The pan-cancer landscape of prognostic germline variants in 10,582 patients

dc.contributor.author Chatrath, Ajay
dc.contributor.author Przanowska, Roza
dc.contributor.author Kiran, Shashi
dc.contributor.author Su, Zhangli
dc.contributor.author Saha, Shekhar
dc.contributor.author Wilson, Briana
dc.contributor.author Tsunematsu, Takaaki
dc.contributor.author Ahn, Ji Hye
dc.contributor.author Lee, Kyung Yong
dc.contributor.author Paulsen, Teressa
dc.contributor.author Sobierajska, Ewelina
dc.contributor.author Kiran, Manjari
dc.contributor.author Tang, Xiwei
dc.contributor.author Li, Tianxi
dc.contributor.author Kumar, Pankaj
dc.contributor.author Ratan, Aakrosh
dc.contributor.author Dutta, Anindya
dc.date.accessioned 2022-03-27T04:56:32Z
dc.date.available 2022-03-27T04:56:32Z
dc.date.issued 2020-02-17
dc.description.abstract Background: While clinical factors such as age, grade, stage, and histological subtype provide physicians with information about patient prognosis, genomic data can further improve these predictions. Previous studies have shown that germline variants in known cancer driver genes are predictive of patient outcome, but no study has systematically analyzed multiple cancers in an unbiased way to identify genetic loci that can improve patient outcome predictions made using clinical factors. Methods: We analyzed sequencing data from the over 10,000 cancer patients available through The Cancer Genome Atlas to identify germline variants associated with patient outcome using multivariate Cox regression models. Results: We identified 79 prognostic germline variants in individual cancers and 112 prognostic germline variants in groups of cancers. The germline variants identified in individual cancers provide additional predictive power about patient outcomes beyond clinical information currently in use and may therefore augment clinical decisions based on expected tumor aggressiveness. Molecularly, at least 12 of the germline variants are likely associated with patient outcome through perturbation of protein structure and at least five through association with gene expression differences. Almost half of these germline variants are in previously reported tumor suppressors, oncogenes or cancer driver genes with the other half pointing to genomic loci that should be further investigated for their roles in cancers. Conclusions: Germline variants are predictive of outcome in cancer patients and specific germline variants can improve patient outcome predictions beyond predictions made using clinical factors alone. The germline variants also implicate new means by which known oncogenes, tumor suppressor genes, and driver genes are perturbed in cancer and suggest roles in cancer for other genes that have not been extensively studied in oncology. Further studies in other cancer cohorts are necessary to confirm that germline variation is associated with outcome in cancer patients as this is a proof-of-principle study.
dc.identifier.citation Genome Medicine. v.12(1)
dc.identifier.uri 10.1186/s13073-020-0718-7
dc.identifier.uri https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-020-0718-7
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/7582
dc.subject Cancer biology
dc.subject Driver gene
dc.subject eQTL
dc.subject Germline variants
dc.subject Non-synonymous mutation
dc.subject Oncogene
dc.subject Pan-cancer
dc.subject Single nucleotide polymorphism
dc.subject Survival analysis
dc.subject Tumor suppressor
dc.title The pan-cancer landscape of prognostic germline variants in 10,582 patients
dc.type Journal. Article
dspace.entity.type
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