Combining Gene Signatures Improves Prediction of Breast Cancer Survival

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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

Combining gene signatures improves prediction of breast cancer survival.

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Xi Zhao

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

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

International Nuclear Information System (INIS)

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

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

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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

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.

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

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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

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

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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.

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

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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

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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

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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.

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...

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

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Hallett Robin M

2012-05-01

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

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

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Ghosh Debashis

2004-12-01

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

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

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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.

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

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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.

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

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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.

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.

*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...

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.

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

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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

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.

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

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.

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

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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

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

Real time gamma-ray signature identifier

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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...

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...

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

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.

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...

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.

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

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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.

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.

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...

*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.

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.

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....

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

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.

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.

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

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

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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

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

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Barbara A Jennings

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

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.

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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.

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

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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.

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

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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.

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

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

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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

Identifying microRNA/mRNA dysregulations in ovarian cancer.

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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

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

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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.

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

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Liu Yufeng

2011-01-01

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

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

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Matthew R Mason

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

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

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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.

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

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Srivastava Mousami

2012-11-01

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

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

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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

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

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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...

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

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

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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

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

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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

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

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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.

Radiation Gene-expression Signatures in Primary Breast Cancer Cells.

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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.

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

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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

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.

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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.

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

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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

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

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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.

Cell-type independent MYC target genes reveal a primordial signature involved in biomass accumulation.

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Hongkai Ji

Full Text Available The functions of key oncogenic transcription factors independent of context have not been fully delineated despite our richer understanding of the genetic alterations in human cancers. The MYC oncogene, which produces the Myc transcription factor, is frequently altered in human cancer and is a major regulatory hub for many cancers. In this regard, we sought to unravel the primordial signature of Myc function by using high-throughput genomic approaches to identify the cell-type independent core Myc target gene signature. Using a model of human B lymphoma cells bearing inducible MYC, we identified a stringent set of direct Myc target genes via chromatin immunoprecipitation (ChIP, global nuclear run-on assay, and changes in mRNA levels. We also identified direct Myc targets in human embryonic stem cells (ESCs. We further document that a Myc core signature (MCS set of target genes is shared in mouse and human ESCs as well as in four other human cancer cell types. Remarkably, the expression of the MCS correlates with MYC expression in a cell-type independent manner across 8,129 microarray samples, which include 312 cell and tissue types. Furthermore, the expression of the MCS is elevated in vivo in Eμ-Myc transgenic murine lymphoma cells as compared with premalignant or normal B lymphocytes. Expression of the MCS in human B cell lymphomas, acute leukemia, lung cancers or Ewing sarcomas has the highest correlation with MYC expression. Annotation of this gene signature reveals Myc's primordial function in RNA processing, ribosome biogenesis and biomass accumulation as its key roles in cancer and stem cells.

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

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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

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

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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.

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

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

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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

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

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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.

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

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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

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

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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.

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

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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...

A 6-gene signature identifies four molecular subgroups of neuroblastoma

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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

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

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

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)

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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...

Validation of a Radiosensitivity Molecular Signature in Breast Cancer

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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

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

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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.

Predictive gene signatures: molecular markers distinguishing colon adenomatous polyp and carcinoma.

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Janice E Drew

Full Text Available Cancers exhibit abnormal molecular signatures associated with disease initiation and progression. Molecular signatures could improve cancer screening, detection, drug development and selection of appropriate drug therapies for individual patients. Typically only very small amounts of tissue are available from patients for analysis and biopsy samples exhibit broad heterogeneity that cannot be captured using a single marker. This report details application of an in-house custom designed GenomeLab System multiplex gene expression assay, the hCellMarkerPlex, to assess predictive gene signatures of normal, adenomatous polyp and carcinoma colon tissue using archived tissue bank material. The hCellMarkerPlex incorporates twenty-one gene markers: epithelial (EZR, KRT18, NOX1, SLC9A2, proliferation (PCNA, CCND1, MS4A12, differentiation (B4GANLT2, CDX1, CDX2, apoptotic (CASP3, NOX1, NTN1, fibroblast (FSP1, COL1A1, structural (ACTG2, CNN1, DES, gene transcription (HDAC1, stem cell (LGR5, endothelial (VWF and mucin production (MUC2. Gene signatures distinguished normal, adenomatous polyp and carcinoma. Individual gene targets significantly contributing to molecular tissue types, classifier genes, were further characterised using real-time PCR, in-situ hybridisation and immunohistochemistry revealing aberrant epithelial expression of MS4A12, LGR5 CDX2, NOX1 and SLC9A2 prior to development of carcinoma. Identified gene signatures identify aberrant epithelial expression of genes prior to cancer development using in-house custom designed gene expression multiplex assays. This approach may be used to assist in objective classification of disease initiation, staging, progression and therapeutic responses using biopsy material.

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

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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.

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

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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.

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

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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...

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.

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...

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

Polyphenols as Promising Drugs against Main Breast Cancer Signatures

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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.

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

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

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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.

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.

A 6-gene signature identifies four molecular subgroups of neuroblastoma

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Kogner Per

2011-04-01

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

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

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Ning An

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

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...

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.

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...

Raman spectral signatures of cervical exfoliated cells from liquid-based cytology samples

Science.gov (United States)

Kearney, Padraig; Traynor, Damien; Bonnier, Franck; Lyng, Fiona M.; O'Leary, John J.; Martin, Cara M.

2017-10-01

It is widely accepted that cervical screening has significantly reduced the incidence of cervical cancer worldwide. The primary screening test for cervical cancer is the Papanicolaou (Pap) test, which has extremely variable specificity and sensitivity. There is an unmet clinical need for methods to aid clinicians in the early detection of cervical precancer. Raman spectroscopy is a label-free objective method that can provide a biochemical fingerprint of a given sample. Compared with studies on infrared spectroscopy, relatively few Raman spectroscopy studies have been carried out to date on cervical cytology. The aim of this study was to define the Raman spectral signatures of cervical exfoliated cells present in liquid-based cytology Pap test specimens and to compare the signature of high-grade dysplastic cells to each of the normal cell types. Raman spectra were recorded from single exfoliated cells and subjected to multivariate statistical analysis. The study demonstrated that Raman spectroscopy can identify biochemical signatures associated with the most common cell types seen in liquid-based cytology samples; superficial, intermediate, and parabasal cells. In addition, biochemical changes associated with high-grade dysplasia could be identified suggesting that Raman spectroscopy could be used to aid current cervical screening tests.

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

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

On reliable discovery of molecular signatures

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Björkegren Johan

2009-01-01

Full Text Available Abstract Background Molecular signatures are sets of genes, proteins, genetic variants or other variables that can be used as markers for a particular phenotype. Reliable signature discovery methods could yield valuable insight into cell biology and mechanisms of human disease. However, it is currently not clear how to control error rates such as the false discovery rate (FDR in signature discovery. Moreover, signatures for cancer gene expression have been shown to be unstable, that is, difficult to replicate in independent studies, casting doubts on their reliability. Results We demonstrate that with modern prediction methods, signatures that yield accurate predictions may still have a high FDR. Further, we show that even signatures with low FDR may fail to replicate in independent studies due to limited statistical power. Thus, neither stability nor predictive accuracy are relevant when FDR control is the primary goal. We therefore develop a general statistical hypothesis testing framework that for the first time provides FDR control for signature discovery. Our method is demonstrated to be correct in simulation studies. When applied to five cancer data sets, the method was able to discover molecular signatures with 5% FDR in three cases, while two data sets yielded no significant findings. Conclusion Our approach enables reliable discovery of molecular signatures from genome-wide data with current sample sizes. The statistical framework developed herein is potentially applicable to a wide range of prediction problems in bioinformatics.

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.

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

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

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

Identifying prognostic features by bottom-up approach and correlating to drug repositioning.

Directory of Open Access Journals (Sweden)

Wei Li

Full Text Available Traditionally top-down method was used to identify prognostic features in cancer research. That is to say, differentially expressed genes usually in cancer versus normal were identified to see if they possess survival prediction power. The problem is that prognostic features identified from one set of patient samples can rarely be transferred to other datasets. We apply bottom-up approach in this study: survival correlated or clinical stage correlated genes were selected first and prioritized by their network topology additionally, then a small set of features can be used as a prognostic signature.Gene expression profiles of a cohort of 221 hepatocellular carcinoma (HCC patients were used as a training set, 'bottom-up' approach was applied to discover gene-expression signatures associated with survival in both tumor and adjacent non-tumor tissues, and compared with 'top-down' approach. The results were validated in a second cohort of 82 patients which was used as a testing set.Two sets of gene signatures separately identified in tumor and adjacent non-tumor tissues by bottom-up approach were developed in the training cohort. These two signatures were associated with overall survival times of HCC patients and the robustness of each was validated in the testing set, and each predictive performance was better than gene expression signatures reported previously. Moreover, genes in these two prognosis signature gave some indications for drug-repositioning on HCC. Some approved drugs targeting these markers have the alternative indications on hepatocellular carcinoma.Using the bottom-up approach, we have developed two prognostic gene signatures with a limited number of genes that associated with overall survival times of patients with HCC. Furthermore, prognostic markers in these two signatures have the potential to be therapeutic targets.

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

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

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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.)

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. | Office of Cancer Genomics

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We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival.

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

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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.

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

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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.

Toward a comprehensive and systematic methylome signature in colorectal cancers.

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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.

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

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

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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

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

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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

An eleven gene molecular signature for extra-capsular spread in oral squamous cell carcinoma serves as a prognosticator of outcome in patients without nodal metastases.

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Wang, Weining; Lim, Weng Khong; Leong, Hui Sun; Chong, Fui Teen; Lim, Tony K H; Tan, Daniel S W; Teh, Bin Tean; Iyer, N Gopalakrishna

2015-04-01

Extracapsular spread (ECS) is an important prognostic factor for oral squamous cell carcinoma (OSCC) and is used to guide management. In this study, we aimed to identify an expression profile signature for ECS in node-positive OSCC using data derived from two different sources: a cohort of OSCC patients from our institution (National Cancer Centre Singapore) and The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSCC) cohort. We also sought to determine if this signature could serve as a prognostic factor in node negative cancers. Patients with a histological diagnosis of OSCC were identified from an institutional database and fresh tumor samples were retrieved. RNA was extracted and gene expression profiling was performed using the Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray platform. RNA sequence data and corresponding clinical data for the TCGA HNSCC cohort were downloaded from the TCGA Data Portal. All data analyses were conducted using R package and SPSS. We identified an 11 gene signature (GGH, MTFR1, CDKN3, PSRC1, SMIM3, CA9, IRX4, CPA3, ZSCAN16, CBX7 and ZFP3) which was robust in segregating tumors by ECS status. In node negative patients, patients harboring this ECS signature had a significantly worse overall survival (p=0.04). An eleven gene signature for ECS was derived. Our results also suggest that this signature is prognostic in a separate subset of patients with no nodal metastasis Further validation of this signature on other datasets and immunohistochemical studies are required to establish utility of this signature in stratifying early stage OSCC patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gene expression patterns associated with p53 status in breast cancer

International Nuclear Information System (INIS)

Troester, Melissa A; Herschkowitz, Jason I; Oh, Daniel S; He, Xiaping; Hoadley, Katherine A; Barbier, Claire S; Perou, Charles M

2006-01-01

Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors. Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data. In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes

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

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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

An algorithm to discover gene signatures with predictive potential

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Hallett Robin M

2010-09-01

Full Text Available Abstract Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training.

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

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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.

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.

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

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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...

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

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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.

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

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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

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

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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.

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

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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

Hepatocellular carcinoma displays distinct DNA methylation signatures with potential as clinical predictors.

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Hector Hernandez-Vargas

Full Text Available BACKGROUND: Hepatocellular carcinoma (HCC is characterized by late detection and fast progression, and it is believed that epigenetic disruption may be the cause of its molecular and clinicopathological heterogeneity. A better understanding of the global deregulation of methylation states and how they correlate with disease progression will aid in the design of strategies for earlier detection and better therapeutic decisions. METHODS AND FINDINGS: We characterized the changes in promoter methylation in a series of 30 HCC tumors and their respective surrounding tissue and identified methylation signatures associated with major risk factors and clinical correlates. A wide panel of cancer-related gene promoters was analyzed using Illumina bead array technology, and CpG sites were then selected according to their ability to classify clinicopathological parameters. An independent series of HCC tumors and matched surrounding tissue was used for validation of the signatures. We were able to develop and validate a signature of methylation in HCC. This signature distinguished HCC from surrounding tissue and from other tumor types, and was independent of risk factors. However, aberrant methylation of an independent subset of promoters was associated with tumor progression and etiological risk factors (HBV or HCV infection and alcohol consumption. Interestingly, distinct methylation of an independent panel of gene promoters was strongly correlated with survival after cancer therapy. CONCLUSION: Our study shows that HCC tumors exhibit specific DNA methylation signatures associated with major risk factors and tumor progression stage, with potential clinical applications in diagnosis and prognosis.

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

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

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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

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

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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

Functional signatures of radio-induction in sarcomas developing in the radiation field after radiotherapy

International Nuclear Information System (INIS)

Hadj-Hamou, N.S.

2010-01-01

Radiotherapy plays an important role in the treatment of cancers. However, exposure to ionizing radiation is a well-known risk factor for secondary cancer development. Currently, rigorous defined scientific criteria are lacking to establish if an individual tumor has a radiation-induced or a sporadic origin. The main aim of my thesis program was to identify a transcriptome signature of the ionizing radiation effects in radiation-induced cancers. The series of cancers used in this study is composed of sarcomas developing in the irradiation field of patients treated by radiotherapy for a primary cancer. Strict selection criteria (histology different from the primary cancer, latency longer than 5 years) were used to establish with a high probability the sarcomas-radiation induced origin. Their transcriptomes were compared with those from patients without irradiation history. A method of classification adapted to small series was used for the study of all the 60 collected sarcomas (34 radiation-induced and 26 sporadic). A learning set composed of 24 sarcomas from known aetiology allowed us to determine a signature of 135 genes discriminating the sarcomas according to their aetiology. The signature classified 86% of the remaining sarcomas as a function of their aetiology with an accuracy of 97%. The analysis of the genes-function shows that the radiation-induced sarcomas suffered the effects of a chronic oxidative stress mainly generated by mitochondrial dysfunctions. This study shows, for the first time, that it is possible to diagnose, at the case by case level, radiation-induced sarcomas on a rigorous scientific basis. (author)

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

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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

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

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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

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

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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

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

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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.

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

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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.

Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

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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.

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

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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

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

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...

Hypermutation in pancreatic cancer

OpenAIRE

Humphris, Jeremy L.; Patch, Ann-Marie; Nones, Katia; Bailey, Peter J.; Johns, Amber L.; McKay, Skye; Chang, David K.; Miller, David K.; Pajic, Marina; Kassahn, Karin S.; Quinn, Michael C.J.; Bruxner, Timothy J.C.; Christ, Angelika N.; Harliwong, Ivon; Idrisoglu, Senel

2017-01-01

Pancreatic cancer is molecularly diverse, with few effective therapies. Increased mutation burden and defective DNA repair are associated with response to immune checkpoint inhibitors in several other cancer types. We interrogated 385 pancreatic cancer genomes to define hypermutation and its causes. Mutational signatures inferring defects in DNA repair were enriched in those with the highest mutation burdens. Mismatch repair deficiency was identified in 1% of tumors harboring different mechan...

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

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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.

Integrated analysis of HPV-mediated immune alterations in cervical cancer.

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Chen, Long; Luan, Shaohong; Xia, Baoguo; Liu, Yansheng; Gao, Yuan; Yu, Hongyan; Mu, Qingling; Zhang, Ping; Zhang, Weina; Zhang, Shengmiao; Wei, Guopeng; Yang, Min; Li, Ke

2018-05-01

Human papillomavirus (HPV) infection is the primary cause of cervical cancer. HPV-mediated immune alterations are known to play crucial roles in determining viral persistence and host cell transformation. We sought to thoroughly understand HPV-directed immune alterations in cervical cancer by exploring publically available datasets. 130 HPV positive and 7 HPV negative cervical cancer cases from The Cancer Genome Atlas were compared for differences in gene expression levels and functional enrichment. Analyses for copy number variation (CNV) and genetic mutation were conducted for differentially expressed immune genes. Kaplan-Meier analysis was performed to assess survival and relapse differences across cases with or without alterations of the identified immune signature genes. Genes up-regulated in HPV positive cervical cancer were enriched for various gene ontology terms of immune processes (P=1.05E-14~1.00E-05). Integrated analysis of the differentially expressed immune genes identified 9 genes that displayed either CNV, genetic mutation and/or gene expression changes in at least 10% of the cases of HPV positive cervical cancer. Genomic amplification may cause elevated levels of these genes in some HPV positive cases. Finally, patients with alterations in at least one of the nine signature genes overall had earlier relapse compared to those without any alterations. The altered expression of either TFRC or MMP13 may indicate poor survival for a subset of cervical cancer patients (P=1.07E-07). We identified a novel immune gene signature for HPV positive cervical cancer that is potentially associated with early relapse of cervical cancer. Copyright © 2018. Published by Elsevier Inc.

