive and negative directional selection in the human genome, relatively little work has been devoted to balancing selection. This lack of attention is likely due to the paucity of sophisticated methods for identifying sites under balancing selection. Here we develop two composite likelihood ratio tests for detecting balancing selection. Using simulations, we show that these methods outperform competing methods under a variety of assumptions and demographic models. We apply the new methods to whole-genome human data, and find a number of previously-identified loci with strong evidence of balancing selection, including several HLA genes. Additionally, we find evidence for many novel candidates, the strongest of which is FANK1, an imprinted gene that suppresses apoptosis, is expressed during meiosis in males, and displays marginal signs of segregation distortion. We hypothesize that balancing selection acts on this locus to stabilize the segregation distortion and negative fitness effects of the distorter allele. Thus, our methods are able to reproduce many previously-hypothesized signals of balancing selection, as well as discover novel interesting candidates.

  20. Exosomes Derived From Pancreatic Stellate Cells: MicroRNA Signature and Effects on Pancreatic Cancer Cells.

    Science.gov (United States)

    Takikawa, Tetsuya; Masamune, Atsushi; Yoshida, Naoki; Hamada, Shin; Kogure, Takayuki; Shimosegawa, Tooru

    2017-01-01

    Pancreatic stellate cells (PSCs) interact with pancreatic cancer cells in the tumor microenvironment. Cell constituents including microRNAs may be exported from cells within membranous nanovesicles termed exosomes. Exosomes might play a pivotal role in intercellular communication. This study aimed to clarify the microRNA signature of PSC-derived exosomes and their effects on pancreatic cancer cells. Exosomes were prepared from the conditioned medium of immortalized human PSCs. MicroRNAs were prepared from the exosomes and their source PSCs, and the microRNA expression profiles were compared by microarray. The effects of PSC-derived exosomes on proliferation, migration, and the mRNA expression profiles were examined in pancreatic cancer cells. Pancreatic stellate cell-derived exosomes contained a variety of microRNAs including miR-21-5p. Several microRNAs such as miR-451a were enriched in exosomes compared to their source PSCs. Pancreatic stellate cell-derived exosomes stimulated the proliferation, migration and expression of mRNAs for chemokine (C - X - C motif) ligands 1 and 2 in pancreatic cancer cells. The stimulation of proliferation, migration, and chemokine gene expression by the conditioned medium of PSCs was suppressed by GW4869, an exosome inhibitor. We clarified the microRNA expression profile in PSC-derived exosomes. Pancreatic stellate cell-derived exosomes might play a role in the interactions between PSCs and pancreatic cancer cells.

  1. Spectral signatures of fluorescence and light absorption to identify crude oils found in the marine environment

    Science.gov (United States)

    Baszanowska, E.; Otremba, Z.

    2014-08-01

    To protect the natural marine ecosystem, it is necessary to continuously enhance knowledge of environmental contamination, including oil pollution. Therefore, to properly track the qualitative and quantitative changes in the natural components of seawater, a description of the essential spectral features describing petroleum products is necessary. This study characterises two optically-different types of crude oils (Petrobaltic and Romashkino) - substances belonging to multi-fluorophoric systems. To obtain the spectral features of crude oils, the excitation-emission spectroscopy technique was applied. The fluorescence and light absorption properties for various concentrations of oils at a stabilised temperature are described. Both excitation-emission spectra (EEMs) and absorption spectra of crude oils are discussed. Based on the EEM spectra, both excitation end emission peaks for the wavelengthindependent fluorescence maximum (Exmax/ Emmax) - characteristic points for each type of oil - were identified and compared with the literature data concerning typical marine chemical structures.

  2. Identification of cell proliferation, immune response and cell migration as critical pathways in a prognostic signature for HER2+:ERα- breast cancer.

    Directory of Open Access Journals (Sweden)

    Jeffrey C Liu

    Full Text Available Multi-gene prognostic signatures derived from primary tumor biopsies can guide clinicians in designing an appropriate course of treatment. Identifying genes and pathways most essential to a signature performance may facilitate clinical application, provide insights into cancer progression, and uncover potentially new therapeutic targets. We previously developed a 17-gene prognostic signature (HTICS for HER2+:ERα- breast cancer patients, using genes that are differentially expressed in tumor initiating cells (TICs versus non-TICs from MMTV-Her2/neu mammary tumors. Here we probed the pathways and genes that underlie the prognostic power of HTICS.We used Leave-One Out, Data Combination Test, Gene Set Enrichment Analysis (GSEA, Correlation and Substitution analyses together with Receiver Operating Characteristic (ROC and Kaplan-Meier survival analysis to identify critical biological pathways within HTICS. Publically available cohorts with gene expression and clinical outcome were used to assess prognosis. NanoString technology was used to detect gene expression in formalin-fixed paraffin embedded (FFPE tissues.We show that three major biological pathways: cell proliferation, immune response, and cell migration, drive the prognostic power of HTICS, which is further tuned by Homeostatic and Glycan metabolic signalling. A 6-gene minimal Core that retained a significant prognostic power, albeit less than HTICS, also comprised the proliferation/immune/migration pathways. Finally, we developed NanoString probes that could detect expression of HTICS genes and their substitutions in FFPE samples.Our results demonstrate that the prognostic power of a signature is driven by the biological processes it monitors, identify cell proliferation, immune response and cell migration as critical pathways for HER2+:ERα- cancer progression, and defines substitutes and Core genes that should facilitate clinical application of HTICS.

  3. Association of tRNA methyltransferase NSUN2/IGF-II molecular signature with ovarian cancer survival.

    Science.gov (United States)

    Yang, Jia-Cheng; Risch, Eric; Zhang, Meiqin; Huang, Chan; Huang, Huatian; Lu, Lingeng

    2017-09-01

    To investigate the association between NSUN2/IGF-II signature and ovarian cancer survival. Using a publicly accessible dataset of RNA sequencing and clinical follow-up data, we performed Classification and Regression Tree and survival analyses. Patients with NSUN2 high IGF-II low had significantly superior overall and disease progression-free survival, followed by NSUN2 low IGF-II low , NSUN2 high IGF-II high and NSUN2 low IGF-II high (p IGF-II signature with the risks of death and relapse remained significant in multivariate Cox regression models. Random-effects meta-analyses show the upregulated NSUN2 and IGF-II expression in ovarian cancer versus normal tissues. The NSUN2/IGF-II signature associates with heterogeneous outcome and may have clinical implications in managing ovarian cancer.

  4. Association analysis identifies 65 new breast cancer risk loci

    OpenAIRE

    Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew

    2017-01-01

    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer ri...

  5. 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.

    Directory of Open Access Journals (Sweden)

    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

  6. Community Engagement for Identifying Cancer Education Needs in Puerto Rico.

    Science.gov (United States)

    Jiménez, Julio; Ramos, Axel; Ramos-Rivera, Francisco E; Gwede, Clement; Quinn, Gwendolyn P; Vadaparampil, Susan; Brandon, Thomas; Simmons, Vani; Castro, Eida

    2018-02-01

    Cancer is the leading cause of death in Puerto Rico, suggesting a need for improved strategies, programs, and resources devoted to cancer prevention. Enhanced prevention needs in Puerto Rico were initially identified in pilot studies conducted by the Ponce School of Medicine (PSM) in collaboration with the H. Lee Moffitt Cancer Center (MCC). In the current study, we used community engagement to identify specific needs in cancer prevention and education and strategies to create culturally attuned, effective cancer prevention education programs. A total of 37 participants attended a community forum and were assigned to one of three discussion groups: patients/survivors (n = 14); family/caregivers (n = 11); or healthcare providers (n = 12). Most participants were women (73 %), over 35 years of age, and a majority were married (58 %) and had a university education (81 %). The sessions were recorded and transcribed and analyzed for key themes. Participants wanted improved awareness of cancer prevention in Puerto Rico and believed cancer prevention education should start early, ideally in elementary school. Participants also stressed the importance of creating partnerships with private and government agencies to coordinate educational efforts. Suggested strategies included outreach to communities with limited resources, incorporating the testimony of cancer survivors, and utilizing social media to disseminate cancer prevention information.

  7. Genetic differences in transcript responses to low-dose ionizing radiation identify tissue functions associated with breast cancer susceptibility.

    Science.gov (United States)

    Snijders, Antoine M; Marchetti, Francesco; Bhatnagar, Sandhya; Duru, Nadire; Han, Ju; Hu, Zhi; Mao, Jian-Hua; Gray, Joe W; Wyrobek, Andrew J

    2012-01-01

    High dose ionizing radiation (IR) is a well-known risk factor for breast cancer but the health effects after low-dose (LD, differences in their sensitivity to radiation-induced mammary cancer (BALB/c and C57BL/6) for the purpose of identifying mechanisms of mammary cancer susceptibility. Unirradiated mammary and blood tissues of these strains differed significantly in baseline expressions of DNA repair, tumor suppressor, and stress response genes. LD exposures of 7.5 cGy (weekly for 4 weeks) did not induce detectable genomic instability in either strain. However, the mammary glands of the sensitive strain but not the resistant strain showed early transcriptional responses involving: (a) diminished immune response, (b) increased cellular stress, (c) altered TGFβ-signaling, and (d) inappropriate expression of developmental genes. One month after LD exposure, the two strains showed opposing responses in transcriptional signatures linked to proliferation, senescence, and microenvironment functions. We also discovered a pre-exposure expression signature in both blood and mammary tissues that is predictive for poor survival among human cancer patients (p = 0.0001), and a post-LD-exposure signature also predictive for poor patient survival (pidentify genetic features that predispose or protect individuals from LD-induced breast cancer.

  8. Transcriptome signature identifies distinct cervical pathways induced in lipopolysaccharide-mediated preterm birth.

    Science.gov (United States)

    Willcockson, Alexandra R; Nandu, Tulip; Liu, Cheuk-Lun; Nallasamy, Shanmugasundaram; Kraus, W Lee; Mahendroo, Mala

    2018-03-01

    With half a million babies born preterm each year in the USA and about 15 million worldwide, preterm birth (PTB) remains a global health issue. Preterm birth is a primary cause of infant morbidity and mortality and can impact lives long past infancy. The fact that there are numerous, and many currently unidentified, etiologies of PTB has hindered development of tools for risk evaluation and preventative therapies. Infection is estimated to be involved in nearly 40% of PTBs of known etiology; therefore, understanding how infection-mediated inflammation alters the cervical milieu and leads to preterm tissue biomechanical changes are questions of interest. Using RNA-seq, we identified enrichment of components involved in inflammasome activation and unique proteases in the mouse cervix during lipopolysaccharide (LPS)-mediated PTB and not physiologically at term before labor. Despite transcriptional induction of inflammasome components, there was no evidence of functional activation based on assessment of mature IL1B and IL18 proteins. The increased transcription of proteases that target both elastic fibers and collagen and concentration of myeloid-derived cells capable of protease synthesis in the cervical stroma support the structural disruption of elastic fibers as a functional output of protease activity. The recent demonstration that elastic fibers contribute to the biomechanical function of the pregnant cervix suggests their protease-induced disruption in the infection model of LPS-mediated PTB and may contribute to premature loss of mechanical competency and preterm delivery. Collectively, the transcriptomics and ultrastructural data provide new insights into the distinct mechanisms of premature cervical remodeling in response to infection.

  9. 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.

  10. Lipid Biomarkers Identified for Liver Cancer | Center for Cancer Research

    Science.gov (United States)

    Hepatocellular carcinoma (HCC) is an aggressive cancer of the liver with poor prognosis and growing incidence in developed countries. Pathology and genetic profiles of HCC are heterogeneous, suggesting that it can begin growing in different cell types. Although human tumors such as HCC have been profiled in-depth by genomics-based studies, not much is known about their overall

  11. 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

    controls using LNA-based quantitative real-time PCR (qRT-PCR). A signature of miRNAs was subsequently validated in an independent set of 111 serum samples from 60 patients with early-stage breast cancer and 51 healthy controls and further tested for reproducibility in 3 independent data sets from the GEO...... Database. RESULTS: A multivariable signature consisting of 9 miRNAs (miR-15a, miR-18a, miR-107, miR-133a, miR-139-5p, miR-143, miR-145, miR-365, miR-425) was identified that provided considerable discrimination between breast cancer patients and healthy controls. Further, the ability of the 9 mi......RNA signature to stratify samples from breast cancer patients and healthy controls was confirmed in the validation set (p = 0.012) with a corresponding AUC = 0.665 in the ROC-curve analysis. No association between miRNA expression and tumor grade, tumor size, menopausal- or lymph node status was observed...

  12. Lipidomic Profiling of Lung Pleural Effusion Identifies Unique Metabotype for EGFR Mutants in Non-Small Cell Lung Cancer

    OpenAIRE

    Ying Swan Ho; Lian Yee Yip; Nurhidayah Basri; Vivian Su Hui Chong; Chin Chye Teo; Eddy Tan; Kah Ling Lim; Gek San Tan; Xulei Yang; Si Yong Yeo; Mariko Si Yue Koh; Anantham Devanand; Angela Takano; Eng Huat Tan; Daniel Shao Weng Tan

    2016-01-01

    Cytology and histology forms the cornerstone for the diagnosis of non-small cell lung cancer (NSCLC) but obtaining sufficient tumour cells or tissue biopsies for these tests remains a challenge. We investigate the lipidome of lung pleural effusion (PE) for unique metabolic signatures to discriminate benign versus malignant PE and EGFR versus non-EGFR malignant subgroups to identify novel diagnostic markers that is independent of tumour cell availability. Using liquid chromatography mass spect...

  13. Signature pathways identified from gene expression profiles in the human uterine cervix before and after spontaneous term parturition

    Science.gov (United States)

    HASSAN, Sonia S.; ROMERO, Roberto; TARCA, Adi L.; DRAGHICI, Sorin; PINELES, Beth; BUGRIM, Andrej; KHALEK, Nahla; CAMACHO, Natalia; MITTAL, Pooja; YOON, Bo Hyun; ESPINOZA, Jimmy; KIM, Chong Jai; SOROKIN, Yoram; MALONE, John

    2008-01-01

    Objective This study aimed to discover ‘signature pathways’ characterizing biological processes based on genes differentially expressed in the uterine cervix before and after spontaneous labor. Study Design The cervical transcriptome was previously characterized from biopsies taken before and after term labor. Pathway analysis was used to study the differentially expressed genes based on two gene-to-pathway annotation databases (KEGG and Metacore™). Over-represented and highly impacted pathways and connectivity nodes were identified. Results Fifty-two pathways in the Metacore™ database were significantly enriched in differentially expressed genes. Three of the top 5 pathways were known to be involved in cervical remodeling.Two novel pathways were: plasmin signaling and plasminogen activator urokinase (PLAU) signaling. The same analysis in the KEGG database identified 4 significant pathways, of which impact analysis confirmed. Multiple nodes providing connectivity within the plasmin and PLAU signaling pathways were identified.. Conclusions Three strategies for pathway analysis were consistent in their identification of novel, unexpected as well as expected networks, suggesting that this approach is both valid and effective for the elucidation of biological mechanisms involved in cervical dilation and remodeling. PMID:17826407

  14. 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.

  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)

    Skiöld, Sara; Azimzadeh, Omid; Merl-Pham, Juliane; Naslund, Ingemar; Wersall, Peter; Lidbrink, Elisabet; Tapio, Soile; Harms-Ringdahl, Mats; Haghdoost, Siamak

    2015-01-01

    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. Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate cancer progression

    International Nuclear Information System (INIS)

    Oudes, Asa J; Roach, Jared C; Walashek, Laura S; Eichner, Lillian J; True, Lawrence D; Vessella, Robert L; Liu, Alvin Y

    2005-01-01

    Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases

  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

    2016-05-17

    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. 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.

  20. The response to neoadjuvant chemoradiotherapy with 5-fluorouracil in locally advanced rectal cancer patients: a predictive proteomic signature.

    Science.gov (United States)

    Chauvin, Anaïs; Wang, Chang-Shu; Geha, Sameh; Garde-Granger, Perrine; Mathieu, Alex-Ane; Lacasse, Vincent; Boisvert, François-Michel

    2018-01-01

    Colorectal cancer is the third most common and the fourth most lethal cancer in the world. In the majority of cases, patients are diagnosed at an advanced stage or even metastatic, thus explaining the high mortality. The standard treatment for patients with locally advanced non-metastatic rectal cancer is neoadjuvant radio-chemotherapy (NRCT) with 5-fluorouracil (5-FU) followed by surgery, but the resistance rate to this treatment remains high with approximately 30% of non-responders. The lack of evidence available in clinical practice to predict NRCT resistance to 5-FU and to guide clinical practice therefore encourages the search for biomarkers of this resistance. From twenty-three formalin-fixed paraffin-embedded (FFPE) biopsies performed before NRCT with 5-FU of locally advanced non-metastatic rectal cancer patients, we extracted and analysed the tumor proteome of these patients. From clinical data, we were able to classify the twenty-three patients in our cohort into three treatment response groups: non-responders (NR), partial responders (PR) and total responders (TR), and to compare the proteomes of these different groups. We have highlighted 384 differentially abundant proteins between NR and PR, 248 between NR and TR and 417 between PR and TR. Among these proteins, we have identified many differentially abundant proteins identified as having a role in cancer (IFIT1, FASTKD2, PIP4K2B, ARID1B, SLC25A33: overexpressed in TR; CALD1, CPA3, B3GALT5, CD177, RIPK1: overexpressed in NR). We have also identified that DPYD, the main degradation enzyme of 5-FU, was overexpressed in NR, as well as several ribosomal and mitochondrial proteins also overexpressed in NR. Data are available via ProteomeXchange with identifier PXD008440. From these retrospective study, we implemented a protein extraction protocol from FFPE biopsy to highlight protein differences between different response groups to RCTN with 5-FU in patients with locally advanced non-metastatic rectal cancer

  1. In silico mining identifies IGFBP3 as a novel target of methylation in prostate cancer.

    LENUS (Irish Health Repository)

    Perry, A S

    2007-05-21

    Promoter hypermethylation is central in deregulating gene expression in cancer. Identification of novel methylation targets in specific cancers provides a basis for their use as biomarkers of disease occurrence and progression. We developed an in silico strategy to globally identify potential targets of promoter hypermethylation in prostate cancer by screening for 5\\' CpG islands in 631 genes that were reported as downregulated in prostate cancer. A virtual archive of 338 potential targets of methylation was produced. One candidate, IGFBP3, was selected for investigation, along with glutathione-S-transferase pi (GSTP1), a well-known methylation target in prostate cancer. Methylation of IGFBP3 was detected by quantitative methylation-specific PCR in 49\\/79 primary prostate adenocarcinoma and 7\\/14 adjacent preinvasive high-grade prostatic intraepithelial neoplasia, but in only 5\\/37 benign prostatic hyperplasia (P < 0.0001) and in 0\\/39 histologically normal adjacent prostate tissue, which implies that methylation of IGFBP3 may be involved in the early stages of prostate cancer development. Hypermethylation of IGFBP3 was only detected in samples that also demonstrated methylation of GSTP1 and was also correlated with Gleason score > or =7 (P=0.01), indicating that it has potential as a prognostic marker. In addition, pharmacological demethylation induced strong expression of IGFBP3 in LNCaP prostate cancer cells. Our concept of a methylation candidate gene bank was successful in identifying a novel target of frequent hypermethylation in early-stage prostate cancer. Evaluation of further relevant genes could contribute towards a methylation signature of this disease.

  2. Metabolic signature of breast cancer cell line MCF-7: profiling of modified nucleosides via LC-IT MS coupling

    Directory of Open Access Journals (Sweden)

    Gleiter Christoph H

    2007-11-01

    Full Text Available Abstract Background Cancer, like other diseases accompanied by strong metabolic disorders, shows characteristic effects on cell turnover rate, activity of modifying enzymes and DNA/RNA modifications, resulting also in elevated amounts of excreted modified nucleosides. For a better understanding of the impaired RNA metabolism in breast cancer cells, we screened these metabolites in the cell culture supernatants of the breast cancer cell line MCF-7 and compared it to the human mammary epithelial cells MCF-10A. The nucleosides were isolated and analyzed via 2D-chromatographic techniques: In the first dimension by cis-diol specific boronate affinity extraction and subsequently by reversed phase chromatography coupled to an ion trap mass spectrometer. Results Besides the determination of ribonucleosides, additional compounds with cis-diol structure, deriving from cross-linked biochemical pathways, like purine-, histidine- and polyamine metabolism were detected. In total, 36 metabolites were identified by comparison of fragmentation patterns and retention time. Relation to the internal standard isoguanosine yielded normalized area ratios for each identified compound and enabled a semi-quantitative metabolic signature of both analyzed cell lines. 13 of the identified 26 modified ribonucleosides were elevated in the cell culture supernatants of MCF-7 cells, with 5-methyluridine, N2,N2,7-trimethylguanosine, N6-methyl-N6-threonylcarbamoyladenosine and 3-(3-aminocarboxypropyl-uridine showing the most significant differences. 1-ribosylimidazole-4-acetic acid, a histamine metabolite, was solely found in the supernatants of MCF-10A cells, whereas 1-ribosyl-4-carboxamido-5-aminoimidazole and S-adenosylmethionine occurred only in supernatants of MCF-7 cells. Conclusion The obtained results are discussed against the background of pathological changes in cell metabolism, resulting in new perspectives for modified nucleosides and related metabolites as possible

  3. 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......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 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....

  4. Association analysis identifies 65 new breast cancer risk loci

    Science.gov (United States)

    Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K.; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D.; Chen, Xiao Qing; Fachal, Laura; McCue, Karen; McCart Reed, Amy E.; Ghoussaini, Maya; Carroll, Jason; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N.; Arndt, Volker; Aronson, Kristan J.; Arun, Banu; Auer, Paul L.; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W.; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S.; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W.; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y.; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D.; Castelao, Jose E.; Chan, Tsun L.; Cheng, Ting-Yuan David; Chia, Kee Seng; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L.; Collée, Margriet; Conroy, Don M.; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Devilee, Peter; Doheny, Kimberly F.; Dörk, Thilo; dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M.; Ekici, Arif B.; Eliassen, A. Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M.; García-Sáenz, José A.; Gaudet, Mia M.; Georgoulias, Vassilios; Giles, Graham G.; Glendon, Gord; Goldberg, Mark S.; Goldgar, David E.; González-Neira, Anna; Grenaker Alnæs, Grethe I.; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A.; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N.; Hartikainen, Jaana M.; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M.; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J.; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I.; Kim, Sung-Won; Knight, Julia A.; Kosma, Veli-Matti; Kristensen, Vessela N.; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Marchand, Loic Le; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Lee, Chuen Neng; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P.; Ma, Edmond S.K.; MacInnis, Robert J.; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E.; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Mohd Taib, Nur Aishah; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F.; Noh, Dong-Young; Nordestgaard, Børge G.; Norman, Aaron; Olopade, Olufunmilayo I.; Olson, Janet E.; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V. Shane; Park, Sue K.; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I.A.; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofieva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S.; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J. Th.; Saloustros, Emmanouil; Sandler, Dale P.; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmutzler, Rita K.; Schneeweiss, Andreas; Schoemaker, Minouk J.; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J.; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E.; Shrubsole, Martha J.; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C.; Spinelli, John J.; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A.; Tengström, Maria; Teo, Soo H.; Terry, Mary Beth; Tessier, Daniel C.; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A.E.M.; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J.; Van Den Berg, David; van den Ouweland, Ans M.W.; van der Kolk, Lizet; van der Luijt, Rob B.; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R.; Wendt, Camilla; Whittemore, Alice S.; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H.; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R.; Yip, Cheng Har; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R.; Antoniou, Antonis C.; Droit, Arnaud; Andrulis, Irene L.; Amos, Christopher I.; Couch, Fergus J.; Pharoah, Paul D.P.; Chang-Claude, Jenny; Hall, Per; Hunter, David J.; Milne, Roger L.; García-Closas, Montserrat; Schmidt, Marjanka K.; Chanock, Stephen J.; Dunning, Alison M.; Edwards, Stacey L.; Bader, Gary D.; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F.

    2017-01-01

    Breast cancer risk is influenced by rare coding variants in susceptibility genes such as BRCA1 and many common, mainly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. We report results from a genome-wide association study (GWAS) of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry1. We identified 65 new loci associated with overall breast cancer at pcancer due to all SNPs in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the utility of genetic risk scores for individualized screening and prevention. PMID:29059683

  5. Association analysis identifies 65 new breast cancer risk loci

    DEFF Research Database (Denmark)

    Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe

    2017-01-01

    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast...... cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P risk single-nucleotide polymorphisms in these loci fall......-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores...

  6. Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

    Science.gov (United States)

    Drier, Yotam; Domany, Eytan

    2011-03-14

    The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

  7. Do two machine-learning based prognostic signatures for breast cancer capture the same biological processes?

    Directory of Open Access Journals (Sweden)

    Yotam Drier

    2011-03-01

    Full Text Available The fact that there is very little if any overlap between the genes of different prognostic signatures for early-discovery breast cancer is well documented. The reasons for this apparent discrepancy have been explained by the limits of simple machine-learning identification and ranking techniques, and the biological relevance and meaning of the prognostic gene lists was questioned. Subsequently, proponents of the prognostic gene lists claimed that different lists do capture similar underlying biological processes and pathways. The present study places under scrutiny the validity of this claim, for two important gene lists that are at the focus of current large-scale validation efforts. We performed careful enrichment analysis, controlling the effects of multiple testing in a manner which takes into account the nested dependent structure of gene ontologies. In contradiction to several previous publications, we find that the only biological process or pathway for which statistically significant concordance can be claimed is cell proliferation, a process whose relevance and prognostic value was well known long before gene expression profiling. We found that the claims reported by others, of wider concordance between the biological processes captured by the two prognostic signatures studied, were found either to be lacking statistical rigor or were in fact based on addressing some other question.

  8. Urinary volatile compounds as biomarkers for lung cancer: a proof of principle study using odor signatures in mouse models of lung cancer.

    Directory of Open Access Journals (Sweden)

    Koichi Matsumura

    2010-01-01

    Full Text Available A potential strategy for diagnosing lung cancer, the leading cause of cancer-related death, is to identify metabolic signatures (biomarkers of the disease. Although data supports the hypothesis that volatile compounds can be detected in the breath of lung cancer patients by the sense of smell or through bioanalytical techniques, analysis of breath samples is cumbersome and technically challenging, thus limiting its applicability. The hypothesis explored here is that variations in small molecular weight volatile organic compounds ("odorants" in urine could be used as biomarkers for lung cancer. To demonstrate the presence and chemical structures of volatile biomarkers, we studied mouse olfactory-guided behavior and metabolomics of volatile constituents of urine. Sensor mice could be trained to discriminate between odors of mice with and without experimental tumors demonstrating that volatile odorants are sufficient to identify tumor-bearing mice. Consistent with this result, chemical analyses of urinary volatiles demonstrated that the amounts of several compounds were dramatically different between tumor and control mice. Using principal component analysis and supervised machine-learning, we accurately discriminated between tumor and control groups, a result that was cross validated with novel test groups. Although there were shared differences between experimental and control animals in the two tumor models, we also found chemical differences between these models, demonstrating tumor-based specificity. The success of these studies provides a novel proof-of-principle demonstration of lung tumor diagnosis through urinary volatile odorants. This work should provide an impetus for similar searches for volatile diagnostic biomarkers in the urine of human lung cancer patients.

  9. Terahertz spectral unmixing based method for identifying gastric cancer

    Science.gov (United States)

    Cao, Yuqi; Huang, Pingjie; Li, Xian; Ge, Weiting; Hou, Dibo; Zhang, Guangxin

    2018-02-01

    At present, many researchers are exploring biological tissue inspection using terahertz time-domain spectroscopy (THz-TDS) techniques. In this study, based on a modified hard modeling factor analysis method, terahertz spectral unmixing was applied to investigate the relationships between the absorption spectra in THz-TDS and certain biomarkers of gastric cancer in order to systematically identify gastric cancer. A probability distribution and box plot were used to extract the distinctive peaks that indicate carcinogenesis, and the corresponding weight distributions were used to discriminate the tissue types. The results of this work indicate that terahertz techniques have the potential to detect different levels of cancer, including benign tumors and polyps.

  10. Systematic profiling of alternative splicing signature reveals prognostic predictor for ovarian cancer.

    Science.gov (United States)

    Zhu, Junyong; Chen, Zuhua; Yong, Lei

    2018-02-01

    The majority of genes are alternatively spliced and growing evidence suggests that alternative splicing is modified in cancer and is associated with cancer progression. Systematic analysis of alternative splicing signature in ovarian cancer is lacking and greatly needed. We profiled genome-wide alternative splicing events in 408 ovarian serous cystadenocarcinoma (OV) patients in TCGA. Seven types of alternative splicing events were curated and prognostic analyses were performed with predictive models and splicing network built for OV patients. Among 48,049 mRNA splicing events in 10,582 genes, we detected 2,611 alternative splicing events in 2,036 genes which were significant associated with overall survival of OV patients. Exon skip events were the most powerful prognostic factors among the seven types. The area under the curve of the receiver-operator characteristic curve for prognostic predictor, which was built with top significant alternative splicing events, was 0.937 at 2,000 days of overall survival, indicating powerful efficiency in distinguishing patient outcome. Interestingly, splicing correlation network suggested obvious trends in the role of splicing factors in OV. In summary, we built powerful prognostic predictors for OV patients and uncovered interesting splicing networks which could be underlying mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Optimized outcome prediction in breast cancer by combining the 70-gene signature with clinical risk prediction algorithms

    NARCIS (Netherlands)

    Drukker, C.A.; Nijenhuis, M.V.; Bueno de Mesquita, J.M.; Retel, V.P.; Retel, Valesca; van Harten, Willem H.; van Tinteren, H.; Wesseling, J.; Schmidt, M.K.; van 't Veer, L.J.; Sonke, G.S.; Rutgers, E.J.T.; van de Vijver, M.J.; Linn, S.C.

