Clinical risk prediction in lung adenocarcinoma using MAL gene and tumor microenvironment features

利用MAL基因和肿瘤微环境特征预测肺腺癌的临床风险

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Abstract

BACKGROUND: The tumor microenvironment (TME) plays a pivotal role in the progression and treatment response of lung adenocarcinoma (LUAD). This study established a TME-derived prognostic signature and investigated the role of MAL. METHODS: LUAD data from TCGA and GEO were utilized to identify molecular subtypes through NMF clustering of TME-related genes. A six-gene prognostic signature (MAL, PLEK2, GPI, VGLL3, LPGAT1, CTLA4) was developed using Cox regression, followed by internal and external validation. MAL’s biological functions were examined in vitro via siRNA-mediated knockdown in A549 cells. RESULTS: NMF clustering of TME-related genes revealed two distinct subtypes (C1 and C2) with significant differences in overall survival (OS) and progression-free survival (PFS). The six-gene prognostic signature was constructed, and patients in the high-risk group exhibited significantly worse OS in both the TCGA cohort (P < 0.001) and the external validation cohort (P < 0.001). The risk score emerged as an independent prognostic factor, inversely correlating with CD8 + T cell infiltration and tumor mutation burden (TMB). Functional assays demonstrated that MAL knockdown enhanced proliferation, migration, invasion, and PD-L1 expression in LUAD cells, suggesting its potential role as a tumor suppressor. Clinically, reduced MAL expression correlated with poorer survival, decreased CD8 + T cell infiltration, and more advanced disease. CONCLUSION: This study presents a robust TME-based six-gene prognostic model for LUAD risk stratification. MAL was identified as a key tumor suppressor that inhibits malignancy and modulates the immune microenvironment through PD-L1 regulation. These findings provide valuable prognostic insights and position MAL as a potential therapeutic target in LUAD.

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