Two predicted models based on ceRNAs and immune cells in lung adenocarcinoma

It is well accepted that both competitive endogenous RNAs (ceRNAs) and immune microenvironment exert crucial roles in the tumor prognosis. The present study aimed to find prognostic ceRNAs and immune cells in lung adenocarcinoma (LUAD).

More specifically, we explored the associations of crucial ceRNAs with the immune microenvironment. The Cancer Genome Atlas (TCGA) database was employed to obtain expression profiles of ceRNAs and clinical data. CIBERSORT was utilized to quantify the proportion of 22 immune cells in LUAD.

We constructed two cox regression models based on crucial ceRNAs and immune cells to predict prognosis in LUAD. Subsequently, seven ceRNAs and seven immune cells were involved in prognostic models. We validated both predicted models via an independent cohort GSE72094. Interestingly, both predicted models proved that the longer patients were smoking, the higher risk scores would be obtained. We further investigated the relationships between seven genes and immune/stromal scores via the ESTIMATE algorithm. The results indicated that CDC14A and H1F0 expression were significantly related to stromal scores/immune scores in LUAD. Moreover, based on the result of the ceRNA model, single-sample gene set enrichment analysis (ssGSEA) suggested that differences in immune status were evident between high- and low-risk groups.