    2014-01-01

    Clinical guidelines for breast cancer treatment differ in their selection of patients at a high risk of recurrence who are eligible to receive adjuvant systemic treatment (AST). The 70-gene signature is a molecular tool to better guide AST decisions. The aim of this study was to evaluate whether

  12. 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.

  13. Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.

    Science.gov (United States)

    Ackermann, Amanda M; Wang, Zhiping; Schug, Jonathan; Naji, Ali; Kaestner, Klaus H

    2016-03-01

    human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

  14. 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 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.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.The method showed high sensitivity in a collection of specimens in which a significant portion of the total (13/31, equal to 42% was considered CaP on the basis

  15. Molecular signatures of thyroid follicular neoplasia

    DEFF Research Database (Denmark)

    Borup, R.; Rossing, M.; Henao, Ricardo

    2010-01-01

    The molecular pathways leading to thyroid follicular neoplasia are incompletely understood, and the diagnosis of follicular tumors is a clinical challenge. To provide leads to the pathogenesis and diagnosis of the tumors, we examined the global transcriptome signatures of follicular thyroid...... a mechanism for cancer progression, which is why we exploited the results in order to generate a molecular classifier that could identify 95% of all carcinomas. Validation employing public domain and cross-platform data demonstrated that the signature was robust and could diagnose follicular nodules...... and robust genetic signature for the diagnosis of FA and FC. Endocrine-Related Cancer (2010) 17 691-708...

  16. Massively parallel signature sequencing and bioinformatics analysis identifies up-regulation of TGFBI and SOX4 in human glioblastoma.

    Directory of Open Access Journals (Sweden)

    Biaoyang Lin

    Full Text Available BACKGROUND: A comprehensive network-based understanding of molecular pathways abnormally altered in glioblastoma multiforme (GBM is essential for developing effective therapeutic approaches for this deadly disease. METHODOLOGY/PRINCIPAL FINDINGS: Applying a next generation sequencing technology, massively parallel signature sequencing (MPSS, we identified a total of 4535 genes that are differentially expressed between normal brain and GBM tissue. The expression changes of three up-regulated genes, CHI3L1, CHI3L2, and FOXM1, and two down-regulated genes, neurogranin and L1CAM, were confirmed by quantitative PCR. Pathway analysis revealed that TGF- beta pathway related genes were significantly up-regulated in GBM tumor samples. An integrative pathway analysis of the TGF beta signaling network identified two alternative TGF-beta signaling pathways mediated by SOX4 (sex determining region Y-box 4 and TGFBI (Transforming growth factor beta induced. Quantitative RT-PCR and immunohistochemistry staining demonstrated that SOX4 and TGFBI expression is elevated in GBM tissues compared with normal brain tissues at both the RNA and protein levels. In vitro functional studies confirmed that TGFBI and SOX4 expression is increased by TGF-beta stimulation and decreased by a specific inhibitor of TGF-beta receptor 1 kinase. CONCLUSIONS/SIGNIFICANCE: Our MPSS database for GBM and normal brain tissues provides a useful resource for the scientific community. The identification of non-SMAD mediated TGF-beta signaling pathways acting through SOX4 and TGFBI (GENE ID:7045 in GBM indicates that these alternative pathways should be considered, in addition to the canonical SMAD mediated pathway, in the development of new therapeutic strategies targeting TGF-beta signaling in GBM. Finally, the construction of an extended TGF-beta signaling network with overlaid gene expression changes between GBM and normal brain extends our understanding of the biology of GBM.

  17. Identifying Malnutrition: Nutritional Status in Newly Diagnosed Patients With Cancer.

    Science.gov (United States)

    Krishnasamy, Karthikayini; Li Yoong, Tang; Mei Chan, Chong; Peng Choong, Lau; Chinna, Karuthan

    2017-02-01

    Malnutrition is common among patients with cancer, but little attention is given to its risks and consequences. The aim of this study is to assess the nutritional status and identify the factors associated with malnutrition among newly diagnosed patients with cancer. Patients admitted with newly diagnosed cancer at a teaching hospital in Malaysia were recruited from January to April 2015. Nutritional status was assessed before treatment initiation, and patients were classified into three categories. A total of 132 pretreatment patients were recruited into the study. About half were severely malnourished. Patients with stage III cancer had the highest prevalence of severe malnourishment. Clinical parameters and disease characteristics were significantly associated with nutritional status. Demographic variables were also statistically significantly associated with severe nutritional status.

  18. In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer

    Science.gov (United States)

    Colaprico, Antonio; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-01

    Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. PMID:29562723

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

    International Nuclear Information System (INIS)

    Tutt, Andrew; Shu, Henry; Springall, Robert; Cane, Paul; McCallie, Blair; Kam-Morgan, Lauren; Anderson, Steve; Buerger, Horst; Gray, Joe; Bennington, James; Esserman, Laura; Wang, Alice; Hastie, Trevor; Broder, Samuel; Sninsky, John; Brandt, Burkhard; Waldman, Fred; Rowland, Charles; Gillett, Cheryl; Lau, Kit; Chew, Karen; Dai, Hongyue; Kwok, Shirley; Ryder, Kenneth

    2008-01-01

    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. 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. A 14-gene signature was found to be significantly associated (p < 0.05) with distant metastasis in a training set and subsequently in an independent validation set. In the validation set, the hazard ratios (HR) of the high risk compared to low risk groups were 4.02 (95% CI 1.91–8.44) for the endpoint of DMFS and 1.97 (95% CI 1.28 to 3.04) for overall survival after adjustment for age, tumor size and grade. The low and high MS risk groups had 10-year estimates (95% CI) of 96% (90–99%) and 72% (64–78%) respectively, for DMFS and 91% (84–95%) and 68% (61–75%), respectively for overall survival. Performance characteristics of the signature in the two sets were similar. Ki-67 labeling index (LI) was predictive for recurrent disease in the training set, but lost significance after adjustment for the expression signature. In a study of tamoxifen-treated patients, the HR for DMFS in high compared to low risk groups was 3.61 (95% CI 0.86–15.14). The 14-gene signature is significantly

  20. 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 gen...

  1. Association analysis identifies 65 new breast cancer risk loci.

    Science.gov (United States)

    Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D; Qing Chen, Xiao; Fachal, Laura; McCue, Karen; McCart Reed, Amy E; Ghoussaini, Maya; Carroll, Jason S; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Aronson, Kristan J; Arun, Banu; Auer, Paul L; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D; Castelao, Jose E; Chan, Tsun L; David Cheng, Ting-Yuan; Seng Chia, Kee; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L; Collée, Margriet; Conroy, Don M; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Doheny, Kimberly F; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M; Ekici, Arif B; Eliassen, A Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M; García-Sáenz, José A; Gaudet, Mia M; Georgoulias, Vassilios; Giles, Graham G; Glendon, Gord; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Grenaker Alnæs, Grethe I; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Robert N; Hopper, John L; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Kosma, Veli-Matti; Kristensen, Vessela N; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Le Marchand, Loic; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Neng Lee, Chuen; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P; Ma, Edmond S K; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Malone, Kathleen E; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Taib, Nur Aishah Mohd; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F; Noh, Dong-Young; Nordestgaard, Børge G; Norman, Aaron; Olopade, Olufunmilayo I; Olson, Janet E; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V Shane; Park, Sue K; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofyeva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J T; Saloustros, Emmanouil; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schmutzler, Rita K; Schneeweiss, Andreas; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E; Shrubsole, Martha J; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A; Tengström, Maria; Teo, Soo H; Beth Terry, Mary; Tessier, Daniel C; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-Chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van der Kolk, Lizet; van der Luijt, Rob B; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R; Wendt, Camilla; Whittemore, Alice S; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R; Har Yip, Cheng; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R; Antoniou, Antonis C; Droit, Arnaud; Andrulis, Irene L; Amos, Christopher I; Couch, Fergus J; Pharoah, Paul D P; Chang-Claude, Jenny; Hall, Per; Hunter, David J; Milne, Roger L; García-Closas, Montserrat; Schmidt, Marjanka K; Chanock, Stephen J; Dunning, Alison M; Edwards, Stacey L; Bader, Gary D; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F

    2017-11-02

    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10 -8 . The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

  2. 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.

  3. PSA response signatures - a powerful new prognostic indicator after radiation for prostate cancer?

    International Nuclear Information System (INIS)

    Denham, James W.; Lamb, David S.; Joseph, David; Matthews, John; Atkinson, Chris; Spry, Nigel A.; Duchesne, Gillian; Ebert, Martin; Steigler, Allison; D'Este, Catherine

    2009-01-01

    Background: We sought to determine whether inter-patient variations in pattern of PSA changes after radiation exist and, if so, are they prognostically significant. Methods: In the Trans-Tasman Radiation Oncology Group (TROG) 96.01 randomized controlled trial, patients with T2b,c,3,4 N0 prostate cancer (PC) were randomised to 0, 3 or 6 months maximal androgen deprivation prior to 66 Gy to the prostate and seminal vesicles (XRT). Patterns of anatomical site of failure were one of the trial endpoints. Serial serum PSA's were mandated at all follow-up visits. Pattern recognition software was developed to characterize PSA response 'signatures' (PRS) after therapy in individual patients. Results: By 2000, 270 eligible patients were randomised to radiation alone. Individual patient PSA values were observed to descend after radiation according to one of two characteristic 'signatures': single exponential (PRS Type 1), non-exponential (PRS Type 2). Compared to PRS Type 1, men with PRS Type 2 (50% of the group) had lower PSA nadir (nPSA) levels (p < .0001), longer doubling times on relapse (p = .006) and significantly lower rates of local (hazard ratio [HR]: 0.47, 95% confidence interval [0.30-0.75], p = .0014) and distant failure (HR: 0.25[0.13-0.46], p < .0001), death due to PC (HR: 0.20[0.10-0.42], p < .0001) and death due to any cause (HR: 0.37 [0.23-0.60], p < .0001). PRS retained its powerful prognostic significance in Cox models that incorporated all key pre-treatment covariates and nPSA. Conclusions: PRS reflect the presence of tumor phenotypes that vary substantially in their clinical behavior and response to XRT. Molecular characterization is now necessary

  4. Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

    International Nuclear Information System (INIS)

    Klopfleisch, Robert; Lenze, Dido; Hummel, Michael; Gruber, Achim D

    2010-01-01

    Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs are in some aspects suitable as a

  5. Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer.

    Science.gov (United States)

    Zang, Hongyan; Li, Ning; Pan, Yuling; Hao, Jingguang

    2017-03-01

    Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

  6. Identifying candidate driver genes by integrative ovarian cancer genomics data

    Science.gov (United States)

    Lu, Xinguo; Lu, Jibo

    2017-08-01

    Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

  7. A gene expression signature of retinoblastoma loss-of-function is a predictive biomarker of resistance to palbociclib in breast cancer cell lines and is prognostic in patients with ER positive early breast cancer.

    Science.gov (United States)

    Malorni, Luca; Piazza, Silvano; Ciani, Yari; Guarducci, Cristina; Bonechi, Martina; Biagioni, Chiara; Hart, Christopher D; Verardo, Roberto; Di Leo, Angelo; Migliaccio, Ilenia

    2016-09-13

    Palbociclib is a CDK4/6 inhibitor that received FDA approval for treatment of hormone receptor positive (HR+) HER2 negative (HER2neg) advanced breast cancer. To better personalize patients treatment it is critical to identify subgroups that would mostly benefit from it. We hypothesize that complex alterations of the Retinoblastoma (Rb) pathway might be implicated in resistance to CDK4/6 inhibitors and aim to investigate whether signatures of Rb loss-of-function would identify breast cancer cell lines resistant to palbociclib. We established a gene expression signature of Rb loss-of-function (RBsig) by identifying genes correlated with E2F1 and E2F2 expression in breast cancers within The Cancer Genome Atlas. We assessed the RBsig prognostic role in the METABRIC and in a comprehensive breast cancer meta-dataset. Finally, we analyzed whether RBsig would discriminate palbociclib-sensitive and -resistant breast cancer cells in a large RNA sequencing-based dataset. The RBsig was associated with RB1 genetic status in all tumors (p <7e-32) and in luminal or basal subtypes (p < 7e-11 and p < 0.002, respectively). The RBsig was prognostic in the METABRIC dataset (discovery: HR = 1.93 [1.5-2.4] p = 1.4e-08; validation: HR = 2.01 [1.6-2.5] p = 1.3e-09). Untreated and endocrine treated patients with estrogen receptor positive breast cancer expressing high RBsig had significantly worse recurrence free survival compared to those with low RBsig (HR = 2.37 [1.8 - 3.2] p = 1.87e-08 and HR = 2.62 [1.9- 3.5] p = 8.6e-11, respectively). The RBsig was able to identify palbociclib resistant and sensitive breast cancer cells (ROC AUC = 0,7778). Signatures of RB loss might be helpful in personalizing treatment of patients with HR+/HER2neg breast cancer. Further validation in patients receiving palbociclib is warranted.

  8. Constructive Technology Assessment (CTA) as a tool in coverage with evidence development: the case of the 70-gene prognosis signature for breast cancer diagnostics.

    Science.gov (United States)

    Retèl, Valesca P; Bueno-de-Mesquita, Jolien M; Hummel, Marjan J M; van de Vijver, Marc J; Douma, Kirsten F L; Karsenberg, Kim; van Dam, Frits S A M; van Krimpen, Cees; Bellot, Frank E; Roumen, Rudi M H; Linn, Sabine C; van Harten, Wim H

    2009-01-01

    Constructive Technology Assessment (CTA) is a means to guide early implementation of new developments in society, and can be used as an evaluation tool for Coverage with Evidence Development (CED). We used CTA for the introduction of a new diagnostic test in the Netherlands, the 70-gene prognosis signature (MammaPrint) for node-negative breast cancer patients. Studied aspects were (organizational) efficiency, patient-centeredness and diffusion scenarios. Pre-post structured surveys were conducted in fifteen community hospitals concerning changes in logistics and teamwork as a consequence of the introduction of the 70-gene signature. Patient-centeredness was measured by questionnaires and interviews regarding knowledge and psychological impact of the test. Diffusion scenarios, which are commonly applied in industry to anticipate on future development and diffusion of their products, have been applied in this study. Median implementation-time of the 70-gene signature was 1.2 months. Most changes were seen in pathology processes and adjuvant treatment decisions. Physicians valued the addition of the 70-gene signature information as beneficial for patient management. Patient-centeredness (n = 77, response 78 percent): patients receiving a concordant high-risk and discordant clinical low/high risk-signature showed significantly more negative emotions with respect to receiving both test-results compared with concordant low-risk and discordant clinical high/low risk-signature patients. The first scenario was written in 2004 before the introduction of the 70-gene signature and identified hypothetical developments that could influence diffusion; especially the "what-if" deviation describing a discussion on validity among physicians proved to be realistic. Differences in speed of implementation and influenced treatment decisions were seen. Impact on patients seems especially related to discordance and its successive communication. In the future, scenario drafting will lead

  9. Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle.

    Science.gov (United States)

    Sharifi, Somayeh; Pakdel, Abbas; Ebrahimi, Mansour; Reecy, James M; Fazeli Farsani, Samaneh; Ebrahimie, Esmaeil

    2018-01-01

    Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the main agents that cause severe mastitis disease with clinical signs in dairy cattle. Rapid detection of this disease is so important in order to prevent transmission to other cows and helps to reduce inappropriate use of antibiotics. With the rapid progress in high-throughput technologies, and accumulation of various kinds of '-omics' data in public repositories, there is an opportunity to retrieve, integrate, and reanalyze these resources to improve the diagnosis and treatment of different diseases and to provide mechanistic insights into host resistance in an efficient way. Meta-analysis is a relatively inexpensive option with good potential to increase the statistical power and generalizability of single-study analysis. In the current meta-analysis research, six microarray-based studies that investigate the transcriptome profile of mammary gland tissue after induced mastitis by E. coli infection were used. This meta-analysis not only reinforced the findings in individual studies, but also several novel terms including responses to hypoxia, response to drug, anti-apoptosis and positive regulation of transcription from RNA polymerase II promoter enriched by up-regulated genes. Finally, in order to identify the small sets of genes that are sufficiently informative in E. coli mastitis, the differentially expressed gene introduced by meta-analysis were prioritized by using ten different attribute weighting algorithms. Twelve meta-genes were detected by the majority of attribute weighting algorithms (with weight above 0.7) as most informative genes including CXCL8 (IL8), NFKBIZ, HP, ZC3H12A, PDE4B, CASP4, CXCL2, CCL20, GRO1(CXCL1), CFB, S100A9, and S100A8. Interestingly, the results have been demonstrated that all of these genes are the key genes in the immune response, inflammation or mastitis. The Decision tree models efficiently discovered the best combination of the meta-genes as

  10. Lung cancer and risk factors: how to identify phenotypic markers?

    International Nuclear Information System (INIS)

    Clement-Duchene, Christelle

    2009-01-01

    Lung cancer is the leading cause of death in the world. Most lung cancer are diagnosed at an advanced stage (IIIB and IV), with a poor prognosis. The main risk factors are well known like active smoking, and occupational exposure (asbestos), but 10 a 20% occur in never smokers. In this population, various studies have been conducted in order to identify possible risk factors, and although many have been identified, none seem to explain more than a small percentage of the cases. According to the histological types, adenocarcinoma is now the more frequent type, and its association with the main risk factors (tobacco exposure, asbestos exposure) is still studied. The tumoral location is associated with the exposure to the risk factors. Finally, the survival seems to be different between gender, and between smokers, and never smokers. All these characteristics are perhaps associated with different pathways of carcinogenesis. In this context, we have analyzed a cohort of 1493 patients with lung cancer in order to identify phenotypic markers, and to understand the mechanisms of the lung carcinogenesis. (author) [fr

  11. Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities

    Science.gov (United States)

    2017-10-01

    15.3%) NA 6 (6%) 6 (5.4%) Prostate - specific Antigen (PSA) ng/mL 76.7 (42.9) 78.2 (40.7) pTNM Stage T2 68 (67.3%) 48 (43.2%) T3 29 (28.7%) 58...Profiles Primary Aim #1: Determine if methylation profiles differ by race/ancestry Primary Aim #2: Identify ethnicity- specific markers of prostate ...by ethnicity and to identify ethnicity- specific methylation features of prostate cancer that could contribute the racial disparities that exist in

  12. Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.

    Science.gov (United States)

    San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul

    2014-12-01

    Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.

  13. 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

    Genes that are commonly deregulated in cancer are clinically attractive as candidate pan-diagnostic markers and therapeutic targets. To globally identify such targets, we compared Cap Analysis of Gene Expression (CAGE) profiles from 225 different cancer cell lines and 339 corresponding primary cell...

  14. 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.

  15. Multiplex flow cytometry barcoding and antibody arrays identify surface antigen profiles of primary and metastatic colon cancer cell lines.

    Directory of Open Access Journals (Sweden)

    Kumar Sukhdeo

    Full Text Available Colon cancer is a deadly disease affecting millions of people worldwide. Current treatment challenges include management of disease burden as well as improvements in detection and targeting of tumor cells. To identify disease state-specific surface antigen signatures, we combined fluorescent cell barcoding with high-throughput flow cytometric profiling of primary and metastatic colon cancer lines (SW480, SW620, and HCT116. Our multiplexed technique offers improvements over conventional methods by permitting the simultaneous and rapid screening of cancer cells with reduced effort and cost. The method uses a protein-level analysis with commercially available antibodies on live cells with intact epitopes to detect potential tumor-specific targets that can be further investigated for their clinical utility. Multiplexed antibody arrays can easily be applied to other tumor types or pathologies for discovery-based approaches to target identification.

  16. 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 accumulation of similar genomic scars also show increased sensitivity to platinum-based chemotherapy. Therefore, reliable biomarkers to identify DNA repair-deficient cancers prior to treatment may be useful for directing patients to platinum chemotherapy and possibly PARP inhibitors. Recently, three SNP array...... may be strong candidates for clinical trials with PARP inhibitors or platinum-based chemotherapeutic regimens....

  17. Molecular profiling of prostate cancer derived exosomes may reveal a predictive signature for response to docetaxel.

    Science.gov (United States)

    Kharaziha, Pedram; Chioureas, Dimitris; Rutishauser, Dorothea; Baltatzis, George; Lennartsson, Lena; Fonseca, Pedro; Azimi, Alireza; Hultenby, Kjell; Zubarev, Roman; Ullén, Anders; Yachnin, Jeffrey; Nilsson, Sten; Panaretakis, Theocharis

    2015-08-28

    Docetaxel is a cornerstone treatment for metastatic, castration resistant prostate cancer (CRPC) which remains a leading cause of cancer-related deaths, worldwide. The clinical usage of docetaxel has resulted in modest gains in survival, primarily due to the development of resistance. There are currently no clinical biomarkers available that predict whether a CRPC patient will respond or acquire resistance to this therapy. Comparative proteomics analysis of exosomes secreted from DU145 prostate cancer cells that are sensitive (DU145 Tax-Sen) or have acquired resistance (DU145 Tax-Res) to docetaxel, demonstrated significant differences in the amount of exosomes secreted and in their molecular composition. A panel of proteins was identified by proteomics to be differentially enriched in DU145 Tax-Res compared to DU145 Tax-Sen exosomes and was validated by western blotting. Importantly, we identified MDR-1, MDR-3, Endophilin-A2 and PABP4 that were enriched only in DU145 Tax-Res exosomes. We validated the presence of these proteins in the serum of a small cohort of patients. DU145 cells that have uptaken DU145 Tax-Res exosomes show properties of increased matrix degradation. In summary, exosomes derived from DU145 Tax-Res cells may be a valuable source of biomarkers for response to therapy.

  18. 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.

  19. DNA methylation analysis of paediatric low-grade astrocytomas identifies a tumour-specific hypomethylation signature in pilocytic astrocytomas.

    Science.gov (United States)

    Jeyapalan, Jennie N; Doctor, Gabriel T; Jones, Tania A; Alberman, Samuel N; Tep, Alexander; Haria, Chirag M; Schwalbe, Edward C; Morley, Isabel C F; Hill, Alfred A; LeCain, Magdalena; Ottaviani, Diego; Clifford, Steven C; Qaddoumi, Ibrahim; Tatevossian, Ruth G; Ellison, David W; Sheer, Denise

    2016-05-27

    Low-grade gliomas (LGGs) account for about a third of all brain tumours in children. We conducted a detailed study of DNA methylation and gene expression to improve our understanding of the biology of pilocytic and diffuse astrocytomas. Pilocytic astrocytomas were found to have a distinctive signature at 315 CpG sites, of which 312 were hypomethylated and 3 were hypermethylated. Genomic analysis revealed that 182 of these sites are within annotated enhancers. The signature was not present in diffuse astrocytomas, or in published profiles of other brain tumours and normal brain tissue. The AP-1 transcription factor was predicted to bind within 200 bp of a subset of the 315 differentially methylated CpG sites; the AP-1 factors, FOS and FOSL1 were found to be up-regulated in pilocytic astrocytomas. We also analysed splice variants of the AP-1 target gene, CCND1, which encodes cell cycle regulator cyclin D1. CCND1a was found to be highly expressed in both pilocytic and diffuse astrocytomas, but diffuse astrocytomas have far higher expression of the oncogenic variant, CCND1b. These findings highlight novel genetic and epigenetic differences between pilocytic and diffuse astrocytoma, in addition to well-described alterations involving BRAF, MYB and FGFR1.

  20. Inflammation, Adenoma and Cancer: Objective Classification of Colon Biopsy Specimens with Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Orsolya Galamb

    2008-01-01

    Full Text Available Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples, colorectal carcinomas (CRC (15 and inflammatory bowel diseases (IBD (14. Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2. Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

  1. Prediction of disease-free survival by the PET/CT radiomic signature in non-small cell lung cancer patients undergoing surgery

    Energy Technology Data Exchange (ETDEWEB)

    Kirienko, Margarita; Fogliata, Antonella; Sollini, Martina [Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Milan (Italy); Cozzi, Luca [Humanitas Clinical and Research Center, Radiotherapy and Radiosurgery, Rozzano, Milan (Italy); Antunovic, Lidija [Humanitas Clinical and Research Center, Nuclear Medicine, Rozzano, Milan (Italy); Lozza, Lisa [Orobix Srl, Bergamo (Italy); Voulaz, Emanuele [Humanitas Clinical and Research Center, Thoracic Surgery, Rozzano, Milan (Italy); Rossi, Alexia [Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Milan (Italy); Humanitas Clinical and Research Center, Radiology, Rozzano, Milan (Italy); Chiti, Arturo [Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, Milan (Italy); Humanitas Clinical and Research Center, Nuclear Medicine, Rozzano, Milan (Italy)

    2018-02-15

    Radiomic features derived from the texture analysis of different imaging modalities e show promise in lesion characterisation, response prediction, and prognostication in lung cancer patients. The present study aimed to identify an images-based radiomic signature capable of predicting disease-free survival (DFS) in non-small cell lung cancer (NSCLC) patients undergoing surgery. A cohort of 295 patients was selected. Clinical parameters (age, sex, histological type, tumour grade, and stage) were recorded for all patients. The endpoint of this study was DFS. Both computed tomography (CT) and fluorodeoxyglucose positron emission tomography (PET) images generated from the PET/CT scanner were analysed. Textural features were calculated using the LifeX package. Statistical analysis was performed using the R platform. The datasets were separated into two cohorts by random selection to perform training and validation of the statistical models. Predictors were fed into a multivariate Cox proportional hazard regression model and the receiver operating characteristic (ROC) curve as well as the corresponding area under the curve (AUC) were computed for each model built. The Cox models that included radiomic features for the CT, the PET, and the PET+CT images resulted in an AUC of 0.75 (95%CI: 0.65-0.85), 0.68 (95%CI: 0.57-0.80), and 0.68 (95%CI: 0.58-0.74), respectively. The addition of clinical predictors to the Cox models resulted in an AUC of 0.61 (95%CI: 0.51-0.69), 0.64 (95%CI: 0.53-0.75), and 0.65 (95%CI: 0.50-0.72) for the CT, the PET, and the PET+CT images, respectively. A radiomic signature, for either CT, PET, or PET/CT images, has been identified and validated for the prediction of disease-free survival in patients with non-small cell lung cancer treated by surgery. (orig.)

  2. Identification of a robust gene signature that predicts breast cancer outcome in independent data sets

    International Nuclear Information System (INIS)

    Korkola, James E; Waldman, Frederic M; Blaveri, Ekaterina; DeVries, Sandy; Moore, Dan H II; Hwang, E Shelley; Chen, Yunn-Yi; Estep, Anne LH; Chew, Karen L; Jensen, Ronald H

    2007-01-01

    Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients. We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression. A subset of 55 tumors with extensive follow-up was used to identify gene sets that predicted outcome. The predictive gene set was further tested in previously published data sets. We used different statistical methods to identify three gene sets associated with disease free survival. A fourth gene set, consisting of 21 genes in common to all three sets, also had the ability to predict patient outcome. To validate the predictive utility of this derived gene set, it was tested in two published data sets from other groups. This gene set resulted in significant separation of patients on the basis of survival in these data sets, correctly predicting outcome in 62–65% of patients. By comparing outcome prediction within subgroups based on ER status, grade, and nodal status, we found that our gene set was most effective in predicting outcome in ER positive and node negative tumors. This robust gene selection with extensive validation has identified a predictive gene set that may have clinical utility for outcome prediction in breast cancer patients

  3. Use of signature-tagged mutagenesis to identify virulence determinants in Haemophilus ducreyi responsible for ulcer formation.

    Science.gov (United States)

    Yeung, Angela; Cameron, D William; Desjardins, Marc; Lee, B Craig

    2011-02-01

    Elucidating the molecular mechanisms responsible for chancroid, a genital ulcer disease caused by Haemophilus ducreyi, has been hampered in part by the relative genetic intractability of the organism. A whole genome screen using signature-tagged mutagenesis in the temperature-dependent rabbit model (TDRM) of H. ducreyi infection uncovered 26 mutants with a presumptive attenuated phenotype. Insertions in two previously recognized virulence determinants, hgbA and lspA1, validated this genome scanning technique. Database interrogation allowed assignment of 24 mutants to several functional classes, including transport, metabolism, DNA repair, stress response and gene regulation. The attenuated virulence for a 3 strain with a mutation in hicB was confirmed by individual infection in the TDRM. The results from this preliminary study indicate that this high throughput strategy will further the understanding of the pathogenesis of H. ducreyi infection. Copyright © 2010 Elsevier B.V. All rights reserved.

