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Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification

Yishai Shimoni, Bing Zhang
2018 PLoS Computational Biology  
Author summary Multiple gene sets have been published as predictive of cancer progression and metastasis in several cancer types.  ...  Our results suggest that the predictive power of random gene sets may be used to identify the existence of sub-classes in the data, and thus may allow better understanding of patient stratification.  ...  Acknowledgments The results shown here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/. The authors thank Dr.  ... 
doi:10.1371/journal.pcbi.1006026 pmid:29470520 pmcid:PMC5839591 fatcat:ymn7mmk6qremvbo4hibqtk6yae

PIMKL: Pathway-Induced Multiple Kernel Learning

Matteo Manica, Joris Cadow, Roland Mathis, María Rodríguez Martínez
2019 npj Systems Biology and Applications  
PIMKL exploits prior knowledge in the form of a molecular interaction network and annotated gene sets, by optimizing a mixture of pathway-induced kernels using a Multiple Kernel Learning (MKL) algorithm  ...  While state-of-the-art machine learning approaches for sample classification continue to push boundaries in terms of performance, most of these methods are not able to integrate different data types and  ...  ACKNOWLEDGEMENTS We thank Yupeng Cun for kindly providing results 13 for the creation of Figs. 1a and S1.  ... 
doi:10.1038/s41540-019-0086-3 pmid:30854223 pmcid:PMC6401099 fatcat:nv7rall7crepdcnk6gwzyqwk3e

Robust pathway-based multi-omics data integration using directed random walks for survival prediction in multiple cancer studies

So Yeon Kim, Hyun-Hwan Jeong, Jaesik Kim, Jeong-Hyeon Moon, Kyung-Ah Sohn
2019 Biology Direct  
Integrating the rich information from multi-omics data has been a popular approach to survival prediction and bio-marker identification for several cancer studies.  ...  To facilitate the integrative analysis of multiple genomic profiles, several studies have suggested utilizing pathway information rather than using individual genomic profiles.  ...  Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.  ... 
doi:10.1186/s13062-019-0239-8 pmid:31036036 pmcid:PMC6489180 fatcat:cogl3d73zne3ngh6cxj662oisq

Stem Cell-Like Gene Expression in Ovarian Cancer Predicts Type II Subtype and Prognosis

Matthew Schwede, Dimitrios Spentzos, Stefan Bentink, Oliver Hofmann, Benjamin Haibe-Kains, David Harrington, John Quackenbush, Aedín C. Culhane, Vincenzo Coppola
2013 PLoS ONE  
Genes that are expressed by stem cells may characterize a subset of less differentiated tumors and aid in prognostic classification of ovarian cancer.  ...  We identified a stem-like subtype characterized by a 51-gene signature, which is significantly enriched in tumors with properties of Type II ovarian cancer; high grade, serous tumors, and poor survival  ...  We are grateful to Professor Win Hide and his group for assistance in curation of stem cell gene signatures and for interpretation of results and Ms. Renee Rubio and Ms.  ... 
doi:10.1371/journal.pone.0057799 pmid:23536770 pmcid:PMC3594231 fatcat:6wkmv54dm5hifc4sbnulhagj3q

Molecular Classification of Renal Cell Carcinoma and Its Implication in Future Clinical Practice

Jozefina Casuscelli, Yann-Alexandre Vano, Wolf Herve Fridman, James J. Hsieh
2017 Kidney Cancer  
The incorporation of targeted therapies and immune checkpoint inhibitors into the current practice of mRCC has markedly improved the median overall survival of clear cell RCC (ccRCC) patients, the most  ...  Renal cell carcinoma (RCC) encompasses a wide spectrum of morphologically and molecularly distinct (>10) cancer subtypes originated from the kidney epithelium.  ...  The m1 subtype was characterized by gene sets associated with chromatin remodeling processes and a higher frequency of PBRM1 mutations (39% in m1 vs. 27% in others, P = 0.027).  ... 
doi:10.3233/kca-170008 pmid:30334000 pmcid:PMC6179110 fatcat:rdvdb3ivffcbdmtti6zfsccfpe

Identifying epigenetic biomarkers of established prognostic factors and survival in a clinical cohort of individuals with oropharyngeal cancer

