Association of cancer susceptibility variants with risk of multiple primary cancers: The population architecture using genomics and epidemiology study

Background: Multiple primary cancers account for approximately 16% of all incident cancers in the United States. Although genome-wide association studies (GWAS) have identified many common genetic variants associated with various cancer sites, no study has examined the association of these genetic variants with risk of multiple primary cancers (MPC). Methods: As part of the National Human Genome Research Institute (NHGRI) Population Architecture using Genomics and Epidemiology (PAGE) study, we used data from the Multiethnic Cohort (MEC) and Women's Health Initiative (WHI). Incident MPC (IMPC) cases (n = 1,385) were defined as participants diagnosed with more than one incident cancer after cohort entry. Participants diagnosed with only one incident cancer after cohort entry with follow-up equal to or longer than IMPC cases served as controls (single-index cancer controls; n = 9,626). Fixed-effects meta-analyses of unconditional logistic regression analyses were used to evaluate the associations between 188 cancer risk variants and IMPC risk. To account for multiple comparisons, we used the false-positive report probability (FPRP) to determine statistical significance. Results: A nicotine dependence-associated and lung cancer variant, CHRNA3 rs578776 [OR, 1.16; 95% confidence interval (CI), 1.05-1.26; P = 0.004], and two breast cancer variants, EMBP1 rs11249433 and TOX3 rs3803662 (OR, 1.16; 95% CI, 1.04-1.28; P = 0.005 and OR, 1.13; 95% CI, 1.03-1.23; P = 0.006), were significantly associated with risk of IMPC. The associations for rs578776 and rs11249433 remained (P < 0.05) after removing subjects who had lung or breast cancers, respectively (P ≤ 0.046). These associations did not show significant heterogeneity by smoking status (P_{heterogeneity} ≥ 0.53). Conclusions: Our study has identified rs578776 and rs11249433 as risk variants for IMPC. Impact: These findings may help to identify genetic regions associated with IMPC risk.