Potentially functional genetic variants in the TNF/TNFR signaling pathway genes predict survival of patients with non-small cell lung cancer in the PLCO cancer screening trial.

The tumor necrosis factor (TNF)/TNF receptor (TNFR) pathway is known to influence survival of patients with cancer. We hypothesize that single nucleotide polymorphisms (SNPs) in the TNF/TNFR pathway genes related to apoptosis are associated with survival of patients with non-small cell lung cancer (NSCLC). We used 1185 patients with NSCLC in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and 984 patients with NSCLC in the Harvard Lung Cancer Susceptibility Study as the discovery and validation datasets, respectively. We selected 6788 SNPs in 71 genes in the TNF/TNFR signaling pathway and extracted their genotyping data from the PLCO genowide-association study (GWAS) dataset. We performed Cox proportional hazards regression analysis to evaluate associations between the identified SNPs and survival and validated the significant SNPs, which were further analyzed for their functional relevance. We found that genotypes of two validated SNPs, IKBKAP rs4978754 CT + TT and TNFRSF1B rs677844 TC + CC, as well as their combined genotypes predicted a better overall survival (P = 0.004, 0.002 and <0.001, respectively). These two validated SNPs were predicted by the RegulomeDB score to be potentially functional. In addition, IKBKAP mRNA expression levels were significantly higher, while TNFRSF1B mRNA expression levels were significantly lower in lung cancer tissues than in adjacent normal tissues (P < 0.001). The Cancer Genome Atlas (TCGA)-based expression quantitative trait loci analysis showed that IKBKAP rs4978754 and TNFRSF1B rs677844 genotypes were significantly associated with their corresponding mRNA expression levels in lung cancer tissues in a recessive model (P = 0.035 and 0.045, respectively). Therefore, we identified two potentially functional SNPs (IKBKAP rs4978754 C > T and TNFRSF1B rs677844 T > C) to be associated with survival of patients with NSCLC.

Duke Scholars

Author Sheng Luo Biostatistics & Bioinformatics, Division of Biostatistics

Author Patricia Gripka Moorman Family Medicine and Community Health, Prevention Research

Author Qingyi Wei Population Health Sciences