Tumors develop mechanisms to recruit tolerogenic immune cells and to induce the expression of molecules that act as immune checkpoints. This regulation of the immune microenvironment favors immune tolerance to the neoplastic cells. In this study, we have investigated the prognostic role of immune-checkpoint expression markers in a cohort of resectable non-small cell lung cancer (NSCLC) patients. RNA was isolated from fresh-frozen lung specimens (tumor and normal lung) (n = 178). RTqPCR was performed to analyze the relative expression of 20 immune-related genes that were normalized by the use of endogenous genes selected by GeNorm algorithm. Patients with higher expression levels of IL23A and LGALS2 presented better outcomes. In the clustering expression patterns, we observed that patients with higher expression of immunoregulatory genes had better survival rates. Additionally, these data were used to develop a gene expression score. Since CTLA4 and PD1 were associated with prognosis based on Cox regression analysis (Z-score > 1.5), a multivariate model including these two genes was created. Absolute regression coefficients from this analysis were used in order to calculate the immune-checkpoint score: (PD1×0.116) + (CTLA4×0.059) for each case. Kaplan-Meier survival analysis showed that patients with high immune-checkpoint score have longer overall survival (OS) [NR vs. 40.4 mo, p = 0.008] and longer relapse-free survival (RFS) [82.6 vs. 23 mo, p = 0.009]. Multivariate analysis in the entire cohort indicated that the immune-checkpoint score was an independent biomarker of prognosis for OS [HR: 0.308; 95% CI, 0.156-0.609; p = 0.001] and RFS [HR: 0.527; 95% CI, 0.298-0.933; p = 0.028] in early-stage NSCLC patients. In conclusion, this score provides relevant prognostic information for a better characterization of early stage NSCLS patients with strikingly different outcomes and who may be candidates for immune-based therapies.

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