Mahfuz A M U B, Zubair-Bin-Mahfuj A M, Podder Dibya Joti
Department of Biotechnology & Genetic Engineering, Faculty of Life Science, University of Development Alternative, Dhaka 1209, Bangladesh.
Department of Oral and Maxillofacial Surgery, Dhaka Dental College, Dhaka 1216, Bangladesh.
Genomics Inform. 2021 Jun;19(2):e16. doi: 10.5808/gi.21019. Epub 2021 Jun 30.
Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.
即使在当今先进医学时代,恶性腹膜间皮瘤(MPM)的预后仍然很差。导致MPM发生和发展的分子机制在很大程度上仍不清楚。本研究采用综合生物信息学方法,旨在确定导致MPM的关键基因和途径。通过分析一个微阵列基因表达数据集,已确定了与健康对照者腹膜相比在MPM中差异表达的基因。对这些差异表达基因(DEG)进行了基因本体论和京都基因与基因组百科全书通路分析,以获得更深入的了解。使用STRING构建了由DEG编码的蛋白质的蛋白质-蛋白质相互作用(PPI)网络,并通过分析该网络检测到了枢纽基因。接下来,检测了对枢纽基因可能具有调控作用的转录因子和miRNA。最后,使用GEPIA2网络服务器基于枢纽基因进行了生存分析。发现有606个基因在MPM中差异表达;133个上调,473个下调。分析STRING生成的PPI网络,确定了6个密集模块和12个枢纽基因。已确定15个转录因子和10个miRNA对DEG具有最广泛的调控功能。通过生物信息学分析,这项工作深入了解了参与MPM的潜在基因和途径。