生物
卵巢癌
鉴定(生物学)
上皮性卵巢癌
遗传学
计算生物学
癌症
生态学
作者
Catherine M. Phelan,Karoline Kuchenbaecker,Jonathan P. Tyrer,Siddhartha Kar,Kate Lawrenson,Stacey J. Winham,Joe Dennis,Ailith Pirie,Marjorie J. Riggan,Ganna Chornokur,Madalene A. Earp,Paulo C. Lyra,Janet M. Lee,Simon G. Coetzee,Jonathan Beesley,Lesley McGuffog,Penny Soucy,Ed Dicks,Andrew Lee,Daniel Barrowdale
出处
期刊:Nature Genetics
[Nature Portfolio]
日期:2017-03-27
卷期号:49 (5): 680-691
被引量:468
摘要
Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1. To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.
科研通智能强力驱动
Strongly Powered by AbleSci AI