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

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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.

Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target

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2016-06-01

AWARD NUMBER: W81XWH-14-1-0107 TITLE: Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target PRINCIPAL...AND SUBTITLE Tumor Microenvironment Gene Signature as a 5a. CONTRACT NUMBER W81XWH-14-1-0107 Prognostic Classifier and Therapeutic Target 5b...gene signature that correlates with poor survival in ovarian cancer patients. We are refining this gene signature to develop biomarkers for the

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)

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

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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.

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

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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

Biomarkers of HIV-associated Cancer

OpenAIRE

Flepisi, Brian Thabile; Bouic, Patrick; Sissolak, Gerhard; Rosenkranz, Bernd

2014-01-01

Cancer biomarkers have provided great opportunities for improving the management of cancer patients by enhancing the efficiency of early detection, diagnosis, and efficacy of treatment. Every cell type has a unique molecular signature, referred to as biomarkers, which are identifiable characteristics such as levels or activities of a myriad of genes, proteins, or other molecular features. Biomarkers can facilitate the molecular definition of cancer, provide information about the course of can...

Five Guidelines for Selecting Hydrological Signatures

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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

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

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

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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

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

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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.

Identifying pathways affected by cancer mutations.

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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.

Network information improves cancer outcome prediction.

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Roy, Janine; Winter, Christof; Isik, Zerrin; Schroeder, Michael

2014-07-01

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease progression and patient outcome variables from gene expression in order to personalize treatment options. Despite first diagnostic kits in the market, there are open problems such as the choice of random gene signatures or noisy expression data. One approach to deal with these two problems employs protein-protein interaction networks and ranks genes using the random surfer model of Google's PageRank algorithm. In this work, we created a benchmark dataset collection comprising 25 cancer outcome prediction datasets from literature and systematically evaluated the use of networks and a PageRank derivative, NetRank, for signature identification. We show that the NetRank performs significantly better than classical methods such as fold change or t-test. Despite an order of magnitude difference in network size, a regulatory and protein-protein interaction network perform equally well. Experimental evaluation on cancer outcome prediction in all of the 25 underlying datasets suggests that the network-based methodology identifies highly overlapping signatures over all cancer types, in contrast to classical methods that fail to identify highly common gene sets across the same cancer types. Integration of network information into gene expression analysis allows the identification of more reliable and accurate biomarkers and provides a deeper understanding of processes occurring in cancer development and progression. © The Author 2012. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

A gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence

International Nuclear Information System (INIS)

Reis, Patricia P; Simpson, Colleen; Goldstein, David; Brown, Dale; Gilbert, Ralph; Gullane, Patrick; Irish, Jonathan; Jurisica, Igor; Kamel-Reid, Suzanne; Waldron, Levi; Perez-Ordonez, Bayardo; Pintilie, Melania; Galloni, Natalie Naranjo; Xuan, Yali; Cervigne, Nilva K; Warner, Giles C; Makitie, Antti A

2011-01-01

Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence. We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients. We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Over-expression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test). Gene expression alterations occur in histologically normal margins in OSCC. Over-expression of the 4-gene signature in histologically normal surgical margins was validated and highly predictive of recurrence in an independent patient cohort. Our findings may be applied to develop a molecular test, which would be clinically useful to help predict which patients are at a higher risk of local recurrence

A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures.

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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.

Proteomic maps of breast cancer subtypes

DEFF Research Database (Denmark)

Tyanova, Stefka; Albrechtsen, Reidar; Kronqvist, Pauliina

2016-01-01

Systems-wide profiling of breast cancer has almost always entailed RNA and DNA analysis by microarray and sequencing techniques. Marked developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analysed 40...... oestrogen receptor positive (luminal), Her2 positive and triple negative breast tumours and reached a quantitative depth of >10,000 proteins. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell......-cell communication. Furthermore, we derived a signature of 19 proteins, which differ between the breast cancer subtypes, through support vector machine (SVM)-based classification and feature selection. Remarkably, only three proteins of the signature were associated with gene copy number variations and eleven were...

Gene expression signature of normal cell-of-origin predicts ovarian tumor outcomes.

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Melissa A Merritt

Full Text Available The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV and fallopian tube (FT epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.

Hyperspectral signature analysis of skin parameters

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Vyas, Saurabh; Banerjee, Amit; Garza, Luis; Kang, Sewon; Burlina, Philippe

2013-02-01

The temporal analysis of changes in biological skin parameters, including melanosome concentration, collagen concentration and blood oxygenation, may serve as a valuable tool in diagnosing the progression of malignant skin cancers and in understanding the pathophysiology of cancerous tumors. Quantitative knowledge of these parameters can also be useful in applications such as wound assessment, and point-of-care diagnostics, amongst others. We propose an approach to estimate in vivo skin parameters using a forward computational model based on Kubelka-Munk theory and the Fresnel Equations. We use this model to map the skin parameters to their corresponding hyperspectral signature. We then use machine learning based regression to develop an inverse map from hyperspectral signatures to skin parameters. In particular, we employ support vector machine based regression to estimate the in vivo skin parameters given their corresponding hyperspectral signature. We build on our work from SPIE 2012, and validate our methodology on an in vivo dataset. This dataset consists of 241 signatures collected from in vivo hyperspectral imaging of patients of both genders and Caucasian, Asian and African American ethnicities. In addition, we also extend our methodology past the visible region and through the short-wave infrared region of the electromagnetic spectrum. We find promising results when comparing the estimated skin parameters to the ground truth, demonstrating good agreement with well-established physiological precepts. This methodology can have potential use in non-invasive skin anomaly detection and for developing minimally invasive pre-screening tools.

Identification of endometrial cancer methylation features using combined methylation analysis methods.

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Michael P Trimarchi

Full Text Available DNA methylation is a stable epigenetic mark that is frequently altered in tumors. DNA methylation features are attractive biomarkers for disease states given the stability of DNA methylation in living cells and in biologic specimens typically available for analysis. Widespread accumulation of methylation in regulatory elements in some cancers (specifically the CpG island methylator phenotype, CIMP can play an important role in tumorigenesis. High resolution assessment of CIMP for the entire genome, however, remains cost prohibitive and requires quantities of DNA not available for many tissue samples of interest. Genome-wide scans of methylation have been undertaken for large numbers of tumors, and higher resolution analyses for a limited number of cancer specimens. Methods for analyzing such large datasets and integrating findings from different studies continue to evolve. An approach for comparison of findings from a genome-wide assessment of the methylated component of tumor DNA and more widely applied methylation scans was developed.Methylomes for 76 primary endometrial cancer and 12 normal endometrial samples were generated using methylated fragment capture and second generation sequencing, MethylCap-seq. Publically available Infinium HumanMethylation 450 data from The Cancer Genome Atlas (TCGA were compared to MethylCap-seq data.Analysis of methylation in promoter CpG islands (CGIs identified a subset of tumors with a methylator phenotype. We used a two-stage approach to develop a 13-region methylation signature associated with a "hypermethylator state." High level methylation for the 13-region methylation signatures was associated with mismatch repair deficiency, high mutation rate, and low somatic copy number alteration in the TCGA test set. In addition, the signature devised showed good agreement with previously described methylation clusters devised by TCGA.We identified a methylation signature for a "hypermethylator phenotype" in

Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case-Control Study in EPIC.

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Assi, Nada; Thomas, Duncan C; Leitzmann, Michael; Stepien, Magdalena; Chajès, Véronique; Philip, Thierry; Vineis, Paolo; Bamia, Christina; Boutron-Ruault, Marie-Christine; Sandanger, Torkjel M; Molinuevo, Amaia; Boshuizen, Hendriek C; Sundkvist, Anneli; Kühn, Tilman; Travis, Ruth C; Overvad, Kim; Riboli, Elio; Gunter, Marc J; Scalbert, Augustin; Jenab, Mazda; Ferrari, Pietro; Viallon, Vivian

2018-05-01

Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites. Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk. Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%. Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk. Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators

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

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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.

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.

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

Cross-species analysis of genetically engineered mouse models of MAPK-driven colorectal cancer identifies hallmarks of the human disease

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Peter J. Belmont

2014-06-01

Full Text Available Effective treatment options for advanced colorectal cancer (CRC are limited, survival rates are poor and this disease continues to be a leading cause of cancer-related deaths worldwide. Despite being a highly heterogeneous disease, a large subset of individuals with sporadic CRC typically harbor relatively few established ‘driver’ lesions. Here, we describe a collection of genetically engineered mouse models (GEMMs of sporadic CRC that combine lesions frequently altered in human patients, including well-characterized tumor suppressors and activators of MAPK signaling. Primary tumors from these models were profiled, and individual GEMM tumors segregated into groups based on their genotypes. Unique allelic and genotypic expression signatures were generated from these GEMMs and applied to clinically annotated human CRC patient samples. We provide evidence that a Kras signature derived from these GEMMs is capable of distinguishing human tumors harboring KRAS mutation, and tracks with poor prognosis in two independent human patient cohorts. Furthermore, the analysis of a panel of human CRC cell lines suggests that high expression of the GEMM Kras signature correlates with sensitivity to targeted pathway inhibitors. Together, these findings implicate GEMMs as powerful preclinical tools with the capacity to recapitulate relevant human disease biology, and support the use of genetic signatures generated in these models to facilitate future drug discovery and validation efforts.

Cubic Bezier Curve Approach for Automated Offline Signature Verification with Intrusion Identification

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Arun Vijayaragavan

2014-01-01

Full Text Available Authentication is a process of identifying person’s rights over a system. Many authentication types are used in various systems, wherein biometrics authentication systems are of a special concern. Signature verification is a basic biometric authentication technique used widely. The signature matching algorithm uses image correlation and graph matching technique which provides false rejection or acceptance. We proposed a model to compare knowledge from signature. Intrusion in the signature repository system results in copy of the signature that leads to false acceptance. Our approach uses a Bezier curve algorithm to identify the curve points and uses the behaviors of the signature for verification. An analyzing mobile agent is used to identify the input signature parameters and compare them with reference signature repository. It identifies duplication of signature over intrusion and rejects it. Experiments are conducted on a database with thousands of signature images from various sources and the results are favorable.

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...

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

TCGA study identifies genomic features of cervical cancer

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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.

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.

RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes

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Ashish Saini

2014-01-01

Full Text Available Background. Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification. Methods. We propose a novel method to measure and extract the reliable (biologically true or valid interactions from gene interaction networks and incorporate the extracted reliable gene interactions into our proposed RRHGE algorithm to identify significant gene signatures from microarray gene expression data for classifying ER+ and ER− breast cancer samples. Results. The evaluation on real breast cancer samples showed that our RRHGE algorithm achieved higher classification accuracy than the existing approaches.

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

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

Genes influenced by the non-muscle isoform of Myosin light chain kinase impact human cancer prognosis.

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Tong Zhou

Full Text Available The multifunctional non-muscle isoform of myosin light chain kinase (nmMLCK is critical to the rapid dynamic coordination of the cytoskeleton involved in cancer cell proliferation and migration. We identified 45 nmMLCK-influenced genes by bioinformatic filtering of genome-wide expression in wild type and nmMLCK knockout (KO mice exposed to preclinical models of murine acute inflammatory lung injury, pathologies that are well established to include nmMLCK as an essential participant. To determine whether these nmMLCK-influenced genes were relevant to human cancers, the 45 mouse genes were matched to 38 distinct human orthologs (M38 signature (GeneCards definition and underwent Kaplan-Meier survival analysis in training and validation cohorts. These studies revealed that in training cohorts, the M38 signature successfully identified cancer patients with poor overall survival in breast cancer (P<0.001, colon cancer (P<0.001, glioma (P<0.001, and lung cancer (P<0.001. In validation cohorts, the M38 signature demonstrated significantly reduced overall survival for high-score patients of breast cancer (P = 0.002, colon cancer (P = 0.035, glioma (P = 0.023, and lung cancer (P = 0.023. The association between M38 risk score and overall survival was confirmed by univariate Cox proportional hazard analysis of overall survival in the both training and validation cohorts. This study, providing a novel prognostic cancer gene signature derived from a murine model of nmMLCK-associated lung inflammation, strongly supports nmMLCK-involved pathways in tumor growth and progression in human cancers and nmMLCK as an attractive candidate molecular target in both inflammatory and neoplastic processes.

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

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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

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

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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

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.

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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.

Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics

DEFF Research Database (Denmark)

Khurana, Ekta; Fu, Yao; Colonna, Vincenza

2013-01-01

Identifying Important Identifiers Each of us has millions of sequence variations in our genomes. Signatures of purifying or negative selection should help identify which of those variations is functionally important. Khurana et al. (1235587) used sequence polymorphisms from 1092 humans across 14...... sites tended to occur in network hub promoters. Many recurrent somatic cancer variants occurred in noncoding regulatory regions and thus might indicate mutations that drive cancer....

Biomarker Gene Signature Discovery Integrating Network Knowledge

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Holger Fröhlich

2012-02-01

Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

The Immune Landscape of Cancer

OpenAIRE

Thorsson, Vésteinn; Gibbs, David L.; Brown, Scott D.; Wolf, Denise; Bortone, Dante S.; Ou Yang, Tai Hsien; Porta-Pardo, Eduard; Gao, Galen F.; Plaisier, Christopher L.; Eddy, James A.; Ziv, Elad; Culhane, Aedin C.; Paull, Evan O.; Sivakumar, I. K.Ashok; Gentles, Andrew J.

2018-01-01

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell prolifer...

Aberrant chimeric RNA GOLM1-MAK10 encoding a secreted fusion protein as a molecular signature for human esophageal squamous cell carcinoma

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Zhang, Hao; Lin, Wan; Kannan, Kalpana; Luo, Liming; Li, Jing; Chao, Pei-Wen; Wang, Yan; Chen, Yu-Ping; Gu, Jiang; Yen, Laising

2013-01-01

It is increasingly recognized that chimeric RNAs may exert a novel layer of cellular complexity that contributes to oncogenesis and cancer progression, and could be utilized as molecular biomarkers and therapeutic targets. To date yet no fusion chimeric RNAs have been identified in esophageal cancer, the 6th most frequent cause of cancer death in the world. While analyzing the expression of 32 recurrent cancer chimeric RNAs in esophageal squamous cell carcinoma (ESCC) from patients and cancer cell lines, we identified GOLM1-MAK10, as a highly cancer-enriched chimeric RNA in ESCC. In situ hybridization revealed that the expression of the chimera is largely restricted to cancer cells in patient tumors, and nearly undetectable in non-neoplastic esophageal tissue from normal subjects. The aberrant chimera closely correlated with histologic differentiation and lymph node metastasis. Furthermore, we demonstrate that chimera GOLM1-MAK10 encodes a secreted fusion protein. Mechanistic studies reveal that GOLM1-MAK10 is likely derived from transcription read-through/splicing rather than being generated from a fusion gene. Collectively, these findings provide novel insights into the molecular mechanism involved in ESCC and provide a novel potential target for future therapies. The secreted fusion protein translated from GOLM1-MAK10 could also serve as a unique protein signature detectable by standard non-invasive assays. These observations are critical as there is no clinically useful molecular signature available for detecting this deadly disease or monitoring the treatment response. PMID:24243830

Identification of a robust subpathway-based signature for acute myeloid leukemia prognosis using an miRNA integrated strategy.

