Malignant pleural mesothelioma (MPM) is a rare but highly aggressive thoracic malignancy. ESTIMATE algorithm-derived immune scores are commonly used to quantify the immune and stromal components in tumors. Thus, this algorithm may help determine the tumor microenvironment (TME)-related gene expression profile associated with tumor immunity. This study aimed at mining public databases to determine a potential correlation between differentially expressed genes (DEGs) and survival in patients with MPM. We categorized patients from the Gene Expression Omnibus database according to their immune/stromal scores into high- and low-score groups. Functional enrichment analysis and the construction of protein-protein interaction networks showed that the DEGs identified were primarily involved in the TME. Furthermore, we validated these genes in an independent cohort of patients with MPM from The Cancer Genome Atlas database. DEG analysis showed that 29 DEGs were cancer driver genes. Subsequently, 14 TME-related genes, which have been previously neglected, were shown to exhibit significant prognostic potential in MPM. In conclusion, immune/stromal scores are novel predictors of a poor prognosis in patients with MPM. We identified DEGs that are involved in immunity against MPM and may contribute to patient survival. Owing to their potential as prognostic factors for MPM, these 14 TME-related genes need to be studied in detail in the future.
Keywords: ESTIMATE algorithm; immune signature; malignant pleural mesothelioma; prognosis; tumor microenvironment.
Copyright © 2020 Xu, Cheng, Fan and Mao.