  4. 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

    2010-01-01

    Full Text Available 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.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.Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.

  5. Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

    Science.gov (United States)

    Choi, Jonghwan; Park, Sanghyun; Yoon, Youngmi; Ahn, Jaegyoon

    2017-11-15

    Identification of genes that can be used to predict prognosis in patients with cancer is important in that it can lead to improved therapy, and can also promote our understanding of tumor progression on the molecular level. One of the common but fundamental problems that render identification of prognostic genes and prediction of cancer outcomes difficult is the heterogeneity of patient samples. To reduce the effect of sample heterogeneity, we clustered data samples using K-means algorithm and applied modified PageRank to functional interaction (FI) networks weighted using gene expression values of samples in each cluster. Hub genes among resulting prioritized genes were selected as biomarkers to predict the prognosis of samples. This process outperformed traditional feature selection methods as well as several network-based prognostic gene selection methods when applied to Random Forest. We were able to find many cluster-specific prognostic genes for each dataset. Functional study showed that distinct biological processes were enriched in each cluster, which seems to reflect different aspect of tumor progression or oncogenesis among distinct patient groups. Taken together, these results provide support for the hypothesis that our approach can effectively identify heterogeneous prognostic genes, and these are complementary to each other, improving prediction accuracy. https://github.com/mathcom/CPR. jgahn@inu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  6. 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. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  7. Radiation signatures

    International Nuclear Information System (INIS)

    McGlynn, S.P.; Varma, M.N.

    1992-01-01

    A new concept for modelling radiation risk is proposed. This concept is based on the proposal that the spectrum of molecular lesions, which we dub ''the radiation signature'', can be used to identify the quality of the causal radiation. If the proposal concerning radiation signatures can be established then, in principle, both prospective and retrospective risk determination can be assessed on an individual basis. A major goal of biophysical modelling is to relate physical events such as ionization, excitation, etc. to the production of radiation carcinogenesis. A description of the physical events is provided by track structure. The track structure is determined by radiation quality, and it can be considered to be the ''physical signature'' of the radiation. Unfortunately, the uniqueness characteristics of this signature are dissipated in biological systems in ∼10 -9 s. Nonetheless, it is our contention that this physical disturbance of the biological system eventuates later, at ∼10 0 s, in molecular lesion spectra which also characterize the causal radiation. (author)

  8. Tumour-derived exosomes as a signature of pancreatic cancer - liquid biopsies as indicators of tumour progression.

    Science.gov (United States)

    Nuzhat, Zarin; Kinhal, Vyjayanthi; Sharma, Shayna; Rice, Gregory E; Joshi, Virendra; Salomon, Carlos

    2017-03-07

    Pancreatic cancer is the fourth most common cause of death due to cancer in the world. It is known to have a poor prognosis, mostly because early stages of the disease are generally asymptomatic. Progress in pancreatic cancer research has been slow, leaving several fundamental questions pertaining to diagnosis and treatment unanswered. Recent studies highlight the putative utility of tissue-specific vesicles (i.e. extracellular vesicles) in the diagnosis of disease onset and treatment monitoring in pancreatic cancer. Extracellular vesicles are membrane-limited structures derived from the cell membrane. They contain specific molecules including proteins, mRNA, microRNAs and non-coding RNAs that are secreted in the extracellular space. Extracellular vesicles can be classified according to their size and/or origin into microvesicles (~150-1000 nm) and exosomes (~40-120 nm). Microvesicles are released by budding from the plasmatic membrane, whereas exosomes are released via the endocytic pathway by fusion of multivesicular bodies with the plasmatic membrane. This endosomal origin means that exosomes contain an abundance of cell-specific biomolecules which may act as a 'fingerprint' of the cell of origin. In this review, we discuss our current knowledge in the diagnosis and treatment of pancreatic cancer, particularly the potential role of EVs in these facets of disease management. In particular, we suggest that as exosomes contain cellular protein and RNA molecules in a cell type-specific manner, they may provide extensive information about the signature of the tumour and pancreatic cancer progression.

  9. Distinct Gene Expression Signatures in Lynch Syndrome and Familial Colorectal Cancer Type X

    DEFF Research Database (Denmark)

    Valentin, Mev; Therkildsen, Christina; Veerla, Srinivas

    2013-01-01

    Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects.......Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects....

  10. ColoFinder: a prognostic 9-gene signature improves prognosis for 871 stage II and III colorectal cancer patients

    Directory of Open Access Journals (Sweden)

    Mingguang Shi

    2016-03-01

    Full Text Available Colorectal cancer (CRC is a heterogeneous disease with a high mortality rate and is still lacking an effective treatment. Our goal is to develop a robust prognosis model for predicting the prognosis in CRC patients. In this study, 871 stage II and III CRC samples were collected from six gene expression profilings. ColoFinder was developed using a 9-gene signature based Random Survival Forest (RSF prognosis model. The 9-gene signature recurrence score was derived with a 5-fold cross validation to test the association with relapse-free survival, and the value of AUC was gained with 0.87 in GSE39582(95% CI [0.83–0.91]. The low-risk group had a significantly better relapse-free survival (HR, 14.8; 95% CI [8.17–26.8]; P < 0.001 than the high-risk group. We also found that the 9-gene signature recurrence score contributed more information about recurrence than standard clinical and pathological variables in univariate and multivariate Cox analyses when applied to GSE17536(p = 0.03 and p = 0.01 respectively. Furthermore, ColoFinder improved the predictive ability and better stratified the risk subgroups when applied to CRC gene expression datasets GSE14333, GSE17537, GSE12945and GSE24551. In summary, ColoFinder significantly improves the risk assessment in stage II and III CRC patients. The 9-gene prognostic classifier informs patient prognosis and treatment response.

  11. Glypican1 identifies cancer exosomes and facilitates early detection of cancer

    Science.gov (United States)

    Melo, Sonia A.; Luecke, Linda B.; Kahlert, Christoph; Fernandez, Agustin F.; Gammon, Seth T.; Kaye, Judith; LeBleu, Valerie S.; Mittendorf, Elizabeth A.; Weitz, Juergen; Rahbari, Nuh; Reissfelder, Christoph; Pilarsky, Christian; Fraga, Mario F.; Piwnica-Worms, David; Kalluri, Raghu

    2016-01-01

    Summary Exosomes are lipid bilayer-enclosed extracellular vesicles (EVs) that contain proteins and nucleic acids. They are secreted by all cells and circulate in the blood. Specific detection and isolation of cancer cell-derived exosomes in circulation is currently lacking. Using mass spectrometry analyses, we identified a cell surface proteoglycan, glypican-1 (GPC1), specifically enriched on cancer cell-derived exosomes. GPC1+ circulating exosomes (crExos) were monitored and isolated using flow cytometry from the serum of cancer patients and mice with cancer. GPC1+ crExos were detected in the serum of patients with pancreas cancer with absolute specificity and sensitivity, distinguishing healthy subjects and patients with a benign pancreas disease from patients with early and late stage pancreas cancer. Levels of GPC1+ crExos correlate with tumor burden and survival in patients pre- and post-surgical tumor resection. GPC1+ crExos from patients and from mice with spontaneous pancreas tumors driven by oncogenic KRAS contained RNA with specific KRAS mutation, and it emerges as a reliable biomarker for the detection of PanIN lesions despite negative signal by MRI in mice. GPC1+ crExos may serve as a potential non-invasive diagnostic and screening tool to detect early stages of pancreas cancer to facilitate possible curative surgical therapy. PMID:26106858

  12. Signatures derived from increase in SHARPIN gene copy number are associated with poor prognosis in patients with breast cancer

    Directory of Open Access Journals (Sweden)

    Diane Ojo

    2017-12-01

    Full Text Available We report three signatures produced from SHARPIN gene copy number increase (GCN-Increase and their effects on patients with breast cancer (BC. In the Metabric dataset (n = 2059, cBioPortal, SHARPIN GCN-Increase occurs preferentially or mutual exclusively with mutations in TP53, PIK3CA, and CDH1. These genomic alterations constitute a signature (SigMut that significantly correlates with reductions in overall survival (OS in BC patients (n = 1980; p = 1.081e−6. Additionally, SHARPIN GCN-Increase is associated with 4220 differentially expressed genes (DEGs. These DEGs are enriched in activation of the pathways regulating cell cycle progression, RNA transport, ribosome biosynthesis, DNA replication, and in downregulation of the pathways related to extracellular matrix. These DEGs are thus likely to facilitate the proliferation and metastasis of BC cells. Additionally, through forward (FWD and backward (BWD stepwise variate selections among the top 160 downregulated and top 200 upregulated DEGs using the Cox regression model, a 6-gene (SigFWD and a 50-gene (SigBWD signature were derived. Both signatures robustly associate with decreases in OS in BC patients within the Curtis (n = 1980; p = 6.16e−11 for SigFWD; p = 1.06e−10, for SigBWD and TCGA cohort (n = 817; p = 4.53e−4 for SigFWD and p = 0.00525 for SigBWD. After adjusting for known clinical factors, SigMut (HR 1.21, p = 0.0297, SigBWD (HR 1.25, p = 0.0263, and likely SigFWD (HR 1.17, p = 0.062 remain independent risk factors of BC deaths. Furthermore, the proportion of patients positive for these signatures is significantly increased in ER−, Her2-enriched, basal-like, and claudin-low BCs compared to ER+ and luminal BCs. Collectively, these SHARPIN GCN-Increase-derived signatures may have clinical applications in management of patients with BC.

  13. 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...

  14. Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology.

    Science.gov (United States)

    Smith, Benjamin R; Ashton, Katherine M; Brodbelt, Andrew; Dawson, Timothy; Jenkinson, Michael D; Hunt, Neil T; Palmer, David S; Baker, Matthew J

    2016-06-07

    Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical technique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy is very unpleasant for the patient, potentially dangerous and can occasionally be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm(-1). To begin the development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spectral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Furthermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete

  15. 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

    2016-03-03

    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.

  16. Phosphoproteomics of Primary Cells Reveals Druggable Kinase Signatures in Ovarian Cancer

    DEFF Research Database (Denmark)

    Francavilla, Chiara; Lupia, Michela; Tsafou, Kalliopi

    2017-01-01

    Our understanding of the molecular determinants of cancer is still inadequate because of cancer heterogeneity. Here, using epithelial ovarian cancer (EOC) as a model system, we analyzed a minute amount of patient-derived epithelial cells from either healthy or cancerous tissues by single-shot mas...

  17. 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

    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 evalua...

  18. 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...

  19. Exosomal microRNA Signatures in the Diagnosis and Prognosis of Ovarian Cancer

    Science.gov (United States)

    2013-10-01

    including CLL ,41 breast cancer,42 glioblastoma,43 thyroid papillary carcinoma,44 hepatocellular carcinoma,45 ovarian cancer,46 colon...modify cancer cell gene expression. Extracellular vesicles derived from cancer stem cells were shown to contain pro-angiogenic RNAs able to induce a pre...content differs. Extracellular vesicles from cancer stem cells contained miR29a, miR650, and miR151, all associated with tumor invasion and

  20. Genetic Mutation and Exosome Signature of Human Papilloma Virus Associated Oropharyngeal Cancer

    Science.gov (United States)

    Kannan, Anbarasu; Hertweck, Kate L.; Philley, Julie V.; Wells, Robert B.; Dasgupta, Santanu

    2017-01-01

    Human papilloma virus-16 (HPV-16) associated oropharyngeal cancer (HPVOPC) is increasing alarmingly in the United States. We performed whole genome sequencing of a 44 year old, male HPVOPC subject diagnosed with moderately differentiated tonsillar carcinoma. We identified new somatic mutation in MUC16 (A.k.a. CA-125), MUC12, MUC4, MUC6, MUC2, SIRPA, HLA-DRB1, HLA-A and HLA-B molecules. Increased protein expression of MUC16, SIRPA and decreased expression of HLA-DRB1 was further demonstrated in this HPVOPC subject and an additional set of 15 HPVOPC cases. Copy number gain (3 copies) was also observed for MUC2, MUC4, MUC6 and SIRPA. Enhanced expression of MUC16, SIRPA and HPV-16-E7 protein was detectable in the circulating exosomes of numerous HPVOPC subjects. Treatment of non-tumorigenic mammary epithelial cells with exosomes derived from aggressive HPVOPC cells harboring MUC16, SIRPA and HPV-16-E7 proteins augmented invasion and induced epithelial to mesenchymal transition (EMT) accompanied by an increased expression ratio of the EMT markers Vimentin/E-cadherin. Exosome based screening of key HPVOPC associated molecules could be beneficial for early cancer diagnosis, monitoring and surveillance. PMID:28383029

  1. Identifying the subtle signatures of feedback from distant AGN using ALMA observations and the EAGLE hydrodynamical simulations

    Science.gov (United States)

    Scholtz, J.; Alexander, D. M.; Harrison, C. M.; Rosario, D. J.; McAlpine, S.; Mullaney, J. R.; Stanley, F.; Simpson, J.; Theuns, T.; Bower, R. G.; Hickox, R. C.; Santini, P.; Swinbank, A. M.

    2018-03-01

    We present sensitive 870 μm continuum measurements from our ALMA programmes of 114 X-ray selected active galactic nuclei (AGN) in the Chandra Deep Field-South and Cosmic Evolution Survey fields. We use these observations in combination with data from Spitzer and Herschel to construct a sample of 86 X-ray selected AGN, 63 with ALMA constraints at z = 1.5-3.2 with stellar mass >2 × 1010 M⊙. We constructed broad-band spectral energy distributions in the infrared band (8-1000 μm) and constrain star-formation rates (SFRs) uncontaminated by the AGN. Using a hierarchical Bayesian method that takes into account the information from upper limits, we fit SFR and specific SFR (sSFR) distributions. We explore these distributions as a function of both X-ray luminosity and stellar mass. We compare our measurements to two versions of the Evolution and Assembly of GaLaxies and their Environments (EAGLE) hydrodynamical simulations: the reference model with AGN feedback and the model without AGN. We find good agreement between the observations and that predicted by the EAGLE reference model for the modes and widths of the sSFR distributions as a function of both X-ray luminosity and stellar mass; however, we found that the EAGLE model without AGN feedback predicts a significantly narrower width when compared to the data. Overall, from the combination of the observations with the model predictions, we conclude that (1) even with AGN feedback, we expect no strong relationship between the sSFR distribution parameters and instantaneous AGN luminosity and (2) a signature of AGN feedback is a broad distribution of sSFRs for all galaxies (not just those hosting an AGN) with stellar masses above ≈1010 M⊙.

  2. Signaling profiling at the single-cell level identifies a distinct signaling signature in murine hematopoietic stem cells.

    Science.gov (United States)

    Du, Juan; Wang, Jinyong; Kong, Guangyao; Jiang, Jing; Zhang, Jingfang; Liu, Yangang; Tong, Wei; Zhang, Jing

    2012-07-01

    Hematopoietic stem cell (HSC) function is tightly regulated by cytokine signaling. Although phospho-flow cytometry allows us to study signaling in defined populations of cells, there has been tremendous hurdle to carry out this study in rare HSCs due to unrecoverable critical HSC markers, low HSC number, and poor cell recovery rate. Here, we overcame these difficulties and developed a "HSC phospho-flow" method to analyze cytokine signaling in murine HSCs at the single-cell level and compare HSC signaling profile to that of multipotent progenitors (MPPs), a cell type immediately downstream of HSCs, and commonly used Lin(-) cKit(+) cells (LK cells, enriched for myeloid progenitors). We chose to study signaling evoked from three representative cytokines, stem cell factor (SCF) and thrombopoietin (TPO) that are essential for HSC function and granulocyte macrophage-colony-stimulating factor (GM-CSF) that is dispensable for HSCs. HSCs display a distinct TPO and GM-CSF signaling signature from MPPs and LK cells, which highly correlates with receptor surface expression. In contrast, although majority of LK cells express lower levels of cKit than HSCs and MPPs, SCF-evoked ERK1/2 activation in LK cells shows a significantly increased magnitude for a prolonged period. These results suggest that specific cellular context plays a more important role than receptor surface expression in SCF signaling. Our study of HSC signaling at the homeostasis stage paves the way to investigate signaling changes in HSCs under conditions of stress, aging, and hematopoietic diseases. Copyright © 2012 AlphaMed Press.

  3. 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.

  4. 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.

  5. Identifying Determinants of PARP Inhibitor Sensitivity in Ovarian Cancer

    Science.gov (United States)

    2017-10-01

    Cancer Center Philadelphia, PA 19111 REPORT DATE: TYPE OF REPORT: Annual PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick...in Ovarian Cancer October 2017 The views, opinions and/or findings contained in this report are those of the author(s) and should not be construed...ORGANIZATION NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER The Research Institute of Fox Chase Cancer Center 333 Cottman Avenue Philadelphia

  6. 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...... than in controls. These miRNAs were tested in the training cohort, and four diagnostic panels were constructed that included 5 or 12 miRNAs (miR-16, -18a, -20a, -24, -25, -27a, -29c, -30a.5p, -191, -323.3p, -345 and -483.5p). Diagnostic accuracy of detecting PC in the training cohort was AUC (Index I 0.......90-0.96) and accuracy 0.88 (0.84-0.91)]. In conclusion, we identified four diagnostic panels based on 5 or 12 miRNAs in serum that could distinguish patients with PC from HS and CP....

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

    Science.gov (United States)

    Sánchez-Aragó, María; Cuezva, José M

    2011-02-08

    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). 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. 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. Overall, we suggest that the determination of the bioenergetic signature of colon carcinomas could

  8. A gene expression signature of Retinoblastoma loss-of-function predicts resistance to neoadjuvant chemotherapy in ER-positive/HER2-positive breast cancer patients.

    Science.gov (United States)

    Risi, Emanuela; Grilli, Andrea; Migliaccio, Ilenia; Biagioni, Chiara; McCartney, Amelia; Guarducci, Cristina; Bonechi, Martina; Benelli, Matteo; Vitale, Stefania; Biganzoli, Laura; Bicciato, Silvio; Di Leo, Angelo; Malorni, Luca

    2018-07-01

    HER2-positive (HER2+) breast cancers show heterogeneous response to chemotherapy, with the ER-positive (ER+) subgroup deriving less benefit. Loss of retinoblastoma tumor suppressor gene (RB1) function has been suggested as a cardinal feature of breast cancers that are more sensitive to chemotherapy and conversely resistant to CDK4/6 inhibitors. We performed a retrospective analysis exploring RBsig, a gene signature of RB loss, as a potential predictive marker of response to neoadjuvant chemotherapy in ER+/HER2+ breast cancer patients. We selected clinical trials of neoadjuvant chemotherapy ± anti-HER2 therapy in HER2+ breast cancer patients with available information on gene expression data, hormone receptor status, and pathological complete response (pCR) rates. RBsig expression was computed in silico and correlated with pCR. Ten studies fulfilled the inclusion criteria and were included in the analysis (514 patients). Overall, of 211 ER+/HER2+ breast cancer patients, 49 achieved pCR (23%). The pCR rate following chemotherapy ± anti-HER2 drugs in patients with RBsig low expression was significantly lower compared to patients with RBsig high expression (16% vs. 30%, respectively; Fisher's exact test p = 0.015). The area under the ROC curve (AUC) was 0.62 (p = 0.005). In the 303 ER-negative (ER-)/HER2+ patients treated with chemotherapy ± anti-HER2 drugs, the pCR rate was 43%. No correlation was found between RBsig expression and pCR rate in this group. Low expression of RBsig identifies a subset of ER+/HER2+ patients with low pCR rates following neoadjuvant chemotherapy ± anti-HER2 therapy. These patients may potentially be spared chemotherapy in favor of anti-HER2, endocrine therapy, and CDK 4/6 inhibitor combinations.

  9. 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.

  10. Quantitative proteomic analysis of paired colorectal cancer and non-tumorigenic tissues reveals signature proteins and perturbed pathways involved in CRC progression and metastasis.

    Science.gov (United States)

    Sethi, Manveen K; Thaysen-Andersen, Morten; Kim, Hoguen; Park, Cheol Keun; Baker, Mark S; Packer, Nicolle H; Paik, Young-Ki; Hancock, William S; Fanayan, Susan

    2015-08-03

    Modern proteomics has proven instrumental in our understanding of the molecular deregulations associated with the development and progression of cancer. Herein, we profile membrane-enriched proteome of tumor and adjacent normal tissues from eight CRC patients using label-free nanoLC-MS/MS-based quantitative proteomics and advanced pathway analysis. Of the 948 identified proteins, 184 proteins were differentially expressed (P1.5) between the tumor and non-tumor tissue (69 up-regulated and 115 down-regulated in tumor tissues). The CRC tumor and non-tumor tissues clustered tightly in separate groups using hierarchical cluster analysis of the differentially expressed proteins, indicating a strong CRC-association of this proteome subset. Specifically, cancer associated proteins such as FN1, TNC, DEFA1, ITGB2, MLEC, CDH17, EZR and pathways including actin cytoskeleton and RhoGDI signaling were deregulated. Stage-specific proteome signatures were identified including up-regulated ribosomal proteins and down-regulated annexin proteins in early stage CRC. Finally, EGFR(+) CRC tissues showed an EGFR-dependent down-regulation of cell adhesion molecules, relative to EGFR(-) tissues. Taken together, this study provides a detailed map of the altered proteome and associated protein pathways in CRC, which enhances our mechanistic understanding of CRC biology and opens avenues for a knowledge-driven search for candidate CRC protein markers. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall

    Directory of Open Access Journals (Sweden)

    Eduardo Fukutani

    2018-05-01

    Full Text Available The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV was published, providing new data to investigate whether this “infection” gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.

  12. Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall.

    Science.gov (United States)

    Fukutani, Eduardo; Rodrigues, Moreno; Kasprzykowski, José Irahe; Araujo, Cintia Figueiredo de; Paschoal, Alexandre Rossi; Ramos, Pablo Ivan Pereira; Fukutani, Kiyoshi Ferreira; Queiroz, Artur Trancoso Lopo de

    2018-01-01

    The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this "infection" gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.

  13. Association analysis identifies 65 new breast cancer risk loci

    NARCIS (Netherlands)

    Michailidou, Kyriaki; Lindström, Sara; Dennis, Joe; Beesley, Jonathan; Hui, Shirley; Kar, Siddhartha; Lemaçon, Audrey; Soucy, Penny; Glubb, Dylan; Rostamianfar, Asha; Bolla, Manjeet K.; Wang, Qin; Tyrer, Jonathan; Dicks, Ed; Lee, Andrew; Wang, Zhaoming; Allen, Jamie; Keeman, Renske; Eilber, Ursula; French, Juliet D.; Qing Chen, Xiao; Fachal, Laura; McCue, Karen; McCart Reed, Amy E.; Ghoussaini, Maya; Carroll, Jason S.; Jiang, Xia; Finucane, Hilary; Adams, Marcia; Adank, Muriel A.; Ahsan, Habibul; Aittomäki, Kristiina; Anton-Culver, Hoda; Antonenkova, Natalia N.; Arndt, Volker; Aronson, Kristan J.; Arun, Banu; Auer, Paul L.; Bacot, François; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W.; Behrens, Sabine; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Brand, Judith S.; Brauch, Hiltrud; Brennan, Paul; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brock, Ian W.; Broeks, Annegien; Brooks-Wilson, Angela; Brucker, Sara Y.; Brüning, Thomas; Burwinkel, Barbara; Butterbach, Katja; Cai, Qiuyin; Cai, Hui; Caldés, Trinidad; Canzian, Federico; Carracedo, Angel; Carter, Brian D.; Castelao, Jose E.; Chan, Tsun L.; David Cheng, Ting-Yuan; Seng Chia, Kee; Choi, Ji-Yeob; Christiansen, Hans; Clarke, Christine L.; Collée, Margriet; Conroy, Don M.; Cordina-Duverger, Emilie; Cornelissen, Sten; Cox, David G.; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Devilee, Peter; Doheny, Kimberly F.; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Durcan, Lorraine; Dwek, Miriam; Eccles, Diana M.; Ekici, Arif B.; Eliassen, A. Heather; Ellberg, Carolina; Elvira, Mingajeva; Engel, Christoph; Eriksson, Mikael; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gaborieau, Valerie; Gabrielson, Marike; Gago-Dominguez, Manuela; Gao, Yu-Tang; Gapstur, Susan M.; García-Sáenz, José A.; Gaudet, Mia M.; Georgoulias, Vassilios; Giles, Graham G.; Glendon, Gord; Goldberg, Mark S.; Goldgar, David E.; González-Neira, Anna; Grenaker Alnæs, Grethe I.; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Guénel, Pascal; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A.; Håkansson, Niclas; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Harrington, Patricia; Hart, Steven N.; Hartikainen, Jaana M.; Hartman, Mikael; Hein, Alexander; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Ho, Dona N.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Hou, Ming-Feng; Hsiung, Chia-Ni; Huang, Guanmengqian; Humphreys, Keith; Ishiguro, Junko; Ito, Hidemi; Iwasaki, Motoki; Iwata, Hiroji; Jakubowska, Anna; Janni, Wolfgang; John, Esther M.; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kasuga, Yoshio; Kerin, Michael J.; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I.; Kim, Sung-Won; Knight, Julia A.; Kosma, Veli-Matti; Kristensen, Vessela N.; Krüger, Ute; Kwong, Ava; Lambrechts, Diether; Le Marchand, Loic; Lee, Eunjung; Lee, Min Hyuk; Lee, Jong Won; Neng Lee, Chuen; Lejbkowicz, Flavio; Li, Jingmei; Lilyquist, Jenna; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Lophatananon, Artitaya; Lubinski, Jan; Luccarini, Craig; Lux, Michael P.; Ma, Edmond S. K.; MacInnis, Robert J.; Maishman, Tom; Makalic, Enes; Malone, Kathleen E.; Kostovska, Ivana Maleva; Mannermaa, Arto; Manoukian, Siranoush; Manson, JoAnn E.; Margolin, Sara; Mariapun, Shivaani; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; McKay, James; McLean, Catriona; Meijers-Heijboer, Hanne; Meindl, Alfons; Menéndez, Primitiva; Menon, Usha; Meyer, Jeffery; Miao, Hui; Miller, Nicola; Taib, Nur Aishah Mohd; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F.; Noh, Dong-Young; Nordestgaard, Børge G.; Norman, Aaron; Olopade, Olufunmilayo I.; Olson, Janet E.; Olsson, Håkan; Olswold, Curtis; Orr, Nick; Pankratz, V. Shane; Park, Sue K.; Park-Simon, Tjoung-Won; Lloyd, Rachel; Perez, Jose I. A.; Peterlongo, Paolo; Peto, Julian; Phillips, Kelly-Anne; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Prokofyeva, Darya; Pugh, Elizabeth; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gadi; Rennert, Hedy S.; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Ruddy, Kathryn J.; Rüdiger, Thomas; Rudolph, Anja; Ruebner, Matthias; Rutgers, Emiel J. T.; Saloustros, Emmanouil; Sandler, Dale P.; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmutzler, Rita K.; Schneeweiss, Andreas; Schoemaker, Minouk J.; Schumacher, Fredrick; Schürmann, Peter; Scott, Rodney J.; Scott, Christopher; Seal, Sheila; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Grace; Sherman, Mark E.; Shrubsole, Martha J.; Shu, Xiao-Ou; Smeets, Ann; Sohn, Christof; Southey, Melissa C.; Spinelli, John J.; Stegmaier, Christa; Stewart-Brown, Sarah; Stone, Jennifer; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Tamimi, Rulla; Taylor, Jack A.; Tengström, Maria; teo, Soo H.; Beth Terry, Mary; Tessier, Daniel C.; Thanasitthichai, Somchai; Thöne, Kathrin; Tollenaar, Rob A. E. M.; Tomlinson, Ian; Tong, Ling; Torres, Diana; Truong, Thérèse; Tseng, Chiu-Chen; Tsugane, Shoichiro; Ulmer, Hans-Ulrich; Ursin, Giske; Untch, Michael; Vachon, Celine; van Asperen, Christi J.; van den Berg, David; van den Ouweland, Ans M. W.; van der Kolk, Lizet; van der Luijt, Rob B.; Vincent, Daniel; Vollenweider, Jason; Waisfisz, Quinten; Wang-Gohrke, Shan; Weinberg, Clarice R.; Wendt, Camilla; Whittemore, Alice S.; Wildiers, Hans; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H.; Xia, Lucy; Yamaji, Taiki; Yang, Xiaohong R.; Har Yip, Cheng; Yoo, Keun-Young; Yu, Jyh-Cherng; Zheng, Wei; Zheng, Ying; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Lakhani, Sunil R.; Antoniou, Antonis C.; Droit, Arnaud; Andrulis, Irene L.; Amos, Christopher I.; Couch, Fergus J.; Pharoah, Paul D. P.; Chang-Claude, Jenny; Hall, Per; Hunter, David J.; Milne, Roger L.; García-Closas, Montserrat; Schmidt, Marjanka K.; Chanock, Stephen J.; Dunning, Alison M.; Edwards, Stacey L.; Bader, Gary D.; Chenevix-Trench, Georgia; Simard, Jacques; Kraft, Peter; Easton, Douglas F.

