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Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts

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: Util...

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Autores principales: Shi, Zhuqing, Yu, Hongjie, Wu, Yishuo, Lin, Xiaoling, Bao, Quanwa, Jia, Haifei, Perschon, Chelsea, Duggan, David, Helfand, Brian T., Zheng, Siqun L., Xu, Jianfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558466/
https://www.ncbi.nlm.nih.gov/pubmed/30968590
http://dx.doi.org/10.1002/cam4.2143
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author Shi, Zhuqing
Yu, Hongjie
Wu, Yishuo
Lin, Xiaoling
Bao, Quanwa
Jia, Haifei
Perschon, Chelsea
Duggan, David
Helfand, Brian T.
Zheng, Siqun L.
Xu, Jianfeng
author_facet Shi, Zhuqing
Yu, Hongjie
Wu, Yishuo
Lin, Xiaoling
Bao, Quanwa
Jia, Haifei
Perschon, Chelsea
Duggan, David
Helfand, Brian T.
Zheng, Siqun L.
Xu, Jianfeng
author_sort Shi, Zhuqing
collection PubMed
description 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.
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spelling pubmed-65584662019-06-13 Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts Shi, Zhuqing Yu, Hongjie Wu, Yishuo Lin, Xiaoling Bao, Quanwa Jia, Haifei Perschon, Chelsea Duggan, David Helfand, Brian T. Zheng, Siqun L. Xu, Jianfeng Cancer Med Cancer Prevention 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. John Wiley and Sons Inc. 2019-04-09 /pmc/articles/PMC6558466/ /pubmed/30968590 http://dx.doi.org/10.1002/cam4.2143 Text en © 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Cancer Prevention
Shi, Zhuqing
Yu, Hongjie
Wu, Yishuo
Lin, Xiaoling
Bao, Quanwa
Jia, Haifei
Perschon, Chelsea
Duggan, David
Helfand, Brian T.
Zheng, Siqun L.
Xu, Jianfeng
Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
title Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
title_full Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
title_fullStr Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
title_full_unstemmed Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
title_short Systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in The Cancer Genome Atlas and Electronic Medical Records and Genomics cohorts
title_sort systematic evaluation of cancer‐specific genetic risk score for 11 types of cancer in the cancer genome atlas and electronic medical records and genomics cohorts
topic Cancer Prevention
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558466/
https://www.ncbi.nlm.nih.gov/pubmed/30968590
http://dx.doi.org/10.1002/cam4.2143
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