ArticleGenomics & informatics2021
A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma.
Article in Genomics & informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Methylation biomarkers can distinguish pleural mesothelioma from healthy pleura and other pleural pathologies.Molecular oncology · 2026Article
- Graph-based and molecular modeling approaches to identify TpiA as a noval therapeutic target in Neisseria meningitidis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Proteomic atlas of human peritoneal tissue.Scientific reports · 2026Article
- Prognostic markers and molecular pathways in primary colorectal cancer with a high potential of liver metastases: a systems biology approach.Research in pharmaceutical sciences · 2025Article
- Atopic dermatitis-associated genetic variants regulate LOC100294145 expression implicating interleukin-27 production and type 1 interferon signaling.The World Allergy Organization journal · 2024Article
- Prognostic biomarkers and molecular pathways mediating Helicobacter pylori-induced gastric cancer: a network-biology approach.Genomics & informatics · 2023Article
- Potential Biomarkers and Signaling Pathways Associated with the Pathogenesis of Primary Ameloblastoma: A Systems Biology Approach.International journal of dentistry · 2022Article
- Molecular Pathways in Peritoneal Mesothelioma: A Minireview of New Insights.Frontiers in oncology · 2022Review
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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