    2017-01-01

    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast

  14. Maximizing biomarker discovery by minimizing gene signatures

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    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

  15. Distinct Molecular Signature of Murine Fetal Liver and Adult Hematopoietic Stem Cells Identify Novel Regulators of Hematopoietic Stem Cell Function.

    Science.gov (United States)

    Manesia, Javed K; Franch, Monica; Tabas-Madrid, Daniel; Nogales-Cadenas, Ruben; Vanwelden, Thomas; Van Den Bosch, Elisa; Xu, Zhuofei; Pascual-Montano, Alberto; Khurana, Satish; Verfaillie, Catherine M

    2017-04-15

    During ontogeny, fetal liver (FL) acts as a major site for hematopoietic stem cell (HSC) maturation and expansion, whereas HSCs in the adult bone marrow (ABM) are largely quiescent. HSCs in the FL possess faster repopulation capacity as compared with ABM HSCs. However, the molecular mechanism regulating the greater self-renewal potential of FL HSCs has not yet extensively been assessed. Recently, we published RNA sequencing-based gene expression analysis on FL HSCs from 14.5-day mouse embryo (E14.5) in comparison to the ABM HSCs. We reanalyzed these data to identify key transcriptional regulators that play important roles in the expansion of HSCs during development. The comparison of FL E14.5 with ABM HSCs identified more than 1,400 differentially expressed genes. More than 200 genes were shortlisted based on the gene ontology (GO) annotation term "transcription." By morpholino-based knockdown studies in zebrafish, we assessed the function of 18 of these regulators, previously not associated with HSC proliferation. Our studies identified a previously unknown role for tdg, uhrf1, uchl5, and ncoa1 in the emergence of definitive hematopoiesis in zebrafish. In conclusion, we demonstrate that identification of genes involved in transcriptional regulation differentially expressed between expanding FL HSCs and quiescent ABM HSCs, uncovers novel regulators of HSC function.

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

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    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.

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

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    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.

  18. Epitopes of MUC1 Tandem Repeats in Cancer as Revealed by Antibody Crystallography: Toward Glycopeptide Signature-Guided Therapy

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    Dapeng Zhou

    2018-05-01

    Full Text Available Abnormally O-glycosylated MUC1 tandem repeat glycopeptide epitopes expressed by multiple types of cancer have long been attractive targets for therapy in the race against genetic mutations of tumor cells. Glycopeptide signature-guided therapy might be a more promising avenue than mutation signature-guided therapy. Three O-glycosylated peptide motifs, PDTR, GSTA, and GVTS, exist in a tandem repeat HGVTSAPDTRPAPGSTAPPA, containing five O-glycosylation sites. The exact peptide and sugar residues involved in antibody binding are poorly defined. Co-crystal structures of glycopeptides and respective monoclonal antibodies are very few. Here we review 3 groups of monoclonal antibodies: antibodies which only bind to peptide portion, antibodies which only bind to sugar portion, and antibodies which bind to both peptide and sugar portions. The antigenicity of peptide and sugar portions of glyco-MUC1 tandem repeat were analyzed according to available biochemical and structural data, especially the GSTA and GVTS motifs independent from the most studied PDTR. Tn is focused as a peptide-modifying residue in vaccine design, to induce glycopeptide-binding antibodies with cross reactivity to Tn-related tumor glycans, but not glycans of healthy cells. The unique requirement for the designs of antibody in antibody-drug conjugate, bi-specific antibodies, and chimeric antigen receptors are also discussed.

  19. High-throughput, signature-tagged mutagenic approach to identify novel virulence factors of Yersinia pestis CO92 in a mouse model of infection.

    Science.gov (United States)

    Ponnusamy, Duraisamy; Fitts, Eric C; Sha, Jian; Erova, Tatiana E; Kozlova, Elena V; Kirtley, Michelle L; Tiner, Bethany L; Andersson, Jourdan A; Chopra, Ashok K

    2015-05-01

    The identification of new virulence factors in Yersinia pestis and understanding their molecular mechanisms during an infection process are necessary in designing a better vaccine or to formulate an appropriate therapeutic intervention. By using a high-throughput, signature-tagged mutagenic approach, we created 5,088 mutants of Y. pestis strain CO92 and screened them in a mouse model of pneumonic plague at a dose equivalent to 5 50% lethal doses (LD50) of wild-type (WT) CO92. From this screen, we obtained 118 clones showing impairment in disseminating to the spleen, based on hybridization of input versus output DNA from mutant pools with 53 unique signature tags. In the subsequent screen, 20/118 mutants exhibited attenuation at 8 LD50 when tested in a mouse model of bubonic plague, with infection by 10/20 of the aforementioned mutants resulting in 40% or higher survival rates at an infectious dose of 40 LD50. Upon sequencing, six of the attenuated mutants were found to carry interruptions in genes encoding hypothetical proteins or proteins with putative functions. Mutants with in-frame deletion mutations of two of the genes identified from the screen, namely, rbsA, which codes for a putative sugar transport system ATP-binding protein, and vasK, a component of the type VI secretion system, were also found to exhibit some attenuation at 11 or 12 LD50 in a mouse model of pneumonic plague. Likewise, among the remaining 18 signature-tagged mutants, 9 were also attenuated (40 to 100%) at 12 LD50 in a pneumonic plague mouse model. Previously, we found that deleting genes encoding Braun lipoprotein (Lpp) and acyltransferase (MsbB), the latter of which modifies lipopolysaccharide function, reduced the virulence of Y. pestis CO92 in mouse models of bubonic and pneumonic plague. Deletion of rbsA and vasK genes from either the Δlpp single or the Δlpp ΔmsbB double mutant augmented the attenuation to provide 90 to 100% survivability to mice in a pneumonic plague model at 20

  20. Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival.

    Science.gov (United States)

    Nicolau, Monica; Levine, Arnold J; Carlsson, Gunnar

    2011-04-26

    High-throughput biological data, whether generated as sequencing, transcriptional microarrays, proteomic, or other means, continues to require analytic methods that address its high dimensional aspects. Because the computational part of data analysis ultimately identifies shape characteristics in the organization of data sets, the mathematics of shape recognition in high dimensions continues to be a crucial part of data analysis. This article introduces a method that extracts information from high-throughput microarray data and, by using topology, provides greater depth of information than current analytic techniques. The method, termed Progression Analysis of Disease (PAD), first identifies robust aspects of cluster analysis, then goes deeper to find a multitude of biologically meaningful shape characteristics in these data. Additionally, because PAD incorporates a visualization tool, it provides a simple picture or graph that can be used to further explore these data. Although PAD can be applied to a wide range of high-throughput data types, it is used here as an example to analyze breast cancer transcriptional data. This identified a unique subgroup of Estrogen Receptor-positive (ER(+)) breast cancers that express high levels of c-MYB and low levels of innate inflammatory genes. These patients exhibit 100% survival and no metastasis. No supervised step beyond distinction between tumor and healthy patients was used to identify this subtype. The group has a clear and distinct, statistically significant molecular signature, it highlights coherent biology but is invisible to cluster methods, and does not fit into the accepted classification of Luminal A/B, Normal-like subtypes of ER(+) breast cancers. We denote the group as c-MYB(+) breast cancer.

  1. Gene expression signatures to predict the development of metastasis in breast cancer

    NARCIS (Netherlands)

    Nuyten, Dimitry S. A.; van de Vijver, Marc J.

    2006-01-01

    Understanding and preventing the development of distant metastases is the most important aim in research and treatment of malignant tumors, including breast cancer. In patients with primary breast cancer without lymph node metastases who are under 50 years of age, approximately 25% will develop

  2. 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

  3. Identifying a clinical signature of suicidality among patients with mood disorders: A pilot study using a machine learning approach.

    Science.gov (United States)

    Passos, Ives Cavalcante; Mwangi, Benson; Cao, Bo; Hamilton, Jane E; Wu, Mon-Ju; Zhang, Xiang Yang; Zunta-Soares, Giovana B; Quevedo, Joao; Kauer-Sant'Anna, Marcia; Kapczinski, Flávio; Soares, Jair C

    2016-03-15

    A growing body of evidence has put forward clinical risk factors associated with patients with mood disorders that attempt suicide. However, what is not known is how to integrate clinical variables into a clinically useful tool in order to estimate the probability of an individual patient attempting suicide. A total of 144 patients with mood disorders were included. Clinical variables associated with suicide attempts among patients with mood disorders and demographic variables were used to 'train' a machine learning algorithm. The resulting algorithm was utilized in identifying novel or 'unseen' individual subjects as either suicide attempters or non-attempters. Three machine learning algorithms were implemented and evaluated. All algorithms distinguished individual suicide attempters from non-attempters with prediction accuracy ranging between 65% and 72% (pdisorder (PTSD) comorbidity. Risk for suicide attempt among patients with mood disorders can be estimated at an individual subject level by incorporating both demographic and clinical variables. Future studies should examine the performance of this model in other populations and its subsequent utility in facilitating selection of interventions to prevent suicide. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Targeted Serum Metabolite Profiling Identifies Metabolic Signatures in Patients with Alzheimer's Disease, Normal Pressure Hydrocephalus and Brain Tumor

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    Matej Orešič

    2018-01-01

    Full Text Available Progression to AD is preceded by elevated levels of 2,4-dihydroxybutanoic acid (2,4-DHB, implicating hypoxia in early pathogenesis. Since hypoxia may play a role in multiple CNS disorders, we investigated serum metabolite profiles across three disorders, AD, Normal Pressure Hydrocephalus (NPH and brain tumors (BT. Blood samples were collected from 27 NPH and 20 BT patients. The profiles of 21 metabolites were examined. Additionally, data from 37 AD patients and 46 controls from a previous study were analyzed together with the newly acquired data. No differences in 2,4-DHB were found across AD, NPH and BT samples. In the BT group, the fatty acids were increased as compared to HC and NPH groups, while the ketone body 3-hydroxybutyrate was increased as compared to AD. Glutamic acid was increased in AD as compared to the HC group. In the AD group, 3-hydroxybutyrate tended to be decreased with respect to all other groups (mean values −30% or more, but the differences were not statistically significant. Serine was increased in NPH as compared to BT. In conclusion, AD, NPH and BT have different metabolic profiles. This preliminary study may help in identifying the blood based markers that are specific to these three CNS diseases.

  5. The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker.

    Science.gov (United States)

    Fadini, Gian Paolo; Albiero, Mattia; Millioni, Renato; Poncina, Nicol; Rigato, Mauro; Scotton, Rachele; Boscari, Federico; Brocco, Enrico; Arrigoni, Giorgio; Villano, Gianmarco; Turato, Cristian; Biasiolo, Alessandra; Pontisso, Patrizia; Avogaro, Angelo

    2014-09-01

    Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with α1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patients.

  6. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer

    DEFF Research Database (Denmark)

    Bertini, Ivano; Cacciatore, Stefano; Jensen, Benny V

    2012-01-01

    Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance ((1)H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist...... survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P = 1.33 × 10(-6)). A number of metabolites concurred with the (1)H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that (1)H-NMR profiling of patient serum can provide a strong metabolomic signature of m...

  7. Matrix Metalloproteinases: The Gene Expression Signatures of Head and Neck Cancer Progression

    Energy Technology Data Exchange (ETDEWEB)

    Iizuka, Shinji [Sanford-Burnham Medical Research Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037 (United States); Ishimaru, Naozumi; Kudo, Yasusei, E-mail: yasusei@tokushima-u.ac.jp [Department of Oral Molecular Pathology, Institute of Health Biosciences, The University of Tokushima Graduate School, 3-8-15 Kuramoto, Tokushima 770-8504 (Japan)

    2014-02-13

    Extracellular matrix degradation by matrix metalloproteinases (MMPs) plays a pivotal role in cancer progression by promoting motility, invasion and angiogenesis. Studies have shown that MMP expression is increased in head and neck squamous cell carcinomas (HNSCCs), one of the most common cancers in the world, and contributes to poor outcome. In this review, we examine the expression pattern of MMPs in HNSCC by microarray datasets and summarize the current knowledge of MMPs, specifically MMP-1, -3, -7 -10, -12, -13, 14 and -19, that are highly expressed in HNSCCs and involved cancer invasion and angiogenesis.

  8. Using Breast Cancer Risk Associated Polymorphisms to Identify Women for Breast Cancer Chemoprevention.

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    Elad Ziv

    Full Text Available Breast cancer can be prevented with selective estrogen receptor modifiers (SERMs and aromatase inhibitors (AIs. The US Preventive Services Task Force recommends that women with a 5-year breast cancer risk ≥3% consider chemoprevention for breast cancer. More than 70 single nucleotide polymorphisms (SNPs have been associated with breast cancer. We sought to determine how to best integrate risk information from SNPs with other risk factors to risk stratify women for chemoprevention.We used the risk distribution among women ages 35-69 estimated by the Breast Cancer Surveillance Consortium (BCSC risk model. We modeled the effect of adding 70 SNPs to the BCSC model and examined how this would affect how many women are reclassified above and below the threshold for chemoprevention.We found that most of the benefit of SNP testing a population is achieved by testing a modest fraction of the population. For example, if women with a 5-year BCSC risk of >2.0% are tested (~21% of all women, ~75% of the benefit of testing all women (shifting women above or below 3% 5-year risk would be derived. If women with a 5-year risk of >1.5% are tested (~36% of all women, ~90% of the benefit of testing all women would be derived.SNP testing is effective for reclassification of women for chemoprevention, but is unlikely to reclassify women with <1.5% 5-year risk. These results can be used to implement an efficient two-step testing approach to identify high risk women who may benefit from chemoprevention.

  9. Experimentally-derived fibroblast gene signatures identify molecular pathways associated with distinct subsets of systemic sclerosis patients in three independent cohorts.

    Directory of Open Access Journals (Sweden)

    Michael E Johnson

    Full Text Available Genome-wide expression profiling in systemic sclerosis (SSc has identified four 'intrinsic' subsets of disease (fibroproliferative, inflammatory, limited, and normal-like, each of which shows deregulation of distinct signaling pathways; however, the full set of pathways contributing to this differential gene expression has not been fully elucidated. Here we examine experimentally derived gene expression signatures in dermal fibroblasts for thirteen different signaling pathways implicated in SSc pathogenesis. These data show distinct and overlapping sets of genes induced by each pathway, allowing for a better understanding of the molecular relationship between profibrotic and immune signaling networks. Pathway-specific gene signatures were analyzed across a compendium of microarray datasets consisting of skin biopsies from three independent cohorts representing 80 SSc patients, 4 morphea, and 26 controls. IFNα signaling showed a strong association with early disease, while TGFβ signaling spanned the fibroproliferative and inflammatory subsets, was associated with worse MRSS, and was higher in lesional than non-lesional skin. The fibroproliferative subset was most strongly associated with PDGF signaling, while the inflammatory subset demonstrated strong activation of innate immune pathways including TLR signaling upstream of NF-κB. The limited and normal-like subsets did not show associations with fibrotic and inflammatory mediators such as TGFβ and TNFα. The normal-like subset showed high expression of genes associated with lipid signaling, which was absent in the inflammatory and limited subsets. Together, these data suggest a model by which IFNα is involved in early disease pathology, and disease severity is associated with active TGFβ signaling.

  10. 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...

  11. 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...

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

    NARCIS (Netherlands)

    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; dos Santos Silva, Isabel; 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

  13. An RNA-Based Digital Circulating Tumor Cell Signature Is Predictive of Drug Response and Early Dissemination in Prostate Cancer.

    Science.gov (United States)

    Miyamoto, David T; Lee, Richard J; Kalinich, Mark; LiCausi, Joseph A; Zheng, Yu; Chen, Tianqi; Milner, John D; Emmons, Erin; Ho, Uyen; Broderick, Katherine; Silva, Erin; Javaid, Sarah; Kwan, Tanya Todorova; Hong, Xin; Dahl, Douglas M; McGovern, Francis J; Efstathiou, Jason A; Smith, Matthew R; Sequist, Lecia V; Kapur, Ravi; Wu, Chin-Lee; Stott, Shannon L; Ting, David T; Giobbie-Hurder, Anita; Toner, Mehmet; Maheswaran, Shyamala; Haber, Daniel A

    2018-03-01

    Blood-based biomarkers are critical in metastatic prostate cancer, where characteristic bone metastases are not readily sampled, and they may enable risk stratification in localized disease. We established a sensitive and high-throughput strategy for analyzing prostate circulating tumor cells (CTC) using microfluidic cell enrichment followed by digital quantitation of prostate-derived transcripts. In a prospective study of 27 patients with metastatic castration-resistant prostate cancer treated with first-line abiraterone, pretreatment elevation of the digital CTC M score identifies a high-risk population with poor overall survival (HR = 6.0; P = 0.01) and short radiographic progression-free survival (HR = 3.2; P = 0.046). Expression of HOXB13 in CTCs identifies 6 of 6 patients with ≤12-month survival, with a subset also expressing the ARV7 splice variant. In a second cohort of 34 men with localized prostate cancer, an elevated preoperative CTC L score predicts microscopic dissemination to seminal vesicles and/or lymph nodes ( P digital quantitation of CTC-specific transcripts enables noninvasive monitoring that may guide treatment selection in both metastatic and localized prostate cancer. Significance: There is an unmet need for biomarkers to guide prostate cancer therapies, for curative treatment of localized cancer and for application of molecularly targeted agents in metastatic disease. Digital quantitation of prostate CTC-derived transcripts in blood specimens is predictive of abiraterone response in metastatic cancer and of early dissemination in localized cancer. Cancer Discov; 8(3); 288-303. ©2018 AACR. See related commentary by Heitzer and Speicher, p. 269 This article is highlighted in the In This Issue feature, p. 253 . ©2018 American Association for Cancer Research.

  14. Molecular Signature Reveals Which Liver Cancer Patients May Benefit from a New Drug | Center for Cancer Research

    Science.gov (United States)

    Only one drug currently on the market has the potential to extend survival for patients with advanced-stage liver cancer and only 30 percent of patients are eligible to receive it. As the fastest-growing type of cancer by incidence in the United States, liver cancer represents a major public health problem and there is an urgent need to develop new treatment strategies.

  15. Generation and Characterisation of Cisplatin-Resistant Non-Small Cell Lung Cancer Cell Lines Displaying a Stem-Like Signature

    Science.gov (United States)

    Barr, Martin P.; Gray, Steven G.; Hoffmann, Andreas C.; Hilger, Ralf A.; Thomale, Juergen; O’Flaherty, John D.; Fennell, Dean A.; Richard, Derek; O’Leary, John J.; O’Byrne, Kenneth J.

    2013-01-01

    Introduction Inherent and acquired cisplatin resistance reduces the effectiveness of this agent in the management of non-small cell lung cancer (NSCLC). Understanding the molecular mechanisms underlying this process may result in the development of novel agents to enhance the sensitivity of cisplatin. Methods An isogenic model of cisplatin resistance was generated in a panel of NSCLC cell lines (A549, SKMES-1, MOR, H460). Over a period of twelve months, cisplatin resistant (CisR) cell lines were derived from original, age-matched parent cells (PT) and subsequently characterized. Proliferation (MTT) and clonogenic survival assays (crystal violet) were carried out between PT and CisR cells. Cellular response to cisplatin-induced apoptosis and cell cycle distribution were examined by FACS analysis. A panel of cancer stem cell and pluripotent markers was examined in addition to the EMT proteins, c-Met and β-catenin. Cisplatin-DNA adduct formation, DNA damage (γH2AX) and cellular platinum uptake (ICP-MS) was also assessed. Results Characterisation studies demonstrated a decreased proliferative capacity of lung tumour cells in response to cisplatin, increased resistance to cisplatin-induced cell death, accumulation of resistant cells in the G0/G1 phase of the cell cycle and enhanced clonogenic survival ability. Moreover, resistant cells displayed a putative stem-like signature with increased expression of CD133+/CD44+cells and increased ALDH activity relative to their corresponding parental cells. The stem cell markers, Nanog, Oct-4 and SOX-2, were significantly upregulated as were the EMT markers, c-Met and β-catenin. While resistant sublines demonstrated decreased uptake of cisplatin in response to treatment, reduced cisplatin-GpG DNA adduct formation and significantly decreased γH2AX foci were observed compared to parental cell lines. Conclusion Our results identified cisplatin resistant subpopulations of NSCLC cells with a putative stem-like signature, providing

  16. Generation and characterisation of cisplatin-resistant non-small cell lung cancer cell lines displaying a stem-like signature.

    Directory of Open Access Journals (Sweden)

    Martin P Barr

    Full Text Available Inherent and acquired cisplatin resistance reduces the effectiveness of this agent in the management of non-small cell lung cancer (NSCLC. Understanding the molecular mechanisms underlying this process may result in the development of novel agents to enhance the sensitivity of cisplatin.An isogenic model of cisplatin resistance was generated in a panel of NSCLC cell lines (A549, SKMES-1, MOR, H460. Over a period of twelve months, cisplatin resistant (CisR cell lines were derived from original, age-matched parent cells (PT and subsequently characterized. Proliferation (MTT and clonogenic survival assays (crystal violet were carried out between PT and CisR cells. Cellular response to cisplatin-induced apoptosis and cell cycle distribution were examined by FACS analysis. A panel of cancer stem cell and pluripotent markers was examined in addition to the EMT proteins, c-Met and β-catenin. Cisplatin-DNA adduct formation, DNA damage (γH2AX and cellular platinum uptake (ICP-MS was also assessed.Characterisation studies demonstrated a decreased proliferative capacity of lung tumour cells in response to cisplatin, increased resistance to cisplatin-induced cell death, accumulation of resistant cells in the G0/G1 phase of the cell cycle and enhanced clonogenic survival ability. Moreover, resistant cells displayed a putative stem-like signature with increased expression of CD133+/CD44+cells and increased ALDH activity relative to their corresponding parental cells. The stem cell markers, Nanog, Oct-4 and SOX-2, were significantly upregulated as were the EMT markers, c-Met and β-catenin. While resistant sublines demonstrated decreased uptake of cisplatin in response to treatment, reduced cisplatin-GpG DNA adduct formation and significantly decreased γH2AX foci were observed compared to parental cell lines.Our results identified cisplatin resistant subpopulations of NSCLC cells with a putative stem-like signature, providing a further understanding of the

  17. 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.

  18. Signature Balancing

    NARCIS (Netherlands)

    Noordkamp, H.W.; Brink, M. van den

    2006-01-01

    Signatures are an important part of the design of a ship. In an ideal situation, signatures must be as low as possible. However, due to budget constraints it is most unlikely to reach this ideal situation. The arising question is which levels of signatures are optimal given the different scenarios

  19. Prospectively Identified Incident Testicular Cancer Risk in a Familial Testicular Cancer Cohort.

    Science.gov (United States)

    Pathak, Anand; Adams, Charleen D; Loud, Jennifer T; Nichols, Kathryn; Stewart, Douglas R; Greene, Mark H

    2015-10-01

    Human testicular germ cell tumors (TGCT) have a strong genetic component and a high familial relative risk. However, linkage analyses have not identified a rare, highly penetrant familial TGCT (FTGCT) susceptibility locus. Currently, multiple low-penetrance genes are hypothesized to underlie the familial multiple-case phenotype. The observation that two is the most common number of affected individuals per family presents an impediment to FTGCT gene discovery. Clinically, the prospective TGCT risk in the multiple-case family context is unknown. We performed a prospective analysis of TGCT incidence in a cohort of multiple-affected-person families and sporadic-bilateral-case families; 1,260 men from 140 families (10,207 person-years of follow-up) met our inclusion criteria. Age-, gender-, and calendar time-specific standardized incidence ratios (SIR) for TGCT relative to the general population were calculated using SEER*Stat. Eight incident TGCTs occurred during prospective FTGCT cohort follow-up (versus 0.67 expected; SIR = 11.9; 95% CI, 5.1-23.4; excess absolute risk = 7.2/10,000). We demonstrate that the incidence rate of TGCT is greater among bloodline male relatives from multiple-case testicular cancer families than that expected in the general population, a pattern characteristic of adult-onset Mendelian cancer susceptibility disorders. Two of these incident TGCTs occurred in relatives of sporadic-bilateral cases (0.15 expected; SIR = 13.4; 95% CI, 1.6-48.6). Our data are the first to indicate that despite relatively low numbers of affected individuals per family, members of both multiple-affected-person FTGCT families and sporadic-bilateral TGCT families comprise high-risk groups for incident testicular cancer. Men at high TGCT risk might benefit from tailored risk stratification and surveillance strategies. ©2015 American Association for Cancer Research.

  20. Local mechanical properties of bladder cancer cells measured by AFM as a signature of metastatic potential

    Science.gov (United States)

    Abidine, Y.; Laurent, V. M.; Michel, R.; Duperray, A.; Verdier, C.

    2015-10-01

    The rheological properties of bladder cancer cells of different invasivities have been investigated using a microrheological technique well adapted in the range [1-300Hz] of interest to understand local changes in the cytoskeleton microstructure, in particular actin fibres. Drugs disrupting actin and acto-myosin functions were used to study the resistance of such cancer cells. Results on a variety of cell lines were fitted with a model revealing the importance of two parameters, the elastic shear plateau modulus G N 0 as well as the glassy transition frequency f T. These parameters are good markers for invasiveness, with the notable exception of the cell periphery, which is stiffer for less invasive cells, and could be of importance in cancer metastasis.

  1. CCR 20th Anniversary Commentary: Gene-Expression Signature in Breast Cancer--Where Did It Start and Where Are We Now?

    Science.gov (United States)

    Gingras, Isabelle; Desmedt, Christine; Ignatiadis, Michail; Sotiriou, Christos

    2015-11-01

    Desmedt and colleagues published two articles, one in the June 1, 2007 issue, and the other in the August 15, 2008, issue of Clinical Cancer Research, that showed gene-expression signatures to be proliferation driven and time dependent, with their prognostic power decreasing with increasing follow-up years. Moreover, the articles showed that immune response is a crucial determinant of prognosis in the HER2-positive and estrogen receptor-negative/HER2-negative subtypes, providing a rationale to further explore the role of the antitumor immune response in these breast cancer subtypes. ©2015 American Association for Cancer Research.

  2. Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Yi [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Song, Jie; Pollom, Erqi; Alagappan, Muthuraman [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Shirato, Hiroki [Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Chang, Daniel T.; Koong, Albert C. [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Stanford Cancer Institute, Stanford, California (United States); Li, Ruijiang, E-mail: rli2@stanford.edu [Department of Radiation Oncology, Stanford University, Palo Alto, California (United States); Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo (Japan); Stanford Cancer Institute, Stanford, California (United States)

    2016-09-01

    Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6

  3. 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...

  4. Identifying aggressive prostate cancer foci using a DNA methylation classifier.

    Science.gov (United States)

    Mundbjerg, Kamilla; Chopra, Sameer; Alemozaffar, Mehrdad; Duymich, Christopher; Lakshminarasimhan, Ranjani; Nichols, Peter W; Aron, Manju; Siegmund, Kimberly D; Ukimura, Osamu; Aron, Monish; Stern, Mariana; Gill, Parkash; Carpten, John D; Ørntoft, Torben F; Sørensen, Karina D; Weisenberger, Daniel J; Jones, Peter A; Duddalwar, Vinay; Gill, Inderbir; Liang, Gangning

    2017-01-12

    Slow-growing prostate cancer (PC) can be aggressive in a subset of cases. Therefore, prognostic tools to guide clinical decision-making and avoid overtreatment of indolent PC and undertreatment of aggressive disease are urgently needed. PC has a propensity to be multifocal with several different cancerous foci per gland. Here, we have taken advantage of the multifocal propensity of PC and categorized aggressiveness of individual PC foci based on DNA methylation patterns in primary PC foci and matched lymph node metastases. In a set of 14 patients, we demonstrate that over half of the cases have multiple epigenetically distinct subclones and determine the primary subclone from which the metastatic lesion(s) originated. Furthermore, we develop an aggressiveness classifier consisting of 25 DNA methylation probes to determine aggressive and non-aggressive subclones. Upon validation of the classifier in an independent cohort, the predicted aggressive tumors are significantly associated with the presence of lymph node metastases and invasive tumor stages. Overall, this study provides molecular-based support for determining PC aggressiveness with the potential to impact clinical decision-making, such as targeted biopsy approaches for early diagnosis and active surveillance, in addition to focal therapy.

  5. A Cell Proliferation Signature Is a Marker of Extremely Poor Outcome in a Subpopulation of Breast Cancer Patients

    NARCIS (Netherlands)

    Dai, H.; Veer, L.J. van 't; Lamb, J.; He, Y.; Mao, M.; Fine, B.M.; Bernards, R.A.; Vijver, M.J.; Deutsch, P.; Sachs, A.; Stoughton, R.; Friend, S.H.

