Guojun Lu ^1* Hongliang Liu ² Huilin Wang ³ Xiaozhun Tang ³ Sheng Luo ⁴ Mulong Du ⁵ David C. Christiani ⁶ Qingyi Wei ^2*

• ¹ Department of Respiratory Medicine, Nanjing Chest Hospital, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, Liaoning Province, China
• ² Duke Cancer Institute, School of Medicine, Duke University, Durham, North Carolina, United States
• ³ Guangxi Medical University Cancer Hospital, Nanning, Guangxi Zhuang Region, China
• ⁴ Department of Biostatistics and Bioinformatics, School of Medicine, Duke University, Durham, North Carolina, United States
• ⁵ Department of Environmental Health, School of Public Health, Harvard University, Boston, Massachusetts, United States
• ⁶ Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States

Background: T cell exhaustion is a state in which T cells become dysfunctional and is associated with a decreased efficacy of immune checkpoint inhibitors. Lung cancer has the highest mortality among all cancers. However, the roles of genetic variants of the T cell exhaustion-related genes in the prognosis of non-small cell lung cancer (NSCLC) patients has not been reported. Methods: We conducted a two-stage multivariable Cox proportional hazards regression analysis with two previous genome-wide association study (GWAS) datasets to explore associations between genetic variants in the T cell exhaustion-related genes and survival of NSCLC patients. We also performed expression quantitative trait loci analysis for functional validation of the identified variants. Results: Of all the 52,103 single nucleotide polymorphisms (SNPs) in 672 T cell exhaustion-related genes, 1,721 SNPs were found to be associated with overall survival (OS) of 1185 NSCLC patients of the discovery GWAS dataset from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, and 125 of these 1,721 SNPs remained significant after validation in an additional independent replication GWAS dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. After multivariable stepwise Cox model analysis, three independent SNPs (i.e., LRRC8C rs10493829 T>C, OAS2 rs2239193 A>G, and CCL25 rs3136651 T>A) remained significantly associated with OS with hazards ratios (HRs) of 0.86 (95% confidence interval (CI) = 0.77-0.96, P = 0.008), 1.48 (95% CI = 1.18-1.85, P < 0.0001) and 0.78 (95% CI = 0.66-0.91, P = 0.002), respectively. Further combined analysis for these three SNPs suggested that an unfavorable genotype score was associated with a poor OS and disease-specific survival. Expression quantitative trait loci analysis suggested that the LRRC8C rs10493829 C allele was associated with elevated LRRC8C mRNA expression levels in normal lymphoblastoid cells, lung tissue, and whole blood. Conclusion: Our findings suggested that these functional SNPs in the T cell exhaustion-related genes may be prognostic predictors for survival of NSCLC patients, possibly via a mechanism of modulating corresponding gene expression.