Unveiling the prognostic and immunotherapeutic role of Tregs in lung cancer using integrated analysis of single‑cell and bulk RNA‑sequencing

The infiltration of regulatory T cells (Tregs) in lung adenocarcinoma (LUAD) is associated with a poor prognosis. The present study aimed to explore the potential function of Treg marker genes in prognosis and immunotherapy using the transcriptome profiles of five LUAD cohorts sourced from public databases. Among them, the single‑cell dataset GSE131907 was employed to identify cell types in lung cancer tissues and to identify Treg markers. The prognostic Treg markers were screened using univariate Cox and Least Absolute Shrinkage and Selection Operator regression analyses. Subsequently, a prognostic model was constructed and assessed using Kaplan‑Meier and receiver operating characteristic curves. Furthermore, the effect of prognostic Treg markers on clinical characteristics, the immune microenvironment and tumor mutation burden (TMB) were evaluated. In addition, the function of genes strongly correlated with the prognostic risk score were investigated using Spearman and functional enrichment analysis. Finally, the genes expression levels were assessed using reverse transcription‑quantitative PCR (RT‑qPCR) and western blotting. By analyzing the single‑cell data, 13 Treg markers [centromere protein M (CENPM), pituitary tumor‑transforming gene 1 protein, interleukin 1 receptor type 2, baculoviral IAP repeat containing 3, glucocorticoid induced 1 (GLCCI1), melanoma‑associated antigen H1 (MAGEH1), CD5, cytokine inducible SH2 containing protein, zinc finger protein 101 (ZNF101), Ikaros family zinc finger protein 4 (IKZF4), ankyrin repeat and SOCS box protein 2, zinc finger CCCH‑type containing 12D and C‑C motif chemokine receptor 6] were identified as prognostic features. The prognostic model constructed using these 13 genes revealed that the high‑risk group had a poorer prognosis than the low‑risk group. Moreover, it was demonstrated that the risk score could be an independent prognostic factor affecting the prognosis of patients with LUAD. Additionally, the high‑risk group had a lower ESTIMATE score, higher TMB score and lower T cell receptor richness than the low‑risk group. Finally, RT‑qPCR and western blotting showed that the expression levels of CENPM, ZNF101, MAGEH1 and IKZF4 were significantly altered in cancer tissues compared with the adjacent normal tissues. In conclusion, a reliable prognostic model based on 13 Treg markers was developed. The comprehensive characterization of the Treg markers of LUAD may help to monitor the prognosis and provide new strategies for LUAD treatment.