    2005-01-01

    Breast cancer comprises a group of distinct subtypes that despite having similar histologic appearances, have very different metastatic potentials. Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed

  6. A cell proliferation signature is a marker of extremely poor outcome in a subpopulation of breast cancer patients

    NARCIS (Netherlands)

    Dai, Hongyue; van't Veer, Laura; Lamb, John; He, Yudong D.; Mao, Mao; Fine, Bernard M.; Bernards, Rene; van de Vijver, Marc; Deutsch, Paul; Sachs, Alan; Stoughton, Roland; Friend, Stephen

    2005-01-01

    Breast cancer comprises a group of distinct subtypes that despite having similar histologic appearances, have very different metastatic potentials. Being able to identify the biological driving force, even for a subset of patients, is crucially important given the large population of women diagnosed

  7. Small RNA sequencing reveals a comprehensive miRNA signature of BRCA1-associated high-grade serous ovarian cancer

    NARCIS (Netherlands)

    Brouwer, Jan; Kluiver, Joost; de Almeida, Rodrigo C.; Modderman, Rutger; Terpstra, Martijn; Kok, Klaas; Withoff, Sebo; Hollema, Harry; Reitsma, Welmoed; de Bock, Geertruida H.; Mourits, Marian J. E.; van den Berg, Anke

    2016-01-01

    AimsBRCA1 mutation carriers are at increased risk of developing high-grade serous ovarian cancer (HGSOC), a malignancy that originates from fallopian tube epithelium. We aimed to identify differentially expressed known and novel miRNAs in BRCA1-associated HGSOC. Methods Small RNA sequencing was

  8. 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

  9. 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

  10. Epigenome-wide analysis of DNA methylation reveals a rectal cancer-specific epigenomic signature

    Czech Academy of Sciences Publication Activity Database

    Vymetálková, Veronika; Vodička, Pavel; Pardini, Barbara; Rosa, F.; Levý, M.; Schneiderová, M.; Liška, V.; Vodičková, Ludmila; Nilsson, T.K.; Farkas, S. A.

    2016-01-01

    Roč. 8, č. 9 (2016), s. 1193-1207 ISSN 1750-1911 R&D Projects: GA MZd(CZ) NT13424; GA MZd(CZ) NV15-27580A; GA ČR(CZ) GA15-08239S; GA MŠk(CZ) LD14050 Institutional support: RVO:68378041 Keywords : DNA methylation * Illumina Human Methylation 450 BeadChip * rectal cancer Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.541, year: 2016

  11. Developing a PTEN-ERG Signature to Improve Molecular Risk Stratification in Prostate Cancer

    Science.gov (United States)

    2017-10-01

    performed exploratory data analysis on all clinically annotated prostate cancer datasets available from the public domain and through the collaboration...with GenomeDX. We used statistical summaries and data visualizations techniques (e.g., principal component analysis , hierarchical clustering) to...associated with PTEN loss on genetically homogeneous ERG-positive and ERG- negative backgrounds. Timeline (Months) Major Task 2: Perform CAGE analysis

  12. Prospectively-Identified Incident Testicular Cancer Risk in a Familial Testicular Cancer Cohort

    Science.gov (United States)

    Pathak, Anand; Adams, Charleen D.; Loud, Jennifer T.; Nichols, Kathryn; Stewart, Douglas R.; Greene, Mark H.

    2015-01-01

    Background Human testicular germ cell tumors (TGCT) have a strong genetic component and a high familial relative risk. However, linkage analyses have not identified a rare, highly-penetrant familial TGCT (FTGCT) susceptibility locus. Currently, multiple low-penetrance genes are hypothesized to underlie the familial multiple-case phenotype. The observation that two is the most common number of affected individuals per family presents an impediment to FTGCT gene discovery. Clinically, the prospective TGCT risk in the multiple-case family context is unknown. Methods We performed a prospective analysis of TGCT incidence in a cohort of multiple-affected-person families and sporadic-bilateral-case families; 1,260 men from 140 families (10,207 person-years of follow-up) met our inclusion criteria. Age-, gender-, and calendar time-specific standardized incidence ratios (SIR) for TGCT relative to the general population were calculated using SEER*Stat. Results Eight incident TGCTs occurred during prospective FTGCT cohort follow-up (versus 0.67 expected; SIR=11.9; 95% confidence interval [CI]=5.1–23.4; excess absolute risk=7.2/10,000). We demonstrate that the incidence rate of TGCT is greater among bloodline male relatives from multiple-case testicular cancer families than that expected in the general population, a pattern characteristic of adult-onset Mendelian cancer susceptibility disorders. Two of these incident TGCTs occurred in relatives of sporadic-bilateral cases (0.15 expected; SIR=13.4; 95%CI=1.6–48.6). Conclusions Our data are the first indicating that despite relatively low numbers of affected individuals per family, members of both multiple-affected-person FTGCT families and sporadic-bilateral TGCT families comprise high-risk groups for incident testicular cancer. Impact Men at high TGCT risk might benefit from tailored risk stratification and surveillance strategies. PMID:26265202

  13. 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

  14. MicroRNA signature of cis-platin resistant vs. cis-platin sensitive ovarian cancer cell lines

    Directory of Open Access Journals (Sweden)

    Kumar Smriti

    2011-09-01

    Full Text Available Abstract Background Ovarian cancer is the leading cause of death from gynecologic cancer in women worldwide. According to the National Cancer Institute, ovarian cancer has the highest mortality rate among all the reproductive cancers in women. Advanced stage diagnosis and chemo/radio-resistance is a major obstacle in treating advanced ovarian cancer. The most commonly employed chemotherapeutic drug for ovarian cancer treatment is cis-platin. As with most chemotherapeutic drugs, many patients eventually become resistant to cis-platin and therefore, diminishing its effect. The efficacy of current treatments may be improved by increasing the sensitivity of cancer cells to chemo/radiation therapies. Methods The present study is focused on identifying the differential expression of regulatory microRNAs (miRNAs between cis-platin sensitive (A2780, and cis-platin resistant (A2780/CP70 cell lines. Cell proliferation assays were conducted to test the sensitivity of the two cell lines to cis-platin. Differential expression patterns of miRNA between cis-platin sensitive and cis-platin resistant cell lines were analyzed using novel LNA technology. Results Our results revealed changes in expression of 11 miRNAs out of 1,500 miRNAs analyzed. Out of the 11 miRNAs identified, 5 were up-regulated in the A2780/CP70 cell line and 6 were down regulated as compared to cis-platin sensitive A2780 cells. Our microRNA data was further validated by quantitative real-time PCR for these selected miRNAs. Ingenuity Pathway Analysis (IPA and Kyoto Encyclopedia of Genes and Genomes (KEGG analysis was performed for the selected miRNAs and their putative targets to identify the potential pathways and networks involved in cis-platin resistance. Conclusions Our data clearly showed the differential expression of 11 miRNAs in cis-platin resistant cells, which could potentially target many important pathways including MAPK, TGF-β signaling, actin cytoskeleton, ubiquitin mediated

  15. Spatial analyses identify the geographic source of patients at a National Cancer Institute Comprehensive Cancer Center.

    Science.gov (United States)

    Su, Shu-Chih; Kanarek, Norma; Fox, Michael G; Guseynova, Alla; Crow, Shirley; Piantadosi, Steven

    2010-02-01

    We examined the geographic distribution of patients to better understand the service area of the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, a designated National Cancer Institute (NCI) comprehensive cancer center located in an urban center. Like most NCI cancer centers, the Sidney Kimmel Comprehensive Cancer Center serves a population beyond city limits. Urban cancer centers are expected to serve their immediate neighborhoods and to address disparities in access to specialty care. Our purpose was to learn the extent and nature of the cancer center service area. Statistical clustering of patient residence in the continental United States was assessed for all patients and by gender, cancer site, and race using SaTScan. Primary clusters detected for all cases and demographically and tumor-defined subpopulations were centered at Baltimore City and consisted of adjacent counties in Delaware, Pennsylvania, Virginia, West Virginia, New Jersey and New York, and the District of Columbia. Primary clusters varied in size by race, gender, and cancer site. Spatial analysis can provide insights into the populations served by urban cancer centers, assess centers' performance relative to their communities, and aid in developing a cancer center business plan that recognizes strengths, regional utility, and referral patterns. Today, 62 NCI cancer centers serve a quarter of the U.S. population in their immediate communities. From the Baltimore experience, we might project that the population served by these centers is actually more extensive and varies by patient characteristics, cancer site, and probably cancer center services offered.

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

    International Nuclear Information System (INIS)

    Bermudo, Raquel; Martínez-A, Carlos; Ortiz, Ángel R; Fernández, Pedro L; Thomson, Timothy M; Abia, David; Ferrer, Berta; Nayach, Iracema; Benguria, Alberto; Zaballos, Ángel; Rey, Javier del; Miró, Rosa; Campo, Elías

    2008-01-01

    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

  17. The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways.

    Science.gov (United States)

    Sun, Yahui; Ma, Chenkai; Halgamuge, Saman

    2017-12-28

    Cancer constitutes a momentous health burden in our society. Critical information on cancer may be hidden in its signaling pathways. However, even though a large amount of money has been spent on cancer research, some critical information on cancer-related signaling pathways still remains elusive. Hence, new works towards a complete understanding of cancer-related signaling pathways will greatly benefit the prevention, diagnosis, and treatment of cancer. We propose the node-weighted Steiner tree approach to identify important elements of cancer-related signaling pathways at the level of proteins. This new approach has advantages over previous approaches since it is fast in processing large protein-protein interaction networks. We apply this new approach to identify important elements of two well-known cancer-related signaling pathways: PI3K/Akt and MAPK. First, we generate a node-weighted protein-protein interaction network using protein and signaling pathway data. Second, we modify and use two preprocessing techniques and a state-of-the-art Steiner tree algorithm to identify a subnetwork in the generated network. Third, we propose two new metrics to select important elements from this subnetwork. On a commonly used personal computer, this new approach takes less than 2 s to identify the important elements of PI3K/Akt and MAPK signaling pathways in a large node-weighted protein-protein interaction network with 16,843 vertices and 1,736,922 edges. We further analyze and demonstrate the significance of these identified elements to cancer signal transduction by exploring previously reported experimental evidences. Our node-weighted Steiner tree approach is shown to be both fast and effective to identify important elements of cancer-related signaling pathways. Furthermore, it may provide new perspectives into the identification of signaling pathways for other human diseases.

  18. Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning.

    Science.gov (United States)

    Dorman, Stephanie N; Baranova, Katherina; Knoll, Joan H M; Urquhart, Brad L; Mariani, Gabriella; Carcangiu, Maria Luisa; Rogan, Peter K

    2016-01-01

    Increasingly, the effectiveness of adjuvant chemotherapy agents for breast cancer has been related to changes in the genomic profile of tumors. We investigated correspondence between growth inhibitory concentrations of paclitaxel and gemcitabine (GI50) and gene copy number, mutation, and expression first in breast cancer cell lines and then in patients. Genes encoding direct targets of these drugs, metabolizing enzymes, transporters, and those previously associated with chemoresistance to paclitaxel (n = 31 genes) or gemcitabine (n = 18) were analyzed. A multi-factorial, principal component analysis (MFA) indicated expression was the strongest indicator of sensitivity for paclitaxel, and copy number and expression were informative for gemcitabine. The factors were combined using support vector machines (SVM). Expression of 15 genes (ABCC10, BCL2, BCL2L1, BIRC5, BMF, FGF2, FN1, MAP4, MAPT, NFKB2, SLCO1B3, TLR6, TMEM243, TWIST1, and CSAG2) predicted cell line sensitivity to paclitaxel with 82% accuracy. Copy number profiles of 3 genes (ABCC10, NT5C, TYMS) together with expression of 7 genes (ABCB1, ABCC10, CMPK1, DCTD, NME1, RRM1, RRM2B), predicted gemcitabine response with 85% accuracy. Expression and copy number studies of two independent sets of patients with known responses were then analyzed with these models. These included tumor blocks from 21 patients that were treated with both paclitaxel and gemcitabine, and 319 patients on paclitaxel and anthracycline therapy. A new paclitaxel SVM was derived from an 11-gene subset since data for 4 of the original genes was unavailable. The accuracy of this SVM was similar in cell lines and tumor blocks (70-71%). The gemcitabine SVM exhibited 62% prediction accuracy for the tumor blocks due to the presence of samples with poor nucleic acid integrity. Nevertheless, the paclitaxel SVM predicted sensitivity in 84% of patients with no or minimal residual disease. Copyright © 2015 Federation of European Biochemical Societies

  19. Epigenetic Signature: A New Player as Predictor of Clinically Significant Prostate Cancer (PCa) in Patients on Active Surveillance (AS).

    Science.gov (United States)

    Ferro, Matteo; Ungaro, Paola; Cimmino, Amelia; Lucarelli, Giuseppe; Busetto, Gian Maria; Cantiello, Francesco; Damiano, Rocco; Terracciano, Daniela

    2017-05-27

    Widespread prostate-specific antigen (PSA) testing notably increased the number of prostate cancer (PCa) diagnoses. However, about 30% of these patients have low-risk tumors that are not lethal and remain asymptomatic during their lifetime. Overtreatment of such patients may reduce quality of life and increase healthcare costs. Active surveillance (AS) has become an accepted alternative to immediate treatment in selected men with low-risk PCa. Despite much progress in recent years toward identifying the best candidates for AS in recent years, the greatest risk remains the possibility of misclassification of the cancer or missing a high-risk cancer. This is particularly worrisome in men with a life expectancy of greater than 10-15 years. The Prostate Cancer Research International Active Surveillance (PRIAS) study showed that, in addition to age and PSA at diagnosis, both PSA density (PSA-D) and the number of positive cores at diagnosis (two compared with one) are the strongest predictors for reclassification biopsy or switching to deferred treatment. However, there is still no consensus upon guidelines for placing patients on AS. Each institution has its own protocol for AS that is based on PRIAS criteria. Many different variables have been proposed as tools to enrol patients in AS: PSA-D, the percentage of freePSA, and the extent of cancer on biopsy (number of positive cores or percentage of core involvement). More recently, the Prostate Health Index (PHI), the 4 Kallikrein (4K) score, and other patient factors, such as age, race, and family history, have been investigated as tools able to predict clinically significant PCa. Recently, some reports suggested that epigenetic mapping differs significantly between cancer patients and healthy subjects. These findings indicated as future prospect the use of epigenetic markers to identify PCa patients with low-grade disease, who are likely candidates for AS. This review explores literature data about the potential of

  20. Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer

    NARCIS (Netherlands)

    Klein, Alison P.; Wolpin, Brian M.; Risch, Harvey A.; Stolzenberg-Solomon, Rachael Z.; Mocci, Evelina; Zhang, Mingfeng; Canzian, Federico; Childs, Erica J.; Hoskins, Jason W.; Jermusyk, Ashley; Zhong, Jun; Chen, Fei; Albanes, Demetrius; Andreotti, Gabriella; Arslan, Alan A.; Babic, Ana; Bamlet, William R.; Beane-Freeman, Laura; Berndt, Sonja I.; Blackford, Amanda; Borges, Michael; Borgida, Ayelet; Bracci, Paige M.; Brais, Lauren; Brennan, Paul; Brenner, Hermann; Bueno-de-Mesquita, Bas; Buring, Julie; Campa, Daniele; Capurso, Gabriele; Cavestro, Giulia Martina; Chaffee, Kari G.; Chung, Charles C.; Cleary, Sean; Cotterchio, Michelle; Dijk, Frederike; Duell, Eric J.; Foretova, Lenka; Fuchs, Charles; Funel, Niccola; Gallinger, Steven; M Gaziano, J. Michael; Gazouli, Maria; Giles, Graham G.; Giovannucci, Edward; Goggins, Michael; Goodman, Gary E.; Goodman, Phyllis J.; Hackert, Thilo; Haiman, Christopher; Hartge, Patricia; Hasan, Manal; Hegyi, Peter; Helzlsouer, Kathy J.; Herman, Joseph; Holcatova, Ivana; Holly, Elizabeth A.; Hoover, Robert; Hung, Rayjean J.; Jacobs, Eric J.; Jamroziak, Krzysztof; Janout, Vladimir; Kaaks, Rudolf; Khaw, Kay-Tee; Klein, Eric A.; Kogevinas, Manolis; Kooperberg, Charles; Kulke, Matthew H.; Kupcinskas, Juozas; Kurtz, Robert J.; Laheru, Daniel; Landi, Stefano; Lawlor, Rita T.; Lee, I.-Min; Lemarchand, Loic; Lu, Lingeng; Malats, Núria; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L.; Mohelníková-Duchoňová, Beatrice; Neale, Rachel E.; Neoptolemos, John P.; Oberg, Ann L.; Olson, Sara H.; Orlow, Irene; Pasquali, Claudio; Patel, Alpa V.; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Real, Francisco X.; Rothman, Nathaniel; Scelo, Ghislaine; Sesso, Howard D.; Severi, Gianluca; Shu, Xiao-Ou; Silverman, Debra; Smith, Jill P.; Soucek, Pavel; Sund, Malin; Talar-Wojnarowska, Renata; Tavano, Francesca; Thornquist, Mark D.; Tobias, Geoffrey S.; van den Eeden, Stephen K.; Vashist, Yogesh; Visvanathan, Kala; Vodicka, Pavel; Wactawski-Wende, Jean; Wang, Zhaoming; Wentzensen, Nicolas; White, Emily; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Kraft, Peter; Li, Donghui; Chanock, Stephen; Obazee, Ofure; Petersen, Gloria M.; Amundadottir, Laufey T.

    2018-01-01

    In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic

  1. Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

    NARCIS (Netherlands)

    Klein, Alison P; Wolpin, Brian M; Risch, Harvey A; Stolzenberg-Solomon, Rachael Z; Mocci, Evelina; Zhang, Mingfeng; Canzian, Federico; Childs, Erica J; Hoskins, Jason W; Jermusyk, Ashley; Zhong, Jun; Sund, Malin; Talar-Wojnarowska, Renata; Tavano, Francesca; Thornquist, Mark D; Tobias, Geoffrey S; Van Den Eeden, Stephen K; Vashist, Yogesh; Visvanathan, Kala; Vodicka, Pavel; Wactawski-Wende, Jean; Chen, Fei; Wang, Zhaoming; Wentzensen, Nicolas; White, Emily; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Kraft, Peter; Li, Donghui; Chanock, Stephen; Albanes, Demetrius; Obazee, Ofure; Petersen, Gloria M; Amundadottir, Laufey T; Andreotti, Gabriella; Arslan, Alan A; Babic, Ana; Bamlet, William R; Beane-Freeman, Laura; Berndt, Sonja I; Blackford, Amanda; Borges, Michael; Borgida, Ayelet; Bracci, Paige M; Brais, Lauren; Brennan, Paul; Brenner, Hermann; Bueno-de-Mesquita, Bas; Buring, Julie; Campa, Daniele; Capurso, Gabriele; Cavestro, Giulia Martina; Chaffee, Kari G; Chung, Charles C; Cleary, Sean; Cotterchio, Michelle; Dijk, Frederike; Duell, Eric J; Foretova, Lenka; Fuchs, Charles; Funel, Niccola; Gallinger, Steven; M Gaziano, J Michael; Gazouli, Maria; Giles, Graham G; Giovannucci, Edward; Goggins, Michael; Goodman, Gary E; Goodman, Phyllis J; Hackert, Thilo; Haiman, Christopher; Hartge, Patricia; Hasan, Manal; Hegyi, Peter; Helzlsouer, Kathy J; Herman, Joseph; Holcatova, Ivana; Holly, Elizabeth A; Hoover, Robert; Hung, Rayjean J; Jacobs, Eric J; Jamroziak, Krzysztof; Janout, Vladimir; Kaaks, Rudolf; Khaw, Kay-Tee; Klein, Eric A; Kogevinas, Manolis; Kooperberg, Charles; Kulke, Matthew H; Kupcinskas, Juozas; Kurtz, Robert J; Laheru, Daniel; Landi, Stefano; Lawlor, Rita T; Lee, I-Min; LeMarchand, Loic; Lu, Lingeng; Malats, Núria; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L; Mohelníková-Duchoňová, Beatrice; Neale, Rachel E; Neoptolemos, John P; Oberg, Ann L; Olson, Sara H; Orlow, Irene; Pasquali, Claudio; Patel, Alpa V; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Real, Francisco X; Rothman, Nathaniel; Scelo, Ghislaine; Sesso, Howard D; Severi, Gianluca; Shu, Xiao-Ou; Silverman, Debra; Smith, Jill P; Soucek, Pavel

    2018-01-01

    In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic

  2. 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...

  3. COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration.

    Science.gov (United States)

    Southey, Melissa C; Park, Daniel J; Nguyen-Dumont, Tu; Campbell, Ian; Thompson, Ella; Trainer, Alison H; Chenevix-Trench, Georgia; Simard, Jacques; Dumont, Martine; Soucy, Penny; Thomassen, Mads; Jønson, Lars; Pedersen, Inge S; Hansen, Thomas Vo; Nevanlinna, Heli; Khan, Sofia; Sinilnikova, Olga; Mazoyer, Sylvie; Lesueur, Fabienne; Damiola, Francesca; Schmutzler, Rita; Meindl, Alfons; Hahnen, Eric; Dufault, Michael R; Chris Chan, Tl; Kwong, Ava; Barkardóttir, Rosa; Radice, Paolo; Peterlongo, Paolo; Devilee, Peter; Hilbers, Florentine; Benitez, Javier; Kvist, Anders; Törngren, Therese; Easton, Douglas; Hunter, David; Lindstrom, Sara; Kraft, Peter; Zheng, Wei; Gao, Yu-Tang; Long, Jirong; Ramus, Susan; Feng, Bing-Jian; Weitzel, Jeffrey N; Nathanson, Katherine; Offit, Kenneth; Joseph, Vijai; Robson, Mark; Schrader, Kasmintan; Wang, San; Kim, Yeong C; Lynch, Henry; Snyder, Carrie; Tavtigian, Sean; Neuhausen, Susan; Couch, Fergus J; Goldgar, David E

    2013-06-21

    Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  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

    Purpose: To assess the ability of genes selected from those reflecting chromosomal instability to identify good and poor prognostic subsets of Grade 2 breast carcinomas. Methods: We selected genes for splitting grade 2 tumours into low and high grade type groups by using public databases. Patient...

  7. Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer.

    Science.gov (United States)

    Shukla, Hem D

    2017-10-25

    During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA), and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein-protein interaction, and pharmacogenomics

  8. Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

    Directory of Open Access Journals (Sweden)

    Hem D. Shukla

    2017-10-01

    Full Text Available During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA, and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein–protein interaction

  9. Multiple strategies of oxygen supply in Drosophila malignancies identify tracheogenesis as a novel cancer hallmark.

    Science.gov (United States)

    Grifoni, Daniela; Sollazzo, Manuela; Fontana, Elisabetta; Froldi, Francesca; Pession, Annalisa

    2015-03-12

    Angiogenesis is the term used to describe all the alterations in blood vessel growth induced by a tumour mass following hypoxic stress. The occurrence of multiple strategies of vessel recruitment favours drug resistance, greatly complicating the treatment of certain tumours. In Drosophila, oxygen is conveyed to the internal organs by the tracheal system, a closed tubular network whose role in cancer growth is so far unexplored. We found that, as observed in human cancers, Drosophila malignant cells suffer from oxygen shortage, release pro-tracheogenic factors, co-opt nearby vessels and get incorporated into the tracheal walls. We also found that the parallelisms observed in cellular behaviours are supported by genetic and molecular conservation. Finally, we identified a molecular circuitry associated with the differentiation of cancer cells into tracheal cells. In summary, our findings identify tracheogenesis as a novel cancer hallmark in Drosophila, further expanding the power of the fly model in cancer research.

  10. Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

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    Bing Jiang

    2017-01-01

    Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

  11. The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures

    International Nuclear Information System (INIS)

    Cockburn, Jessica G.; Hallett, Robin M.; Gillgrass, Amy E.; Dias, Kay N.; Whelan, T.; Levine, M. N.; Hassell, John A.; Bane, Anita

    2016-01-01

    Lymph node (LN) status is the most important prognostic variable used to guide ER positive (+) breast cancer treatment. While a positive nodal status is traditionally associated with a poor prognosis, a subset of these patients respond well to treatment and achieve long-term survival. Several gene signatures have been established as a means of predicting outcome of breast cancer patients, but the development and indication for use of these assays varies. Here we compare the capacity of two approved gene signatures and a third novel signature to predict outcome in distinct LN negative (-) and LN+ populations. We also examine biological differences between tumours associated with LN- and LN+ disease. Gene expression data from publically available data sets was used to compare the ability of Oncotype DX and Prosigna to predict Distant Metastasis Free Survival (DMFS) using an in silico platform. A novel gene signature (Ellen) was developed by including patients with both LN- and LN+ disease and using Prediction Analysis of Microarrays (PAM) software. Gene Set Enrichment Analysis (GSEA) was used to determine biological pathways associated with patient outcome in both LN- and LN+ tumors. The Oncotype DX gene signature, which only used LN- patients during development, significantly predicted outcome in LN- patients, but not LN+ patients. The Prosigna gene signature, which included both LN- and LN+ patients during development, predicted outcome in both LN- and LN+ patient groups. Ellen was also able to predict outcome in both LN- and LN+ patient groups. GSEA suggested that epigenetic modification may be related to poor outcome in LN- disease, whereas immune response may be related to good outcome in LN+ disease. We demonstrate the importance of incorporating lymph node status during the development of prognostic gene signatures. Ellen may be a useful tool to predict outcome of patients regardless of lymph node status, or for those with unknown lymph node status. Finally we

  12. Tumor xenograft modeling identifies an association between TCF4 loss and breast cancer chemoresistance

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    Gorka Ruiz de Garibay

    2018-05-01

    Full Text Available Understanding the mechanisms of cancer therapeutic resistance is fundamental to improving cancer care. There is clear benefit from chemotherapy in different breast cancer settings; however, knowledge of the mutations and genes that mediate resistance is incomplete. In this study, by modeling chemoresistance in patient-derived xenografts (PDXs, we show that adaptation to therapy is genetically complex and identify that loss of transcription factor 4 (TCF4; also known as ITF2 is associated with this process. A triple-negative BRCA1-mutated PDX was used to study the genetics of chemoresistance. The PDX was treated in parallel with four chemotherapies for five iterative cycles. Exome sequencing identified few genes with de novo or enriched mutations in common among the different therapies, whereas many common depleted mutations/genes were observed. Analysis of somatic mutations from The Cancer Genome Atlas (TCGA supported the prognostic relevance of the identified genes. A mutation in TCF4 was found de novo in all treatments, and analysis of drug sensitivity profiles across cancer cell lines supported the link to chemoresistance. Loss of TCF4 conferred chemoresistance in breast cancer cell models, possibly by altering cell cycle regulation. Targeted sequencing in chemoresistant tumors identified an intronic variant of TCF4 that may represent an expression quantitative trait locus associated with relapse outcome in TCGA. Immunohistochemical studies suggest a common loss of nuclear TCF4 expression post-chemotherapy. Together, these results from tumor xenograft modeling depict a link between altered TCF4 expression and breast cancer chemoresistance.

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

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    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.

  14. Evaluation of algorithms to identify incident cancer cases by using French health administrative databases.

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    Ajrouche, Aya; Estellat, Candice; De Rycke, Yann; Tubach, Florence

    2017-08-01

    Administrative databases are increasingly being used in cancer observational studies. Identifying incident cancer in these databases is crucial. This study aimed to develop algorithms to estimate cancer incidence by using health administrative databases and to examine the accuracy of the algorithms in terms of national cancer incidence rates estimated from registries. We identified a cohort of 463 033 participants on 1 January 2012 in the Echantillon Généraliste des Bénéficiaires (EGB; a representative sample of the French healthcare insurance system). The EGB contains data on long-term chronic disease (LTD) status, reimbursed outpatient treatments and procedures, and hospitalizations (including discharge diagnoses, and costly medical procedures and drugs). After excluding cases of prevalent cancer, we applied 15 algorithms to estimate the cancer incidence rates separately for men and women in 2012 and compared them to the national cancer incidence rates estimated from French registries by indirect age and sex standardization. The most accurate algorithm for men combined information from LTD status, outpatient anticancer drugs, radiotherapy sessions and primary or related discharge diagnosis of cancer, although it underestimated the cancer incidence (standardized incidence ratio (SIR) 0.85 [0.80-0.90]). For women, the best algorithm used the same definition of the algorithm for men but restricted hospital discharge to only primary or related diagnosis with an additional inpatient procedure or drug reimbursement related to cancer and gave comparable estimates to those from registries (SIR 1.00 [0.94-1.06]). The algorithms proposed could be used for cancer incidence monitoring and for future etiological cancer studies involving French healthcare databases. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  15. Comprehensive profiling of DNA repair defects in breast cancer identifies a novel class of endocrine therapy resistance drivers.

