Characteristics of folic acid metabolism-related genes unveil prognosis and treatment strategy in lung adenocarcinoma.

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Folic acid metabolism-related genes (FAMGs) have received increased attention because of their distinct role in DNA synthesis and repair. Nevertheless, the function of FAMGs in LUAD remains ambiguous.

METHODS

LUAD transcriptome data from GEO and TCGA were analyzed. Patients were classified into two clusters based on gene expression levels, revealing distinct overall survival (OS) outcomes. Common differentially expressed genes (DEGs) were identified between LUAD and normal tissues, as well as between the two clusters. A prognostic risk model was established using Cox regression analysis to predict outcomes of LUAD patients and was validated with Kaplan-Meier and ROC curve analysis. Clinical correlations and enrichment analyses were carried out to explore the functions of DEGs and their associations with clinical characteristics of LUAD patients. The tumor microenvironment and drug sensitivity were evaluated between two risk subgroups. Moreover, expression levels of prognostic genes were validated across datasets using the Wilcoxon-test.

RESULTS

The study identified seventy-seven common DEGs and nine prognostic genes (ANLN, PLK1, DLGAP5, PRC1, CYP4B1, MKI67, KIF23, BIRC5, TK1). The risk model could effectively predict the prognosis of LUAD patients. Clinical correlation analysis revealed that age, pathologic-T, pathologic-N, and tumor stage were significantly correlated with the risk score. Enrichment analysis showed that DEGs between the two risk subgroups were predominantly enriched in cell cycle and cellular senescence pathways. Differences in immune cell infiltration and immunotherapy markers were markedly noted between the two risk subgroups. Drug sensitivity analysis disclosed significantly diverse responses to sixty-eight drugs between the two risk subgroups. Consistent expression tendencies of prognostic genes were observed across datasets.

CONCLUSION

The prognostic model based on FAMGs demonstrates considerable potential for guiding diagnosis and clinical management of LUAD patients.