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Chang, Huijuan; Gao, Qiuying; Ding, Wei; Qing, Xueqin

2018-01-01

Acute myeloid leukemia (AML) is a heterogeneous disease, and survival signatures are urgently needed to better monitor treatment. MiRNAs displayed vital regulatory roles on target genes, which was necessary involved in the complex disease. We therefore examined the expression levels of miRNAs and genes to identify robust signatures for survival benefit analyses. First, we reconstructed subpathway graphs by embedding miRNA components that were derived from low-throughput miRNA-gene interactions. Then, we randomly divided the data sets from The Cancer Genome Atlas (TCGA) into training and testing sets, and further formed 100 subsets based on the training set. Using each subset, we identified survival-related miRNAs and genes, and identified survival subpathways based on the reconstructed subpathway graphs. After statistical analyses of these survival subpathways, the most robust subpathways with the top three ranks were identified, and risk scores were calculated based on these robust subpathways for AML patient prognoses. Among these robust subpathways, three representative subpathways, path: 05200_10 from Pathways in cancer, path: 04110_20 from Cell cycle, and path: 04510_8 from Focal adhesion, were significantly associated with patient survival in the TCGA training and testing sets based on subpathway risk scores. In conclusion, we performed integrated analyses of miRNAs and genes to identify robust prognostic subpathways, and calculated subpathway risk scores to characterize AML patient survival.

Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

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Lin, Yan; Lv, Yufeng; Liang, Rong; Yuan, Chunling; Zhang, Jinyan; He, Dan; Zheng, Xiaowen; Zhang, Jianfeng

2018-01-01

The aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD). Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Based on our cutoff criteria ( P 1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan-Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group ( P =0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways. Taken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

ADAGE signature analysis: differential expression analysis with data-defined gene sets.

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Tan, Jie; Huyck, Matthew; Hu, Dongbo; Zelaya, René A; Hogan, Deborah A; Greene, Casey S

2017-11-22

Gene set enrichment analysis and overrepresentation analyses are commonly used methods to determine the biological processes affected by a differential expression experiment. This approach requires biologically relevant gene sets, which are currently curated manually, limiting their availability and accuracy in many organisms without extensively curated resources. New feature learning approaches can now be paired with existing data collections to directly extract functional gene sets from big data. Here we introduce a method to identify perturbed processes. In contrast with methods that use curated gene sets, this approach uses signatures extracted from public expression data. We first extract expression signatures from public data using ADAGE, a neural network-based feature extraction approach. We next identify signatures that are differentially active under a given treatment. Our results demonstrate that these signatures represent biological processes that are perturbed by the experiment. Because these signatures are directly learned from data without supervision, they can identify uncurated or novel biological processes. We implemented ADAGE signature analysis for the bacterial pathogen Pseudomonas aeruginosa. For the convenience of different user groups, we implemented both an R package (ADAGEpath) and a web server ( http://adage.greenelab.com ) to run these analyses. Both are open-source to allow easy expansion to other organisms or signature generation methods. We applied ADAGE signature analysis to an example dataset in which wild-type and ∆anr mutant cells were grown as biofilms on the Cystic Fibrosis genotype bronchial epithelial cells. We mapped active signatures in the dataset to KEGG pathways and compared with pathways identified using GSEA. The two approaches generally return consistent results; however, ADAGE signature analysis also identified a signature that revealed the molecularly supported link between the MexT regulon and Anr. We designed

Selection signatures in worldwide sheep populations.

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Fariello, Maria-Ines; Servin, Bertrand; Tosser-Klopp, Gwenola; Rupp, Rachel; Moreno, Carole; San Cristobal, Magali; Boitard, Simon

2014-01-01

The diversity of populations in domestic species offers great opportunities to study genome response to selection. The recently published Sheep HapMap dataset is a great example of characterization of the world wide genetic diversity in sheep. In this study, we re-analyzed the Sheep HapMap dataset to identify selection signatures in worldwide sheep populations. Compared to previous analyses, we made use of statistical methods that (i) take account of the hierarchical structure of sheep populations, (ii) make use of linkage disequilibrium information and (iii) focus specifically on either recent or older selection signatures. We show that this allows pinpointing several new selection signatures in the sheep genome and distinguishing those related to modern breeding objectives and to earlier post-domestication constraints. The newly identified regions, together with the ones previously identified, reveal the extensive genome response to selection on morphology, color and adaptation to new environments.

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

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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.

Hypermutation In Pancreatic Cancer.

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Humphris, Jeremy L; Patch, Ann-Marie; Nones, Katia; Bailey, Peter J; Johns, Amber L; McKay, Skye; Chang, David K; Miller, David K; Pajic, Marina; Kassahn, Karin S; Quinn, Michael C J; Bruxner, Timothy J C; Christ, Angelika N; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourse, Craig; Nourbakhsh, Ehsan; Stone, Andrew; Wilson, Peter J; Anderson, Matthew; Fink, J Lynn; Holmes, Oliver; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Mead, Ronald S; Xu, Qinying; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Nagrial, Adnan M; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Chou, Angela; Scarlett, Christopher J; Pinho, Andreia V; Rooman, Ilse; Giry-Laterriere, Marc; Samra, Jaswinder S; Kench, James G; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Jamieson, Nigel B; McKay, Colin J; Carter, C Ross; Dickson, Euan J; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Morton, Jennifer P; Sansom, Owen J; Grützmann, Robert; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Rusev, Borislav; Corbo, Vincenzo; Salvia, Roberto; Cataldo, Ivana; Tortora, Giampaolo; Tempero, Margaret A; Hofmann, Oliver; Eshleman, James R; Pilarsky, Christian; Scarpa, Aldo; Musgrove, Elizabeth A; Gill, Anthony J; Pearson, John V; Grimmond, Sean M; Waddell, Nicola; Biankin, Andrew V

2017-01-01

Pancreatic cancer is molecularly diverse, with few effective therapies. Increased mutation burden and defective DNA repair are associated with response to immune checkpoint inhibitors in several other cancer types. We interrogated 385 pancreatic cancer genomes to define hypermutation and its causes. Mutational signatures inferring defects in DNA repair were enriched in those with the highest mutation burdens. Mismatch repair deficiency was identified in 1% of tumors harboring different mechanisms of somatic inactivation of MLH1 and MSH2. Defining mutation load in individual pancreatic cancers and the optimal assay for patient selection may inform clinical trial design for immunotherapy in pancreatic cancer. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

A signature-based method for indexing cell cycle phase distribution from microarray profiles

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Mizuno Hideaki

2009-03-01

Full Text Available Abstract Background The cell cycle machinery interprets oncogenic signals and reflects the biology of cancers. To date, various methods for cell cycle phase estimation such as mitotic index, S phase fraction, and immunohistochemistry have provided valuable information on cancers (e.g. proliferation rate. However, those methods rely on one or few measurements and the scope of the information is limited. There is a need for more systematic cell cycle analysis methods. Results We developed a signature-based method for indexing cell cycle phase distribution from microarray profiles under consideration of cycling and non-cycling cells. A cell cycle signature masterset, composed of genes which express preferentially in cycling cells and in a cell cycle-regulated manner, was created to index the proportion of cycling cells in the sample. Cell cycle signature subsets, composed of genes whose expressions peak at specific stages of the cell cycle, were also created to index the proportion of cells in the corresponding stages. The method was validated using cell cycle datasets and quiescence-induced cell datasets. Analyses of a mouse tumor model dataset and human breast cancer datasets revealed variations in the proportion of cycling cells. When the influence of non-cycling cells was taken into account, "buried" cell cycle phase distributions were depicted that were oncogenic-event specific in the mouse tumor model dataset and were associated with patients' prognosis in the human breast cancer datasets. Conclusion The signature-based cell cycle analysis method presented in this report, would potentially be of value for cancer characterization and diagnostics.

Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures.

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Pride, David T; Schoenfeld, Thomas

2008-09-17

Metagenomic analysis provides a rich source of biological information for otherwise intractable viral communities. However, study of viral metagenomes has been hampered by its nearly complete reliance on BLAST algorithms for identification of DNA sequences. We sought to develop algorithms for examination of viral metagenomes to identify the origin of sequences independent of BLAST algorithms. We chose viral metagenomes obtained from two hot springs, Bear Paw and Octopus, in Yellowstone National Park, as they represent simple microbial populations where comparatively large contigs were obtained. Thermal spring metagenomes have high proportions of sequences without significant Genbank homology, which has hampered identification of viruses and their linkage with hosts. To analyze each metagenome, we developed a method to classify DNA fragments using genome signature-based phylogenetic classification (GSPC), where metagenomic fragments are compared to a database of oligonucleotide signatures for all previously sequenced Bacteria, Archaea, and viruses. From both Bear Paw and Octopus hot springs, each assembled contig had more similarity to other metagenome contigs than to any sequenced microbial genome based on GSPC analysis, suggesting a genome signature common to each of these extreme environments. While viral metagenomes from Bear Paw and Octopus share some similarity, the genome signatures from each locale are largely unique. GSPC using a microbial database predicts most of the Octopus metagenome has archaeal signatures, while bacterial signatures predominate in Bear Paw; a finding consistent with those of Genbank BLAST. When using a viral database, the majority of the Octopus metagenome is predicted to belong to archaeal virus Families Globuloviridae and Fuselloviridae, while none of the Bear Paw metagenome is predicted to belong to archaeal viruses. As expected, when microbial and viral databases are combined, each of the Octopus and Bear Paw metagenomic contigs

A five-gene hedgehog signature developed as a patient preselection tool for hedgehog inhibitor therapy in medulloblastoma.

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Shou, Yaping; Robinson, Douglas M; Amakye, Dereck D; Rose, Kristine L; Cho, Yoon-Jae; Ligon, Keith L; Sharp, Thad; Haider, Asifa S; Bandaru, Raj; Ando, Yuichi; Geoerger, Birgit; Doz, François; Ashley, David M; Hargrave, Darren R; Casanova, Michela; Tawbi, Hussein A; Rodon, Jordi; Thomas, Anne L; Mita, Alain C; MacDonald, Tobey J; Kieran, Mark W

2015-02-01

Distinct molecular subgroups of medulloblastoma, including hedgehog (Hh) pathway-activated disease, have been reported. We identified and clinically validated a five-gene Hh signature assay that can be used to preselect patients with Hh pathway-activated medulloblastoma. Gene characteristics of the Hh medulloblastoma subgroup were identified through published bioinformatic analyses. Thirty-two genes shown to be differentially expressed in fresh-frozen and formalin-fixed paraffin-embedded tumor samples and reproducibly analyzed by RT-PCR were measured in matched samples. These data formed the basis for building a multi-gene logistic regression model derived through elastic net methods from which the five-gene Hh signature emerged after multiple iterations. On the basis of signature gene expression levels, the model computed a propensity score to determine Hh activation using a threshold set a priori. The association between Hh activation status and tumor response to the Hh pathway inhibitor sonidegib (LDE225) was analyzed. Five differentially expressed genes in medulloblastoma (GLI1, SPHK1, SHROOM2, PDLIM3, and OTX2) were found to associate with Hh pathway activation status. In an independent validation study, Hh activation status of 25 medulloblastoma samples showed 100% concordance between the five-gene signature and Affymetrix profiling. Further, in medulloblastoma samples from 50 patients treated with sonidegib, all 6 patients who responded were found to have Hh-activated tumors. Three patients with Hh-activated tumors had stable or progressive disease. No patients with Hh-nonactivated tumors responded. This five-gene Hh signature can robustly identify Hh-activated medulloblastoma and may be used to preselect patients who might benefit from sonidegib treatment. ©2014 American Association for Cancer Research.

A 65‑gene signature for prognostic prediction in colon adenocarcinoma.

Science.gov (United States)

Jiang, Hui; Du, Jun; Gu, Jiming; Jin, Liugen; Pu, Yong; Fei, Bojian

2018-04-01

The aim of the present study was to examine the molecular factors associated with the prognosis of colon cancer. Gene expression datasets were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases to screen differentially expressed genes (DEGs) between colon cancer samples and normal samples. Survival‑related genes were selected from the DEGs using the Cox regression method. A co‑expression network of survival‑related genes was then constructed, and functional clusters were extracted from this network. The significantly enriched functions and pathways of the genes in the network were identified. Using Bayesian discriminant analysis, a prognostic prediction system was established to distinguish the positive from negative prognostic samples. The discrimination efficacy of the system was validated in the GSE17538 dataset using Kaplan‑Meier survival analysis. A total of 636 and 1,892 DEGs between the colon cancer samples and normal samples were screened from the TCGA and GSE44861 dataset, respectively. There were 155 survival‑related genes selected. The co‑expression network of survival‑related genes included 138 genes, 534 lines (connections) and five functional clusters, including the signaling pathway, cellular response to cAMP, and immune system process functional clusters. The molecular function, cellular components and biological processes were the significantly enriched functions. The peroxisome proliferator‑activated receptor signaling pathway, Wnt signaling pathway, B cell receptor signaling pathway, and cytokine‑cytokine receptor interactions were the significant pathways. A prognostic prediction system based on a 65‑gene signature was established using this co‑expression network. Its discriminatory effect was validated in the TCGA dataset (P=3.56e‑12) and the GSE17538 dataset (P=1.67e‑6). The 65‑gene signature included kallikrein‑related peptidase 6 (KLK6), collagen type XI α1 (COL11A1), cartilage

Epigenetic Biomarkers of Breast Cancer Risk: Across the Breast Cancer Prevention Continuum.

Science.gov (United States)

Terry, Mary Beth; McDonald, Jasmine A; Wu, Hui Chen; Eng, Sybil; Santella, Regina M

2016-01-01

Epigenetic biomarkers, such as DNA methylation, can increase cancer risk through altering gene expression. The Cancer Genome Atlas (TCGA) Network has demonstrated breast cancer-specific DNA methylation signatures. DNA methylation signatures measured at the time of diagnosis may prove important for treatment options and in predicting disease-free and overall survival (tertiary prevention). DNA methylation measurement in cell free DNA may also be useful in improving early detection by measuring tumor DNA released into the blood (secondary prevention). Most evidence evaluating the use of DNA methylation markers in tertiary and secondary prevention efforts for breast cancer comes from studies that are cross-sectional or retrospective with limited corresponding epidemiologic data, raising concerns about temporality. Few prospective studies exist that are large enough to address whether DNA methylation markers add to the prediction of tertiary and secondary outcomes over and beyond standard clinical measures. Determining the role of epigenetic biomarkers in primary prevention can help in identifying modifiable pathways for targeting interventions and reducing disease incidence. The potential is great for DNA methylation markers to improve cancer outcomes across the prevention continuum. Large, prospective epidemiological studies will provide essential evidence of the overall utility of adding these markers to primary prevention efforts, screening, and clinical care.

NMR (1H and 13C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect

International Nuclear Information System (INIS)

Bag, Swarnendu; Banerjee, Deb Ranjan; Basak, Amit; Das, Amit Kumar; Pal, Mousumi; Banerjee, Rita; Paul, Ranjan Rashmi; Chatterjee, Jyotirmoy

2015-01-01

At functional levels, besides genes and proteins, changes in metabolome profiles are instructive for a biological system in health and disease including malignancy. It is understood that metabolomic alterations in association with proteomic and transcriptomic aberrations are very fundamental to unravel malignant micro-ambient criticality and oral cancer is no exception. Hence deciphering intricate dimensions of oral cancer metabolism may be contributory both for integrated appreciation of its pathogenesis and to identify any critical but yet unexplored dimension of this malignancy with high mortality rate. Although several methods do exist, NMR provides higher analytical precision in identification of cancer metabolomic signature. Present study explored abnormal signatures in choline metabolism in oral squamous cell carcinoma (OSCC) using 1 H and 13 C NMR analysis of serum. It has demonstrated down-regulation of choline with concomitant up-regulation of its break-down product in the form of trimethylamine N-oxide in OSCC compared to normal counterpart. Further, no significant change in lactate profile in OSCC possibly indicated that well-known Warburg effect was not a prominent phenomenon in such malignancy. Amongst other important metabolites, malonate has shown up-regulation but D-glucose, saturated fatty acids, acetate and threonine did not show any significant change. Analyzing these metabolomic findings present study proposed trimethyl amine N-oxide and malonate as important metabolic signature for oral cancer with no prominent Warburg effect. - Highlights: • NMR ( 1 H and 13 C) study of Oral Squamous cell Carcinoma Serum. • Abnormal Choline metabolomic signatures. • Up-regulation of Trimethylamine N-oxide. • Unchanged lactate profile indicates no prominent Warburg effect. • Proposed alternative glucose metabolism path through up-regulation of malonate

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.

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...

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.