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    Anurag, Meenakshi; Punturi, Nindo; Hoog, Jeremy; Bainbridge, Matthew N; Ellis, Matthew J; Haricharan, Svasti

    2018-05-23

    This study was undertaken to conduct a comprehensive investigation of the role of DNA damage repair (DDR) defects in poor outcome ER+ disease. Expression and mutational status of DDR genes in ER+ breast tumors were correlated with proliferative response in neoadjuvant aromatase inhibitor therapy trials (discovery data set), with outcomes in METABRIC, TCGA and Loi data sets (validation data sets), and in patient derived xenografts. A causal relationship between candidate DDR genes and endocrine treatment response, and the underlying mechanism, was then tested in ER+ breast cancer cell lines. Correlations between loss of expression of three genes: CETN2 (p<0.001) and ERCC1 (p=0.01) from the nucleotide excision repair (NER) and NEIL2 (p=0.04) from the base excision repair (BER) pathways were associated with endocrine treatment resistance in discovery data sets, and subsequently validated in independent patient cohorts. Complementary mutation analysis supported associations between mutations in NER and BER pathways and reduced endocrine treatment response. A causal role for CETN2, NEIL2 and ERCC1 loss in intrinsic endocrine resistance was experimentally validated in ER+ breast cancer cell lines, and in ER+ patient-derived xenograft models. Loss of CETN2, NEIL2 or ERCC1 induced endocrine treatment response by dysregulating G1/S transition, and therefore, increased sensitivity to CDK4/6 inhibitors. A combined DDR signature score was developed that predicted poor outcome in multiple patient cohorts. This report identifies DDR defects as a new class of endocrine treatment resistance drivers and indicates new avenues for predicting efficacy of CDK4/6 inhibition in the adjuvant treatment setting. Copyright ©2018, American Association for Cancer Research.

  16. 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.

  17. CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes.

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    Kong, Hualei; Tong, Pan; Zhao, Xiaodong; Sun, Jielin; Li, Hua

    2018-03-01

    In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and

  18. 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

    2016-04-05

    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.

  19. Prostate Cancer Associated Lipid Signatures in Serum Studied by ESI-Tandem Mass Spectrometryas Potential New Biomarkers.

    Science.gov (United States)

    Duscharla, Divya; Bhumireddy, Sudarshana Reddy; Lakshetti, Sridhar; Pospisil, Heike; Murthy, P V L N; Walther, Reinhard; Sripadi, Prabhakar; Ummanni, Ramesh

    2016-01-01

    Prostate cancer (PCa) is one amongst the most common cancersin western men. Incidence rate ofPCa is on the rise worldwide. The present study deals with theserum lipidome profiling of patients diagnosed with PCa to identify potential new biomarkers. We employed ESI-MS/MS and GC-MS for identification of significantly altered lipids in cancer patient's serum compared to controls. Lipidomic data revealed 24 lipids are significantly altered in cancer patinet's serum (n = 18) compared to normal (n = 18) with no history of PCa. By using hierarchical clustering and principal component analysis (PCA) we could clearly separate cancer patients from control group. Correlation and partition analysis along with Formal Concept Analysis (FCA) have identified that PC (39:6) and FA (22:3) could classify samples with higher certainty. Both the lipids, PC (39:6) and FA (22:3) could influence the cataloging of patients with 100% sensitivity (all 18 control samples are classified correctly) and 77.7% specificity (of 18 tumor samples 4 samples are misclassified) with p-value of 1.612×10-6 in Fischer's exact test. Further, we performed GC-MS to denote fatty acids altered in PCa patients and found that alpha-linolenic acid (ALA) levels are altered in PCa. We also performed an in vitro proliferation assay to determine the effect of ALA in survival of classical human PCa cell lines LNCaP and PC3. We hereby report that the altered lipids PC (39:6) and FA (22:3) offer a new set of biomarkers in addition to the existing diagnostic tests that could significantly improve sensitivity and specificity in PCa diagnosis.

  20. Unique protein expression signatures of survival time in kidney renal clear cell carcinoma through a pan-cancer screening.

    Science.gov (United States)

    Han, Guangchun; Zhao, Wei; Song, Xiaofeng; Kwok-Shing Ng, Patrick; Karam, Jose A; Jonasch, Eric; Mills, Gordon B; Zhao, Zhongming; Ding, Zhiyong; Jia, Peilin

    2017-10-03

    In 2016, it is estimated that there will be 62,700 new cases of kidney cancer in the United States, and 14,240 patients will die from the disease. Because the incidence of kidney renal clear cell carcinoma (KIRC), the most common type of kidney cancer, is expected to continue to increase in the US, there is an urgent need to find effective diagnostic biomarkers for KIRC that could help earlier detection of and customized treatment strategies for the disease. Accordingly, in this study we systematically investigated KIRC's prognostic biomarkers for survival using the reverse phase protein array (RPPA) data and the high throughput sequencing data from The Cancer Genome Atlas (TCGA). With comprehensive data available in TCGA, we systematically screened protein expression based survival biomarkers in 10 major cancer types, among which KIRC presented many protein prognostic biomarkers of survival time. This is in agreement with a previous report that expression level changes (mRNAs, microRNA and protein) may have a better performance for prognosis of KIRC. In this study, we also identified 52 prognostic genes for KIRC, many of which are involved in cell-cycle and cancer signaling, as well as 15 tumor-stage-specific prognostic biomarkers. Notably, we found fewer prognostic biomarkers for early-stage than for late-stage KIRC. Four biomarkers (the RPPA protein IDs: FASN, ACC1, Cyclin_B1 and Rad51) were found to be prognostic for survival based on both protein and mRNA expression data. Through pan-cancer screening, we found that many protein biomarkers were prognostic for patients' survival in KIRC. Stage-specific survival biomarkers in KIRC were also identified. Our study indicated that these protein biomarkers might have potential clinical value in terms of predicting survival in KIRC patients and developing individualized treatment strategies. Importantly, we found many biomarkers in KIRC at both the mRNA expression level and the protein expression level. These

  1. Identifying mRNA targets of microRNA dysregulated in cancer: with application to clear cell Renal Cell Carcinoma

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    Liou Louis S

    2010-04-01

    Full Text Available Abstract Background MicroRNA regulate mRNA levels in a tissue specific way, either by inducing degradation of the transcript or by inhibiting translation or transcription. Putative mRNA targets of microRNA identified from seed sequence matches are available in many databases. However, such matches have a high false positive rate and cannot identify tissue specificity of regulation. Results We describe a simple method to identify direct mRNA targets of microRNA dysregulated in cancers from expression level measurements in patient matched tumor/normal samples. The word "direct" is used here in a strict sense to: a represent mRNA which have an exact seed sequence match to the microRNA in their 3'UTR, b the seed sequence match is strictly conserved across mouse, human, rat and dog genomes, c the mRNA and microRNA expression levels can distinguish tumor from normal with high significance and d the microRNA/mRNA expression levels are strongly and significantly anti-correlated in tumor and/or normal samples. We apply and validate the method using clear cell Renal Cell Carcinoma (ccRCC and matched normal kidney samples, limiting our analysis to mRNA targets which undergo degradation of the mRNA transcript because of a perfect seed sequence match. Dysregulated microRNA and mRNA are first identified by comparing their expression levels in tumor vs normal samples. Putative dysregulated microRNA/mRNA pairs are identified from these using seed sequence matches, requiring that the seed sequence be conserved in human/dog/rat/mouse genomes. These are further pruned by requiring a strong anti-correlation signature in tumor and/or normal samples. The method revealed many new regulations in ccRCC. For instance, loss of miR-149, miR-200c and mir-141 causes gain of function of oncogenes (KCNMA1, LOX, VEGFA and SEMA6A respectively and increased levels of miR-142-3p, miR-185, mir-34a, miR-224, miR-21 cause loss of function of tumor suppressors LRRC2, PTPN13, SFRP1

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

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    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

  3. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Science.gov (United States)

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  4. Phosphoproteomic Analysis Identifies Signaling Pathways Regulated by Curcumin in Human Colon Cancer Cells.

    Science.gov (United States)

    Sato, Tatsuhiro; Higuchi, Yutaka; Shibagaki, Yoshio; Hattori, Seisuke

    2017-09-01

    Curcumin, a major polyphenol of the spice turmeric, acts as a potent chemopreventive and chemotherapeutic agent in several cancer types, including colon cancer. Although various proteins have been shown to be affected by curcumin, how curcumin exerts its anticancer activity is not fully understood. Phosphoproteomic analyses were performed using SW480 and SW620 human colon cancer cells to identify curcumin-affected signaling pathways. Curcumin inhibited the growth of the two cell lines in a dose-dependent manner. Thirty-nine curcumin-regulated phosphoproteins were identified, five of which are involved in cancer signaling pathways. Detailed analyses revealed that the mTORC1 and p53 signaling pathways are main targets of curcumin. Our results provide insight into the molecular mechanisms of the anticancer activities of curcumin and future molecular targets for its clinical application. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  5. 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; Dos Santos Silva, Isabel; 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; Veer, Laura J Van't; 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

    2013-04-01

    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 breast cancer susceptibility.

  6. 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.

  7. Lipidomic Profiling of Lung Pleural Effusion Identifies Unique Metabotype for EGFR Mutants in Non-Small Cell Lung Cancer.

    Science.gov (United States)

    Ho, Ying Swan; Yip, Lian Yee; Basri, Nurhidayah; Chong, Vivian Su Hui; Teo, Chin Chye; Tan, Eddy; Lim, Kah Ling; Tan, Gek San; Yang, Xulei; Yeo, Si Yong; Koh, Mariko Si Yue; Devanand, Anantham; Takano, Angela; Tan, Eng Huat; Tan, Daniel Shao Weng; Lim, Tony Kiat Hon

    2016-10-14

    Cytology and histology forms the cornerstone for the diagnosis of non-small cell lung cancer (NSCLC) but obtaining sufficient tumour cells or tissue biopsies for these tests remains a challenge. We investigate the lipidome of lung pleural effusion (PE) for unique metabolic signatures to discriminate benign versus malignant PE and EGFR versus non-EGFR malignant subgroups to identify novel diagnostic markers that is independent of tumour cell availability. Using liquid chromatography mass spectrometry, we profiled the lipidomes of the PE of 30 benign and 41 malignant cases with or without EGFR mutation. Unsupervised principal component analysis revealed distinctive differences between the lipidomes of benign and malignant PE as well as between EGFR mutants and non-EGFR mutants. Docosapentaenoic acid and Docosahexaenoic acid gave superior sensitivity and specificity for detecting NSCLC when used singly. Additionally, several 20- and 22- carbon polyunsaturated fatty acids and phospholipid species were significantly elevated in the EGFR mutants compared to non-EGFR mutants. A 7-lipid panel showed great promise in the stratification of EGFR from non-EGFR malignant PE. Our data revealed novel lipid candidate markers in the non-cellular fraction of PE that holds potential to aid the diagnosis of benign, EGFR mutation positive and negative NSCLC.

  8. VEGFR-1 Overexpression Identifies a Small Subgroup of Aggressive Prostate Cancers in Patients Treated by Prostatectomy

    Directory of Open Access Journals (Sweden)

    Maria Christina Tsourlakis

    2015-04-01

    Full Text Available The VEGFR-1 is suggested to promote tumor progression. In the current study we analyzed prevalence and prognostic impact of the VEGFR-1 by immunohistochemistry on a tissue microarray containing more than 3000 prostate cancer specimens. Results were compared to tumor phenotype, ETS-related gene (ERG status, and biochemical recurrence. Membranous VEGFR-1 expression was detectable in 32.6% of 2669 interpretable cancers and considered strong in 1.7%, moderate in 6.7% and weak in 24.2% of cases. Strong VEGFR-1 expression was associated with TMPRSS2:ERG fusion status as determined by fluorescence in situ hybridization (FISH and immunohistochemistry (p < 0.0001 each. Elevated VEGFR-1 expression was linked to high Gleason grade and advanced pT stage in TMPRSS2:ERG negative cancers (p = 0.0008 and p = 0.001, while these associations were absent in TMPRSS2:ERG positive cancers. VEGFR-1 expression was also linked to phosphatase and tensin homolog (PTEN deletions. A comparison with prostate specific antigen (PSA recurrence revealed that the 1.7% of prostate cancers with the highest VEGFR-1 levels had a strikingly unfavorable prognosis. This could be seen in all cancers, in the subsets of TMPRSS2:ERG positive or negative, PTEN deleted or undeleted carcinomas (p < 0.0001 each. High level VEGFR-1 expression is infrequent in prostate cancer, but identifies a subgroup of aggressive cancers, which may be candidates for anti-VEGFR-1 targeted therapy.

  9. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

    Directory of Open Access Journals (Sweden)

    Xinguo Lu

    2018-01-01

    Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

  10. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes.

    Science.gov (United States)

    Taube, Joseph H; Herschkowitz, Jason I; Komurov, Kakajan; Zhou, Alicia Y; Gupta, Supriya; Yang, Jing; Hartwell, Kimberly; Onder, Tamer T; Gupta, Piyush B; Evans, Kurt W; Hollier, Brett G; Ram, Prahlad T; Lander, Eric S; Rosen, Jeffrey M; Weinberg, Robert A; Mani, Sendurai A

    2010-08-31

    The epithelial-to-mesenchymal transition (EMT) produces cancer cells that are invasive, migratory, and exhibit stem cell characteristics, hallmarks of cells that have the potential to generate metastases. Inducers of the EMT include several transcription factors (TFs), such as Goosecoid, Snail, and Twist, as well as the secreted TGF-beta1. Each of these factors is capable, on its own, of inducing an EMT in the human mammary epithelial (HMLE) cell line. However, the interactions between these regulators are poorly understood. Overexpression of each of the above EMT inducers up-regulates a subset of other EMT-inducing TFs, with Twist, Zeb1, Zeb2, TGF-beta1, and FOXC2 being commonly induced. Up-regulation of Slug and FOXC2 by either Snail or Twist does not depend on TGF-beta1 signaling. Gene expression signatures (GESs) derived by overexpressing EMT-inducing TFs reveal that the Twist GES and Snail GES are the most similar, although the Goosecoid GES is the least similar to the others. An EMT core signature was derived from the changes in gene expression shared by up-regulation of Gsc, Snail, Twist, and TGF-beta1 and by down-regulation of E-cadherin, loss of which can also trigger an EMT in certain cell types. The EMT core signature associates closely with the claudin-low and metaplastic breast cancer subtypes and correlates negatively with pathological complete response. Additionally, the expression level of FOXC1, another EMT inducer, correlates strongly with poor survival of breast cancer patients.

  11. Functional genomics identifies specific vulnerabilities in PTEN-deficient breast cancer.

    Science.gov (United States)

    Tang, Yew Chung; Ho, Szu-Chi; Tan, Elisabeth; Ng, Alvin Wei Tian; McPherson, John R; Goh, Germaine Yen Lin; Teh, Bin Tean; Bard, Frederic; Rozen, Steven G

    2018-03-22

    Phosphatase and tensin homolog (PTEN) is one of the most frequently inactivated tumor suppressors in breast cancer. While PTEN itself is not considered a druggable target, PTEN synthetic-sick or synthetic-lethal (PTEN-SSL) genes are potential drug targets in PTEN-deficient breast cancers. Therefore, with the aim of identifying potential targets for precision breast cancer therapy, we sought to discover PTEN-SSL genes present in a broad spectrum of breast cancers. To discover broad-spectrum PTEN-SSL genes in breast cancer, we used a multi-step approach that started with (1) a genome-wide short interfering RNA (siRNA) screen of ~ 21,000 genes in a pair of isogenic human mammary epithelial cell lines, followed by (2) a short hairpin RNA (shRNA) screen of ~ 1200 genes focused on hits from the first screen in a panel of 11 breast cancer cell lines; we then determined reproducibility of hits by (3) identification of overlaps between our results and reanalyzed data from 3 independent gene-essentiality screens, and finally, for selected candidate PTEN-SSL genes we (4) confirmed PTEN-SSL activity using either drug sensitivity experiments in a panel of 19 cell lines or mutual exclusivity analysis of publicly available pan-cancer somatic mutation data. The screens (steps 1 and 2) and the reproducibility analysis (step 3) identified six candidate broad-spectrum PTEN-SSL genes (PIK3CB, ADAMTS20, AP1M2, HMMR, STK11, and NUAK1). PIK3CB was previously identified as PTEN-SSL, while the other five genes represent novel PTEN-SSL candidates. Confirmation studies (step 4) provided additional evidence that NUAK1 and STK11 have PTEN-SSL patterns of activity. Consistent with PTEN-SSL status, inhibition of the NUAK1 protein kinase by the small molecule drug HTH-01-015 selectively impaired viability in multiple PTEN-deficient breast cancer cell lines, while mutations affecting STK11 and PTEN were largely mutually exclusive across large pan-cancer data sets. Six genes showed PTEN

  12. 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...

  13. ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

    Science.gov (United States)

    Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

    2015-01-01

    Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

  14. An Evaluation of Algorithms for Identifying Metastatic Breast, Lung, or Colorectal Cancer in Administrative Claims Data.

    Science.gov (United States)

    Whyte, Joanna L; Engel-Nitz, Nicole M; Teitelbaum, April; Gomez Rey, Gabriel; Kallich, Joel D

    2015-07-01

    Administrative health care claims data are used for epidemiologic, health services, and outcomes cancer research and thus play a significant role in policy. Cancer stage, which is often a major driver of cost and clinical outcomes, is not typically included in claims data. Evaluate algorithms used in a dataset of cancer patients to identify patients with metastatic breast (BC), lung (LC), or colorectal (CRC) cancer using claims data. Clinical data on BC, LC, or CRC patients (between January 1, 2007 and March 31, 2010) were linked to a health care claims database. Inclusion required health plan enrollment ≥3 months before initial cancer diagnosis date. Algorithms were used in the claims database to identify patients' disease status, which was compared with physician-reported metastases. Generic and tumor-specific algorithms were evaluated using ICD-9 codes, varying diagnosis time frames, and including/excluding other tumors. Positive and negative predictive values, sensitivity, and specificity were assessed. The linked databases included 14,480 patients; of whom, 32%, 17%, and 14.2% had metastatic BC, LC, and CRC, respectively, at diagnosis and met inclusion criteria. Nontumor-specific algorithms had lower specificity than tumor-specific algorithms. Tumor-specific algorithms' sensitivity and specificity were 53% and 99% for BC, 55% and 85% for LC, and 59% and 98% for CRC, respectively. Algorithms to distinguish metastatic BC, LC, and CRC from locally advanced disease should use tumor-specific primary cancer codes with 2 claims for the specific primary cancer >30-42 days apart to reduce misclassification. These performed best overall in specificity, positive predictive values, and overall accuracy to identify metastatic cancer in a health care claims database.

  15. Chemical biology drug sensitivity screen identifies sunitinib as synergistic agent with disulfiram in prostate cancer cells.

    Directory of Open Access Journals (Sweden)

    Kirsi Ketola

    Full Text Available Current treatment options for castration- and treatment-resistant prostate cancer are limited and novel approaches are desperately needed. Our recent results from a systematic chemical biology sensitivity screen covering most known drugs and drug-like molecules indicated that aldehyde dehydrogenase inhibitor disulfiram is one of the most potent cancer-specific inhibitors of prostate cancer cell growth, including TMPRSS2-ERG fusion positive cancers. However, the results revealed that disulfiram alone does not block tumor growth in vivo nor induce apoptosis in vitro, indicating that combinatorial approaches may be required to enhance the anti-neoplastic effects.In this study, we utilized a chemical biology drug sensitivity screen to explore disulfiram mechanistic details and to identify compounds potentiating the effect of disulfiram in TMPRSS2-ERG fusion positive prostate cancer cells. In total, 3357 compounds including current chemotherapeutic agents as well as drug-like small molecular compounds were screened alone and in combination with disulfiram. Interestingly, the results indicated that androgenic and antioxidative compounds antagonized disulfiram effect whereas inhibitors of receptor tyrosine kinase, proteasome, topoisomerase II, glucosylceramide synthase or cell cycle were among compounds sensitizing prostate cancer cells to disulfiram. The combination of disulfiram and an antiangiogenic agent sunitinib was studied in more detail, since both are already in clinical use in humans. Disulfiram-sunitinib combination induced apoptosis and reduced androgen receptor protein expression more than either of the compounds alone. Moreover, combinatorial exposure reduced metastatic characteristics such as cell migration and 3D cell invasion as well as induced epithelial differentiation shown as elevated E-cadherin expression.Taken together, our results propose novel combinatorial approaches to inhibit prostate cancer cell growth. Disulfiram

  16. 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

  17. 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.

  18. In Vivo Detection of HSP90 Identifies Breast Cancers with Aggressive Behavior.

    Science.gov (United States)

    Osada, Takuya; Kaneko, Kensuke; Gwin, William R; Morse, Michael A; Hobeika, Amy; Pogue, Brian W; Hartman, Zachary C; Hughes, Philip F; Haystead, Timothy; Lyerly, H Kim

    2017-12-15

    Purpose: Hsp90, a chaperone to numerous molecular pathways in malignant cells, is elevated in aggressive breast cancers. We hypothesized that identifying breast cells with elevated Hsp90 activity in situ could result in early detection of aggressive breast cancers. Experimental Design: We exploited the uptake of an Hsp90 inhibitor by malignant cells to create an imaging probe (HS131) of Hsp90 activity by linking it to a near-infrared (nIR) dye. HS131 uptake into cells correlated with cell membrane expression of Hsp90 and was used to image molecular subtypes of murine and human breast cancers in vitro and in murine models. Results: HS131 imaging was both sensitive and specific in detecting the murine 4T1 breast cancer cell line, as well as subclones with differing metastatic potential. Highly metastatic subclones (4T07) had high HS131 uptake, but subclones with lower metastatic potential (67NR, 168FARN) had low HS131 uptake. We generated isogenic cell lines to demonstrate that overexpression of a variety of specific oncogenes resulted in high HS131 uptake and retention. Finally, we demonstrated that HS131 could be used to detect spontaneous tumors in MMTV-neu mice, as well as primary and metastatic human breast cancer xenografts. HS131 could image invasive lobular breast cancer, a histologic subtype of breast cancer which is often undetectable by mammography. Conclusions: An HSP90-targeting nIR probe is sensitive and specific in imaging all molecular subtypes of murine and human breast cancer, with higher uptake in aggressive and highly metastatic clones. Clinical studies with Hsp90-targeting nIR probes will be initiated shortly. Clin Cancer Res; 23(24); 7531-42. ©2017 AACR . ©2017 American Association for Cancer Research.

  19. 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...

  20. Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer.

    Science.gov (United States)

    Sugimoto, Mitsushige; Ban, Hiromitsu; Ichikawa, Hitomi; Sahara, Shu; Otsuka, Taketo; Inatomi, Osamu; Bamba, Shigeki; Furuta, Takahisa; Andoh, Akira

    2017-01-01

    Objective The Kyoto gastritis classification categorizes the endoscopic characteristics of Helicobacter pylori (H. pylori) infection-associated gastritis and identifies patterns associated with a high risk of gastric cancer. We investigated its efficacy, comparing scores in patients with H. pylori-associated gastritis and with gastric cancer. Methods A total of 1,200 patients with H. pylori-positive gastritis alone (n=932), early-stage H. pylori-positive gastric cancer (n=189), and successfully treated H. pylori-negative cancer (n=79) were endoscopically graded according to the Kyoto gastritis classification for atrophy, intestinal metaplasia, fold hypertrophy, nodularity, and diffuse redness. Results The prevalence of O-II/O-III-type atrophy according to the Kimura-Takemoto classification in early-stage H. pylori-positive gastric cancer and successfully treated H. pylori-negative cancer groups was 45.1%, which was significantly higher than in subjects with gastritis alone (12.7%, pgastritis scores of atrophy and intestinal metaplasia in the H. pylori-positive cancer group were significantly higher than in subjects with gastritis alone (all pgastritis classification may thus be useful for detecting these patients.

  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. 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

    2016-09-07

    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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. 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......). We specifically addressed anticipation in phenotypic HNPCC families without disease-predisposing mismatch repair (MMR) defects since risk estimates and age at onset are particularly difficult to determine in this cohort. The national Danish HNPCC register was used to identify families who fulfilled...... 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...

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Fatemeh Vida Zohoori

    Full Text Available 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.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.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.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.

  6. 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

    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...

  7. 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

    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...

  8. 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...

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

    NARCIS (Netherlands)

    N. Orr (Nick); F. Dudbridge (Frank); N. Dryden (Nicola); S. Maguire (Sarah); D. Novo (Daniela); E. Perrakis (Eleni); N. Johnson (Nichola); M. Ghoussaini (Maya); J. Hopper (John); M.C. Southey (Melissa); C. Apicella (Carmel); J. Stone (Jennifer); M.K. Schmidt (Marjanka); A. Broeks (Annegien); L.J. van 't Veer (Laura); F.B.L. Hogervorst (Frans); P.A. Fasching (Peter); L. Haeberle (Lothar); A.B. Ekici (Arif); M.W. Beckmann (Matthias); L.J. Gibson (Lorna); A. Aitken; H. Warren (Helen); E.J. Sawyer (Elinor); I.P. Tomlinson (Ian); M. Kerin (Michael); N. Miller (Nicola); B. Burwinkel (Barbara); F. Marme (Federick); A. Schneeweiss (Andreas); C. Sohn (Chistof); P. Guénel (Pascal); T. Truong (Thérèse); E. Cordina-Duverger (Emilie); M. Sanchez (Marie); S.E. Bojesen (Stig); B.G. Nordestgaard (Børge); S.F. Nielsen (Sune); H. Flyger (Henrik); J. Benítez (Javier); M.P. Zamora (Pilar); J.I.A. Perez (Jose Ignacio Arias); P. Menéndez (Primitiva); H. Anton-Culver (Hoda); S.L. Neuhausen (Susan); H. Brenner (Hermann); A.K. Dieffenbach (Aida Karina); V. Arndt (Volker); C. Stegmaier (Christa); U. Hamann (Ute); H. Brauch (Hiltrud); C. Justenhoven (Christina); T. Brüning (Thomas); Y.-D. Ko (Yon-Dschun); H. Nevanlinna (Heli); K. Aittomäki (Kristiina); C. Blomqvist (Carl); S. Khan (Sofia); N.V. Bogdanova (Natalia); T. Dörk (Thilo); A. Lindblom (Annika); S. Margolin (Sara); A. Mannermaa (Arto); V. Kataja (Vesa); V-M. Kosma (Veli-Matti); J.M. Hartikainen (J.); G. Chenevix-Trench (Georgia); J. Beesley (Jonathan); D. Lambrechts (Diether); M. Moisse (Matthieu); O.A.M. Floris; B. Beuselinck (B.); J. Chang-Claude (Jenny); A. Rudolph (Anja); P. Seibold (Petra); D. Flesch-Janys (Dieter); P. Radice (Paolo); P. Peterlongo (Paolo); B. Peissel (Bernard); V. Pensotti (Valeria); F.J. Couch (Fergus); J.E. Olson (Janet); S. Slettedahl (Seth); C. Vachon (Celine); G.G. Giles (Graham G.); R.L. Milne (Roger L.); C.A. McLean (Catriona Ann); C.A. Haiman (Christopher); B.E. Henderson (Brian); F.R. Schumacher (Fredrick); L. Le Marchand (Loic); J. Simard (Jacques); M.S. Goldberg (Mark); F. Labrèche (France); M. Dumont (Martine); V. Kristensen (Vessela); G.G. Alnæs (Grethe); S. Nord (Silje); A.-L. Borresen-Dale (Anne-Lise); W. Zheng (Wei); S.L. Deming-Halverson (Sandra); M. Shrubsole (Martha); J. Long (Jirong); R. Winqvist (Robert); K. Pykäs (Katri); A. Jukkola-Vuorinen (Arja); M. Grip (Mervi); I.L. Andrulis (Irene); J.A. Knight (Julia); G. Glendon (Gord); S. Tchatchou (Sandrine); P. Devilee (Peter); R.A.E.M. Tollenaar (Robertus A. E. M.); C.M. Seynaeve (Caroline); C.J. van Asperen (Christi); M. García-Closas (Montserrat); J.D. Figueroa (Jonine); S.J. Chanock (Stephen); J. Lissowska (Jolanta); K. Czene (Kamila); H. Darabi (Hatef); M. Eriksson (Mikael); D. Klevebring (Daniel); M.J. Hooning (Maartje); A. Hollestelle (Antoinette); C.H.M. van Deurzen (Carolien); M. Kriege (Mieke); P. Hall (Per); J. Li (Jingmei); J. Liu (Jianjun); M.K. Humphreys (Manjeet); A. Cox (Angela); S.S. Cross (Simon); M.W.R. Reed (Malcolm); P.D.P. Pharoah (Paul); A.M. Dunning (Alison); M. Shah (Mitul); B. Perkins (Barbara); A. Jakubowska (Anna); J. Lubinski (Jan); K. Jaworska-Bieniek (Katarzyna); K. Durda (Katarzyna); A. Ashworth (Alan); A.J. Swerdlow (Anthony ); M. Jones (Michael); M. Schoemaker (Minouk); A. Meindl (Alfons); R.K. Schmutzler (Rita); C. Olswold (Curtis); S. Slager (Susan); A.E. Toland (Amanda); D. Yannoukakos (Drakoulis); K.R. Muir (K.); A. Lophatananon (Artitaya); S. Stewart-Brown (Sarah); P. Siriwanarangsan (Pornthep); K. Matsuo (Keitaro); H. Ito (Hidema); H. Iwata (Hisato); J. Ishiguro (Junko); A.H. Wu (Anna H.); C.-C. Tseng (Chiu-chen); D. Van Den Berg (David); D.O. Stram (Daniel O.); S.-H. Teo (Soo-Hwang); C.H. Yip (Cheng Har); P. Kang (Peter); M.K. Ikram (Kamran); X.-O. Shu (Xiao-Ou); W. Lu (Wei); Y. Gao; H. Cai (Hui); D. Kang (Daehee); J.-Y. Choi (J.); S.K. Park (Sue); D-Y. Noh (Dong-Young); J.M. Hartman (Joost); X. Miao; W.-Y. Lim (Wei-Yen); S.C. Lee (Soo Chin); S. Sangrajrang (Suleeporn); V. Gaborieau (Valerie); P. Brennan (Paul); J.D. McKay (James); P.-E. Wu (Pei-Ei); M.-F. Hou (Ming-Feng); J-C. Yu (Jyh-Cherng); C-Y. Shen (Chen-Yang); W.J. Blot (William); Q. Cai (Qiuyin); L.B. Signorello (Lisa B.); C. Luccarini (Craig); C. Bayes (Caroline); S. Ahmed (Shahana); M. Maranian (Melanie); S. Healey (Sue); A. González-Neira (Anna); G. Pita (Guillermo); M. Rosario Alonso; N. Álvarez (Nuria); D. Herrero (Daniel); D.C. Tessier (Daniel C.); D. Vincent (Daniel); F. Bacot (Francois); D. Hunter (David); S. Lindstrom (Stephen); J. Dennis (Joe); K. Michailidou (Kyriaki); M.K. Bolla (Manjeet); D.F. Easton (Douglas); I. dos Santos Silva (Isabel); O. Fletcher (Olivia); J. Peto (Julian)

    2015-01-01

    textabstractWe 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

  10. 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....

