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Case-control analysis identifies shared properties of rare germline variation in cancer predisposing genes

By Mykyta Artomov, Vijai Joseph, Grace Tiao, Tinu Thomas, Kasmintan Schrader, Robert J Klein, Adam Kiezun, Namrata Gupta, Lauren Margolin, Alexander J. Stratigos, Ivana Kim, Kristen Shannon, Leif W. Ellisen, Daniel Haber, Gad Getz, Hensin Tsao, Stephen M. Lipkin, David Altshuler, Kenneth Offit, Mark J Daly

Posted 12 Jul 2017
bioRxiv DOI: 10.1101/162479 (published DOI: 10.1038/s41431-019-0346-0)

Traditionally, genetic studies in cancer are focused on somatic mutations found in tumors and absent from the normal tissue. Identification of shared attributes in germline variation could aid discrimination of high-risk from likely benign mutations and narrow the search space for new cancer predisposing genes. Extraordinary progress made in analysis of common variation with GWAS methodology does not provide sufficient resolution to understand rare variation. To fulfill missing classification for rare germline variation we assembled datasets of whole exome sequences from >2,000 patients with different types of cancers: breast cancer, colon cancer and cutaneous and ocular melanomas matched to more than 7,000 non-cancer controls and analyzed germline variation in known cancer predisposing genes to identify common properties of disease associated mutations and new candidate cancer susceptibility genes. Lists of all cancer predisposing genes were divided into subclasses according to the mode of inheritance of the related cancer syndrome or contribution to known major cancer pathways. Out of all subclasses only genes linked to dominant syndromes presented significant rare germline variants enrichment in cases. Separate analysis of protein-truncating and missense variation in this subclass of genes confirmed significant prevalence of protein-truncating variants in cases only in loss-of-function tolerant genes (pLI<0.1), while ultra-rare missense mutations were significantly overrepresented in cases only in constrained genes (pLI>0.9). Taken together, our findings provide insights into the distribution and types of mutations underlying inherited cancer predisposition.

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