COMPUTER-IMPLEMENTED METHOD OF PERFORMING A SEARCH USING SIGNATURES

DEFF Research Database (Denmark)

2017-01-01

A computer-implemented method of processing a query vector and a data vector), comprising: generating a set of masks and a first set of multiple signatures and a second set of multiple signatures by applying the set of masks to the query vector and the data vector, respectively, and generating...... candidate pairs, of a first signature and a second signature, by identifying matches of a first signature and a second signature. The set of masks comprises a configuration of the elements that is a Hadamard code; a permutation of a Hadamard code; or a code that deviates from a Hadamard code...

Signature molecular descriptor : advanced applications.

Energy Technology Data Exchange (ETDEWEB)

Visco, Donald Patrick, Jr. (Tennessee Technological University, Cookeville, TN)

2010-04-01

In this work we report on the development of the Signature Molecular Descriptor (or Signature) for use in the solution of inverse design problems as well as in highthroughput screening applications. The ultimate goal of using Signature is to identify novel and non-intuitive chemical structures with optimal predicted properties for a given application. We demonstrate this in three studies: green solvent design, glucocorticoid receptor ligand design and the design of inhibitors for Factor XIa. In many areas of engineering, compounds are designed and/or modified in incremental ways which rely upon heuristics or institutional knowledge. Often multiple experiments are performed and the optimal compound is identified in this brute-force fashion. Perhaps a traditional chemical scaffold is identified and movement of a substituent group around a ring constitutes the whole of the design process. Also notably, a chemical being evaluated in one area might demonstrate properties very attractive in another area and serendipity was the mechanism for solution. In contrast to such approaches, computer-aided molecular design (CAMD) looks to encompass both experimental and heuristic-based knowledge into a strategy that will design a molecule on a computer to meet a given target. Depending on the algorithm employed, the molecule which is designed might be quite novel (re: no CAS registration number) and/or non-intuitive relative to what is known about the problem at hand. While CAMD is a fairly recent strategy (dating to the early 1980s), it contains a variety of bottlenecks and limitations which have prevented the technique from garnering more attention in the academic, governmental and industrial institutions. A main reason for this is how the molecules are described in the computer. This step can control how models are developed for the properties of interest on a given problem as well as how to go from an output of the algorithm to an actual chemical structure. This report

Motif signatures of transcribed enhancers

KAUST Repository

Kleftogiannis, Dimitrios

2017-09-14

In mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.

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.

Genomic scar signatures associated with homologous recombination deficiency predict adverse clinical outcomes in patients with ovarian clear cell carcinoma.

Science.gov (United States)

Chao, Angel; Lai, Chyong-Huey; Wang, Tzu-Hao; Jung, Shih-Ming; Lee, Yun-Shien; Chang, Wei-Yang; Yang, Lan-Yang; Ku, Fei-Chun; Huang, Huei-Jean; Chao, An-Shine; Wang, Chin-Jung; Chang, Ting-Chang; Wu, Ren-Chin

2018-05-03

We investigated whether genomic scar signatures associated with homologous recombination deficiency (HRD), which include telomeric allelic imbalance (TAI), large-scale transition (LST), and loss of heterozygosity (LOH), can predict clinical outcomes in patients with ovarian clear cell carcinoma (OCCC). We enrolled patients with OCCC (n = 80) and high-grade serous carcinoma (HGSC; n = 92) subjected to primary cytoreductive surgery, most of whom received platinum-based adjuvant chemotherapy. Genomic scar signatures based on genome-wide copy number data were determined in all participants and investigated in relation to prognosis. OCCC had significantly lower genomic scar signature scores than HGSC (p < 0.001). Near-triploid OCCC specimens showed higher TAI and LST scores compared with diploid tumors (p < 0.001). While high scores of these genomic scar signatures were significantly associated with better clinical outcomes in patients with HGSC, the opposite was evident for OCCC. Multivariate survival analysis in patients with OCCC identified high LOH scores as the main independent adverse predictor for both cancer-specific (hazard ratio [HR] = 3.22, p = 0.005) and progression-free survival (HR = 2.54, p = 0.01). In conclusion, genomic scar signatures associated with HRD predict adverse clinical outcomes in patients with OCCC. The LOH score was identified as the strongest prognostic indicator in this patient group. Genomic scar signatures associated with HRD are less frequent in OCCC than in HGSC. Genomic scar signatures associated with HRD have an adverse prognostic impact in patients with OCCC. LOH score is the strongest adverse prognostic factor in patients with OCCC.

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.

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.

Estimating physiological skin parameters from hyperspectral signatures

Science.gov (United States)

Vyas, Saurabh; Banerjee, Amit; Burlina, Philippe

2013-05-01

We describe an approach for estimating human skin parameters, such as melanosome concentration, collagen concentration, oxygen saturation, and blood volume, using hyperspectral radiometric measurements (signatures) obtained from in vivo skin. We use a computational model based on Kubelka-Munk theory and the Fresnel equations. This model forward maps the skin parameters to a corresponding multiband reflectance spectra. Machine-learning-based regression is used to generate the inverse map, and hence estimate skin parameters from hyperspectral signatures. We test our methods using synthetic and in vivo skin signatures obtained in the visible through the short wave infrared domains from 24 patients of both genders and Caucasian, Asian, and African American ethnicities. Performance validation shows promising results: good agreement with the ground truth and well-established physiological precepts. These methods have potential use in the characterization of skin abnormalities and in minimally-invasive prescreening of malignant skin cancers.

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...

Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures

Directory of Open Access Journals (Sweden)

Pride David T

2008-09-01

Full Text Available Abstract Background Metagenomic analysis provides a rich source of biological information for otherwise intractable viral communities. However, study of viral metagenomes has been hampered by its nearly complete reliance on BLAST algorithms for identification of DNA sequences. We sought to develop algorithms for examination of viral metagenomes to identify the origin of sequences independent of BLAST algorithms. We chose viral metagenomes obtained from two hot springs, Bear Paw and Octopus, in Yellowstone National Park, as they represent simple microbial populations where comparatively large contigs were obtained. Thermal spring metagenomes have high proportions of sequences without significant Genbank homology, which has hampered identification of viruses and their linkage with hosts. To analyze each metagenome, we developed a method to classify DNA fragments using genome signature-based phylogenetic classification (GSPC, where metagenomic fragments are compared to a database of oligonucleotide signatures for all previously sequenced Bacteria, Archaea, and viruses. Results From both Bear Paw and Octopus hot springs, each assembled contig had more similarity to other metagenome contigs than to any sequenced microbial genome based on GSPC analysis, suggesting a genome signature common to each of these extreme environments. While viral metagenomes from Bear Paw and Octopus share some similarity, the genome signatures from each locale are largely unique. GSPC using a microbial database predicts most of the Octopus metagenome has archaeal signatures, while bacterial signatures predominate in Bear Paw; a finding consistent with those of Genbank BLAST. When using a viral database, the majority of the Octopus metagenome is predicted to belong to archaeal virus Families Globuloviridae and Fuselloviridae, while none of the Bear Paw metagenome is predicted to belong to archaeal viruses. As expected, when microbial and viral databases are combined, each of

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

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

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.

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

Directory of Open Access Journals (Sweden)

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

NMR ({sup 1}H and {sup 13}C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect

Energy Technology Data Exchange (ETDEWEB)

Bag, Swarnendu, E-mail: Swarna.bag@gmail.com [School of Medical Science and Technology, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Banerjee, Deb Ranjan, E-mail: debranjan2@gmail.com [Department of Chemistry, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Basak, Amit, E-mail: absk@chem.iitkgp.ernet.in [Department of Chemistry, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Das, Amit Kumar, E-mail: amitk@hijli.iitkgp.ernet.in [Department of Biotechnology, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Pal, Mousumi, E-mail: drmpal62@gmail.com [Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Sciences and Research, Kolkata, West Bengal (India); Banerjee, Rita, E-mail: ritabanerjee@outlook.com [Department of Science and Technology, New Mehrauli Road, New Delhi 110016 (India); Paul, Ranjan Rashmi, E-mail: dr_rsspaul@yahoo.co.in [Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Sciences and Research, Kolkata, West Bengal (India); Chatterjee, Jyotirmoy, E-mail: jchatterjee.iitkgp@gmail.com [School of Medical Science and Technology, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India)

2015-04-17

At functional levels, besides genes and proteins, changes in metabolome profiles are instructive for a biological system in health and disease including malignancy. It is understood that metabolomic alterations in association with proteomic and transcriptomic aberrations are very fundamental to unravel malignant micro-ambient criticality and oral cancer is no exception. Hence deciphering intricate dimensions of oral cancer metabolism may be contributory both for integrated appreciation of its pathogenesis and to identify any critical but yet unexplored dimension of this malignancy with high mortality rate. Although several methods do exist, NMR provides higher analytical precision in identification of cancer metabolomic signature. Present study explored abnormal signatures in choline metabolism in oral squamous cell carcinoma (OSCC) using {sup 1}H and {sup 13}C NMR analysis of serum. It has demonstrated down-regulation of choline with concomitant up-regulation of its break-down product in the form of trimethylamine N-oxide in OSCC compared to normal counterpart. Further, no significant change in lactate profile in OSCC possibly indicated that well-known Warburg effect was not a prominent phenomenon in such malignancy. Amongst other important metabolites, malonate has shown up-regulation but D-glucose, saturated fatty acids, acetate and threonine did not show any significant change. Analyzing these metabolomic findings present study proposed trimethyl amine N-oxide and malonate as important metabolic signature for oral cancer with no prominent Warburg effect. - Highlights: • NMR ({sup 1}H and {sup 13}C) study of Oral Squamous cell Carcinoma Serum. • Abnormal Choline metabolomic signatures. • Up-regulation of Trimethylamine N-oxide. • Unchanged lactate profile indicates no prominent Warburg effect. • Proposed alternative glucose metabolism path through up-regulation of malonate.

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.

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

Science.gov (United States)

Robertson, A Gordon; Kim, Jaegil; Al-Ahmadie, Hikmat; Bellmunt, Joaquim; Guo, Guangwu; Cherniack, Andrew D; Hinoue, Toshinori; Laird, Peter W; Hoadley, Katherine A; Akbani, Rehan; Castro, Mauro A A; Gibb, Ewan A; Kanchi, Rupa S; Gordenin, Dmitry A; Shukla, Sachet A; Sanchez-Vega, Francisco; Hansel, Donna E; Czerniak, Bogdan A; Reuter, Victor E; Su, Xiaoping; de Sa Carvalho, Benilton; Chagas, Vinicius S; Mungall, Karen L; Sadeghi, Sara; Pedamallu, Chandra Sekhar; Lu, Yiling; Klimczak, Leszek J; Zhang, Jiexin; Choo, Caleb; Ojesina, Akinyemi I; Bullman, Susan; Leraas, Kristen M; Lichtenberg, Tara M; Wu, Catherine J; Schultz, Nicholaus; Getz, Gad; Meyerson, Matthew; Mills, Gordon B; McConkey, David J; Weinstein, John N; Kwiatkowski, David J; Lerner, Seth P

2017-10-19

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments. Copyright © 2017 Elsevier Inc. All rights reserved.

LAVA: An Open-Source Approach To Designing LAMP (Loop-Mediated Isothermal Amplification DNA Signatures

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Gardner Shea N

2011-06-01

Full Text Available Abstract Background We developed an extendable open-source Loop-mediated isothermal AMPlification (LAMP signature design program called LAVA (LAMP Assay Versatile Analysis. LAVA was created in response to limitations of existing LAMP signature programs. Results LAVA identifies combinations of six primer regions for basic LAMP signatures, or combinations of eight primer regions for LAMP signatures with loop primers, which can be used as LAMP signatures. The identified primers are conserved among target organism sequences. Primer combinations are optimized based on lengths, melting temperatures, and spacing among primer sites. We compare LAMP signature candidates for Staphylococcus aureus created both by LAVA and by PrimerExplorer. We also include signatures from a sample run targeting all strains of Mycobacterium tuberculosis. Conclusions We have designed and demonstrated new software for identifying signature candidates appropriate for LAMP assays. The software is available for download at http://lava-dna.googlecode.com/.

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

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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.

Deregulation of MiR-34b/Sox2 Predicts Prostate Cancer Progression.

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Irene Forno

Full Text Available Most men diagnosed with prostate cancer will have an indolent and curable disease, whereas approximately 15% of these patients will rapidly progress to a castrate-resistant and metastatic stage with high morbidity and mortality. Therefore, the identification of molecular signature(s that detect men at risk of progressing disease remains a pressing and still unmet need for these patients. Here, we used an integrated discovery platform combining prostate cancer cell lines, a Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP model and clinically-annotated human tissue samples to identify loss of expression of microRNA-34b as consistently associated with prostate cancer relapse. Mechanistically, this was associated with epigenetics silencing of the MIR34B/C locus and increased DNA copy number loss, selectively in androgen-dependent prostate cancer. In turn, loss of miR-34b resulted in downstream deregulation and overexpression of the "stemness" marker, Sox2. These findings identify loss of miR-34b as a robust biomarker for prostate cancer progression in androgen-sensitive tumors, and anticipate a potential role of progenitor/stem cell signaling in this stage of disease.

Deregulation of MiR-34b/Sox2 Predicts Prostate Cancer Progression.

Science.gov (United States)

Forno, Irene; Ferrero, Stefano; Russo, Maria Veronica; Gazzano, Giacomo; Giangiobbe, Sara; Montanari, Emanuele; Del Nero, Alberto; Rocco, Bernardo; Albo, Giancarlo; Languino, Lucia R; Altieri, Dario C; Vaira, Valentina; Bosari, Silvano

2015-01-01

Most men diagnosed with prostate cancer will have an indolent and curable disease, whereas approximately 15% of these patients will rapidly progress to a castrate-resistant and metastatic stage with high morbidity and mortality. Therefore, the identification of molecular signature(s) that detect men at risk of progressing disease remains a pressing and still unmet need for these patients. Here, we used an integrated discovery platform combining prostate cancer cell lines, a Transgenic Adenocarcinoma of the Mouse Prostate (TRAMP) model and clinically-annotated human tissue samples to identify loss of expression of microRNA-34b as consistently associated with prostate cancer relapse. Mechanistically, this was associated with epigenetics silencing of the MIR34B/C locus and increased DNA copy number loss, selectively in androgen-dependent prostate cancer. In turn, loss of miR-34b resulted in downstream deregulation and overexpression of the "stemness" marker, Sox2. These findings identify loss of miR-34b as a robust biomarker for prostate cancer progression in androgen-sensitive tumors, and anticipate a potential role of progenitor/stem cell signaling in this stage of disease.

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...

MicroRNA signature characterizes primary tumors that metastasize in an esophageal adenocarcinoma rat model.

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Ali H Zaidi

Full Text Available To establish a miRNA signature for metastasis in an animal model of esophageal adenocarcinoma (EAC.The incidence of esophageal adenocarcinoma (EAC has dramatically increased and esophageal cancer is now the sixth leading cause of cancer deaths worldwide. Mortality rates remain high among patients with advanced stage disease and esophagectomy is associated with high complication rates. Hence, early identification of potentially metastatic disease would better guide treatment strategies.The modified Levrat's surgery was performed to induce EAC in Sprague-Dawley rats. Primary EAC and distant metastatic sites were confirmed via histology and immunofluorescence. miRNA profiling was performed on primary tumors with or without metastasis. A unique subset of miRNAs expressed in primary tumors and metastases was identified with Ingenuity Pathway Analysis (IPA along with upstream and downstream targets. miRNA-linked gene expression analysis was performed on a secondary cohort of metastasis positive (n=5 and metastasis negative (n=28 primary tumors.The epithelial origin of distant metastasis was established by IF using villin (VIL1 and mucin 5AC (MUC5AC antibodies. miRNome analysis identified four down-regulated miRNAs in metastasis positive primary tumors compared to metastasis negative tumors: miR-92a-3p (p=0.0001, miR-141-3p (p=0.0022, miR-451-1a (p=0.0181 and miR133a-3p (p=0.0304. Six target genes identified in the top scoring networks by IPA were validated as significantly, differentially expressed in metastasis positive primary tumors: Ago2, Akt1, Kras, Bcl2L11, CDKN1B and Zeb2.In vivo metastasis was confirmed in the modified Levrat's model. Analysis of the primary tumor identified a distinctive miRNA signature for primary tumors that metastasized.