  11. Preferential Allele Expression Analysis Identifies Shared Germline and Somatic Driver Genes in Advanced Ovarian Cancer

    Science.gov (United States)

    Halabi, Najeeb M.; Martinez, Alejandra; Al-Farsi, Halema; Mery, Eliane; Puydenus, Laurence; Pujol, Pascal; Khalak, Hanif G.; McLurcan, Cameron; Ferron, Gwenael; Querleu, Denis; Al-Azwani, Iman; Al-Dous, Eman; Mohamoud, Yasmin A.; Malek, Joel A.; Rafii, Arash

    2016-01-01

    Identifying genes where a variant allele is preferentially expressed in tumors could lead to a better understanding of cancer biology and optimization of targeted therapy. However, tumor sample heterogeneity complicates standard approaches for detecting preferential allele expression. We therefore developed a novel approach combining genome and transcriptome sequencing data from the same sample that corrects for sample heterogeneity and identifies significant preferentially expressed alleles. We applied this analysis to epithelial ovarian cancer samples consisting of matched primary ovary and peritoneum and lymph node metastasis. We find that preferentially expressed variant alleles include germline and somatic variants, are shared at a relatively high frequency between patients, and are in gene networks known to be involved in cancer processes. Analysis at a patient level identifies patient-specific preferentially expressed alleles in genes that are targets for known drugs. Analysis at a site level identifies patterns of site specific preferential allele expression with similar pathways being impacted in the primary and metastasis sites. We conclude that genes with preferentially expressed variant alleles can act as cancer drivers and that targeting those genes could lead to new therapeutic strategies. PMID:26735499

  12. Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types

    NARCIS (Netherlands)

    Starmans, M. H. W.; Krishnapuram, B.; Steck, H.; Horlings, H.; Nuyten, D. S. A.; van de Vijver, M. J.; Seigneuric, R.; Buffa, F. M.; Harris, A. L.; Wouters, B. G.; Lambin, P.

    2008-01-01

    Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable

  13. Identifying women with dense breasts at high risk for interval cancer: a cohort study.

    Science.gov (United States)

    Kerlikowske, Karla; Zhu, Weiwei; Tosteson, Anna N A; Sprague, Brian L; Tice, Jeffrey A; Lehman, Constance D; Miglioretti, Diana L

    2015-05-19

    Twenty-one states have laws requiring that women be notified if they have dense breasts and that they be advised to discuss supplemental imaging with their provider. To better direct discussions of supplemental imaging by determining which combinations of breast cancer risk and Breast Imaging Reporting and Data System (BI-RADS) breast density categories are associated with high interval cancer rates. Prospective cohort. Breast Cancer Surveillance Consortium (BCSC) breast imaging facilities. 365,426 women aged 40 to 74 years who had 831,455 digital screening mammography examinations. BI-RADS breast density, BCSC 5-year breast cancer risk, and interval cancer rate (invasive cancer ≤12 months after a normal mammography result) per 1000 mammography examinations. High interval cancer rate was defined as more than 1 case per 1000 examinations. High interval cancer rates were observed for women with 5-year risk of 1.67% or greater and extremely dense breasts or 5-year risk of 2.50% or greater and heterogeneously dense breasts (24% of all women with dense breasts). The interval rate of advanced-stage disease was highest (>0.4 case per 1000 examinations) among women with 5-year risk of 2.50% or greater and heterogeneously or extremely dense breasts (21% of all women with dense breasts). Five-year risk was low to average (0% to 1.66%) for 51.0% of women with heterogeneously dense breasts and 52.5% with extremely dense breasts, with interval cancer rates of 0.58 to 0.63 and 0.72 to 0.89 case per 1000 examinations, respectively. The benefit of supplemental imaging was not assessed. Breast density should not be the sole criterion for deciding whether supplemental imaging is justified because not all women with dense breasts have high interval cancer rates. BCSC 5-year risk combined with BI-RADS breast density can identify women at high risk for interval cancer to inform patient-provider discussions about alternative screening strategies. National Cancer Institute.

  14. Three surgical planes identified in laparoscopic complete mesocolic excision for right-sided colon cancer.

    Science.gov (United States)

    Zhu, Da-Jian; Chen, Xiao-Wu; OuYang, Man-Zhao; Lu, Yan

    2016-01-12

    Complete mesocolic excision provides a correct anatomical plane for colon cancer surgery. However, manifestation of the surgical plane during laparoscopic complete mesocolic excision versus in computed tomography images remains to be examined. Patients who underwent laparoscopic complete mesocolic excision for right-sided colon cancer underwent an abdominal computed tomography scan. The spatial relationship of the intraoperative surgical planes were examined, and then computed tomography reconstruction methods were applied. The resulting images were analyzed. In 44 right-sided colon cancer patients, the surgical plane for laparoscopic complete mesocolic excision was found to be composed of three surgical planes that were identified by computed tomography imaging with cross-sectional multiplanar reconstruction, maximum intensity projection, and volume reconstruction. For the operations performed, the mean bleeding volume was 73±32.3 ml and the mean number of harvested lymph nodes was 22±9.7. The follow-up period ranged from 6-40 months (mean 21.2), and only two patients had distant metastases. The laparoscopic complete mesocolic excision surgical plane for right-sided colon cancer is composed of three surgical planes. When these surgical planes were identified, laparoscopic complete mesocolic excision was a safe and effective procedure for the resection of colon cancer.

  15. Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

    Science.gov (United States)

    Klein, Alison P; Wolpin, Brian M; Risch, Harvey A; Stolzenberg-Solomon, Rachael Z; Mocci, Evelina; Zhang, Mingfeng; Canzian, Federico; Childs, Erica J; Hoskins, Jason W; Jermusyk, Ashley; Zhong, Jun; Chen, Fei; Albanes, Demetrius; Andreotti, Gabriella; Arslan, Alan A; Babic, Ana; Bamlet, William R; Beane-Freeman, Laura; Berndt, Sonja I; Blackford, Amanda; Borges, Michael; Borgida, Ayelet; Bracci, Paige M; Brais, Lauren; Brennan, Paul; Brenner, Hermann; Bueno-de-Mesquita, Bas; Buring, Julie; Campa, Daniele; Capurso, Gabriele; Cavestro, Giulia Martina; Chaffee, Kari G; Chung, Charles C; Cleary, Sean; Cotterchio, Michelle; Dijk, Frederike; Duell, Eric J; Foretova, Lenka; Fuchs, Charles; Funel, Niccola; Gallinger, Steven; M Gaziano, J Michael; Gazouli, Maria; Giles, Graham G; Giovannucci, Edward; Goggins, Michael; Goodman, Gary E; Goodman, Phyllis J; Hackert, Thilo; Haiman, Christopher; Hartge, Patricia; Hasan, Manal; Hegyi, Peter; Helzlsouer, Kathy J; Herman, Joseph; Holcatova, Ivana; Holly, Elizabeth A; Hoover, Robert; Hung, Rayjean J; Jacobs, Eric J; Jamroziak, Krzysztof; Janout, Vladimir; Kaaks, Rudolf; Khaw, Kay-Tee; Klein, Eric A; Kogevinas, Manolis; Kooperberg, Charles; Kulke, Matthew H; Kupcinskas, Juozas; Kurtz, Robert J; Laheru, Daniel; Landi, Stefano; Lawlor, Rita T; Lee, I-Min; LeMarchand, Loic; Lu, Lingeng; Malats, Núria; Mambrini, Andrea; Mannisto, Satu; Milne, Roger L; Mohelníková-Duchoňová, Beatrice; Neale, Rachel E; Neoptolemos, John P; Oberg, Ann L; Olson, Sara H; Orlow, Irene; Pasquali, Claudio; Patel, Alpa V; Peters, Ulrike; Pezzilli, Raffaele; Porta, Miquel; Real, Francisco X; Rothman, Nathaniel; Scelo, Ghislaine; Sesso, Howard D; Severi, Gianluca; Shu, Xiao-Ou; Silverman, Debra; Smith, Jill P; Soucek, Pavel; Sund, Malin; Talar-Wojnarowska, Renata; Tavano, Francesca; Thornquist, Mark D; Tobias, Geoffrey S; Van Den Eeden, Stephen K; Vashist, Yogesh; Visvanathan, Kala; Vodicka, Pavel; Wactawski-Wende, Jean; Wang, Zhaoming; Wentzensen, Nicolas; White, Emily; Yu, Herbert; Yu, Kai; Zeleniuch-Jacquotte, Anne; Zheng, Wei; Kraft, Peter; Li, Donghui; Chanock, Stephen; Obazee, Ofure; Petersen, Gloria M; Amundadottir, Laufey T

    2018-02-08

    In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10 -8 ). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10 -14 ), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10 -10 ), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10 -8 ), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10 -8 ). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene.

  16. Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

    Science.gov (United States)

    Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily

    2014-01-01

    BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789

  17. 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)

    Rupp, C.

    2010-01-01

    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) [de

  18. xSyn: A Software Tool for Identifying Sophisticated 3-Way Interactions From Cancer Expression Data

    Directory of Open Access Journals (Sweden)

    Baishali Bandyopadhyay

    2017-08-01

    Full Text Available Background: Constructing gene co-expression networks from cancer expression data is important for investigating the genetic mechanisms underlying cancer. However, correlation coefficients or linear regression models are not able to model sophisticated relationships among gene expression profiles. Here, we address the 3-way interaction that 2 genes’ expression levels are clustered in different space locations under the control of a third gene’s expression levels. Results: We present xSyn, a software tool for identifying such 3-way interactions from cancer gene expression data based on an optimization procedure involving the usage of UPGMA (Unweighted Pair Group Method with Arithmetic Mean and synergy. The effectiveness is demonstrated by application to 2 real gene expression data sets. Conclusions: xSyn is a useful tool for decoding the complex relationships among gene expression profiles. xSyn is available at http://www.bdxconsult.com/xSyn.html .

  19. Whole-genome and Transcriptome Sequencing of Prostate Cancer Identify New Genetic Alterations Driving Disease Progression

    DEFF Research Database (Denmark)

    Ren, Shancheng; Wei, Gong-Hong; Liu, Dongbing

    2018-01-01

    BACKGROUND: Global disparities in prostate cancer (PCa) incidence highlight the urgent need to identify genomic abnormalities in prostate tumors in different ethnic populations including Asian men. OBJECTIVE: To systematically explore the genomic complexity and define disease-driven genetic......-scale and comprehensive genomic data of prostate cancer from Asian population. Identification of these genetic alterations may help advance prostate cancer diagnosis, prognosis, and treatment....... alterations in PCa. DESIGN, SETTING, AND PARTICIPANTS: The study sequenced whole-genome and transcriptome of tumor-benign paired tissues from 65 treatment-naive Chinese PCa patients. Subsequent targeted deep sequencing of 293 PCa-relevant genes was performed in another cohort of 145 prostate tumors. OUTCOME...

  20. Engineering and Functional Characterization of Fusion Genes Identifies Novel Oncogenic Drivers of Cancer. | Office of Cancer Genomics

    Science.gov (United States)

    Oncogenic gene fusions drive many human cancers, but tools to more quickly unravel their functional contributions are needed. Here we describe methodology permitting fusion gene construction for functional evaluation. Using this strategy, we engineered the known fusion oncogenes, BCR-ABL1, EML4-ALK, and ETV6-NTRK3, as well as 20 previously uncharacterized fusion genes identified in TCGA datasets.

  1. 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

    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. 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 = 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). 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. These findings should be considered when designing online communities as well as designing and evaluating psychosocial and educational interventions for cancer patients.

  2. [Inherited colorectal cancer predisposition syndromes identified in the Instituto Nacional de Enfermedades Neoplasicas (INEN), Lima, Peru;].

    Science.gov (United States)

    Castro-Mujica, María del Carmen; Sullcahuamán-Allende, Yasser; Barreda-Bolaños, Fernando; Taxa-Rojas, Luis

    2014-04-01

    Colorectal cancer (CRC) is the fourth most common cancer in the world and is classified according to their origin in sporadic CRC (~ 70%) and genetic CRC (~ 30%), this latter involves cases of familial aggregation and inherited síndromes that predispose to CRC. To describe inherited CRC predisposition syndromes, polyposic and non-polyposic, identified in the Oncogenetics Unit at National Institute of Cancer Disease (INEN). A descriptive observational record from the attentions of the Oncogenetics Unit at INEN during 2009 to 2013. We included patients with personal or familiar history of CRC and/or colonic polyposis who were referred for clinical assessment to the Oncogenetics Unitat INEN. 59.3 % were female, 40.7 % male, 69.8% under 50 years old, 60.5% had a single CRC, 23.2% had more than one CRC or CRC associated with other extracolonic neoplasia and 32.6% had a familiar history of cancer with autosomal dominant inheritance. According to the clinical genetic diagnosis, 93.1% of the included cases were inherited syndromes that predispose to CRC, with 33.8% of colonic polyposis syndromes, 23.3% of hereditary nonpolyposis CRC syndromes (HNPCC) and 36.0% of CCRHNP probable cases. Clinical genetic evaluation of patients with personal or familiar history of CRC and/or colonic polyposis can identify inherited colorectal cancer predisposition syndromes and provide an appropriategenetic counseling to patients and relatives at risk, establishing guidelines to follow-up and prevention strategies to prevent morbidity and mortality by cancer.

  3. Specific extracellular matrix remodeling signature of colon hepatic metastases.

    Directory of Open Access Journals (Sweden)

    Maguy Del Rio

    Full Text Available To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment.

  4. Design considerations for identifying breast cancer risk factors in a population-based study in Africa.

    Science.gov (United States)

    Brinton, Louise A; Awuah, Baffour; Nat Clegg-Lamptey, Joe; Wiafe-Addai, Beatrice; Ansong, Daniel; Nyarko, Kofi M; Wiafe, Seth; Yarney, Joel; Biritwum, Richard; Brotzman, Michelle; Adjei, Andrew A; Adjei, Ernest; Aitpillah, Francis; Edusei, Lawrence; Dedey, Florence; Nyante, Sarah J; Oppong, Joseph; Osei-Bonsu, Ernest; Titiloye, Nicholas; Vanderpuye, Verna; Brew Abaidoo, Emma; Arhin, Bernard; Boakye, Isaac; Frempong, Margaret; Ohene Oti, Naomi; Okyne, Victoria; Figueroa, Jonine D

    2017-06-15

    Although breast cancer is becoming more prevalent in Africa, few epidemiologic studies have been undertaken and appropriate methodologic approaches remain uncertain. We therefore conducted a population-based case-control study in Accra and Kumasi, Ghana, enrolling 2,202 women with lesions suspicious for breast cancer and 2,161 population controls. Biopsy tissue for cases prior to neoadjuvant therapy (if given), blood, saliva and fecal samples were sought for study subjects. Response rates, risk factor prevalences and odds ratios for established breast cancer risk factors were calculated. A total of 54.5% of the recruited cases were diagnosed with malignancies, 36.0% with benign conditions and 9.5% with indeterminate diagnoses. Response rates to interviews were 99.2% in cases and 91.9% in controls, with the vast majority of interviewed subjects providing saliva (97.9% in cases vs. 98.8% in controls) and blood (91.8% vs. 82.5%) samples; lower proportions (58.1% vs. 46.1%) provided fecal samples. While risk factor prevalences were unique as compared to women in other countries (e.g., less education, higher parity), cancer risk factors resembled patterns identified elsewhere (elevated risks associated with higher levels of education, familial histories of breast cancer, low parity and larger body sizes). Subjects with benign conditions were younger and exhibited higher socioeconomic profiles (e.g., higher education and lower parity) than those with malignancies, suggesting selective referral influences. While further defining breast cancer risk factors in Africa, this study showed that successful population-based interdisciplinary studies of cancer in Africa are possible but require close attention to diagnostic referral biases and standardized and documented approaches for high-quality data collection, including biospecimens. © 2017 UICC.

  5. CHEK2 c.1100delC allele is rarely identified in Greek breast cancer cases.

    Science.gov (United States)

    Apostolou, Paraskevi; Fostira, Florentia; Papamentzelopoulou, Myrto; Michelli, Maria; Panopoulos, Christos; Fountzilas, George; Konstantopoulou, Irene; Voutsinas, Gerassimos E; Yannoukakos, Drakoulis

    2015-04-01

    The CHEK2 gene encodes a protein kinase that plays a crucial role in maintenance of genomic integrity and the DNA repair mechanism. CHEK2 germline mutations are associated with increased risk of breast cancer and other malignancies. From a clinical perspective, the most significant mutation identified is the c.1100delC mutation, which is associated with an approximately 25% lifetime breast cancer risk. The distribution of this mutation shows wide geographical variation; it is more prevalent in the Northern European countries and less common, or even absent, in Southern Europe. In order to estimate the frequency of the CHEK2 c.1100delC mutation in Greek breast cancer patients, we genotyped 2,449 patients (2,408 females and 41 males), which was the largest series ever tested for c.1100delC. The mean age of female and male breast cancer diagnosis was 49 and 59 years, respectively. All patients had previously tested negative for the Greek BRCA1 founder and recurrent mutations. The CHEK2 c.1100delC mutation was detected in 0.16% (4 of 2,408) of females, all of whom were diagnosed with breast cancer before the age of 50 years. Only one c.1100delC carrier was reported with breast cancer family history. The present study indicates that the CHEK2 c.1100delC mutation does not contribute substantially to hereditary breast cancer in patients of Greek descent. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. 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.

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

    Science.gov (United States)

    Scott, Cheryl Siegel; Jinot, Jennifer

    2011-01-01

    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. PMID:22163205

  8. [Utility of chromosome banding with ALU I enzyme for identifying methylated areas in breast cancer].

    Science.gov (United States)

    Rojas-Atencio, Alicia; Yamarte, Leonard; Urdaneta, Karelis; Soto-Alvarez, Marisol; Alvarez Nava, Francisco; Cañizalez, Jenny; Quintero, Maribel; Atencio, Raquel; González, Richard

    2012-12-01

    Cancer is a group of disorders characterized by uncontrolled cell growth which is produced by two successive events: increased cell proliferation (tumor or neoplasia) and the invasive capacity of these cells (metastasis). DNA methylation is an epigenetic process which has been involved as an important pathogenic factor of cancer. DNA methylation participates in the regulation of gene expression, directly, by preventing the union of transcription factors, and indirectly, by promoting the "closed" structure of the chromatine. The objectives of this study were to identify hypermethyled chromosomal regions through the use of restriction Alu I endonuclease, and to relate cytogenetically these regions with tumor suppressive gene loci. Sixty peripheral blood samples of females with breast cancer were analyzed. Cell cultures were performed and cytogenetic spreads, previously digested with Alu I enzyme, were stained with Giemsa. Chromosomal centromeric and not centromeric regions were stained in 37% of cases. About 96% of stained hypermethyled chromosomal regions (1q, 2q, 6q) were linked with methylated genes associated with breast cancer. In addition, centromeric regions in chromosomes 3, 4, 8, 13, 14, 15 and 17, usually unstained, were found positive to digestion with Alu I enzime and Giemsa staining. We suggest the importance of this technique for the global visualization of the genome which can find methylated genes related to breast cancer, and thus lead to a specific therapy, and therefore a better therapeutic response.

  9. Novel expressed sequences identified in a model of androgen independent prostate cancer

    Directory of Open Access Journals (Sweden)

    Jones Steven JM

    2007-01-01

    Full Text Available Abstract Background Prostate cancer is the most frequently diagnosed cancer in American men, and few effective treatment options are available to patients who develop hormone-refractory prostate cancer. The molecular changes that occur to allow prostate cells to proliferate in the absence of androgens are not fully understood. Results Subtractive hybridization experiments performed with samples from an in vivo model of hormonal progression identified 25 expressed sequences representing novel human transcripts. Intriguingly, these 25 sequences have small open-reading frames and are not highly conserved through evolution, suggesting many of these novel expressed sequences may be derived from untranslated regions of novel transcripts or from non-coding transcripts. Examination of a large metalibrary of human Serial Analysis of Gene Expression (SAGE tags demonstrated that only three of these novel sequences had been previously detected. RT-PCR experiments confirmed that the 6 sequences tested were expressed in specific human tissues, as well as in clinical samples of prostate cancer. Further RT-PCR experiments for five of these fragments indicated they originated from large untranslated regions of unannotated transcripts. Conclusion This study underlines the value of using complementary techniques in the annotation of the human genome. The tissue-specific expression of 4 of the 6 clones tested indicates the expression of these novel transcripts is tightly regulated, and future work will determine the possible role(s these novel transcripts may play in the progression of prostate cancer.

  10. Functional profiling of microtumors to identify cancer associated fibroblast-derived drug targets.

    Science.gov (United States)

    Horman, Shane R; To, Jeremy; Lamb, John; Zoll, Jocelyn H; Leonetti, Nicole; Tu, Buu; Moran, Rita; Newlin, Robbin; Walker, John R; Orth, Anthony P

    2017-11-21

    Recent advances in chemotherapeutics highlight the importance of molecularly-targeted perturbagens. Although these therapies typically address dysregulated cancer cell proteins, there are increasing therapeutic modalities that take into consideration cancer cell-extrinsic factors. Targeting components of tumor stroma such as vascular or immune cells has been shown to represent an efficacious approach in cancer treatment. Cancer-associated fibroblasts (CAFs) exemplify an important stromal component that can be exploited in targeted therapeutics, though their employment in drug discovery campaigns has been relatively minimal due to technical logistics in assaying for CAF-tumor interactions. Here we report a 3-dimensional multi-culture tumor:CAF spheroid phenotypic screening platform that can be applied to high-content drug discovery initiatives. Using a functional genomics approach we systematically profiled 1,024 candidate genes for CAF-intrinsic anti-spheroid activity; identifying several CAF genes important for development and maintenance of tumor:CAF co-culture spheroids. Along with previously reported genes such as WNT, we identify CAF-derived targets such as ARAF and COL3A1 upon which the tumor compartment depends for spheroid development. Specifically, we highlight the G-protein-coupled receptor OGR1 as a unique CAF-specific protein that may represent an attractive drug target for treating colorectal cancer. In vivo , murine colon tumor implants in OGR1 knockout mice displayed delayed tumor growth compared to tumors implanted in wild type littermate controls. These findings demonstrate a robust microphysiological screening approach for identifying new CAF targets that may be applied to drug discovery efforts.

  11. Genome-wide association study identifies novel breast cancer susceptibility loci

    Science.gov (United States)

    Easton, Douglas F.; Pooley, Karen A.; Dunning, Alison M.; Pharoah, Paul D. P.; Thompson, Deborah; Ballinger, Dennis G.; Struewing, Jeffery P.; Morrison, Jonathan; Field, Helen; Luben, Robert; Wareham, Nicholas; Ahmed, Shahana; Healey, Catherine S.; Bowman, Richard; Meyer, Kerstin B.; Haiman, Christopher A.; Kolonel, Laurence K.; Henderson, Brian E.; Marchand, Loic Le; Brennan, Paul; Sangrajrang, Suleeporn; Gaborieau, Valerie; Odefrey, Fabrice; Shen, Chen-Yang; Wu, Pei-Ei; Wang, Hui-Chun; Eccles, Diana; Evans, D. Gareth; Peto, Julian; Fletcher, Olivia; Johnson, Nichola; Seal, Sheila; Stratton, Michael R.; Rahman, Nazneen; Chenevix-Trench, Georgia; Bojesen, Stig E.; Nordestgaard, Børge G.; Axelsson, Christen K.; Garcia-Closas, Montserrat; Brinton, Louise; Chanock, Stephen; Lissowska, Jolanta; Peplonska, Beata; Nevanlinna, Heli; Fagerholm, Rainer; Eerola, Hannaleena; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Ahn, Sei-Hyun; Hunter, David J.; Hankinson, Susan E.; Cox, David G.; Hall, Per; Wedren, Sara; Liu, Jianjun; Low, Yen-Ling; Bogdanova, Natalia; Schürmann, Peter; Dörk, Thilo; Tollenaar, Rob A. E. M.; Jacobi, Catharina E.; Devilee, Peter; Klijn, Jan G. M.; Sigurdson, Alice J.; Doody, Michele M.; Alexander, Bruce H.; Zhang, Jinghui; Cox, Angela; Brock, Ian W.; MacPherson, Gordon; Reed, Malcolm W. R.; Couch, Fergus J.; Goode, Ellen L.; Olson, Janet E.; Meijers-Heijboer, Hanne; van den Ouweland, Ans; Uitterlinden, André; Rivadeneira, Fernando; Milne, Roger L.; Ribas, Gloria; Gonzalez-Neira, Anna; Benitez, Javier; Hopper, John L.; McCredie, Margaret; Southey, Melissa; Giles, Graham G.; Schroen, Chris; Justenhoven, Christina; Brauch, Hiltrud; Hamann, Ute; Ko, Yon-Dschun; Spurdle, Amanda B.; Beesley, Jonathan; Chen, Xiaoqing; Mannermaa, Arto; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana; Day, Nicholas E.; Cox, David R.; Ponder, Bruce A. J.; Luccarini, Craig; Conroy, Don; Shah, Mitul; Munday, Hannah; Jordan, Clare; Perkins, Barbara; West, Judy; Redman, Karen; Driver, Kristy; Aghmesheh, Morteza; Amor, David; Andrews, Lesley; Antill, Yoland; Armes, Jane; Armitage, Shane; Arnold, Leanne; Balleine, Rosemary; Begley, Glenn; Beilby, John; Bennett, Ian; Bennett, Barbara; Berry, Geoffrey; Blackburn, Anneke; Brennan, Meagan; Brown, Melissa; Buckley, Michael; Burke, Jo; Butow, Phyllis; Byron, Keith; Callen, David; Campbell, Ian; Chenevix-Trench, Georgia; Clarke, Christine; Colley, Alison; Cotton, Dick; Cui, Jisheng; Culling, Bronwyn; Cummings, Margaret; Dawson, Sarah-Jane; Dixon, Joanne; Dobrovic, Alexander; Dudding, Tracy; Edkins, Ted; Eisenbruch, Maurice; Farshid, Gelareh; Fawcett, Susan; Field, Michael; Firgaira, Frank; Fleming, Jean; Forbes, John; Friedlander, Michael; Gaff, Clara; Gardner, Mac; Gattas, Mike; George, Peter; Giles, Graham; Gill, Grantley; Goldblatt, Jack; Greening, Sian; Grist, Scott; Haan, Eric; Harris, Marion; Hart, Stewart; Hayward, Nick; Hopper, John; Humphrey, Evelyn; Jenkins, Mark; Jones, Alison; Kefford, Rick; Kirk, Judy; Kollias, James; Kovalenko, Sergey; Lakhani, Sunil; Leary, Jennifer; Lim, Jacqueline; Lindeman, Geoff; Lipton, Lara; Lobb, Liz; Maclurcan, Mariette; Mann, Graham; Marsh, Deborah; McCredie, Margaret; McKay, Michael; McLachlan, Sue Anne; Meiser, Bettina; Milne, Roger; Mitchell, Gillian; Newman, Beth; O'Loughlin, Imelda; Osborne, Richard; Peters, Lester; Phillips, Kelly; Price, Melanie; Reeve, Jeanne; Reeve, Tony; Richards, Robert; Rinehart, Gina; Robinson, Bridget; Rudzki, Barney; Salisbury, Elizabeth; Sambrook, Joe; Saunders, Christobel; Scott, Clare; Scott, Elizabeth; Scott, Rodney; Seshadri, Ram; Shelling, Andrew; Southey, Melissa; Spurdle, Amanda; Suthers, Graeme; Taylor, Donna; Tennant, Christopher; Thorne, Heather; Townshend, Sharron; Tucker, Kathy; Tyler, Janet; Venter, Deon; Visvader, Jane; Walpole, Ian; Ward, Robin; Waring, Paul; Warner, Bev; Warren, Graham; Watson, Elizabeth; Williams, Rachael; Wilson, Judy; Winship, Ingrid; Young, Mary Ann; Bowtell, David; Green, Adele; deFazio, Anna; Chenevix-Trench, Georgia; Gertig, Dorota; Webb, Penny

    2009-01-01

    Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2>0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P<10−7). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P<0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach. PMID:17529967

  12. 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.