Ryan Langdon, Rebecca Richmond, Hannah R. Elliott, Tom Dudding, Nabila Kazmi, Chris Penfold, Kate Ingarfield, Karen Ho, Andrew Bretherick, Chris Haley, Yanni Zeng, Rosie M. Walker (+8 others)
2020 Clinical Epigenetics  
Part of the effect of smoking on survival in those with oropharyngeal cancer may be mediated by methylation at the SPEG gene locus.  ...  Evidence for a causal effect of DNA methylation on survival was only observed in the SPEG gene region (HR per SD increase in methylation score 1.28, 95% CI 1.14 to 1.43, P 2.12 × 10-05).  ...  Acknowledgements The authors are extremely grateful for the provision of IlluminaMethylationEPIC mQTL data from this study, particularly to Andrew Received: 10 January 2020 Accepted: 19 May 2020  ... 
doi:10.1186/s13148-020-00870-0 pmid:32600451 pmcid:PMC7322918 fatcat:n7jvihcnkrhhpjuku572szr4vq

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines

Mehmet Gönen, Barbara A. Weir, Glenn S. Cowley, Francisca Vazquez, Yuanfang Guan, Alok Jaiswal, Masayuki Karasuyama, Vladislav Uzunangelov, Tao Wang, Aviad Tsherniak, Sara Howell, Daniel Marbach (+113 others)
2017 Cell Systems  
In sub-challenge 2, EIF2C2 expression was utilized in multiple gene models (n = 2-395) by 10 out of the 13 teams.  ...  Analysis of Gene Predictability The proportions of variance explained by "gene" and "team" factors using the random effects model are shown for (A) sub-challenge 1, (B) sub-challenge 2, and (C) sub-challenge  ...  Table 1 Top 10 GSEA Results of Gene Predictability Averaged over All Teams in each Sub-challenge  ... 
doi:10.1016/j.cels.2017.09.004 pmid:28988802 pmcid:PMC5814247 fatcat:uczpvur3qraovfbqfuazffed2a

Support Vector Machine Classifier for Estrogen Receptor Positive and Negative Early-Onset Breast Cancer

Rosanna Upstill-Goddard, Diana Eccles, Sarah Ennis, Sajjad Rafiq, William Tapper, Joerg Fliege, Andrew Collins, Syed A. Aziz
2013 PLoS ONE  
Two major breast cancer sub-types are defined by the expression of estrogen receptors on tumour cells.  ...  The model indicates that polygenic variation in more than 100 genes is likely to underlie the estrogen receptor phenotype in earlyonset breast cancer.  ...  Introduction Breast cancer sub-types may be classified according to the number of estrogen receptors present on the tumour.  ... 
doi:10.1371/journal.pone.0068606 pmid:23894323 pmcid:PMC3716652 fatcat:rnxzk43v5bhfrber3dqxjqglki

ATHENA: Identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network

Dokyoon Kim, Ruowang Li, Scott M Dudek, Marylyn D Ritchie
2013 BioData Mining  
The other possible explanation is that gene expression as a single level of genomic data is insufficient to explain the clinical outcomes of interest since cancer can be dysregulated by multiple alterations  ...  However, emerging evidence shows that gene expression-based prediction varies between independent data sets.  ...  Acknowledgements This work was funded by NIH grant 5R01 LM010040-03 and NHLBI grant 2U01 HL065962-10.  ... 
doi:10.1186/1756-0381-6-23 pmid:24359638 pmcid:PMC3912499 fatcat:dhqhbfmkuffbnedewmqwcscf2q

Identification of Signature Genes and Characterizations of Tumor Immune Microenvironment and Tumor Purity in Lung Adenocarcinoma Based on Machine Learning

Haiming Feng, Ye Zhao, Weijian Yan, Xiaoping Wei, Junping Lin, Peng Jiang, Cheng Wang, Bin Li
2022 Frontiers in Medicine  
The association between a cluster of differentiation 274 (CD274) and CSGTPP revealed a higher expression of CD274 in the high CSGTPP group.  ...  association between TME and tumor purity.  ...  Subsequently, a relationship with gene expression data was analyzed to evaluate the effect of the target genes' classification on tumor purity by random forest classification method achieved by R-random  ... 
doi:10.3389/fmed.2022.843749 pmid:35280857 pmcid:PMC8916235 fatcat:2tocyh4rl5aifecuf4kdym26ou

