Hypoxia-related lncRNAs to build prognostic classifier and reveal the immune characteristics of EGFR wild type and low expression of PD-L1 squamous and adenocarcinoma NSCLC.

Background Recently, the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have achieved remarkable survival benefits in non-small cell lung cancer (NSCLC) treatment. However, epidermal growth factor receptor (EGFR) wild type and low expression of programmed death-ligand 1 (PD-L1) NSCLC remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a hypoxia-related lncRNAs (hypolncRNAs) classifier that could successfully identify the high-risk patients and reveal its underlying molecular immunology characteristics. Methods By identifying the bottom 25% PD-L1 expression level as low expression of PD-L1 and removing EGFR mutant samples, a total of 222 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) samples and 93 adjacent non-tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). A 0 or 1 matrix was constructed by cyclically pairing hypoxia-related long non-coding RNAs (hypolncRNAs) and divided into the train set and test set. The univariate Cox regression analysis determined the prognostic hypolncRNAs pairs. Then, the prognostic classifier contained nine hypolncRNAs pairs which were generated by Lasso regression and multivariate Cox analysis. It successfully stratified EGFR wild type and low expression of PD-L1 squamous and adenocarcinoma NSCLC (double-negative LUAD and LUSC) patients into the high- and low-risk groups, whose accuracy was proved by the time-dependent receiver operating characteristic (ROC) curve. Furthermore, diverse acknowledged immunology methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT-ABS, CIBERSORT, and the single-sample gene set enrichment analysis (ssGSEA) revealed its underlying antitumor immunosuppressive status in the high-risk patients. Conclusions It is noteworthy that hypolncRNAs are associated with the survival of double-negative LUAD and LUSC patients, for which the possible mechanism is inhibiting the antitumor immune process.