{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T12:10:17Z","timestamp":1780056617683,"version":"3.54.0"},"reference-count":56,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T00:00:00Z","timestamp":1663804800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902144"],"award-info":[{"award-number":["61902144"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U19A2065"],"award-info":[{"award-number":["U19A2065"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976102"],"award-info":[{"award-number":["61976102"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Abnormal cell proliferation and epithelial-mesenchymal transition (EMT) are the essential events that induce cancer initiation and progression. A fundamental goal in cancer research is to develop an efficient method to detect mutational genes capable of driving cancer. Although several computational methods have been proposed to identify these key mutations, many of them focus on the association between genetic mutations and functional changes in relevant biological processes, but not their real causality. Causal effect inference provides a way to estimate the real induce effect of a certain mutation on vital biological processes of cancer initiation and progression, through addressing the confounder bias due to neutral mutations and unobserved latent variables. In this study, integrating genomic and transcriptomic data, we construct a novel causal inference model based on a deep variational autoencoder to identify key oncogenic somatic mutations. Applied to 10 cancer types, our method quantifies the causal effect of genetic mutations on cell proliferation and EMT by reducing both observed and unobserved confounding biases. The experimental results indicate that genes with higher mutation frequency do not necessarily mean they are more potent in inducing cancer and promoting cancer development. Moreover, our study fills a gap in the use of machine learning for causal inference to identify oncogenic mutations.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1010529","type":"journal-article","created":{"date-parts":[[2022,9,22]],"date-time":"2022-09-22T18:27:58Z","timestamp":1663871278000},"page":"e1010529","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":5,"title":["Identification of key somatic oncogenic mutation based on a confounder-free causal inference model"],"prefix":"10.1371","volume":"18","author":[{"given":"Yijun","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4664-7147","authenticated-orcid":true,"given":"Huiyan","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,9,22]]},"reference":[{"issue":"1","key":"pcbi.1010529.ref001","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.molcel.2018.06.012","article-title":"A systematic p53 mutation library links differential functional impact to cancer mutation pattern and evolutionary conservation","volume":"71","author":"E Kotler","year":"2018","journal-title":"Molecular cell"},{"issue":"13","key":"pcbi.1010529.ref002","doi-asserted-by":"crossref","first-page":"7786","DOI":"10.1093\/nar\/gkx463","article-title":"The interaction between cytosine methylation and processes of DNA replication and repair shape the mutational landscape of cancer genomes","volume":"45","author":"RC Poulos","year":"2017","journal-title":"Nucleic acids research"},{"issue":"6835","key":"pcbi.1010529.ref003","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1038\/35077213","article-title":"Proliferation, cell cycle and apoptosis in cancer","volume":"411","author":"GI Evan","year":"2001","journal-title":"nature"},{"issue":"2","key":"pcbi.1010529.ref004","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1111\/j.1349-7006.2009.01419.x","article-title":"Epithelial\u2013mesenchymal transition in cancer development and its clinical significance","volume":"101","author":"M Iwatsuki","year":"2010","journal-title":"Cancer science"},{"issue":"6","key":"pcbi.1010529.ref005","doi-asserted-by":"crossref","first-page":"1010","DOI":"10.1111\/j.1349-7006.2012.02262.x","article-title":"Regulation of the metabolite profile by an APC gene mutation in colorectal cancer","volume":"103","author":"T Yoshie","year":"2012","journal-title":"Cancer science"},{"issue":"1","key":"pcbi.1010529.ref006","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1038\/ncb2641","article-title":"p53 mutations in cancer","volume":"15","author":"PA Muller","year":"2013","journal-title":"Nature cell biology"},{"issue":"4","key":"pcbi.1010529.ref007","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.cell.2007.01.029","article-title":"The epigenomics of cancer","volume":"128","author":"PA Jones","year":"2007","journal-title":"Cell"},{"issue":"1A","key":"pcbi.1010529.ref008","first-page":"A68","article-title":"The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge.","volume":"19","author":"K Tomczak","year":"2015","journal-title":"Contemporary oncology."