Methylation of cancer-stem-cell-associated Wnt target genes predicts poor prognosis in colorectal cancer patients

NARCIS (Netherlands)

de Sousa E Melo, Felipe; Colak, Selcuk; Buikhuisen, Joyce; Koster, Jan; Cameron, Kate; de Jong, Joan H.; Tuynman, Jurriaan B.; Prasetyanti, Pramudita R.; Fessler, Evelyn; van den Bergh, Saskia P.; Rodermond, Hans; Dekker, Evelien; van der Loos, Chris M.; Pals, Steven T.; van de Vijver, Marc J.; Versteeg, Rogier; Richel, Dick J.; Vermeulen, Louis; Medema, Jan Paul

2011-01-01

Gene signatures derived from cancer stem cells (CSCs) predict tumor recurrence for many forms of cancer. Here, we derived a gene signature for colorectal CSCs defined by high Wnt signaling activity, which in agreement with previous observations predicts poor prognosis. Surprisingly, however, we

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

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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.

Observation of a 27-day solar signature in noctilucent cloud altitude

Science.gov (United States)

Köhnke, Merlin C.; von Savigny, Christian; Robert, Charles E.

2018-05-01

Previous studies have identified solar 27-day signatures in several parameters in the Mesosphere/Lower thermosphere region, including temperature and Noctilucent cloud (NLC) occurrence frequency. In this study we report on a solar 27-day signature in NLC altitude with peak-to-peak variations of about 400 m. We use SCIAMACHY limb-scatter observations from 2002 to 2012 to detect NLCs. The superposed epoch analysis method is applied to extract solar 27-day signatures. A 27-day signature in NLC altitude can be identified in both hemispheres in the SCIAMACHY dataset, but the signature is more pronounced in the northern hemisphere. The solar signature in NLC altitude is found to be in phase with solar activity and temperature for latitudes ≳ 70 ° N. We provide a qualitative explanation for the positive correlation between solar activity and NLC altitude based on published model simulations.

Molecular signature of the radioinduction in the thyroid tumors developed after radiotherapy

International Nuclear Information System (INIS)

Mallard, Ch.

2005-10-01

Several epidemiological studies enlightens an increase of the number of thyroid cancers among children and adolescents exposed to ionizing radiation after an internal exposure ( Chernobylsk accident) or external one as a radiotherapy. No increase arose for adults.The analysis of the transcriptome was realised with micro arrays prepared on the genomic platform of the Cea at Evry that allow to study simultaneously the expression of 6000 genes. this study allows to enlighten a signature of radioinduction constituted by series of genes specifically expressed in one or other type of cancer in function of its etiology. This signature includes 59 genes expressed differentially between the sporadic carcinomas and 45 genes in the case of adenomas. with this signature an analysis in principal components allowed to determine correctly the etiology of 12 tumors among 13, the etiology of a sporadic adenoma was not determined. Besides, the study of the expression of genes specific to thyroid (TSHR, TG, TPO, TTF1, TTF2, PAX8) in relation with the presence of arrangements RET/PTC or mutations of BRAF was made. It allowed to enlighten the loss of TPO expression in the cancers changed for BRAF as well as a new mechanism of BRAF activation. (N.C.)

Bronchial airway gene expression in smokers with lung or head and neck cancer

International Nuclear Information System (INIS)

Van Dyck, Eric; Nazarov, Petr V; Muller, Arnaud; Nicot, Nathalie; Bosseler, Manon; Pierson, Sandrine; Van Moer, Kris; Palissot, Valérie; Mascaux, Céline; Knolle, Ulrich; Ninane, Vincent; Nati, Romain; Bremnes, Roy M; Vallar, Laurent; Berchem, Guy; Schlesser, Marc

2014-01-01

Cigarette smoking is the major cause of cancers of the respiratory tract, including non-small cell lung cancer (NSCLC) and head and neck cancer (HNC). In order to better understand carcinogenesis of the lung and upper airways, we have compared the gene expression profiles of tumor-distant, histologically normal bronchial biopsy specimens obtained from current smokers with NSCLC or HNC (SC, considered as a single group), as well as nonsmokers (NS) and smokers without cancer (SNC). RNA from a total of 97 biopsies was used for gene expression profiling (Affymetrix HG-U133 Plus 2.0 array). Differentially expressed genes were used to compare NS, SNC, and SC, and functional analysis was carried out using Ingenuity Pathway Analysis (IPA). Smoking-related cancer of the respiratory tract was found to affect the expression of genes encoding xenobiotic biotransformation proteins, as well as proteins associated with crucial inflammation/immunity pathways and other processes that protect the airway from the chemicals in cigarette smoke or contribute to carcinogenesis. Finally, we used the prediction analysis for microarray (PAM) method to identify gene signatures of cigarette smoking and cancer, and uncovered a 15-gene signature that distinguished between SNC and SC with an accuracy of 83%. Thus, gene profiling of histologically normal bronchial biopsy specimens provided insight into cigarette-induced carcinogenesis of the respiratory tract and gene signatures of cancer in smokers

Circulating neutrophil transcriptome may reveal intracranial aneurysm signature.

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Vincent M Tutino

Full Text Available Unruptured intracranial aneurysms (IAs are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs.Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts.Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (p<0.05, fold-change ≥2. This signature was able to separate patients with and without IAs on hierarchical clustering. Furthermore, in an independent, unpaired, replication cohort of patients with IAs (n = 5 and controls (n = 5, the 82 transcripts separated 9 of 10 patients into their respective groups.Preliminary findings show that RNA expression from circulating neutrophils carries an IA-associated signature. These findings highlight a potential to use predictive biomarkers from peripheral blood samples to identify patients with IAs.

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

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...

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.

Plasma Signatures of Radial Field Power Dropouts

International Nuclear Information System (INIS)

Lucek, E.A.; Horbury, T.S.; Balogh, A.; McComas, D.J.

1998-01-01

A class of small scale structures, with a near-radial magnetic field and a drop in magnetic field fluctuation power, have recently been identified in the polar solar wind. An earlier study of 24 events, each lasting for 6 hours or more, identified no clear plasma signature. In an extension of that work, radial intervals lasting for 4 hours or more (89 in total), have been used to search for a statistically significant plasma signature. It was found that, despite considerable variations between intervals, there was a small but significant drop, on average, in plasma temperature, density and β during these events

Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

Directory of Open Access Journals (Sweden)

Xi Wang

2015-05-01

Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

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.

A Semi-Supervised Approach for Refining Transcriptional Signatures of Drug Response and Repositioning Predictions.

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Francesco Iorio

Full Text Available We present a novel strategy to identify drug-repositioning opportunities. The starting point of our method is the generation of a signature summarising the consensual transcriptional response of multiple human cell lines to a compound of interest (namely the seed compound. This signature can be derived from data in existing databases, such as the connectivity-map, and it is used at first instance to query a network interlinking all the connectivity-map compounds, based on the similarity of their transcriptional responses. This provides a drug neighbourhood, composed of compounds predicted to share some effects with the seed one. The original signature is then refined by systematically reducing its overlap with the transcriptional responses induced by drugs in this neighbourhood that are known to share a secondary effect with the seed compound. Finally, the drug network is queried again with the resulting refined signatures and the whole process is carried on for a number of iterations. Drugs in the final refined neighbourhood are then predicted to exert the principal mode of action of the seed compound. We illustrate our approach using paclitaxel (a microtubule stabilising agent as seed compound. Our method predicts that glipizide and splitomicin perturb microtubule function in human cells: a result that could not be obtained through standard signature matching methods. In agreement, we find that glipizide and splitomicin reduce interphase microtubule growth rates and transiently increase the percentage of mitotic cells-consistent with our prediction. Finally, we validated the refined signatures of paclitaxel response by mining a large drug screening dataset, showing that human cancer cell lines whose basal transcriptional profile is anti-correlated to them are significantly more sensitive to paclitaxel and docetaxel.

Comparison of a gene expression profiling strategy to standard clinical work-up for determination of tumour origin in cancer of unknown primary (CUP)

DEFF Research Database (Denmark)

Ades, Felipe; de Azambuja, Evandro; Daugaard, Gedske

2013-01-01

CupPrint® is a genomic signature able to identify 47 different cancer types. The aim of our study was to compare the accuracy of this genomic signature to that of a full clinical work-up in diagnosing the primary tumour site. Patients with newly diagnosed, untreated metastatic tumours were eligible...

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

Characteristics and Validation Techniques for PCA-Based Gene-Expression Signatures

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Anders E. Berglund

2017-01-01

Full Text Available Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified.

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.

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.

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.

Signature-based User Authentication

OpenAIRE

Hámorník, Juraj

2015-01-01

This work aims on missing handwritten signature authentication in Windows. Result of this work is standalone software that allow users to log into Windows by writing signature. We focus on security of signature authentification and best overall user experience. We implemented signature authentification service that accept signature and return user access token if signature is genuine. Signature authentification is done by comparing given signature to signature patterns by their similarity. Si...

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.

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....

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

Identifying molecular targets of lifestyle modifications in colon cancer prevention

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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.

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

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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.

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

Genome-scale mutational signatures of aflatoxin in cells, mice, and human tumors

Science.gov (United States)

Huang, Mi Ni; Yu, Willie; Teoh, Wei Wei; Ardin, Maude; Jusakul, Apinya; Ng, Alvin Wei Tian; Boot, Arnoud; Abedi-Ardekani, Behnoush; Villar, Stephanie; Myint, Swe Swe; Othman, Rashidah; Poon, Song Ling; Heguy, Adriana; Olivier, Magali; Hollstein, Monica; Tan, Patrick; Teh, Bin Tean; Sabapathy, Kanaga; Zavadil, Jiri; Rozen, Steven G.

2017-01-01

Aflatoxin B1 (AFB1) is a mutagen and IARC (International Agency for Research on Cancer) Group 1 carcinogen that causes hepatocellular carcinoma (HCC). Here, we present the first whole-genome data on the mutational signatures of AFB1 exposure from a total of >40,000 mutations in four experimental systems: two different human cell lines, in liver tumors in wild-type mice, and in mice that carried a hepatitis B surface antigen transgene—this to model the multiplicative effects of aflatoxin exposure and hepatitis B in causing HCC. AFB1 mutational signatures from all four experimental systems were remarkably similar. We integrated the experimental mutational signatures with data from newly sequenced HCCs from Qidong County, China, a region of well-studied aflatoxin exposure. This indicated that COSMIC mutational signature 24, previously hypothesized to stem from aflatoxin exposure, indeed likely represents AFB1 exposure, possibly combined with other exposures. Among published somatic mutation data, we found evidence of AFB1 exposure in 0.7% of HCCs treated in North America, 1% of HCCs from Japan, but 16% of HCCs from Hong Kong. Thus, aflatoxin exposure apparently remains a substantial public health issue in some areas. This aspect of our study exemplifies the promise of future widespread resequencing of tumor genomes in providing new insights into the contribution of mutagenic exposures to cancer incidence. PMID:28739859

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

Science.gov (United States)

Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

2010-06-30

Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

Directory of Open Access Journals (Sweden)

Paweletz Cloud

2010-06-01

Full Text Available Abstract Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90% sensitivity but relatively low (50% specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical

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

Circulating neutrophil transcriptome may reveal intracranial aneurysm signature

Science.gov (United States)

Tutino, Vincent M.; Poppenberg, Kerry E.; Jiang, Kaiyu; Jarvis, James N.; Sun, Yijun; Sonig, Ashish; Siddiqui, Adnan H.; Snyder, Kenneth V.; Levy, Elad I.; Kolega, John

2018-01-01

Background Unruptured intracranial aneurysms (IAs) are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs. Methods Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts. Results Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (pIAs on hierarchical clustering. Furthermore, in an independent, unpaired, replication cohort of patients with IAs (n = 5) and controls (n = 5), the 82 transcripts separated 9 of 10 patients into their respective groups. Conclusion Preliminary findings show that RNA expression from circulating neutrophils carries an IA-associated signature. These findings highlight a potential to use predictive biomarkers from peripheral blood samples to identify patients with IAs. PMID:29342213

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

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

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...

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

Proteomic analysis of bronchoalveolar lavage fluid (BALF from lung cancer patients using label-free mass spectrometry

Directory of Open Access Journals (Sweden)

Abduladim Hmmier

2017-06-01

General significance: There is good correlation between the trend of protein abundance levels in BALF and that of plasma which validates this approach to develop a blood biomarker to aid lung cancer diagnosis, particularly in the era of lung cancer screening. The protein signatures identified also provide insight into the molecular mechanisms associated with lung malignancy.

Real Traceable Signatures

Science.gov (United States)

Chow, Sherman S. M.

Traceable signature scheme extends a group signature scheme with an enhanced anonymity management mechanism. The group manager can compute a tracing trapdoor which enables anyone to test if a signature is signed by a given misbehaving user, while the only way to do so for group signatures requires revealing the signer of all signatures. Nevertheless, it is not tracing in a strict sense. For all existing schemes, T tracing agents need to recollect all N' signatures ever produced and perform RN' “checks” for R revoked users. This involves a high volume of transfer and computations. Increasing T increases the degree of parallelism for tracing but also the probability of “missing” some signatures in case some of the agents are dishonest.

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

Science.gov (United States)

Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L

2008-08-15

The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

Matrigel Basement Membrane Matrix influences expression of microRNAs in cancer cell lines

International Nuclear Information System (INIS)

Price, Karina J.; Tsykin, Anna; Giles, Keith M.; Sladic, Rosemary T.; Epis, Michael R.; Ganss, Ruth; Goodall, Gregory J.; Leedman, Peter J.

2012-01-01

Highlights: ► Matrigel alters cancer cell line miRNA expression relative to culture on plastic. ► Many identified Matrigel-regulated miRNAs are implicated in cancer. ► miR-1290, -210, -32 and -29b represent a Matrigel-induced miRNA signature. ► miR-32 down-regulates Integrin alpha 5 (ITGA5) mRNA. -- Abstract: Matrigel is a medium rich in extracellular matrix (ECM) components used for three-dimensional cell culture and is known to alter cellular phenotypes and gene expression. microRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression and have roles in cancer. While miRNA profiles of numerous cell lines cultured on plastic have been reported, the influence of Matrigel-based culture on cancer cell miRNA expression is largely unknown. This study investigated the influence of Matrigel on the expression of miRNAs that might facilitate ECM-associated cancer cell growth. We performed miRNA profiling by microarray using two colon cancer cell lines (SW480 and SW620), identifying significant differential expression of miRNAs between cells cultured in Matrigel and on plastic. Many of these miRNAs have previously been implicated in cancer-related processes. A common Matrigel-induced miRNA signature comprised of up-regulated miR-1290 and miR-210 and down-regulated miR-29b and miR-32 was identified using RT-qPCR across five epithelial cancer cell lines (SW480, SW620, HT-29, A549 and MDA-MB-231). Experimental modulation of these miRNAs altered expression of their known target mRNAs involved in cell adhesion, proliferation and invasion, in colon cancer cell lines. Furthermore, ITGA5 was identified as a novel putative target of miR-32 that may facilitate cancer cell interactions with the ECM. We propose that culture of cancer cell lines in Matrigel more accurately recapitulates miRNA expression and function in cancer than culture on plastic and thus is a valuable approach to the in vitro study of miRNAs.

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

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...

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

Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma.

Science.gov (United States)

Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng

2017-09-29

Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

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

A DNA methylation-based definition of biologically distinct breast cancer subtypes.

Science.gov (United States)

Stefansson, Olafur A; Moran, Sebastian; Gomez, Antonio; Sayols, Sergi; Arribas-Jorba, Carlos; Sandoval, Juan; Hilmarsdottir, Holmfridur; Olafsdottir, Elinborg; Tryggvadottir, Laufey; Jonasson, Jon G; Eyfjord, Jorunn; Esteller, Manel

2015-03-01

In cancer, epigenetic states are deregulated and thought to be of significance in cancer development and progression. We explored DNA methylation-based signatures in association with breast cancer subtypes to assess their impact on clinical presentation and patient prognosis. DNA methylation was analyzed using Infinium 450K arrays in 40 tumors and 17 normal breast samples, together with DNA copy number changes and subtype-specific markers by tissue microarrays. The identified methylation signatures were validated against a cohort of 212 tumors annotated for breast cancer subtypes by the PAM50 method (The Cancer Genome Atlas). Selected markers were pyrosequenced in an independent validation cohort of 310 tumors and analyzed with respect to survival, clinical stage and grade. The results demonstrate that DNA methylation patterns linked to the luminal-B subtype are characterized by CpG island promoter methylation events. In contrast, a large fraction of basal-like tumors are characterized by hypomethylation events occurring within the gene body. Based on these hallmark signatures, we defined two DNA methylation-based subtypes, Epi-LumB and Epi-Basal, and show that they are associated with unfavorable clinical parameters and reduced survival. Our data show that distinct mechanisms leading to changes in CpG methylation states are operative in different breast cancer subtypes. Importantly, we show that a few selected proxy markers can be used to detect the distinct DNA methylation-based subtypes thereby providing valuable information on disease prognosis. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

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.

