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  • Genome-wide association stu...
    Labadie, Julia D; Savas, Sevtap; Harrison, Tabitha A; Banbury, Barb; Huang, Yuhan; Buchanan, Daniel D; Campbell, Peter T; Gallinger, Steven J; Giles, Graham G; Gunter, Marc J; Hoffmeister, Michael; Hsu, Li; Jenkins, Mark A; Lin, Yi; Ogino, Shuji; Phipps, Amanda I; Slattery, Martha L; Steinfelder, Robert S; Sun, Wei; Van Guelpen, Bethany; Hua, Xinwei; Figuieredo, Jane C; Pai, Rish K; Nassir, Rami; Qi, Lihong; Chan, Andrew T; Peters, Ulrike; Newcomb, Polly A

    Scientific reports, 01/2022, Letnik: 12, Številka: 1
    Journal Article

    Identification of new genetic markers may improve the prediction of colorectal cancer prognosis. Our objective was to examine genome-wide associations of germline genetic variants with disease-specific survival in an analysis of 16,964 cases of colorectal cancer. We analyzed genotype and colorectal cancer-specific survival data from a consortium of 15 studies. Approximately 7.5 million SNPs were examined under the log-additive model using Cox proportional hazards models, adjusting for clinical factors and principal components. Additionally, we ran secondary analyses stratifying by tumor site and disease stage. We used a genome-wide p-value threshold of 5 × 10 to assess statistical significance. No variants were statistically significantly associated with disease-specific survival in the full case analysis or in the stage-stratified analyses. Three SNPs were statistically significantly associated with disease-specific survival for cases with tumors located in the distal colon (rs698022, HR = 1.48, CI 1.30-1.69, p = 8.47 × 10 ) and the proximal colon (rs189655236, HR = 2.14, 95% CI 1.65-2.77, p = 9.19 × 10 and rs144717887, HR = 2.01, 95% CI 1.57-2.58, p = 3.14 × 10 ), whereas no associations were detected for rectal tumors. Findings from this large genome-wide association study highlight the potential for anatomical-site-stratified genome-wide studies to identify germline genetic risk variants associated with colorectal cancer-specific survival. Larger sample sizes and further replication efforts are needed to more fully interpret these findings.