Molecular Genetics Research Group (GENMOL), Universidad de Antioquia, Medellín, Colombia.
Research Division, Dynamical Business & Science Society - DBSS International SAS, Bogotá, Colombia.
Biochem Genet. 2024 Feb;62(1):352-370. doi: 10.1007/s10528-023-10426-5. Epub 2023 Jun 22.
Malignant pleural mesothelioma (MPM) is a rare and aggressive neoplasm of the pleural tissue that lines the lungs and is mainly associated with long latency from asbestos exposure. This tumor has no effective therapeutic opportunities nowadays and has a very low five-year survival rate. In this sense, identifying molecular events that trigger the development and progression of this tumor is highly important to establish new and potentially effective treatments. We conducted a meta-analysis of genome-wide expression studies publicly available at the Gene Expression Omnibus (GEO) and ArrayExpress databases. The differentially expressed genes (DEGs) were identified, and we performed functional enrichment analysis and protein-protein interaction networks (PPINs) to gain insight into the biological mechanisms underlying these genes. Additionally, we constructed survival prediction models for selected DEGs and predicted the minimum drug inhibition concentration of anticancer drugs for MPM. In total, 115 MPM tumor transcriptomes and 26 pleural tissue controls were analyzed. We identified 1046 upregulated DEGs in the MPM samples. Cellular signaling categories in tumor samples were associated with the TNF, PI3K-Akt, and AMPK pathways. The inflammatory response, regulation of cell migration, and regulation of angiogenesis were overrepresented biological processes. Expression of SOX17 and TACC1 were associated with reduced survival rates. This meta-analysis identified a list of DEGs in MPM tumors, cancer-related signaling pathways, and biological processes that were overrepresented in MPM samples. Some therapeutic targets to treat MPM are suggested, and the prognostic potential of key genes is shown.
恶性胸膜间皮瘤(MPM)是一种罕见且侵袭性的胸膜组织肿瘤,主要与石棉暴露的长潜伏期有关。目前,这种肿瘤没有有效的治疗机会,五年生存率非常低。因此,识别引发这种肿瘤发生和发展的分子事件对于建立新的、有潜在疗效的治疗方法非常重要。我们对基因表达综合数据库(GEO)和 ArrayExpress 数据库中公开的全基因组表达研究进行了荟萃分析。鉴定出差异表达基因(DEGs),并进行功能富集分析和蛋白质-蛋白质相互作用网络(PPINs)分析,以深入了解这些基因背后的生物学机制。此外,我们还为选定的 DEGs 构建了生存预测模型,并预测了 MPM 的抗癌药物最小抑制浓度。共分析了 115 个 MPM 肿瘤转录组和 26 个胸膜组织对照。我们在 MPM 样本中鉴定出 1046 个上调的 DEGs。肿瘤样本中的细胞信号转导类别与 TNF、PI3K-Akt 和 AMPK 途径有关。炎症反应、细胞迁移调节和血管生成调节是过度表达的生物学过程。SOX17 和 TACC1 的表达与降低的生存率相关。这项荟萃分析确定了 MPM 肿瘤、癌症相关信号通路和过度表达的生物学过程中的 DEG 列表。提出了一些治疗 MPM 的治疗靶点,并展示了关键基因的预后潜力。