Abstract
OBJECTIVE: Mesothelioma (MESO) is a rare tumor derived from mesothelium cells. The aim of this study was to explore key candidate genes and potential molecular mechanisms for mesothelioma through bioinformatics analysis. METHODS: The MESO expression profiles came from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The differences in the infiltration levels of immune cells between MESO and normal tissues were assessed using CIBERSORT. Differentially expressed genes (DEGs) were identified by comprehensive analysis of multiple datasets. A protein-protein interaction (PPI) network was constructed, and a hub gene COL1A1 was selected for MESO. The expression and mutation of COL1A1 in MESO were analyzed in the cBioPortal database. The correlation between COL1A1 expression and immune cell infiltration was evaluated using the TIMER database. Gene Set Enrichment Analysis (GSEA) of COL1A1 was then performed. Finally, Kaplan-Meier survival analysis was presented to predict the survival times between high and low COL1A1 expression groups for MESO patients. RESULTS: There were distinct differences in the infiltration levels of immune cells between MESO and normal tissues. A total of 118 DEGs were identified by comprehensively analyzing three expression profile datasets. COL1A1, a hub gene, was identified to be highly expressed in MESO compared to normal tissues. COL1A1 genetic mutation occurred in 9% of MESO samples, and amplification was the most common type of mutation. COL1A1 expression was significantly correlated to the infiltration levels of CD4+ T cells, macrophages, and neutrophils. GSEA results indicated that COL1A1 could be involved in key biological processes and pathways like extracellular matrix and PI3K-Akt pathway. Patients with high COL1A1 expression usually experienced shorten overall survival time than those with its low expression. CONCLUSION: Our findings revealed that COL1A1 could become a potential prognostic biomarker for MESO, which was significantly related to immune cell infiltration.