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

Directory of Open Access Journals (Sweden)

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.

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies.

Science.gov (United States)

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K -means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups.

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

Science.gov (United States)

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.

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.

Field Education as the Signature Pedagogy of Social Work Education

Science.gov (United States)

Wayne, Julianne; Bogo, Marion; Raskin, Miriam

2010-01-01

In its EPAS, CSWE (2008) identifies field education as the signature pedagogy (Shulman, 2005b) of social work education. This article analyzes the field education-signature pedagogy fit. It finds congruence in selected organizational arrangements that are pervasive and routine, and disparities with respect to expectations about public student…

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

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

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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

Some Proxy Signature and Designated verifier Signature Schemes over Braid Groups

OpenAIRE

Lal, Sunder; Verma, Vandani

2009-01-01

Braids groups provide an alternative to number theoretic public cryptography and can be implemented quite efficiently. The paper proposes five signature schemes: Proxy Signature, Designated Verifier, Bi-Designated Verifier, Designated Verifier Proxy Signature And Bi-Designated Verifier Proxy Signature scheme based on braid groups. We also discuss the security aspects of each of the proposed schemes.

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.

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

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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

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.

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....

EMT is the dominant program in human colon cancer

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Tollenaar Rob AEM

2011-01-01

Full Text Available Abstract Background Colon cancer has been classically described by clinicopathologic features that permit the prediction of outcome only after surgical resection and staging. Methods We performed an unsupervised analysis of microarray data from 326 colon cancers to identify the first principal component (PC1 of the most variable set of genes. PC1 deciphered two primary, intrinsic molecular subtypes of colon cancer that predicted disease progression and recurrence. Results Here we report that the most dominant pattern of intrinsic gene expression in colon cancer (PC1 was tightly correlated (Pearson R = 0.92, P -135 with the EMT signature-- both in gene identity and directionality. In a global micro-RNA screen, we further identified the most anti-correlated microRNA with PC1 as MiR200, known to regulate EMT. Conclusions These data demonstrate that the biology underpinning the native, molecular classification of human colon cancer--previously thought to be highly heterogeneous-- was clarified through the lens of comprehensive transcriptome analysis.

Molecular signatures for the Crenarchaeota and the Thaumarchaeota.

Science.gov (United States)

Gupta, Radhey S; Shami, Ali

2011-02-01

Crenarchaeotes found in mesophilic marine environments were recently placed into a new phylum of Archaea called the Thaumarchaeota. However, very few molecular characteristics of this new phylum are currently known which can be used to distinguish them from the Crenarchaeota. In addition, their relationships to deep-branching archaeal lineages are unclear. We report here detailed analyses of protein sequences from Crenarchaeota and Thaumarchaeota that have identified many conserved signature indels (CSIs) and signature proteins (SPs) (i.e., proteins for which all significant blast hits are from these groups) that are specific for these archaeal groups. Of the identified signatures 6 CSIs and 13 SPs are specific for the Crenarchaeota phylum; 6 CSIs and >250 SPs are uniquely found in various Thaumarchaeota (viz. Cenarchaeum symbiosum, Nitrosopumilus maritimus and a number of uncultured marine crenarchaeotes) and 3 CSIs and ~10 SPs are found in both Thaumarchaeota and Crenarchaeota species. Some of the molecular signatures are also present in Korarchaeum cryptofilum, which forms the independent phylum Korarchaeota. Although some of these molecular signatures suggest a distant shared ancestry between Thaumarchaeota and Crenarchaeota, our identification of large numbers of Thaumarchaeota-specific proteins and their deep branching between the Crenarchaeota and Euryarchaeota phyla in phylogenetic trees shows that they are distinct from both Crenarchaeota and Euryarchaeota in both genetic and phylogenetic terms. These observations support the placement of marine mesophilic archaea into the separate phylum Thaumarchaeota. Additionally, many CSIs and SPs have been found that are specific for different orders within Crenarchaeota (viz. Sulfolobales-3 CSIs and 169 SPs, Thermoproteales-5 CSIs and 25 SPs, Desulfurococcales-4 SPs, and Sulfolobales and Desulfurococcales-2 CSIs and 18 SPs). The signatures described here provide novel means for distinguishing the Crenarchaeota and

Detection of colorectal cancer (CRC by urinary volatile organic compound analysis.

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Ramesh P Arasaradnam

Full Text Available Colorectal cancer (CRC is a leading cause of cancer related death in Europe and the USA. There is no universally accepted effective non-invasive screening test for CRC. Guaiac based faecal occult blood (gFOB testing has largely been superseded by Faecal Immunochemical testing (FIT, but sensitivity still remains poor. The uptake of population based FOBt testing in the UK is also low at around 50%. The detection of volatile organic compounds (VOCs signature(s for many cancer subtypes is receiving increasing interest using a variety of gas phase analytical instruments. One such example is FAIMS (Field Asymmetric Ion Mobility Spectrometer. FAIMS is able to identify Inflammatory Bowel disease (IBD patients by analysing shifts in VOCs patterns in both urine and faeces. This study extends this concept to determine whether CRC patients can be identified through non-invasive analysis of urine, using FAIMS. 133 patients were recruited; 83 CRC patients and 50 healthy controls. Urine was collected at the time of CRC diagnosis and headspace analysis undertaken using a FAIMS instrument (Owlstone, Lonestar, UK. Data was processed using Fisher Discriminant Analysis (FDA after feature extraction from the raw data. FAIMS analyses demonstrated that the VOC profiles of CRC patients were tightly clustered and could be distinguished from healthy controls. Sensitivity and specificity for CRC detection with FAIMS were 88% and 60% respectively. This study suggests that VOC signatures emanating from urine can be detected in patients with CRC using ion mobility spectroscopy technology (FAIMS with potential as a novel screening tool.

Detection of colorectal cancer (CRC) by urinary volatile organic compound analysis.

Science.gov (United States)

Arasaradnam, Ramesh P; McFarlane, Michael J; Ryan-Fisher, Courtenay; Westenbrink, Erik; Hodges, Phoebe; Hodges, Paula; Thomas, Matthew G; Chambers, Samantha; O'Connell, Nicola; Bailey, Catherine; Harmston, Christopher; Nwokolo, Chuka U; Bardhan, Karna D; Covington, James A

2014-01-01

Colorectal cancer (CRC) is a leading cause of cancer related death in Europe and the USA. There is no universally accepted effective non-invasive screening test for CRC. Guaiac based faecal occult blood (gFOB) testing has largely been superseded by Faecal Immunochemical testing (FIT), but sensitivity still remains poor. The uptake of population based FOBt testing in the UK is also low at around 50%. The detection of volatile organic compounds (VOCs) signature(s) for many cancer subtypes is receiving increasing interest using a variety of gas phase analytical instruments. One such example is FAIMS (Field Asymmetric Ion Mobility Spectrometer). FAIMS is able to identify Inflammatory Bowel disease (IBD) patients by analysing shifts in VOCs patterns in both urine and faeces. This study extends this concept to determine whether CRC patients can be identified through non-invasive analysis of urine, using FAIMS. 133 patients were recruited; 83 CRC patients and 50 healthy controls. Urine was collected at the time of CRC diagnosis and headspace analysis undertaken using a FAIMS instrument (Owlstone, Lonestar, UK). Data was processed using Fisher Discriminant Analysis (FDA) after feature extraction from the raw data. FAIMS analyses demonstrated that the VOC profiles of CRC patients were tightly clustered and could be distinguished from healthy controls. Sensitivity and specificity for CRC detection with FAIMS were 88% and 60% respectively. This study suggests that VOC signatures emanating from urine can be detected in patients with CRC using ion mobility spectroscopy technology (FAIMS) with potential as a novel screening tool.

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.

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.

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.

Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk.

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Evangelina López de Maturana

Full Text Available The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL, a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.

Methyl-CpG island-associated genome signature tags

Science.gov (United States)

Dunn, John J

2014-05-20

Disclosed is a method for analyzing the organismic complexity of a sample through analysis of the nucleic acid in the sample. In the disclosed method, through a series of steps, including digestion with a type II restriction enzyme, ligation of capture adapters and linkers and digestion with a type IIS restriction enzyme, genome signature tags are produced. The sequences of a statistically significant number of the signature tags are determined and the sequences are used to identify and quantify the organisms in the sample. Various embodiments of the invention described herein include methods for using single point genome signature tags to analyze the related families present in a sample, methods for analyzing sequences associated with hyper- and hypo-methylated CpG islands, methods for visualizing organismic complexity change in a sampling location over time and methods for generating the genome signature tag profile of a sample of fragmented DNA.

SIGNATURE: A workbench for gene expression signature analysis

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Chang Jeffrey T

2011-11-01

Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for gene expression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies gene expression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing gene expression data coupled with a curated database of gene expression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

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

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

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

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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.

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

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

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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.

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.

KEA-71 Smart Current Signature Sensor (SCSS)

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Perotti, Jose M.

2010-01-01

This slide presentation reviews the development and uses of the Smart Current Signature Sensor (SCSS), also known as the Valve Health Monitor (VHM) system. SCSS provides a way to not only monitor real-time the valve's operation in a non invasive manner, but also to monitor its health (Fault Detection and Isolation) and identify potential faults and/or degradation in the near future (Prediction/Prognosis). This technology approach is not only applicable for solenoid valves, and it could be extrapolated to other electrical components with repeatable electrical current signatures such as motors.

Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

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Nolan Priedigkeit

2015-02-01

Full Text Available Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC, is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting "disease map" network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.

Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis.

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Nigel P S Crawford

2007-11-01

Full Text Available A novel candidate metastasis modifier, ribosomal RNA processing 1 homolog B (Rrp1b, was identified through two independent approaches. First, yeast two-hybrid, immunoprecipitation, and functional assays demonstrated a physical and functional interaction between Rrp1b and the previous identified metastasis modifier Sipa1. In parallel, using mouse and human metastasis gene expression data it was observed that extracellular matrix (ECM genes are common components of metastasis predictive signatures, suggesting that ECM genes are either important markers or causal factors in metastasis. To investigate the relationship between ECM genes and poor prognosis in breast cancer, expression quantitative trait locus analysis of polyoma middle-T transgene-induced mammary tumor was performed. ECM gene expression was found to be consistently associated with Rrp1b expression. In vitro expression of Rrp1b significantly altered ECM gene expression, tumor growth, and dissemination in metastasis assays. Furthermore, a gene signature induced by ectopic expression of Rrp1b in tumor cells predicted survival in a human breast cancer gene expression dataset. Finally, constitutional polymorphism within RRP1B was found to be significantly associated with tumor progression in two independent breast cancer cohorts. These data suggest that RRP1B may be a novel susceptibility gene for breast cancer progression and metastasis.

Chromosomal instability as a prognostic marker in cervical cancer

International Nuclear Information System (INIS)

How, Christine; Bruce, Jeff; So, Jonathan; Pintilie, Melania; Haibe-Kains, Benjamin; Hui, Angela; Clarke, Blaise A; Hedley, David W; Hill, Richard P; Milosevic, Michael; Fyles, Anthony; Liu, Fei-Fei

2015-01-01

Cervical cancer is the third most common cancer in women globally, and despite treatment, distant metastasis and nodal recurrence will still develop in approximately 30% of patients. The ability to predict which patients are likely to experience distant relapse would allow clinicians to better tailor treatment. Previous studies have investigated the role of chromosomal instability (CIN) in cancer, which can promote tumour initiation and growth; a hallmark of human malignancies. In this study, we sought to examine the published CIN70 gene signature in a cohort of cervical cancer patients treated at the Princess Margaret (PM) Cancer Centre and an independent cohort of The Cancer Genome Atlas (TCGA) cervical cancer patients, to determine if this CIN signature associated with patient outcome. Cervical cancer samples were collected from 79 patients, treated between 2000–2007 at the PM, prior to undergoing curative chemo-radiation. Total RNA was extracted from each patient sample and analyzed using the GeneChip Human Genome U133 Plus 2.0 array (Affymetrix). High CIN70 scores were significantly related to increased chromosomal alterations in TCGA cervical cancer patients, including a higher percentage of genome altered and a higher number of copy number alterations. In addition, this same CIN70 signature was shown to be predictive of para-aortic nodal relapse in the PM Cancer Centre cohort. These findings demonstrate that chromosomal instability plays an important role in cervical cancer, and is significantly associated with patient outcome. For the first time, this CIN70 gene signature provided prognostic value for patients with cervical cancer

Molecular Signature and Mechanisms of Hepatitis D Virus-Associated Hepatocellular Carcinoma.

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Diaz, Giacomo; Engle, Ronald E; Tice, Ashley; Melis, Marta; Montenegro, Stephanie; Rodriguez-Canales, Jaime; Hanson, Jeffrey; Emmert-Buck, Michael R; Bock, Kevin W; Moore, Ian N; Zamboni, Fausto; Govindarajan, Sugantha; Kleiner, David; Farci, Patrizia

2018-06-01

There is limited data on the molecular mechanisms whereby hepatitis D virus (HDV) promotes liver cancer. Therefore, serum and liver specimens obtained at the time of liver transplantation from well-characterized patients with HDV-HCC (n-5) and with non-HCC HDV cirrhosis (n=7) were studied using an integrated genomic approach. Transcriptomic profiling was performed using laser capture-microdissected (LCM) malignant and non-malignant hepatocytes, tumorous and non-tumorous liver tissue from patients with HDV-HCC, and liver tissue from patients with non-HCC HDV cirrhosis. HDV-HCC was also compared with hepatitis B virus (HBV) HBV-HCC alone and hepatitis C virus (HCV) HCV-HCC. HDV malignant hepatocytes were characterized by an enrichment of up-regulated transcripts associated with pathways involved in cell cycle/DNA replication, damage and repair (sonic hedgehog, GADD45, DNA-damage-induced 14-3-3σ, cyclins and cell cycle regulation, cell cycle: G2/M DNA-damage checkpoint regulation, and hereditary breast cancer). Moreover, a large network of genes identified functionally relate to DNA repair, cell cycle, mitotic apparatus and cell division, including 4 cancer testis antigen genes, attesting to the critical role of genetic instability in this tumor. Besides being over-expressed, these genes were also strongly co-regulated. Gene co-regulation was high not only when compared to non-malignant hepatocytes, but also to malignant hepatocytes from HBV-HCC alone or HCV-HCC. Activation and co-regulation of genes critically associated with DNA replication, damage, and repair point to genetic instability as an important mechanism of HDV hepatocarcinogenesis. This specific HDV-HCC trait emerged also from the comparison of the molecular pathways identified for each hepatitis virus-associated HCC. Despite the dependence of HDV on HBV, these findings suggest that HDV and HBV promote carcinogenesis by distinct molecular mechanisms. This study identifies a molecular signature of HDV

Identifying DNA Methylation Features that Underlie Prostate Cancer Disparities

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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

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.

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.

Identification of Aging-Associated Gene Expression Signatures That Precede Intestinal Tumorigenesis.

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Yoshihisa Okuchi

Full Text Available Aging-associated alterations of cellular functions have been implicated in various disorders including cancers. Due to difficulties in identifying aging cells in living tissues, most studies have focused on aging-associated changes in whole tissues or certain cell pools. Thus, it remains unclear what kinds of alterations accumulate in each cell during aging. While analyzing several mouse lines expressing fluorescent proteins (FPs, we found that expression of FPs is gradually silenced in the intestinal epithelium during aging in units of single crypt composed of clonal stem cell progeny. The cells with low FP expression retained the wild-type Apc allele and the tissues composed of them did not exhibit any histological abnormality. Notably, the silencing of FPs was also observed in intestinal adenomas and the surrounding normal mucosae of Apc-mutant mice, and mediated by DNA methylation of the upstream promoter. Our genome-wide analysis then showed that the silencing of FPs reflects specific gene expression alterations during aging, and that these alterations occur in not only mouse adenomas but also human sporadic and hereditary (familial adenomatous polyposis adenomas. Importantly, pharmacological inhibition of DNA methylation, which suppresses adenoma development in Apc-mutant mice, reverted the aging-associated silencing of FPs and gene expression alterations. These results identify aging-associated gene expression signatures that are heterogeneously induced by DNA methylation and precede intestinal tumorigenesis triggered by Apc inactivation, and suggest that pharmacological inhibition of the signature genes could be a novel strategy for the prevention and treatment of intestinal tumors.

