and are potential targets of immunotherapy in non-small cell lung cancer.

BACKGROUND

Immune checkpoint inhibitors (ICIs) are clinically effective in the treatment of non-small cell lung cancer (NSCLC), but the response rate in nonselective NSCLC patients is approximately 20%. It is important to expand the pool of benefits of immunotherapy. However, current solution strategies are limited. Our research is to identify new targets for combined immunotherapy and expand the beneficiary population of immunotherapy.

METHODS

Functional enrichment analysis was performed for differentially expressed genes (DEGs) in 175 NSCLC immunotherapy cohorts and 494 non-immunotherapy cohorts, and single-sample gene set enrichment analysis (ssGSEA) was used to quantify the level of infiltration of different immune cell subpopulations. Weighted correlation network analysis (WGCNA), univariate Cox regressions, least absolute shrinkage and selection operator (LASSO) regressions, and gene correlation analysis were applied to identify immune signature genes associated with immune cell infiltration, and a nomogram was constructed to predict the survival rate.

RESULTS

The DEGs were not enriched in the classical antitumour immune response and the dendritic cells (DCs) infiltration level in the tumour microenvironment (TME) was at a low level in the immunotherapy cohort. The high expression of and was positively correlated with the level of DCs infiltration, the core of tumour immune response regulation, and can bring better survival prognosis for patients. Besides, targeted activation of and can improve the efficacy of ICIs.

CONCLUSIONS

High expression of and enhances the antitumour immune response, and and may be new prognostic indicators and targets of combined ICIs for lung adenocarcinoma in NSCLC.