Open AccessSystematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
Author(s) -
Shi Zhuqing,
Yu Hongjie,
Wu Yishuo,
Lin Xiaoling,
Bao Quanwa,
Jia Haifei,
Perschon Chelsea,
Duggan David,
Helfand Brian T.,
Zheng Siqun L.,
Xu Jianfeng
Publication year - 2019
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.2143
Subject(s) - medicine , oncology , cancer , prostate cancer , colorectal cancer , population , bladder cancer , single nucleotide polymorphism , breast cancer , thyroid cancer , odds ratio , genotype , biology , genetics , environmental health , gene
Background Genetic risk score (GRS) is an odds ratio (OR)‐weighted and population‐standardized method for measuring cumulative effect of multiple risk‐associated single nucleotide polymorphisms (SNPs). We hypothesize that GRS is a valid tool for risk assessment of most common cancers. Methods Utilizing genotype and phenotype data from The Cancer Genome Atlas (TCGA) and Electronic Medical Records and Genomics (eMERGE), we tested 11 cancer‐specific GRSs (bladder, breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, prostate, renal, and thyroid cancer) for association with the respective cancer type. Cancer‐specific GRSs were calculated, for the first time in these cohorts, based on previously published risk‐associated SNPs using the Caucasian subjects in these two cohorts. Results Mean cancer‐specific GRS in the population controls of eMERGE approximated the expected value of 1.00 (between 0.98 and 1.02) for all 11 types of cancer. Mean cancer‐specific GRS was consistently higher in respective cancer patients than controls for all 11 types of cancer ( P < 0.05). When subjects were categorized into low‐, average‐, and high‐risk groups based on cancer‐specific GRS (<0.5, 0.5‐1.5, and >1.5, respectively), significant dose‐response associations of higher cancer‐specific GRS with higher OR of respective type of cancer were found for nine types of cancer ( P ‐trend < 0.05). More than 64% subjects in the population controls of eMERGE can be classified as high risk for at least one type of these cancers. Conclusion Validity of GRS for predicting cancer risk is demonstrated for most types of cancer. If confirmed in larger studies, cancer‐specific GRS may have the potential for developing personalized cancer screening strategy.