},{"issue":"10","key":"pcbi.1010529.ref009","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1038\/s41568-020-0290-x","article-title":"A compendium of mutational cancer driver genes","volume":"20","author":"F Mart\u00ednez-Jim\u00e9nez","year":"2020","journal-title":"Nature Reviews Cancer"},{"issue":"5","key":"pcbi.1010529.ref010","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1016\/j.cell.2017.09.042","article-title":"Universal patterns of selection in cancer and somatic tissues","volume":"171","author":"I Martincorena","year":"2017","journal-title":"Cell"},{"issue":"1","key":"pcbi.1010529.ref011","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-016-0994-0","article-title":"OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations","volume":"17","author":"L Mularoni","year":"2016","journal-title":"Genome biology"},{"issue":"12","key":"pcbi.1010529.ref012","doi-asserted-by":"crossref","first-page":"1785","DOI":"10.1038\/ng.3987","article-title":"Bayesian inference of negative and positive selection in human cancers","volume":"49","author":"D Weghorn","year":"2017","journal-title":"Nature genetics"},{"issue":"8","key":"pcbi.1010529.ref013","doi-asserted-by":"crossref","first-page":"e45","DOI":"10.1093\/nar\/gkz096","article-title":"DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies","volume":"47","author":"Y Han","year":"2019","journal-title":"Nucleic acids research"},{"key":"pcbi.1010529.ref014","volume-title":"Large sample tests of statistical hypotheses concerning several parameters with applications to problems of estimation. Mathematical Proceedings of the Cambridge Philosophical Society","author":"CR Rao","year":"1948"},{"issue":"1","key":"pcbi.1010529.ref015","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1038\/msb.2012.68","article-title":"Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers","volume":"9","author":"J Reimand","year":"2013","journal-title":"Molecular systems biology"},{"issue":"12","key":"pcbi.1010529.ref016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/gb-2012-13-12-r124","article-title":"DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer","volume":"13","author":"A Bashashati","year":"2012","journal-title":"Genome biology"},{"issue":"21","key":"pcbi.1010529.ref017","doi-asserted-by":"crossref","first-page":"2757","DOI":"10.1093\/bioinformatics\/btt471","article-title":"Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting Events (TieDIE).","volume":"29","author":"EO Paull","year":"2013","journal-title":"Bioinformatics"},{"issue":"suppl_2","key":"pcbi.1010529.ref018","doi-asserted-by":"crossref","first-page":"W424","DOI":"10.1093\/nar\/gkr359","article-title":"ResponseNet: revealing signaling and regulatory networks linking genetic and transcriptomic screening data","volume":"39","author":"A Lan","year":"2011","journal-title":"Nucleic acids research"},{"key":"pcbi.1010529.ref019","doi-asserted-by":"crossref","first-page":"513","DOI":"10.3389\/fpsyg.2013.00513","article-title":"Simpson\u2019s paradox in psychological science: a practical guide.","volume":"4","author":"R Kievit","year":"2013","journal-title":"Frontiers in psychology."},{"key":"pcbi.1010529.ref020","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511803161","volume-title":"Causality","author":"J. Pearl","year":"2009"},{"issue":"2","key":"pcbi.1010529.ref021","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/S0167-5699(99)01552-2","article-title":"Rheumatoid arthritis and p53: how oxidative stress might alter the course of inflammatory diseases","volume":"21","author":"PP Tak","year":"2000","journal-title":"Immunology today"},{"issue":"1","key":"pcbi.1010529.ref022","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1006\/abbi.2001.2295","article-title":"Oxidative stress, human genetic variation, and disease","volume":"389","author":"L Forsberg","year":"2001","journal-title":"Archives of biochemistry and biophysics"},{"key":"pcbi.1010529.ref023","article-title":"Oxidative stress in cancer","author":"JD Hayes","year":"2020","journal-title":"Cancer cell"},{"key":"pcbi.1010529.ref024","doi-asserted-by":"crossref","first-page":"167","DOI":"10.3389\/fnins.2015.00167","article-title":"phMRI: methodological considerations for mitigating potential confounding factors","volume":"9","author":"JH Bourke","year":"2015","journal-title":"Frontiers in