A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma

Our plain-English summary of A network-biology approach for identification of key genes and pathways involved in malignant peritoneal mesothelioma, by A.M.U.B. Mahfuz, A.M. Zubair-Bin-Mahfuj, D.J. Podder (Genomics & Informatics, 2021).

The study

• Authors: A.M.U.B. Mahfuz, A.M. Zubair-Bin-Mahfuj, D.J. Podder
• Journal: Genomics & Informatics
• Published: 2021;19(2):e16
• Cited by: 8 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

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.

In plain English

This was a computer-based (bioinformatics) study. It reanalyzed one publicly available gene-activity dataset (GSE112154) on malignant peritoneal mesothelioma. It compared 47 samples labelled as mesothelioma (45 tumor samples and two peritoneal mesothelioma cell lines) with three healthy peritoneal samples. The study did not examine asbestos or any other exposure. Of 606 genes whose activity differed between the groups, 133 were more active and 473 were less active in the mesothelioma group. Network analysis picked out 12 'hub' genes: two (CDH1 and GAPDH) were more active and ten were less active. No peritoneal survival data were available, so the authors used pleural mesothelioma data to study survival. In those pleural data, higher activity of GAPDH (hazard ratio 2.3), TEK (1.8), VWF (2) and CDH5 (1.9) was associated with shorter overall survival. The authors concluded that they had identified potential genes and pathways involved in peritoneal mesothelioma. They said these candidates need to be confirmed in further laboratory and animal experiments and in patient samples.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Bioinformatics reanalysis of a single publicly available microarray gene-expression dataset, with network, pathway, regulator, drug-database and survival analyses using online tools
• Who was studied: Dataset GSE112154 (deposited by Sciarrillo et al.): 47 samples classified as malignant peritoneal mesothelioma (45 tumor samples and two peritoneal mesothelioma cell lines) compared with three healthy peritoneal samples. Survival analysis used a separate pleural mesothelioma dataset (TCGA MESO), with 41 patients in each of the high- and low-expression groups.
• Exposure: No exposure was studied. The study compared gene activity in mesothelioma samples with healthy peritoneum. Asbestos appears only as background in the introduction.
• Main results:
  • After two withdrawn gene records were excluded, 606 genes differed in activity between the mesothelioma group and healthy peritoneum: 133 were more active and 473 were less active in the mesothelioma group.
  • Of 12 hub genes identified, two (CDH1 and GAPDH) were more active and the other ten were less active in the mesothelioma group.
  • Gene set enrichment analysis identified one pathway, cytokine-cytokine receptor interaction, as reduced in the mesothelioma group (FDR q = 0.0788609, nominal p = 0.043296088).
  • In pleural mesothelioma survival data, higher activity was associated with shorter overall survival for GAPDH (HR 2.3; p = 0.00061), TEK (HR 1.8; p=0.016), VWF (HR 2; p = 0.0056) and CDH5 (HR 1.9; p = 0.0089).
  • The miRNet tool identified 197 transcription factors and 2,305 miRNAs linked to the genes. The authors reported 15 top transcription factors and 10 top miRNAs.
  • A DrugBank search found 237 drugs or drug-like compounds that act on the hub proteins.
• The authors' conclusion: The authors concluded that their network analysis identified potential genes and pathways involved in malignant peritoneal mesothelioma, and that these candidates need to be validated by further experiments and in patient samples.
• Limitations the authors state:
  • TCGA provides data only for pleural mesothelioma, and GTEx has no mesothelium data. The survival relationships were therefore extrapolated from pleural mesothelioma data, not peritoneal data.
  • The candidate genes and pathways have not been confirmed by laboratory experiments or in patient samples.

Topics

Medical terms in this study, explained in our Lexicon: Peritoneal Mesothelioma, Prognosis, Peritoneum.

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