Potentially functional variants of PARK7 and DDR2 in ferroptosis-related genes predict survival of non-small cell lung cancer patients.

Ferroptosis, a form of regulated cell death, is characterized by iron-dependent lipid peroxidation. It is recognized increasingly for its pivotal role in both cancer development and the response to cancer treatments. We assessed associations between 370,027 single-nucleotide polymorphisms (SNPs) within 467 ferroptosis-related genes and survival of non-small cell lung cancer (NSCLC) patients. Data from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial served as our discovery dataset, while the Harvard Lung Cancer Susceptibility Study used as our validation dataset. For SNPs that remained statistically significantly associated with overall survival (OS) in both datasets, we employed a multivariable stepwise Cox proportional hazards regression model with the PLCO dataset. Ultimately, two independent SNPs, PARK7 rs225120 C>T and DDR2 rs881127 T>C, were identified with adjusted hazard ratios of 1.32 (95% confidence interval = 1.15-1.52, p = .0001) and 1.34 (95% confidence interval = 1.09-1.64, p = .006) for OS, respectively. We aggregated these two SNPs into a genetic score reflecting the number of unfavorable genotypes (NUG) in further multivariable analysis, revealing a noteworthy association between increased NUG and diminished OS (ptrend = .001). Additionally, an expression quantitative trait loci analysis indicated that PARK7 rs225120T genotypes were significantly associated with higher PARK7 mRNA expression levels in both whole blood and normal lung tissue. Conversely, DDR2 rs881127C genotypes were significantly associated with lower DDR2 mRNA expression levels in normal lung tissue. Our findings suggest that genetic variants in the ferroptosis-related genes PARK7 and DDR2 are associated with NSCLC survival, potentially through their influence on gene expression levels.

Duke Scholars

Author Sheng Luo Biostatistics & Bioinformatics, Division of Biostatistics

Author Qingyi Wei Population Health Sciences