neuroscience"},{"key":"pcbi.1010529.ref025","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1016\/j.neuroimage.2018.08.022","article-title":"Chained regularization for identifying brain patterns specific to HIV infection","volume":"183","author":"E Adeli","year":"2018","journal-title":"Neuroimage"},{"issue":"1","key":"pcbi.1010529.ref026","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-19784-9","article-title":"Training confounder-free deep learning models for medical applications","volume":"11","author":"Q Zhao","year":"2020","journal-title":"Nature communications"},{"issue":"2","key":"pcbi.1010529.ref027","first-page":"79","article-title":"How to control confounding effects by statistical analysis","volume":"5","author":"MA Pourhoseingholi","year":"2012","journal-title":"Gastroenterology and hepatology from bed to bench"},{"key":"pcbi.1010529.ref028","volume-title":"Partial identification of probability distributions","author":"CF Manski","year":"2003"},{"issue":"2","key":"pcbi.1010529.ref029","doi-asserted-by":"crossref","first-page":"155","DOI":"10.2307\/2648118","article-title":"Measuring living standards with proxy variables.","volume":"37","author":"MR Montgomery","year":"2000","journal-title":"Demography"},{"key":"pcbi.1010529.ref030","article-title":"Causal effect inference with deep latent-variable models.","author":"C Louizos","year":"2017","journal-title":"arXiv preprint arXiv:170508821."},{"issue":"1","key":"pcbi.1010529.ref031","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1214\/ss\/1009211805","article-title":"Confounding and collapsibility in causal inference","volume":"14","author":"S Greenland","year":"1999","journal-title":"Statistical science"},{"issue":"20","key":"pcbi.1010529.ref032","doi-asserted-by":"crossref","first-page":"4399","DOI":"10.1158\/0008-5472.CAN-20-1031","article-title":"ERINA is an estrogen-responsive lncRNA that drives breast cancer through the E2F1\/RB1 pathway","volume":"80","author":"Z Fang","year":"2020","journal-title":"Cancer research"},{"issue":"5","key":"pcbi.1010529.ref033","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1016\/j.trecan.2019.03.005","article-title":"Cell cycle and beyond: exploiting new RB1 controlled mechanisms for cancer therapy.","volume":"5","author":"ES Knudsen","year":"2019","journal-title":"Trends in cancer."},{"key":"pcbi.1010529.ref034","doi-asserted-by":"crossref","first-page":"e10128","DOI":"10.7717\/peerj.10128","article-title":"Immunoglobulin superfamily member 10 is a novel prognostic biomarker for breast cancer","volume":"8","author":"M Wang","year":"2020","journal-title":"PeerJ"},{"issue":"4","key":"pcbi.1010529.ref035","doi-asserted-by":"crossref","first-page":"932","DOI":"10.7150\/jca.33105","article-title":"The BRAF V600E mutation is a predictor of the effect of radioiodine therapy in papillary thyroid cancer","volume":"11","author":"J Ge","year":"2020","journal-title":"Journal of Cancer"},{"key":"pcbi.1010529.ref036","first-page":"2016","article-title":"The Nrf2\/HO-1 axis in cancer cell growth and chemoresistance","author":"A Furfaro","year":"2016","journal-title":"Oxidative medicine and cellular longevity"},{"issue":"10","key":"pcbi.1010529.ref037","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1038\/s41422-020-0333-6","article-title":"Whole-genome sequencing of 508 patients identifies key molecular features associated with poor prognosis in esophageal squamous cell carcinoma","volume":"30","author":"Y Cui","year":"2020","journal-title":"Cell research"},{"issue":"4","key":"pcbi.1010529.ref038","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1007\/s00432-019-02861-y","article-title":"Aggregate analysis based on TCGA: TTN missense mutation correlates with favorable prognosis in lung squamous cell carcinoma","volume":"145","author":"X Cheng","year":"2019","journal-title":"Journal of cancer research and clinical oncology"},{"issue":"1","key":"pcbi.1010529.ref039","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/nrdp.2017.9","article-title":"Renal cell carcinoma","volume":"3","author":"JJ Hsieh","year":"2017","journal-title":"Nature reviews Disease primers"},{"issue":"6","key":"pcbi.1010529.ref040","first-page":"507","article-title":"Treatment of renal cell carcinoma: current status and future directions.","volume":"67","author":"PC Barata","year":"2017","journal-title":"CA: a cancer journal for clinicians"},{"issue":"15","key":"pcbi.1010529.ref041","doi-asserted-by":"crossref","first-page":"3785","DOI":"10.3390\/cancers13153785","article-title":"Significance of RAS Mutations in Thyroid Benign Nodules and Non-Medullary Thyroid Cancer.","volume":"13","author":"V