MicroRNA-Gene Association As a Prognostic Biomarker in Cancer Exposes Disease Mechanisms

Rotem Ben-Hamo, Sol Efroni, Nathan D. Price
2013 PLoS Computational Biology  
Glioblastoma Multiform (GBM) is the most common, aggressive and malignant primary tumor of the brain and is associated with one of the worst 5-year survival rates among all human cancers.  ...  The transcriptional networks that regulate gene expression and modifications to this network are at the core of the cancer phenotype.  ...  The results published here are in whole or part based upon data generated by The Cancer Genome Atlas pilot project established by the NCI and NHGRI.  ... 
doi:10.1371/journal.pcbi.1003351 pmid:24278004 pmcid:PMC3836703 fatcat:grqepdmrfrbddawxuhdvjtfeka

Genomic investigation of etiologic heterogeneity: methodologic challenges

Colin B Begg, Venkatraman E Seshan, Emily C Zabor, Helena Furberg, Arshi Arora, Ronglai Shen, Jodi K Maranchie, Matthew E Nielsen, W Kimryn Rathmell, Sabina Signoretti, Pheroze Tamboli, Jose A Karam (+3 others)
2014 BMC Medical Research Methodology  
The sub-types defined using expression data and methylation data demonstrate considerable congruence and are also clearly correlated with mutations in important cancer genes.  ...  Methods: We use a novel clustering strategy to identify sub-types. This is accomplished independently for the expression, methylation and copy number profiles.  ...  The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.  ... 
doi:10.1186/1471-2288-14-138 pmid:25532962 pmcid:PMC4292824 fatcat:svp3wwurlrea7fibpv25lpawgu

The CINSARC signature as a prognostic marker for clinical outcome in multiple neoplasms

Tom Lesluyes, Lucile Delespaul, Jean-Michel Coindre, Frédéric Chibon
2017 Scientific Reports  
In this study, we used a published resource to investigate CINSARC enrichment in poor outcome-associated genes at pan-cancer level and in 39 cancer types.  ...  CINSARC outperformed more than 15,000 defined signatures (including cancer-related), being enriched in topranked poor outcome-associated genes of 21 cancer types, widest coverage reached among all tested  ...  Acknowledgements Computer time for this study was provided by the computing facilities MCIA (Mésocentre de Calcul Intensif Aquitain) of the Université de Bordeaux and of the Université de Pau et des Pays  ... 
doi:10.1038/s41598-017-05726-x pmid:28710396 pmcid:PMC5511191 fatcat:g4yndf36ffcx3nprnei5bvbgeq

Context-specific gene regulatory networks subdivide intrinsic subtypes of breast cancer

Sara Nasser, Heather Cunliffe, Michael A. Black, Seungchan Kim
2010 Proceedings of the ACM fourth international workshop on Data and text mining in biomedical informatics - DTMBIO '10  
We believe our computational approach led to the generation of novel rationalized hypotheses to explain mechanisms of disease progression within sub-contexts of breast cancer that could be therapeutically  ...  Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable.  ...  Our special thanks to Sungwon Jung, who developed some of the tools used in the analysis. SK is partially supported by NIH 1R21LM009706-01, SFAZ CAA 0243-08, and NIH P01 CA109552-01A1.  ... 
doi:10.1145/1871871.1871875 fatcat:rj4swxhc7fhlxpv7bao2qwicue

Context-specific gene regulatory networks subdivide intrinsic subtypes of breast cancer

Sara Nasser, Heather E Cunliffe, Michael A Black, Seungchan Kim
2011 BMC Bioinformatics  
We believe our computational approach led to the generation of novel rationalized hypotheses to explain mechanisms of disease progression within sub-contexts of breast cancer that could be therapeutically  ...  Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable.  ...  Our special thanks to Sungwon Jung, who developed some of the tools used in the analysis. SK is partially supported by NIH 1R21LM009706-01, SFAZ CAA 0243-08, and NIH P01 CA109552-01A1.  ... 
doi:10.1186/1471-2105-12-s2-s3 pmid:21489222 pmcid:PMC3073183 fatcat:7gdge3a7hrbctof4qbrn6dqnoi
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