Identification of Potential Hub Genes and Therapeutic Drugs in Malignant Pleural Mesothelioma by Integrated Bioinformatics Analysis

Our plain-English summary of Identification of Potential Hub Genes and Therapeutic Drugs in Malignant Pleural Mesothelioma by Integrated Bioinformatics Analysis, by X. Zhang, L. Yang, W. Chen, et al (Oncology Research and Treatment, 2020).

The study

• Authors: X. Zhang, L. Yang, W. Chen, M. Kong
• Journal: Oncology Research and Treatment
• Published: 2020;43(12):656-671
• Cited by: 8 articles, as counted by NIH iCite
• Read it: PubMed · Publisher

Abstract

Introduction: Malignant pleural mesothelioma (MPM) is closely linked to asbestos exposure and is an extremely aggressive tumor with poor prognosis.

Objective: Our study aimed to elucidate hub genes and potential drugs in MPM by integrated bioinformatics analysis.

Methods: GSE42977 was download from the Gene Expression Omnibus (GEO) database; the differentially expressed genes (DEGs) with adj.p value <0.05 and |logFC| ≥2 were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by DAVID database. The STRING database was used to construct a protein-protein interaction network, and modules analysis and hub genes acquisition were performed by Cytoscape. The Gene Expression Profiling Interactive Analysis (GEPIA) database was used to assess the impact of hub genes on the prognosis of MPM patients. The Drug-Gene Interaction database (DGIdb) was used to select the related drugs.

Results: A total of 169 upregulated and 70 downregulated DEGs were identified. These DEGs are enriched in the pathway of extracellular matrix-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, and PPAR signaling pathway. Finally, 10 hub genes (CDC20, CDK1, UBE2C, TOP2A, CCNB2, NUSAP1, KIF20A, AURKA, CEP55, and ASPM) were identified, which are considered to be closely related to the poor prognosis of MPM. In addition, 119 related drugs that may have a therapeutic effect on MPM were filtered out.

Conclusion: These discovered genes and small-molecule drugs provide some new ideas for further research on MPM.

© 2020 The Author(s)Published by S. Karger AG, Basel.

In plain English

This study did not examine asbestos exposure. It was a computer-based reanalysis of existing, publicly available gene-activity data. The authors used a dataset (GSE42977), submitted by De Rienzo et al. in 2013, that contained 24 epithelioid malignant pleural mesothelioma tissue samples and 7 normal pleural tissue samples. They found 239 genes whose activity differed between tumor and normal tissue: 169 upregulated and 70 downregulated. Using network software, they picked 10 'hub' genes: CDC20, CDK1, UBE2C, TOP2A, CCNB2, NUSAP1, KIF20A, AURKA, CEP55 and ASPM. They then checked survival in a general mesothelioma dataset in the GEPIA database, which has no separate pleural mesothelioma dataset. For all 10 genes, high expression was reported as a risk factor for poorer survival compared with low expression. Hazard ratios ranged from 1.9 (ASPM) to 5.3 (TOP2A). A drug-database search listed 119 drugs linked mainly to CDK1, TOP2A and AURKA. This study did not test any of these drugs. The authors said larger studies and laboratory and animal work are needed, and that the drugs require cell experiments and clinical verification.

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 public gene-expression dataset (differential gene expression, network and pathway analysis, database survival check, drug-database search); no new patients or samples were collected
• Who was studied: Public dataset GSE42977 (submitted by De Rienzo et al. in 2013): 24 epithelioid malignant pleural mesothelioma tissues and 7 normal pleural tissues. Survival was checked in the GEPIA general mesothelioma (MESO) dataset; the number of patients in that dataset is not given in the text.
• Exposure: No exposure was studied. Asbestos is mentioned only as background on the cause of the disease; the study compared gene activity in tumor versus normal pleural tissue.
• Main results:
  • 239 genes differed in activity between mesothelioma and normal pleural tissue: 169 upregulated and 70 downregulated
  • The protein-interaction network built from these genes had 111 nodes and 296 edges; the top module was enriched in oocyte meiosis, cell cycle and p53 signaling pathways
  • 10 hub genes were selected by the Maximal Clique Centrality method: CDC20 and CDK1 (connectivity degree 19), UBE2C (18), TOP2A (16), CCNB2 (15), NUSAP1, KIF20A and AURKA (14 each), CEP55 and ASPM (13 each)
  • In the GEPIA mesothelioma dataset, high versus low expression: ASPM HR 1.9 (p = 0.011), AURKA HR 2.8 (p = 3.2e-05), CCNB2 HR 4.1 (p = 3.1e-08), CDC20 HR 3.4 (p = 1.2e-06), CDK1 HR 3.5
  • In the same dataset: CEP55 HR 4.1 (p = 1.7e-08), KIF20A HR 3.8 (p = 6.3e-07), NUSAP1 HR 2.7 (p = 7e-05), TOP2A HR 5.3 (p = 2.9e-10); UBE2C HR 3.1, with its p value printed as a negative number (-6.4e-06)
  • The authors reported that high expression of these 10 genes was a prognostic risk factor relative to low expression
  • A drug-gene database search found 119 drugs related to 3 of the hub genes (mainly CDK1, TOP2A and AURKA); the drugs were not tested in this study
• The authors' conclusion: The authors concluded that their 10 hub genes and the potential drugs provide a reliable theoretical basis for screening, diagnosis and prognosis, as well as new therapeutic targets, for malignant pleural mesothelioma
• Limitations the authors state:
  • Further studies with larger sample sizes are needed
  • The findings come from bioinformatics methods only and remain to be proven in laboratory (in vitro) and animal (in vivo) studies
  • The drugs identified only represent possibilities; cell experiments and clinical verification are needed before any clinical use
  • The survival check used a general mesothelioma dataset because GEPIA has no separate pleural mesothelioma dataset, so it was described as an initial exploration

Topics

The National Library of Medicine indexes this study under subjects our site covers: Mesothelioma.

Medical terms in this study, explained in our Lexicon: Pleural Mesothelioma, Asbestos Exposure, Prognosis.

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