Marotta","year":"2021","journal-title":"Cancers"},{"issue":"11","key":"pcbi.1010529.ref042","doi-asserted-by":"crossref","first-page":"1178","DOI":"10.1158\/2159-8290.CD-15-0330","article-title":"NF2 loss promotes oncogenic RAS-induced thyroid cancers via YAP-dependent transactivation of RAS proteins and sensitizes them to MEK inhibition","volume":"5","author":"ME Garcia-Rendueles","year":"2015","journal-title":"Cancer discovery"},{"key":"pcbi.1010529.ref043","first-page":"1","article-title":"Mann-Whitney U Test.","author":"PE McKnight","year":"2010","journal-title":"The Corsini encyclopedia of psychology"},{"issue":"6","key":"pcbi.1010529.ref044","doi-asserted-by":"crossref","first-page":"R341","DOI":"10.1530\/ERC-13-0364","article-title":"The dual role of filamin A in cancer: can\u2019t live with (too much of) it, can\u2019t live without it.","volume":"20","author":"RM Savoy","year":"2013","journal-title":"Endocrine-related cancer"},{"issue":"42","key":"pcbi.1010529.ref045","doi-asserted-by":"crossref","first-page":"68242","DOI":"10.18632\/oncotarget.11921","article-title":"Quantitative proteomics reveals FLNC as a potential progression marker for the development of hepatocellular carcinoma","volume":"7","author":"Y Qi","year":"2016","journal-title":"Oncotarget"},{"issue":"5","key":"pcbi.1010529.ref046","first-page":"1251","article-title":"Comparative analysis of DNA methylation between primary and metastatic gastric carcinoma","volume":"21","author":"JH Kim","year":"2009","journal-title":"Oncology reports"},{"issue":"3","key":"pcbi.1010529.ref047","doi-asserted-by":"crossref","first-page":"e12760","DOI":"10.1111\/jpi.12760","article-title":"A novel melatonin-regulated lncRNA suppresses TPA-induced oral cancer cell motility through replenishing PRUNE2 expression","volume":"71","author":"SC Su","year":"2021","journal-title":"Journal of pineal research"},{"issue":"10","key":"pcbi.1010529.ref048","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1038\/ng.2764","article-title":"The cancer genome atlas pan-cancer analysis project","volume":"45","author":"JN Weinstein","year":"2013","journal-title":"Nature genetics"},{"issue":"43","key":"pcbi.1010529.ref049","doi-asserted-by":"crossref","first-page":"15545","DOI":"10.1073\/pnas.0506580102","article-title":"Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles","volume":"102","author":"A Subramanian","year":"2005","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1010529.ref050","article-title":"Fast and accurate deep network learning by exponential linear units (elus).","author":"D-A Clevert","year":"2015","journal-title":"arXiv preprint arXiv:151107289."},{"key":"pcbi.1010529.ref051","article-title":"Auto-encoding variational bayes.","author":"DP Kingma","year":"2013","journal-title":"arXiv preprint arXiv:13126114"},{"key":"pcbi.1010529.ref052","article-title":"Tensorflow: Large-scale machine learning on heterogeneous distributed systems.","author":"M Abadi","year":"2016","journal-title":"arXiv preprint arXiv:160304467."},{"key":"pcbi.1010529.ref053","article-title":"Adam: A method for stochastic optimization.","author":"DP Kingma","year":"2014","journal-title":"arXiv preprint arXiv:14126980."},{"issue":"21","key":"pcbi.1010529.ref054","doi-asserted-by":"crossref","first-page":"e169","DOI":"10.1093\/nar\/gks743","article-title":"Functional impact bias reveals cancer drivers","volume":"40","author":"A Gonzalez-Perez","year":"2012","journal-title":"Nucleic acids research"},{"issue":"2","key":"pcbi.1010529.ref055","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1093\/bioinformatics\/btq630","article-title":"Identifying cancer driver genes in tumor genome sequencing studies","volume":"27","author":"A Youn","year":"2011","journal-title":"Bioinformatics"},{"issue":"11","key":"pcbi.1010529.ref056","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1093\/bioinformatics\/bty006","article-title":"Discovering personalized driver mutation profiles of single samples in cancer by network control strategy","volume":"34","author":"W-F Guo","year":"2018","journal-title":"Bioinformatics"}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1010529","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,27]],"date-time":"2023-11-27T14:35:32Z","timestamp":1701095732000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1010529"}},"subtitle":[],"editor":[{"given":"Serdar","family":"Bozdag","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2022,9,22]]},"references-count":56,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,9,22]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1010529","relation":{},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,22]]}}}