Identification of E-cadherin signature motifs functioning as cleavage sites for Helicobacter pylori HtrA

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Schmidt, Thomas P.; Perna, Anna M.; Fugmann, Tim; Böhm, Manja; Jan Hiss; Haller, Sarah; Götz, Camilla; Tegtmeyer, Nicole; Hoy, Benjamin; Rau, Tilman T.; Neri, Dario; Backert, Steffen; Schneider, Gisbert; Wessler, Silja

2016-03-01

The cell adhesion protein and tumour suppressor E-cadherin exhibits important functions in the prevention of gastric cancer. As a class-I carcinogen, Helicobacter pylori (H. pylori) has developed a unique strategy to interfere with E-cadherin functions. In previous studies, we have demonstrated that H. pylori secretes the protease high temperature requirement A (HtrA) which cleaves off the E-cadherin ectodomain (NTF) on epithelial cells. This opens cell-to-cell junctions, allowing bacterial transmigration across the polarised epithelium. Here, we investigated the molecular mechanism of the HtrA-E-cadherin interaction and identified E-cadherin cleavage sites for HtrA. Mass-spectrometry-based proteomics and Edman degradation revealed three signature motifs containing the [VITA]-[VITA]-x-x-D-[DN] sequence pattern, which were preferentially cleaved by HtrA. Based on these sites, we developed a substrate-derived peptide inhibitor that selectively bound and inhibited HtrA, thereby blocking transmigration of H. pylori. The discovery of HtrA-targeted signature sites might further explain why we detected a stable 90 kDa NTF fragment during H. pylori infection, but also additional E-cadherin fragments ranging from 105 kDa to 48 kDa in in vitro cleavage experiments. In conclusion, HtrA targets E-cadherin signature sites that are accessible in in vitro reactions, but might be partially masked on epithelial cells through functional homophilic E-cadherin interactions.

Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

International Nuclear Information System (INIS)

Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

2008-01-01

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

Cancer association study of aminoacyl-tRNA synthetase signaling network in glioblastoma.

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Yong-Wan Kim

Full Text Available Aminoacyl-tRNA synthetases (ARSs and ARS-interacting multifunctional proteins (AIMPs exhibit remarkable functional versatility beyond their catalytic activities in protein synthesis. Their non-canonical functions have been pathologically linked to cancers. Here we described our integrative genome-wide analysis of ARSs to show cancer-associated activities in glioblastoma multiforme (GBM, the most aggressive malignant primary brain tumor. We first selected 23 ARS/AIMPs (together referred to as ARSN, 124 cancer-associated druggable target genes (DTGs and 404 protein-protein interactors (PPIs of ARSs using NCI's cancer gene index. 254 GBM affymetrix microarray data in The Cancer Genome Atlas (TCGA were used to identify the probe sets whose expression were most strongly correlated with survival (Kaplan-Meier plots versus survival times, log-rank t-test <0.05. The analysis identified 122 probe sets as survival signatures, including 5 of ARSN (VARS, QARS, CARS, NARS, FARS, and 115 of DTGs and PPIs (PARD3, RXRB, ATP5C1, HSP90AA1, CD44, THRA, TRAF2, KRT10, MED12, etc. Of note, 61 survival-related probes were differentially expressed in three different prognosis subgroups in GBM patients and showed correlation with established prognosis markers such as age and phenotypic molecular signatures. CARS and FARS also showed significantly higher association with different molecular networks in GBM patients. Taken together, our findings demonstrate evidence for an ARSN biology-dominant contribution in the biology of GBM.

Low Cancer Stem Cell Marker Expression and Low Hypoxia Identify Good Prognosis Subgroups in HPV(-) HNSCC after Postoperative Radiochemotherapy: A Multicenter Study of the DKTK-ROG

DEFF Research Database (Denmark)

Linge, Annett; Löck, Steffen; Gudziol, Volker

2016-01-01

PURPOSE: To investigate the impact of hypoxia-induced gene expression and cancer stem cell (CSC) marker expression on outcome of postoperative cisplatin-based radiochemotherapy (PORT-C) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC). EXPERIMENTAL DESIGN: Expression...... of the CSC markers CD44, MET, and SLC3A2, and hypoxia gene signatures were analyzed in the resected primary tumors using RT-PCR and nanoString technology in a multicenter retrospective cohort of 195 patients. CD44 protein expression was further analyzed in tissue microarrays. Primary endpoint...... was locoregional tumor control. RESULTS: Univariate analysis showed that hypoxia-induced gene expression was significantly associated with a high risk of locoregional recurrence using the 15-gene signature (P = 0.010) or the 26-gene signature (P = 0.002). In multivariate analyses, in patients with HPV16 DNA...

RUNX1 and RUNX3 protect against YAP-mediated EMT, stem-ness and shorter survival outcomes in breast cancer

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Kulkarni, Madhura; Tan, Tuan Zea; Syed Sulaiman, Nurfarhanah Bte; Lamar, John M.; Bansal, Prashali; Cui, Jianzhou; Qiao, Yiting; Ito, Yoshiaki

2018-01-01

Hippo pathway target, YAP has emerged as an important player in solid tumor progression. Here, we identify RUNX1 and RUNX3 as novel negative regulators of oncogenic function of YAP in the context of breast cancer. RUNX proteins are one of the first transcription factors identified to interact with YAP. RUNX1 or RUNX3 expression abrogates YAP-mediated pro-tumorigenic properties of mammary epithelial cell lines in an interaction dependent manner. RUNX1 and RUNX3 inhibit YAP-mediated migration and stem-ness properties of mammary epithelial cell lines by co-regulating YAP-mediated gene expression. Analysis of whole genome expression profiles of breast cancer samples revealed significant co-relation between YAP–RUNX1/RUNX3 expression levels and survival outcomes of breast cancer patients. High RUNX1/RUNX3 expression proved protective towards YAP-dependent patient survival outcomes. High YAP in breast cancer patients’ expression profiles co-related with EMT and stem-ness gene signature enrichment. High RUNX1/RUNX3 expression along with high YAP reflected lower enrichment of EMT and stem-ness signatures. This antagonistic activity of RUNX1 and RUNX3 towards oncogenic function of YAP identified in mammary epithelial cells as well as in breast cancer expression profiles gives a novel mechanistic insight into oncogene–tumor suppressor interplay in the context of breast cancer progression. The novel interplay between YAP, RUNX1 and RUNX3 and its significance in breast cancer progression can serve as a prognostic tool to predict cancer recurrence. PMID:29581836

Modeling ground vehicle acoustic signatures for analysis and synthesis

International Nuclear Information System (INIS)

Haschke, G.; Stanfield, R.

1995-01-01

Security and weapon systems use acoustic sensor signals to classify and identify moving ground vehicles. Developing robust signal processing algorithms for this is expensive, particularly in presence of acoustic clutter or countermeasures. This paper proposes a parametric ground vehicle acoustic signature model to aid the system designer in understanding which signature features are important, developing corresponding feature extraction algorithms and generating low-cost, high-fidelity synthetic signatures for testing. The authors have proposed computer-generated acoustic signatures of armored, tracked ground vehicles to deceive acoustic-sensored smart munitions. They have developed quantitative measures of how accurately a synthetic acoustic signature matches those produced by actual vehicles. This paper describes parameters of the model used to generate these synthetic signatures and suggests methods for extracting these parameters from signatures of valid vehicle encounters. The model incorporates wide-bandwidth and narrow- bandwidth components that are modulated in a pseudo-random fashion to mimic the time dynamics of valid vehicle signatures. Narrow- bandwidth feature extraction techniques estimate frequency, amplitude and phase information contained in a single set of narrow frequency- band harmonics. Wide-bandwidth feature extraction techniques estimate parameters of a correlated-noise-floor model. Finally, the authors propose a method of modeling the time dynamics of the harmonic amplitudes as a means adding necessary time-varying features to the narrow-bandwidth signal components. The authors present results of applying this modeling technique to acoustic signatures recorded during encounters with one armored, tracked vehicle. Similar modeling techniques can be applied to security systems

Predicting cellular growth from gene expression signatures.

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Edoardo M Airoldi

2009-01-01

Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

High-risk populations identified in Childhood Cancer Survivor Study investigations: implications for risk-based surveillance.

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Hudson, Melissa M; Mulrooney, Daniel A; Bowers, Daniel C; Sklar, Charles A; Green, Daniel M; Donaldson, Sarah S; Oeffinger, Kevin C; Neglia, Joseph P; Meadows, Anna T; Robison, Leslie L

2009-05-10

Childhood cancer survivors often experience complications related to cancer and its treatment that may adversely affect quality of life and increase the risk of premature death. The purpose of this manuscript is to review how data derived from Childhood Cancer Survivor Study (CCSS) investigations have facilitated identification of childhood cancer survivor populations at high risk for specific organ toxicity and secondary carcinogenesis and how this has informed clinical screening practices. Articles previously published that used the resource of the CCSS to identify risk factors for specific organ toxicity and subsequent cancers were reviewed and results summarized. CCSS investigations have characterized specific groups to be at highest risk of morbidity related to endocrine and reproductive dysfunction, pulmonary toxicity, cerebrovascular injury, neurologic and neurosensory sequelae, and subsequent neoplasms. Factors influencing risk for specific outcomes related to the individual survivor (eg, sex, race/ethnicity, age at diagnosis, attained age), sociodemographic status (eg, education, household income, health insurance) and cancer history (eg, diagnosis, treatment, time from diagnosis) have been consistently identified. These CCSS investigations that clarify risk for treatment complications related to specific treatment modalities, cumulative dose exposures, and sociodemographic factors identify profiles of survivors at high risk for cancer-related morbidity who deserve heightened surveillance to optimize outcomes after treatment for childhood cancer.

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

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Abigail Bigham

2010-09-01

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

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.

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

Two Opposing Effects (Yin and Yang) Determine Cancer Progression.

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Huang, Shujun; Kurubanjerdjit, Nilubon; Xu, Wayne

2017-01-01

In this review, we introduce a new vision of cancer describing opposing effects that control progression. Cancer is a paradigm of opposing of "Yin" and "Yang," with Yin being the effect to promote cancer and Yang that to maintain the normal state. This Yin Yang hypothesis has been used to select Yin and Yang genes to develop multigene signatures for determining prognosis in lung and breast cancer. Most of the Yin genes are involved in cell survival, growth, and proliferation, whereas most Yang genes are involved in cell apoptosis. Furthermore, Yin and Yang pathways have been identified in breast cancer and compounds that can inhibit the Yin pathways or activate the Yang pathways have been examined, suggesting a new promising targeting therapy for cancer. We are building a Yin Yang model to represent the dynamic change of Yin and Yang genes and pathways.

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

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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.

A Sensitive and Specific Neural Signature for Picture-Induced Negative Affect.

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Luke J Chang

2015-06-01

Full Text Available Neuroimaging has identified many correlates of emotion but has not yet yielded brain representations predictive of the intensity of emotional experiences in individuals. We used machine learning to identify a sensitive and specific signature of emotional responses to aversive images. This signature predicted the intensity of negative emotion in individual participants in cross validation (n =121 and test (n = 61 samples (high-low emotion = 93.5% accuracy. It was unresponsive to physical pain (emotion-pain = 92% discriminative accuracy, demonstrating that it is not a representation of generalized arousal or salience. The signature was comprised of mesoscale patterns spanning multiple cortical and subcortical systems, with no single system necessary or sufficient for predicting experience. Furthermore, it was not reducible to activity in traditional "emotion-related" regions (e.g., amygdala, insula or resting-state networks (e.g., "salience," "default mode". Overall, this work identifies differentiable neural components of negative emotion and pain, providing a basis for new, brain-based taxonomies of affective processes.

Molecular subtyping of cancer: current status and moving toward clinical applications.

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Zhao, Lan; Lee, Victor H F; Ng, Michael K; Yan, Hong; Bijlsma, Maarten F

2018-04-12

Cancer is a collection of genetic diseases, with large phenotypic differences and genetic heterogeneity between different types of cancers and even within the same cancer type. Recent advances in genome-wide profiling provide an opportunity to investigate global molecular changes during the development and progression of cancer. Meanwhile, numerous statistical and machine learning algorithms have been designed for the processing and interpretation of high-throughput molecular data. Molecular subtyping studies have allowed the allocation of cancer into homogeneous groups that are considered to harbor similar molecular and clinical characteristics. Furthermore, this has helped researchers to identify both actionable targets for drug design as well as biomarkers for response prediction. In this review, we introduce five frequently applied techniques for generating molecular data, which are microarray, RNA sequencing, quantitative polymerase chain reaction, NanoString and tissue microarray. Commonly used molecular data for cancer subtyping and clinical applications are discussed. Next, we summarize a workflow for molecular subtyping of cancer, including data preprocessing, cluster analysis, supervised classification and subtype characterizations. Finally, we identify and describe four major challenges in the molecular subtyping of cancer that may preclude clinical implementation. We suggest that standardized methods should be established to help identify intrinsic subgroup signatures and build robust classifiers that pave the way toward stratified treatment of cancer patients.

Adaptive Randomization of Neratinib in Early Breast Cancer.

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Park, John W; Liu, Minetta C; Yee, Douglas; Yau, Christina; van 't Veer, Laura J; Symmans, W Fraser; Paoloni, Melissa; Perlmutter, Jane; Hylton, Nola M; Hogarth, Michael; DeMichele, Angela; Buxton, Meredith B; Chien, A Jo; Wallace, Anne M; Boughey, Judy C; Haddad, Tufia C; Chui, Stephen Y; Kemmer, Kathleen A; Kaplan, Henry G; Isaacs, Claudine; Nanda, Rita; Tripathy, Debasish; Albain, Kathy S; Edmiston, Kirsten K; Elias, Anthony D; Northfelt, Donald W; Pusztai, Lajos; Moulder, Stacy L; Lang, Julie E; Viscusi, Rebecca K; Euhus, David M; Haley, Barbara B; Khan, Qamar J; Wood, William C; Melisko, Michelle; Schwab, Richard; Helsten, Teresa; Lyandres, Julia; Davis, Sarah E; Hirst, Gillian L; Sanil, Ashish; Esserman, Laura J; Berry, Donald A

2016-07-07

The heterogeneity of breast cancer makes identifying effective therapies challenging. The I-SPY 2 trial, a multicenter, adaptive phase 2 trial of neoadjuvant therapy for high-risk clinical stage II or III breast cancer, evaluated multiple new agents added to standard chemotherapy to assess the effects on rates of pathological complete response (i.e., absence of residual cancer in the breast or lymph nodes at the time of surgery). We used adaptive randomization to compare standard neoadjuvant chemotherapy plus the tyrosine kinase inhibitor neratinib with control. Eligible women were categorized according to eight biomarker subtypes on the basis of human epidermal growth factor receptor 2 (HER2) status, hormone-receptor status, and risk according to a 70-gene profile. Neratinib was evaluated against control with regard to 10 biomarker signatures (prospectively defined combinations of subtypes). The primary end point was pathological complete response. Volume changes on serial magnetic resonance imaging were used to assess the likelihood of such a response in each patient. Adaptive assignment to experimental groups within each disease subtype was based on Bayesian probabilities of the superiority of the treatment over control. Enrollment in the experimental group was stopped when the 85% Bayesian predictive probability of success in a confirmatory phase 3 trial of neoadjuvant therapy reached a prespecified threshold for any biomarker signature ("graduation"). Enrollment was stopped for futility if the probability fell to below 10% for every biomarker signature. Neratinib reached the prespecified efficacy threshold with regard to the HER2-positive, hormone-receptor-negative signature. Among patients with HER2-positive, hormone-receptor-negative cancer, the mean estimated rate of pathological complete response was 56% (95% Bayesian probability interval [PI], 37 to 73%) among 115 patients in the neratinib group, as compared with 33% among 78 controls (95% PI, 11 to 54

Unconditionally Secure Quantum Signatures

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Ryan Amiri

2015-08-01

Full Text Available Signature schemes, proposed in 1976 by Diffie and Hellman, have become ubiquitous across modern communications. They allow for the exchange of messages from one sender to multiple recipients, with the guarantees that messages cannot be forged or tampered with and that messages also can be forwarded from one recipient to another without compromising their validity. Signatures are different from, but no less important than encryption, which ensures the privacy of a message. Commonly used signature protocols—signatures based on the Rivest–Adleman–Shamir (RSA algorithm, the digital signature algorithm (DSA, and the elliptic curve digital signature algorithm (ECDSA—are only computationally secure, similar to public key encryption methods. In fact, since these rely on the difficulty of finding discrete logarithms or factoring large primes, it is known that they will become completely insecure with the emergence of quantum computers. We may therefore see a shift towards signature protocols that will remain secure even in a post-quantum world. Ideally, such schemes would provide unconditional or information-theoretic security. In this paper, we aim to provide an accessible and comprehensive review of existing unconditionally securesecure signature schemes for signing classical messages, with a focus on unconditionally secure quantum signature schemes.