  13. 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 (Andrew); 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.Y. Karlan (Beth); 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 (Soo-Hwang); 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. Meijers-Heijboer (Hanne); 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. Durán (Mercedes); 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. Collée (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 (Marjan); 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.K. 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),

  14. 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, François; 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; 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; Dunning, Alison M.; Tessier, Daniel; Cunningham, Julie; Slager, Susan L.; Wang, Chen; Hart, Steven; Stevens, Kristen; Simard, Jacques; Pastinen, Tomi; Pankratz, Vernon S.; Offit, Kenneth; Easton, Douglas F.; Chenevix-Trench, Georgia; Antoniou, Antonis C.

    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

  15. Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk

    DEFF Research Database (Denmark)

    Couch, Fergus J; Wang, Xianshu; McGuffog, Lesley

    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 fur...

  16. 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.|info:eu-repo/dai/nl/413577805; 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.|info:eu-repo/dai/nl/304120995; 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.|info:eu-repo/dai/nl/216532620; 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

  17. A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer

    DEFF Research Database (Denmark)

    Lee, Alice W; Bomkamp, Ashley; Bandera, Elisa V

    2016-01-01

    Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The int...

  18. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

    Science.gov (United States)

    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  19. Identifying critical steps towards improved access to innovation in cancer care: a European CanCer Organisation position paper.

    Science.gov (United States)

    Aapro, Matti; Astier, Alain; Audisio, Riccardo; Banks, Ian; Bedossa, Pierre; Brain, Etienne; Cameron, David; Casali, Paolo; Chiti, Arturo; De Mattos-Arruda, Leticia; Kelly, Daniel; Lacombe, Denis; Nilsson, Per J; Piccart, Martine; Poortmans, Philip; Riklund, Katrine; Saeter, Gunnar; Schrappe, Martin; Soffietti, Riccardo; Travado, Luzia; van Poppel, Hein; Wait, Suzanne; Naredi, Peter

    2017-09-01

    In recent decades cancer care has seen improvements in the speed and accuracy of diagnostic procedures; the effectiveness of surgery, radiation therapy and medical treatments; the power of information technology; and the development of multidisciplinary, specialist-led approaches to care. Such innovations are essential if we are to continue improving the lives of cancer patients across Europe despite financial pressures on our healthcare systems. Investment in innovation must be balanced with the need to ensure the sustainability of healthcare budgets, and all health professionals have a responsibility to help achieve this balance. It requires scrutiny of the way care is delivered; we must be ready to discontinue practices or interventions that are inefficient, and prioritise innovations that may deliver the best outcomes possible for patients within the limits of available resources. Decisions on innovations should take into account their long-term impact on patient outcomes and costs, not just their immediate costs. Adopting a culture of innovation requires a multidisciplinary team approach, with the patient at the centre and an integral part of the team. It must take a whole-system and whole-patient perspective on cancer care and be guided by high-quality real-world data, including outcomes relevant to the patient and actual costs of care; this accurately reflects the impact of any innovation in clinical practice. The European CanCer Organisation is committed to working with its member societies, patient organisations and the cancer community at large to find sustainable ways to identify and integrate the most meaningful innovations into all aspects of cancer care. Copyright © 2017. Published by Elsevier Ltd.

  20. Five Guidelines for Selecting Hydrological Signatures

    Science.gov (United States)

    McMillan, H. K.; Westerberg, I.; Branger, F.

    2017-12-01

    Hydrological signatures are index values derived from observed or modeled series of hydrological data such as rainfall, flow or soil moisture. They are designed to extract relevant information about hydrological behavior, such as to identify dominant processes, and to determine the strength, speed and spatiotemporal variability of the rainfall-runoff response. Hydrological signatures play an important role in model evaluation. They allow us to test whether particular model structures or parameter sets accurately reproduce the runoff generation processes within the watershed of interest. Most modeling studies use a selection of different signatures to capture different aspects of the catchment response, for example evaluating overall flow distribution as well as high and low flow extremes and flow timing. Such studies often choose their own set of signatures, or may borrow subsets of signatures used in multiple other works. The link between signature values and hydrological processes is not always straightforward, leading to uncertainty and variability in hydrologists' signature choices. In this presentation, we aim to encourage a more rigorous approach to hydrological signature selection, which considers the ability of signatures to represent hydrological behavior and underlying processes for the catchment and application in question. To this end, we propose a set of guidelines for selecting hydrological signatures. We describe five criteria that any hydrological signature should conform to: Identifiability, Robustness, Consistency, Representativeness, and Discriminatory Power. We describe an example of the design process for a signature, assessing possible signature designs against the guidelines above. Due to their ubiquity, we chose a signature related to the Flow Duration Curve, selecting the FDC mid-section slope as a proposed signature to quantify catchment overall behavior and flashiness. We demonstrate how assessment against each guideline could be used to

  1. Proteomic profiling of mammary carcinomas identifies C7orf24, a gamma-glutamyl cyclotransferase, as a potential cancer biomarker

    DEFF Research Database (Denmark)

    Gromov, Pavel; Gromova, Irina; Friis, Esbern

    2010-01-01

    Breast cancer is the leading cause of cancer deaths in women today and is the most common cancer (excluding skin cancers) among women in the Western world. Although cancers detected by screening mammography are significantly smaller than nonscreening ones, noninvasive biomarkers for detection......, and a novel protein, C7orf24, was identified as being upregulated in cancer cells. Protein expression levels of C7orf24 were evaluated by immunohistochemical assays to qualify deregulation of this protein. Analysis of C7orf24 expression showed up-regulation in 36.4 and 23.4% of cases present in the discovery...

  2. 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...... using death (P = 0.015) and recurrence (P = 0.002) as outcome. The combined mutation score is strongly associated to upregulation of several growth factor pathways....

  3. Name Recognition to Identify Patients of South Asian Ethnicity within the Cancer Registry

    Directory of Open Access Journals (Sweden)

    Savitri Singh-Carlson

    2016-01-01

    Full Text Available Objective: The goal of this project was to develop a list of forenames and surnames of South Asian (SA women that could be used to identify SA breast cancer patients within the cancer registry. This list was compiled, evaluated, and validated to ensure comprehensiveness, accuracy, and applicability of SA names. Methods: This project was conducted by Canadian researchers who are immersed in conducting behavioral studies with SA women diagnosed with cancer in the province of British Columbia. Recruiting SA cancer patients for research can be a difficult task due to social and cultural factors. Methods used by other researchers to identify ethnicity related unique names were employed to filter surnames and forenames that were not common to this ethnic group. Co-author (Gurpreet Oshan of SA ethnicity rigorously identified and deleted multiple lists and redundant entries along with common English forenames which resulted in a list of 16,888 SA forenames. All co-authors of Indian ethnicity (Gurpreet Oshan, Savitri Singh-Carlson, Harajit Lail were involved in critiquing and manually reviewing the names list throughout this process. Comprehensive lists of SA surnames and women′s forenames were reviewed to identify those that were unique to SA ethnicity. Accuracy was ensured by constantly filtering the redundancy by using an Excel program which helped to illustrate the number of times each name was spelled in different ways. Results: The final lists included 9112 surnames and 16,888 forenames of SA ethnicity. On the basis of the surname linkage only, the sensitivity of the list was 76.6%, specificity was 62.9%, and the positive predictive value was 58.5%. On the basis of both the surname and forename linkage, the specificity of the list was 88.6%. These lists include variations in spelling forenames and surnames as well. Conclusions: The list of surnames and forenames can be useful tools to identify SA ethnic groups from large population database in

  4. Experience of US Patients Who Self-identify as Having an Overdiagnosed Thyroid Cancer

    Science.gov (United States)

    Hendrickson, Chase D.; Hanson, Gregory S.

    2017-01-01

    Importance Overdiagnosis of cancer—the identification of cancers that are unlikely to progress—is a source of discomfort and challenge for patients, physicians, and health care systems. A major cause of this discomfort is the inability to know prospectively with certainty which cancers are overdiagnosed. In thyroid cancer, as patients have begun to understand this concept, some individuals are independently deciding not to intervene, despite this practice not yet being widely accepted. Objective To describe the current experience of people who independently self-identify as having an overdiagnosed cancer and elect not to intervene. Design, Setting, and Participants In this qualitative study, semistructured interviews were conducted between July 1 and December 31, 2015, with 22 community-dwelling adults aged 21 to 75 years who had an incidentally identified thyroid finding that was known or suspected to be malignant and who questioned the intervention recommended by their physicians. Verbatim transcripts were analyzed using constant comparative analysis. Main Outcomes and Measures The experience of individuals who self-identify as having an overdiagnosed cancer and elect not to intervene. Results Of the 22 people interviewed (16 females and 6 males; mean age, 48.5 years), 18 had elected not to intervene on their thyroid finding and had been living with the decision for a mean of 39 months (median, 40 months; range, 1-88 months). Twelve of the 18 participants reported that they experienced significant anxiety about cancer progression, but had considered reasons for choosing nonintervention: understanding issues of precision in diagnostic testing and the varied behavior of cancer, surgical risks, medication use, and low risk of death from the cancer. Twelve participants described their decisions as met with nonreassuring, unsupportive responses. Medical professionals, friends, and internet discussion groups told them they were “being stupid,” “were wrong

  5. Dietary patterns as identified by factor analysis and colorectal cancer among middle-aged Americans.

    Science.gov (United States)

    Flood, Andrew; Rastogi, Tanuja; Wirfält, Elisabet; Mitrou, Panagiota N; Reedy, Jill; Subar, Amy F; Kipnis, Victor; Mouw, Traci; Hollenbeck, Albert R; Leitzmann, Michael; Schatzkin, Arthur

    2008-07-01

    Although diet has long been suspected as an etiological factor for colorectal cancer, studies of single foods and nutrients have provided inconsistent results. We used factor analysis methods to study associations between dietary patterns and colorectal cancer in middle-aged Americans. Diet was assessed among 293,615 men and 198,767 women in the National Institutes of Health-AARP Diet and Health Study. Principal components factor analysis identified 3 primary dietary patterns: a fruit and vegetables, a diet foods, and a red meat and potatoes pattern. State cancer registries identified 2151 incident cases of colorectal cancer in men and 959 in women between 1995 and 2000. Men with high scores on the fruit and vegetable pattern were at decreased risk [relative risk (RR) for quintile (Q) 5 versus Q1: 0.81; 95% CI: 0.70, 0.93; P for trend = 0.004]. Both men and women had a similar risk reduction with high scores on the diet food factor: men (RR: 0.82; 95% CI: 0.72, 0.94; P for trend = 0.001) and women (RR: 0.87; 95% CI: 0.71, 1.07; P for trend = 0.06). High scores on the red meat factor were associated with increased risk: men (RR: 1.17; 95% CI: 1.02, 1.35; P for trend = 0.14) and women (RR: 1.48; 95% CI: 1.20, 1.83; P for trend = 0.0002). These results suggest that dietary patterns characterized by a low frequency of meat and potato consumption and frequent consumption of fruit and vegetables and fat-reduced foods are consistent with a decreased risk of colorectal cancer.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  8. Implementation of Canny and Isotropic Operator with Power Law Transformation to Identify Cervical Cancer

    Science.gov (United States)

    Amalia, A.; Rachmawati, D.; Lestari, I. A.; Mourisa, C.

    2018-03-01

    Colposcopy has been used primarily to diagnose pre-cancer and cancerous lesions because this procedure gives an exaggerated view of the tissues of the vagina and the cervix. But, the poor quality of colposcopy image sometimes makes physician challenging to recognize and analyze it. Generally, Implementation of image processing to identify cervical cancer have to implement a complex classification or clustering method. In this study, we wanted to prove that by only applying the identification of edge detection in the colposcopy image, identification of cervical cancer can be determined. In this study, we implement and comparing two edge detection operator which are isotropic and canny operator. Research methodology in this paper composed by image processing, training, and testing stages. In the image processing step, colposcopy image transformed by nth root power transformation to get better detection result and continued with edge detection process. Training is a process of labelling all dataset image with cervical cancer stage. This process involved pathology doctor as an expert in diagnosing the colposcopy image as a reference. Testing is a process of deciding cancer stage classification by comparing the similarity image of colposcopy results in the testing stage with the image of the results of the training process. We used 30 images as a dataset. The result gets same accuracy which is 80% for both Canny or Isotropic operator. Average running time for Canny operator implementation is 0.3619206 ms while Isotropic get 1.49136262 ms. The result showed that Canny operator is better than isotropic operator because Canny operator generates a more precise edge with a fast time instead.

  9. Stress Marker Signatures in Lesion Mimic Single and Double Mutants Identify a Crucial Leaf Age-Dependent Salicylic Acid Related Defense Signal.

    Science.gov (United States)

    Kaurilind, Eve; Brosché, Mikael

    2017-01-01

    Plants are exposed to abiotic and biotic stress conditions throughout their lifespans that activates various defense programs. Programmed cell death (PCD) is an extreme defense strategy the plant uses to manage unfavorable environments as well as during developmentally induced senescence. Here we investigated the role of leaf age on the regulation of defense gene expression in Arabidopsis thaliana. Two lesion mimic mutants with misregulated cell death, catalase2 (cat2) and defense no death1 (dnd1) were used together with several double mutants to dissect signaling pathways regulating defense gene expression associated with cell death and leaf age. PCD marker genes showed leaf age dependent expression, with the highest expression in old leaves. The salicylic acid (SA) biosynthesis mutant salicylic acid induction deficient2 (sid2) had reduced expression of PCD marker genes in the cat2 sid2 double mutant demonstrating the importance of SA biosynthesis in regulation of defense gene expression. While the auxin- and jasmonic acid (JA)- insensitive auxin resistant1 (axr1) double mutant cat2 axr1 also led to decreased expression of PCD markers; the expression of several marker genes for SA signaling (ISOCHORISMATE SYNTHASE 1, PR1 and PR2) were additionally decreased in cat2 axr1 compared to cat2. The reduced expression of these SA markers genes in cat2 axr1 implicates AXR1 as a regulator of SA signaling in addition to its known role in auxin and JA signaling. Overall, the current study reinforces the important role of SA signaling in regulation of leaf age-related transcript signatures.

  10. Quantifying the number of lymph nodes identified in one-stage versus two-stage axillary dissection in breast cancer

    DEFF Research Database (Denmark)

    Damgaard, Olaf E; Jensen, Maj-Britt; Kroman, Niels

    2013-01-01

    To establish whether a different number of lymph nodes is identified in a delayed versus an immediate axillary lymph node dissection (ALND) in breast cancer patients.......To establish whether a different number of lymph nodes is identified in a delayed versus an immediate axillary lymph node dissection (ALND) in breast cancer patients....

  11. 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.

  12. 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.

  13. 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

  14. Quantitative Analysis of "1"8F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

    International Nuclear Information System (INIS)

    Cui, Yi; Song, Jie; Pollom, Erqi; Alagappan, Muthuraman; Shirato, Hiroki; Chang, Daniel T.; Koong, Albert C.; Li, Ruijiang

    2016-01-01

    Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT "1"8F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162 robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6

  15. 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; Willett, Walter C; Hunter, David J; Simard, Jacques; Benitez, Javier; Dunning, Alison M; Sherman, Mark E; Chenevix-Trench, Georgia; Chanock, Stephen J; Hall, Per; Pharoah, Paul D P; Vachon, Celine; Easton, Douglas F; Haiman, Christopher A; Kraft, Peter

    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

  16. Competing endogenous RNA network analysis identifies critical genes among the different breast cancer subtypes.

    Science.gov (United States)

    Chen, Juan; Xu, Juan; Li, Yongsheng; Zhang, Jinwen; Chen, Hong; Lu, Jianping; Wang, Zishan; Zhao, Xueying; Xu, Kang; Li, Yixue; Li, Xia; Zhang, Yan

    2017-02-07

    Although competing endogenous RNAs (ceRNAs) have been implicated in many solid tumors, their roles in breast cancer subtypes are not well understood. We therefore generated a ceRNA network for each subtype based on the significance of both, positive co-expression and the shared miRNAs, in the corresponding subtype miRNA dys-regulatory network, which was constructed based on negative regulations between differentially expressed miRNAs and targets. All four subtype ceRNA networks exhibited scale-free architecture and showed that the common ceRNAs were at the core of the networks. Furthermore, the common ceRNA hubs had greater connectivity than the subtype-specific hubs. Functional analysis of the common subtype ceRNA hubs highlighted factors involved in proliferation, MAPK signaling pathways and tube morphogenesis. Subtype-specific ceRNA hubs highlighted unique subtype-specific pathways, like the estrogen response and inflammatory pathways in the luminal subtypes or the factors involved in the coagulation process that participates in the basal-like subtype. Ultimately, we identified 29 critical subtype-specific ceRNA hubs that characterized the different breast cancer subtypes. Our study thus provides new insight into the common and specific subtype ceRNA interactions that define the different categories of breast cancer and enhances our understanding of the pathology underlying the different breast cancer subtypes, which can have prognostic and therapeutic implications in the future.

  17. Periostin is identified as a putative metastatic marker in breast cancer-derived exosomes.

    Science.gov (United States)

    Vardaki, Ioulia; Ceder, Sophia; Rutishauser, Dorothea; Baltatzis, George; Foukakis, Theodoros; Panaretakis, Theocharis

    2016-11-15

    Breast cancer (BrCa) is the most frequent cancer type in women and a leading cause of cancer related deaths in the world. Despite the decrease in mortality due to better diagnostics and palliative care, there is a lack of prognostic markers of metastasis. Recently, the exploitation of liquid biopsies and in particular of the extracellular vesicles has shown promise in the identification of such prognostic markers. In this study we compared the proteomic content of exosomes derived from metastatic and non-metastatic human (MCF7 and MDA-MB-231) and mouse (67NR and 4T1) cell lines. We found significant differences not only in the amount of secreted exosomes but most importantly in the protein content of exosomes secreted from metastatic versus non-metastatic ones. We identified periostin as a protein that is enriched in exosomes secreted by metastatic cells and validated its presence in a pilot cohort of breast cancer patient samples with localized disease or lymph node (LN) metastasis.

  18. 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; Dos Santos Silva, Isabel; 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; Berg, David Van Den; 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; Willett, Walter C; Hunter, David J; Simard, Jacques; Benitez, Javier; Dunning, Alison M; Sherman, Mark E; Chenevix-Trench, Georgia; Chanock, Stephen J; Hall, Per; Pharoah, Paul D P; Vachon, Celine; Easton, Douglas F; Haiman, Christopher A; Kraft, Peter

    2013-04-01

    Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. 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.

  19. Seeking informed consent to Phase I cancer clinical trials: identifying oncologists' communication strategies.

    Science.gov (United States)

    Brown, Richard; Bylund, Carma L; Siminoff, Laura A; Slovin, Susan F

    2011-04-01

    Phase I clinical trials are the gateway to effective new cancer treatments. Many physicians have difficulty when discussing Phase I clinical trials. Research demonstrates evidence of suboptimal communication. Little is known about communication strategies used by oncologists when recruiting patients for Phase I trials. We analyzed audio recorded Phase I consultations to identify oncologists' communication strategies. Subjects were consecutive cancer patients from six medical oncologists attending one of three outpatient clinics at a major Cancer Center in the United States. Sixteen patients signed informed consent for audio recording of their consultations in which a Phase I study was discussed. These were transcribed in full and analyzed to identify communication strategies. Six communication themes emerged from the analysis: (1) orienting, (2) educating patients, (3) describing uncertainty and prognosis, (4) persuading, (5) decision making, and (6) making a treatment recommendation. As expected, although there was some common ground between communication in Phase I and the Phase II and III settings, there were distinct differences. Oncologists used persuasive communication, made explicit recommendations, or implicitly expressed a treatment preference and were choice limiting. This highlights the complexity of discussing Phase I trials and the need to develop strategies to aid oncologists and patients in these difficult conversations. Patient centered communication that values patient preferences while preserving the oncologist's agenda can be a helpful approach to these discussions. Copyright © 2010 John Wiley & Sons, Ltd.

  20. Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

    Science.gov (United States)

    Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

    2016-04-26

    Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

  1. 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

  2. Strategies to Identify the Lynch Syndrome Among Patients With Colorectal Cancer

    Science.gov (United States)

    Ladabaum, Uri; Wang, Grace; Terdiman, Jonathan; Blanco, Amie; Kuppermann, Miriam; Boland, C. Richard; Ford, James; Elkin, Elena; Phillips, Kathryn A.

    2013-01-01

    Background Testing has been advocated for all persons with newly diagnosed colorectal cancer to identify families with the Lynch syndrome, an autosomal dominant cancer-predisposition syndrome that is a paradigm for personalized medicine. Objective To estimate the effectiveness and cost-effectiveness of strategies to identify the Lynch syndrome, with attention to sex, age at screening, and differential effects for probands and relatives. Design Markov model that incorporated risk for colorectal, endometrial, and ovarian cancers. Data Sources Published literature. Target Population All persons with newly diagnosed colorectal cancer and their relatives. Time Horizon Lifetime. Perspective Third-party payer. Intervention Strategies based on clinical criteria, prediction algorithms, tumor testing, or up-front germline mutation testing, followed by tailored screening and risk-reducing surgery. Outcome Measures Life-years, cancer cases and deaths, costs, and incremental cost-effectiveness ratios. Results of Base-Case Analysis The benefit of all strategies accrued primarily to relatives with a mutation associated with the Lynch syndrome, particularly women, whose life expectancy could increase by approximately 4 years with hysterectomy and salpingo-oophorectomy and adherence to colorectal cancer screening recommendations. At current rates of germline testing, screening, and prophylactic surgery, the strategies reduced deaths from colorectal cancer by 7% to 42% and deaths from endometrial and ovarian cancer by 1% to 6%. Among tumor-testing strategies, immunohistochemistry followed by BRAF mutation testing was preferred, with an incremental cost-effectiveness ratio of $36 200 per life-year gained. Results of Sensitivity Analysis The number of relatives tested per proband was a critical determinant of both effectiveness and cost-effectiveness, with testing of 3 to 4 relatives required for most strategies to meet a threshold of $50 000 per life-year gained. Immunohistochemistry

  3. New genetic signatures associated with cancer cachexia as defined by low skeletal muscle index and weight loss.

    Science.gov (United States)

    Johns, Neil; Stretch, Cynthia; Tan, Benjamin H L; Solheim, Tora S; Sørhaug, Sveinung; Stephens, Nathan A; Gioulbasanis, Ioannis; Skipworth, Richard J E; Deans, D A Christopher; Vigano, Antonio; Ross, James A; Bathe, Oliver F; Tremblay, Michel L; Kaasa, Stein; Strasser, Florian; Gagnon, Bruno; Baracos, Vickie E; Damaraju, Sambasivarao; Fearon, Kenneth C H

    2017-02-01

    Cachexia affects the majority with advanced cancer. Based on current demographic and clinical factors, it is not possible to predict who will develop cachexia or not. Such variation may, in part, be due to genotype. It has recently been proposed to extend the diagnostic criteria for cachexia to include a direct measure of low skeletal muscle index (LSMI) in addition to weight loss (WL). We aimed to explore our panel of candidate single nucleotide polymorphism (SNPs) for association with WL +/- computerized tomography-defined LSMI. We also explored whether the transcription in muscle of identified genes was altered according to such cachexia phenotype METHODS: A retrospective cohort study design was used. Analysis explored associations of candidate SNPs with WL (n = 1276) and WL + LSMI (n = 943). Human muscle transcriptome (n = 134) was analysed using an Agilent platform. Single nucleotide polymorphisms in the following genes showed association with WL alone: GCKR, LEPR, SELP, ACVR2B, TLR4, FOXO3, IGF1, CPN1, APOE, FOXO1, and GHRL. SNPs in LEPR, ACVR2B, TNF, and ACE were associated with concurrent WL + LSMI. There was concordance between muscle-specific expression for ACVR2B, FOXO1 and 3, LEPR, GCKR, and TLR4 genes and LSMI and/or WL (P < 0.05). The rs1799964 in the TNF gene and rs4291 in the ACE gene are new associations when the definition of cachexia is based on a combination of WL and LSMI. These findings focus attention on pro-inflammatory cytokines and the renin-angiotensin system as biomarkers/mediators of muscle wasting in cachexia. © 2016 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of the Society on Sarcopenia, Cachexia and Wasting Disorders.

  4. Genetic variants identified by GWAS was associated with colorectal cancer in the Han Chinese population

    Directory of Open Access Journals (Sweden)

    Hui-Ping Qiao

    2015-01-01

    Full Text Available Aim of Study: Colorectal cancer (CRC, now the third most common cancer across the world, is known to aggregate in families. Recently, genome-wide association studies have identified two single nucleotide polymorphisms (SNP associated with CRC in Caucasians. Materials and Methods: To validate whether the same variations conferred risk to CRC in the Han Chinese population, we genotyped 760 individuals (380 controls and 380 cases samples recruited from the Han Chinese origin. Results: We found rs11987193 in 8p12 (P = 0.0472 after correction, OR = 0.751 was significantly associated with CRC but rs12080929 in 1p33 (P = 0.0650 after correction, OR = 0.750 was not. Conclusion: Our findings supported that rs11987193 is a susceptibility locus for CRC, and gene DUSP4 was possible to play a role in the pathology of CRC.

  5. 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

  6. 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 < 0.05) and fears about disease recurrence (p < 0.05) compared to those who did not want additional information. Results emphasize the need to develop cancer survivorship 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.

  7. Comparison of Expression Profiles in Ovarian Epithelium In Vivo and Ovarian Cancer Identifies Novel Candidate Genes Involved in Disease Pathogenesis

    Science.gov (United States)

    Emmanuel, Catherine; Gava, Natalie; Kennedy, Catherine; Balleine, Rosemary L.; Sharma, Raghwa; Wain, Gerard; Brand, Alison; Hogg, Russell; Etemadmoghadam, Dariush; George, Joshy; Birrer, Michael J.; Clarke, Christine L.; Chenevix-Trench, Georgia; Bowtell, David D. L.; Harnett, Paul R.; deFazio, Anna

    2011-01-01

    Molecular events leading to epithelial ovarian cancer are poorly understood but ovulatory hormones and a high number of life-time ovulations with concomitant proliferation, apoptosis, and inflammation, increases risk. We identified genes that are regulated during the estrous cycle in murine ovarian surface epithelium and analysed these profiles to identify genes dysregulated in human ovarian cancer, using publically available datasets. We identified 338 genes that are regulated in murine ovarian surface epithelium during the estrous cycle and dysregulated in ovarian cancer. Six of seven candidates selected for immunohistochemical validation were expressed in serous ovarian cancer, inclusion cysts, ovarian surface epithelium and in fallopian tube epithelium. Most were overexpressed in ovarian cancer compared with ovarian surface epithelium and/or inclusion cysts (EpCAM, EZH2, BIRC5) although BIRC5 and EZH2 were expressed as highly in fallopian tube epithelium as in ovarian cancer. We prioritised the 338 genes for those likely to be important for ovarian cancer development by in silico analyses of copy number aberration and mutation using publically available datasets and identified genes with established roles in ovarian cancer as well as novel genes for which we have evidence for involvement in ovarian cancer. Chromosome segregation emerged as an important process in which genes from our list of 338 were over-represented including two (BUB1, NCAPD2) for which there is evidence of amplification and mutation. NUAK2, upregulated in ovarian surface epithelium in proestrus and predicted to have a driver mutation in ovarian cancer, was examined in a larger cohort of serous ovarian cancer where patients with lower NUAK2 expression had shorter overall survival. In conclusion, defining genes that are activated in normal epithelium in the course of ovulation that are also dysregulated in cancer has identified a number of pathways and novel candidate genes that may contribute

  8. Genetic screens to identify pathogenic gene variants in the common cancer predisposition Lynch syndrome

    DEFF Research Database (Denmark)

    Drost, Mark; Lützen, Anne; van Hees, Sandrine

    2013-01-01

    In many individuals suspected of the common cancer predisposition Lynch syndrome, variants of unclear significance (VUS), rather than an obviously pathogenic mutations, are identified in one of the DNA mismatch repair (MMR) genes. The uncertainty of whether such VUS inactivate MMR, and