Objective ‒ Data mining was applied to explore the expression, functional enrichment, and signal pathway of methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) gene in non-small cell lung cancer (NSCLC) and its relationship with patient prognosis. Methods ‒ The expression of MTHFD2 gene in NSCLC and its adjacent tissues was studied by bioinformatics data analysis. The biological function and signal pathway of MTHFD2 gene were enriched, and the MTHFD2 protein– protein interaction (PPI) network was constructed in the string database. The relationship between MTHFD2 expression and overall survival (OS), disease free survival (DFS) of NSCLC patients was analyzed in GEPIA database. Results ‒ In NSCLC patients, the expression level of MTHFD2 in cancer tissues was significantly higher than that in adjacent normal tissues (P < 0.05). There were 21 related proteins in the PPI network, and the interaction relationship between proteins was 173 with the average local clustering coefficient of 0.881. The biological process of MTHFD2 and relevant genes was mainly enriched in tetrahydrofolate metabolic process, onecarbon metabolic process, and folic acid metabolic process. The KEGG pathway of MTHFD2 and relevant genes wasmainly enriched in one carbon pool by folate, metabolic pathways, and antifolate resistance pathway. The OS of patients with high expression of MTHFD2 gene in lung adenocarcinoma (LUAD) was significantly lower than that of patients with low expression (hazard ratio [HR] = 1.6, P = 0.0041), while the expression level of MTHFD2 was not related to DFS of LUAD (HR = 1.4, P = 0.05), lung squamous cell carcinoma (LUSC; HR = 1.3, P = 0.16), and OS of LUSC (HR = 0.82, P = 0.15). MTHFD2 expression level was correlated with B cells, CD8+ T (r = 0.143, P < 0.05) and CD4+ T lymphocyte infiltration. Conclusion ‒ MTHFD2 gene is highly expressed in NSCLC and participates in the metabolism of folic acid and one carbon unit. Its high expression is related to the poor prognosis of patients and may apply as a potential new target for therapy of NSCLC. However, the primary findings are derived from bioinformatic analyses, which, while valuable, necessitate further validation through further empirical methods.
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