Signatures of selection in tilapia revealed by whole genome resequencing.

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Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

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

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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.

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

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

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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.

Identifying candidate driver genes by integrative ovarian cancer genomics data

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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.

Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

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Kim Seon-Young

2009-05-01

Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.

A prospective blood RNA signature for tuberculosis disease risk

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Zak, Daniel E.; Penn-Nicholson, Adam; Scriba, Thomas J.; Thompson, Ethan; Suliman, Sara; Amon, Lynn M.; Mahomed, Hassan; Erasmus, Mzwandile; Whatney, Wendy; Hussey, Gregory D.; Abrahams, Deborah; Kafaar, Fazlin; Hawkridge, Tony; Verver, Suzanne; Hughes, E. Jane; Ota, Martin; Sutherland, Jayne; Howe, Rawleigh; Dockrell, Hazel M.; Boom, W. Henry; Thiel, Bonnie; Ottenhoff, Tom H.M.; Mayanja-Kizza, Harriet; Crampin, Amelia C; Downing, Katrina; Hatherill, Mark; Valvo, Joe; Shankar, Smitha; Parida, Shreemanta K; Kaufmann, Stefan H.E.; Walzl, Gerhard; Aderem, Alan; Hanekom, Willem A.

2016-01-01

Background Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease may lead to interventions that impact the epidemic. Methods Healthy, M. tuberculosis infected South African adolescents were followed for 2 years; blood was collected every 6 months. A prospective signature of risk was derived from whole blood RNA-Sequencing data by comparing participants who ultimately developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. The latter participants were household contacts of adults with active pulmonary tuberculosis disease. Findings Of 6,363 adolescents screened, 46 progressors and 107 matched controls were identified. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% confidence interval, 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA-Seq and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values Bill and Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union and the South African Medical Research Council (detail at end of text). PMID:27017310

Strategies to Identify the Lynch Syndrome Among Patients With Colorectal Cancer

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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

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.

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...

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.

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

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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.

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.

Signature Pedagogies and Legal Education in Universities: Epistemological and Pedagogical Concerns with Langdellian Case Method

Science.gov (United States)

Hyland, Aine; Kilcommins, Shane

2009-01-01

This paper offers an analysis of Lee S. Shulman's concept of "signature pedagogies" as it relates to legal education. In law, the signature pedagogy identified by Shulman is the Langdellian case method. Though the concept of signature pedagogies provides an excellent infrastructure for the exchange of teaching ideas, Shulman has a tendency to…

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

Finding cancer driver mutations in the era of big data research.

Science.gov (United States)

Poulos, Rebecca C; Wong, Jason W H

2018-04-02

In the last decade, the costs of genome sequencing have decreased considerably. The commencement of large-scale cancer sequencing projects has enabled cancer genomics to join the big data revolution. One of the challenges still facing cancer genomics research is determining which are the driver mutations in an individual cancer, as these contribute only a small subset of the overall mutation profile of a tumour. Focusing primarily on somatic single nucleotide mutations in this review, we consider both coding and non-coding driver mutations, and discuss how such mutations might be identified from cancer sequencing datasets. We describe some of the tools and database that are available for the annotation of somatic variants and the identification of cancer driver genes. We also address the use of genome-wide variation in mutation load to establish background mutation rates from which to identify driver mutations under positive selection. Finally, we describe the ways in which mutational signatures can act as clues for the identification of cancer drivers, as these mutations may cause, or arise from, certain mutational processes. By defining the molecular changes responsible for driving cancer development, new cancer treatment strategies may be developed or novel preventative measures proposed.

Single-cell transcriptomics uncovers distinct molecular signatures of stem cells in chronic myeloid leukemia.

Science.gov (United States)

Giustacchini, Alice; Thongjuea, Supat; Barkas, Nikolaos; Woll, Petter S; Povinelli, Benjamin J; Booth, Christopher A G; Sopp, Paul; Norfo, Ruggiero; Rodriguez-Meira, Alba; Ashley, Neil; Jamieson, Lauren; Vyas, Paresh; Anderson, Kristina; Segerstolpe, Åsa; Qian, Hong; Olsson-Strömberg, Ulla; Mustjoki, Satu; Sandberg, Rickard; Jacobsen, Sten Eirik W; Mead, Adam J

2017-06-01

Recent advances in single-cell transcriptomics are ideally placed to unravel intratumoral heterogeneity and selective resistance of cancer stem cell (SC) subpopulations to molecularly targeted cancer therapies. However, current single-cell RNA-sequencing approaches lack the sensitivity required to reliably detect somatic mutations. We developed a method that combines high-sensitivity mutation detection with whole-transcriptome analysis of the same single cell. We applied this technique to analyze more than 2,000 SCs from patients with chronic myeloid leukemia (CML) throughout the disease course, revealing heterogeneity of CML-SCs, including the identification of a subgroup of CML-SCs with a distinct molecular signature that selectively persisted during prolonged therapy. Analysis of nonleukemic SCs from patients with CML also provided new insights into cell-extrinsic disruption of hematopoiesis in CML associated with clinical outcome. Furthermore, we used this single-cell approach to identify a blast-crisis-specific SC population, which was also present in a subclone of CML-SCs during the chronic phase in a patient who subsequently developed blast crisis. This approach, which might be broadly applied to any malignancy, illustrates how single-cell analysis can identify subpopulations of therapy-resistant SCs that are not apparent through cell-population analysis.

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

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Kim YW

2014-02-01

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

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.

Infrared signatures for remote sensing

International Nuclear Information System (INIS)

McDowell, R.S.; Sharpe, S.W.; Kelly, J.F.

1994-04-01

PNL's capabilities for infrared and near-infrared spectroscopy include tunable-diode-laser (TDL) systems covering 300--3,000 cm -1 at 2 laser. PNL also has a beam expansion source with a 12-cm slit, which provides a 3-m effective path for gases at ∼10 K, giving a Doppler width of typically 10 MHz; and long-path static gas cells (to 100 m). In applying this equipment to signatures work, the authors emphasize the importance of high spectral resolution for detecting and identifying atmospheric interferences; for identifying the optimum analytical frequencies; for deriving, by spectroscopic analysis, the molecular parameters needed for modeling; and for obtaining data on species and/or bands that are not in existing databases. As an example of such spectroscopy, the authors have assigned and analyzed the C-Cl stretching region of CCl 4 at 770--800 cm -1 . This is an important potential signature species whose IR absorption has remained puzzling because of the natural isotopic mix, extensive hot-band structure, and a Fermi resonance involving a nearby combination band. Instrument development projects include the IR sniffer, a small high-sensitivity, high-discrimination (Doppler-limited) device for fence-line or downwind monitoring that is effective even in regions of atmospheric absorption; preliminary work has achieved sensitivities at the low-ppb level. Other work covers trace species detection with TDLs, and FM-modulated CO 2 laser LIDAR. The authors are planning a field experiment to interrogate the Hanford tank farm for signature species from Rattlesnake Mountain, a standoff of ca. 15 km, to be accompanied by simultaneous ground-truthing at the tanks

Identification of lung cancer with high sensitivity and specificity by blood testing

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Stephan Bernhard

2010-02-01

Full Text Available Abstract Background Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. Methods We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. Results The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%. Conclusion We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be seprated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.

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

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Eric L. Allen

2016-10-01

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

Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

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Zhou, Xionghui; Liu, Juan

2014-01-01

Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

Remodeling of the methylation landscape in breast cancer metastasis.

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Marsha Reyngold

Full Text Available The development of breast cancer metastasis is accompanied by dynamic transcriptome changes and dramatic alterations in nuclear and chromatin structure. The basis of these changes is incompletely understood. The DNA methylome of primary breast cancers contribute to transcriptomic heterogeneity and different metastatic behavior. Therefore we sought to characterize methylome remodeling during regional metastasis. We profiled the DNA methylome and transcriptome of 44 matched primary breast tumors and regional metastases. Striking subtype-specific patterns of metastasis-associated methylome remodeling were observed, which reflected the molecular heterogeneity of breast cancers. These divergent changes occurred primarily in CpG island (CGI-poor areas. Regions of methylome reorganization shared by the subtypes were also observed, and we were able to identify a metastasis-specific methylation signature that was present across the breast cancer subclasses. These alterations also occurred outside of CGIs and promoters, including sequences flanking CGIs and intergenic sequences. Integrated analysis of methylation and gene expression identified genes whose expression correlated with metastasis-specific methylation. Together, these findings significantly enhance our understanding of the epigenetic reorganization that occurs during regional breast cancer metastasis across the major breast cancer subtypes and reveal the nature of methylome remodeling during this process.

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.

Electronic Signature Policy

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Establishes the United States Environmental Protection Agency's approach to adopting electronic signature technology and best practices to ensure electronic signatures applied to official Agency documents are legally valid and enforceable

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

Identification and Validation of a New Set of Five Genes for Prediction of Risk in Early Breast Cancer

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Giorgio Mustacchi

2013-05-01

Full Text Available Molecular tests predicting the outcome of breast cancer patients based on gene expression levels can be used to assist in making treatment decisions after consideration of conventional markers. In this study we identified a subset of 20 mRNA differentially regulated in breast cancer analyzing several publicly available array gene expression data using R/Bioconductor package. Using RTqPCR we evaluate 261 consecutive invasive breast cancer cases not selected for age, adjuvant treatment, nodal and estrogen receptor status from paraffin embedded sections. The biological samples dataset was split into a training (137 cases and a validation set (124 cases. The gene signature was developed on the training set and a multivariate stepwise Cox analysis selected five genes independently associated with DFS: FGF18 (HR = 1.13, p = 0.05, BCL2 (HR = 0.57, p = 0.001, PRC1 (HR = 1.51, p = 0.001, MMP9 (HR = 1.11, p = 0.08, SERF1a (HR = 0.83, p = 0.007. These five genes were combined into a linear score (signature weighted according to the coefficients of the Cox model, as: 0.125FGF18 − 0.560BCL2 + 0.409PRC1 + 0.104MMP9 − 0.188SERF1A (HR = 2.7, 95% CI = 1.9–4.0, p < 0.001. The signature was then evaluated on the validation set assessing the discrimination ability by a Kaplan Meier analysis, using the same cut offs classifying patients at low, intermediate or high risk of disease relapse as defined on the training set (p < 0.001. Our signature, after a further clinical validation, could be proposed as prognostic signature for disease free survival in breast cancer patients where the indication for adjuvant chemotherapy added to endocrine treatment is uncertain.

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

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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

Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

International Nuclear Information System (INIS)

Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

2010-01-01

Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ('model signatures') constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer. Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways. We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that

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.

Blinding for unanticipated signatures

NARCIS (Netherlands)

D. Chaum (David)

1987-01-01

textabstractPreviously known blind signature systems require an amount of computation at least proportional to the number of signature types, and also that the number of such types be fixed in advance. These requirements are not practical in some applications. Here, a new blind signature technique

Exploring Signature Pedagogies in Undergraduate Leadership Education

Science.gov (United States)

Jenkins, Daniel M.

2012-01-01

This research explores the instructional strategies most frequently used by leadership educators who teach academic credit-bearing undergraduate leadership studies courses through a national survey and identifies signature pedagogies within the leadership discipline. Findings from this study suggest that class discussion--whether in the form of…

Comparing human pancreatic cell secretomes by in vitro aptamer selection identifies cyclophilin B as a candidate pancreatic cancer biomarker.

Science.gov (United States)

Ray, Partha; Rialon-Guevara, Kristy L; Veras, Emanuela; Sullenger, Bruce A; White, Rebekah R

2012-05-01

Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition-based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer.

APOBEC3 cytidine deaminases in double-strand DNA break repair and cancer promotion.

Science.gov (United States)

Nowarski, Roni; Kotler, Moshe

2013-06-15

High frequency of cytidine to thymidine conversions was identified in the genome of several types of cancer cells. In breast cancer cells, these mutations are clustered in long DNA regions associated with single-strand DNA (ssDNA), double-strand DNA breaks (DSB), and genomic rearrangements. The observed mutational pattern resembles the deamination signature of cytidine to uridine carried out by members of the APOBEC3 family of cellular deaminases. Consistently, APOBEC3B (A3B) was recently identified as the mutational source in breast cancer cells. A3G is another member of the cytidine deaminases family predominantly expressed in lymphoma cells, where it is involved in mutational DSB repair following ionizing radiation treatments. This activity provides us with a new paradigm for cancer cell survival and tumor promotion and a mechanistic link between ssDNA, DSBs, and clustered mutations. Cancer Res; 73(12); 3494-8. ©2013 AACR. ©2013 AACR.

An integrated approach to the prediction of chemotherapeutic response in patients with breast cancer.

Directory of Open Access Journals (Sweden)

Kelly H Salter

Full Text Available A major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective.Using gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%. When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06. Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8% of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04, representing a viable alternative therapy.Our results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding micro

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.

The spectrum of genomic signatures: from dinucleotides to chaos game representation.

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Wang, Yingwei; Hill, Kathleen; Singh, Shiva; Kari, Lila

2005-02-14

In the post genomic era, access to complete genome sequence data for numerous diverse species has opened multiple avenues for examining and comparing primary DNA sequence organization of entire genomes. Previously, the concept of a genomic signature was introduced with the observation of species-type specific Dinucleotide Relative Abundance Profiles (DRAPs); dinucleotides were identified as the subsequences with the greatest bias in representation in a majority of genomes. Herein, we demonstrate that DRAP is one particular genomic signature contained within a broader spectrum of signatures. Within this spectrum, an alternative genomic signature, Chaos Game Representation (CGR), provides a unique visualization of patterns in sequence organization. A genomic signature is associated with a particular integer order or subsequence length that represents a measure of the resolution or granularity in the analysis of primary DNA sequence organization. We quantitatively explore the organizational information provided by genomic signatures of different orders through different distance measures, including a novel Image Distance. The Image Distance and other existing distance measures are evaluated by comparing the phylogenetic trees they generate for 26 complete mitochondrial genomes from a diversity of species. The phylogenetic tree generated by the Image Distance is compatible with the known relatedness of species. Quantitative evaluation of the spectrum of genomic signatures may be used to ultimately gain insight into the determinants and biological relevance of the genome signatures.

1 CFR 18.7 - Signature.

Science.gov (United States)

2010-01-01

... 1 General Provisions 1 2010-01-01 2010-01-01 false Signature. 18.7 Section 18.7 General Provisions... PREPARATION AND TRANSMITTAL OF DOCUMENTS GENERALLY § 18.7 Signature. The original and each duplicate original... stamped beneath the signature. Initialed or impressed signatures will not be accepted. Documents submitted...

Attribute-Based Digital Signature System

NARCIS (Netherlands)

Ibraimi, L.; Asim, Muhammad; Petkovic, M.

2011-01-01

An attribute-based digital signature system comprises a signature generation unit (1) for signing a message (m) by generating a signature (s) based on a user secret key (SK) associated with a set of user attributes, wherein the signature generation unit (1) is arranged for combining the user secret

DNA copy-number alterations underlie gene expression differences between microsatellite stable and unstable colorectal cancers

DEFF Research Database (Denmark)

Jorissen, Robert N; Lipton, Lara; Gibbs, Peter

2008-01-01

Purpose: About 15% of colorectal cancers harbor microsatellite instability (MSI). MSI-associated gene expression changes have been identified in colorectal cancers, but little overlap exists between signatures hindering an assessment of overall consistency. Little is known about the causes...... and downstream effects of differential gene expression. Experimental Design: DNA microarray data on 89 MSI and 140 microsatellite-stable (MSS) colorectal cancers from this study and 58 MSI and 77 MSS cases from three published reports were randomly divided into test and training sets. MSI-associated gene......-number data. Results: MSI-associated gene expression changes in colorectal cancers were found to be highly consistent across multiple studies of primary tumors and cancer cell lines from patients of different ethnicities (P