Clinical Trial, Phase III
Journal Article
Multicenter Study
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
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Genome-wide association studies of survival in 1520 cancer patients treated with bevacizumab-containing regimens.

Germline variants might predict cancer progression. Bevacizumab improves overall survival (OS) in patients with advanced cancers. No biomarkers are available to identify patients that benefit from bevacizumab. A meta-analysis of genome-wide association studies (GWAS) was conducted in 1,520 patients from Phase III trials (CALGB 80303, 40503, 80405 and ICON7), where bevacizumab was randomized to treatment without bevacizumab. We aimed to identify genes and single nucleotide polymorphisms (SNPs) associated with survival independently of bevacizumab treatment or through interaction with bevacizumab. A cause-specific Cox model was used to test the SNP-OS association in both arms combined (prognostic), and the effect of SNPs-bevacizumab interaction on OS (predictive) in each study. The SNP effects across studies were combined using inverse variance. Findings were tested for replication in advanced colorectal and ovarian cancer patients from The Cancer Genome Atlas (TGCA). In the GWAS meta-analysis, patients with rs680949 in PRUNE2 experienced shorter OS compared to patients without it (P = 1.02 × 10-7 , hazard ratio [HR] = 1.57, 95% confidence interval [CI] 1.33-1.86), as well as in TCGA (P = .0219, HR = 1.58, 95% CI 1.07-2.35). In the GWAS meta-analysis, patients with rs16852804 in BARD1 experienced shorter OS compared to patients without it (P = 1.40 × 10-5 , HR = 1.51, 95% CI 1.25-1.82) as well as in TCGA (P = 1.39 × 10-4 , HR = 3.09, 95% CI 1.73-5.51). Patients with rs3795897 in AGAP1 experienced shorter OS in the bevacizumab arm compared to the nonbevacizumab arm (P = 1.43 × 10-5 ). The largest GWAS meta-analysis of bevacizumab treated patients identified PRUNE2 and BARD1 (tumor suppressor genes) as prognostic genes of colorectal and ovarian cancer, respectively, and AGAP1 as a potentially predictive gene that interacts with bevacizumab with respect to patient survival.

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