Novel genetic variants in KIF16B and NEDD4L in the endosome-related genes are associated with nonsmall cell lung cancer survival.

The endosome is a membrane-bound organ inside most eukaryotic cells, playing an important role in adaptive immunity by delivering endocytosed antigens to both MHC class I and II pathways. Here, by analyzing genotyping data from two published genome-wide association studies (GWASs), we evaluated associations between genetic variants in the endosome-related gene-set and survival of patients with nonsmall cell lung cancer (NSCLC). The discovery included 44,112 (3,478 genotyped and 40,634 imputed) single-nucleotide polymorphisms (SNPs) in 220 genes in a singlelocus analysis for their associations with survival of 1,185 NSCLC patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. After validation of the 821 survival-associated significant SNPs in additional 984 NSCLC patients from the Harvard Lung Cancer Susceptibility Study, 14 SNPs remained significant. The final multivariate stepwise Cox proportional hazards regression modeling of the PLCO dataset identified three potentially functional and independent SNPs (i.e., KIF16B rs1555195 C>T, NEDD4L rs11660748 A>G and rs73440898 A>G) with an adjusted hazards ratio (HR) of 0.86 (95% confidence interval [CI] = 0.79-0.94, p = 0.0007), 1.31 (1.16-1.47, p = 6.0 × 10-5 ) and 1.27 (1.12-1.44, p = 0.0001) for overall survival (OS), respectively. Combined analysis of the adverse genotypes of these three SNPs revealed a trend in the genotype-survival association (ptrend < 0.0001 for OS and ptrend < 0.0001 for disease-specific survival). Furthermore, the survival-associated KIF16B rs1555195T allele was significantly associated with decreased mRNA expression levels of KIF16B in both lung tissues and blood cells. Therefore, genetic variants of the endosome-related genes may be biomarker for NSCLC survival, possibly through modulating the expression of corresponding genes.

Duke Scholars

Author Sheng Luo Biostatistics & Bioinformatics, Division of Biostatistics

Author Carolyn Glass Pathology

Author Qingyi Wei Population Health Sciences