Introduction: Black/white disparities in lung cancer incidence and mortality mandate an evaluation of underlying biological differences. We have previously shown higher risks of lung cancer associated with prior emphysema in African American compared with white patients with lung cancer.
Methods: We therefore evaluated a panel of 1440 inflammatory gene variants in a two-phase analysis (discovery and replication), added top genome-wide association studies (GWAS) lung cancer hits from white populations, and 28 single-nucleotide polymorphisms (SNPs) from a published gene panel. The discovery set (477 self-designated African Americans cases, 366 controls matched on age, ethnicity, and gender) were from Houston, Texas. The external replication set (330 cases and 342 controls) was from the EXHALE study at Wayne State University.
Results: In discovery, 154 inflammation SNPs were significant (p < 0.05) on univariate analysis, as was one of the gene panel SNPs (rs308738 in REV1, p = 0.0013), and three GWAS hits, rs16969968 p = 0.0014 and rs10519203 p = 0.0003 in the 15q locus and rs2736100, in the HTERT locus, p = 0.0002. One inflammation SNP, rs950286, was successfully replicated with a concordant odds ratio of 1.46 (1.14-1.87) in discovery, 1.37 (1.05-1.77) in replication, and a combined odds ratio of 1.40 (1.17-1.68). This SNP is intergenic between IRF4 and EXOC2 genes. We also constructed and validated epidemiologic and extended risk prediction models. The area under the curve (AUC) for the epidemiologic discovery model was 0.77 and 0.80 for the extended model. For the combined datasets, the AUC values were 0.75 and 0.76, respectively.
Conclusions: As has been reported for other cancer sites and populations, incorporating top genetic hits into risk prediction models, provides little improvement in model performance and no clinical relevance.