Exploiting systems biology to investigate the gene modules and drugs in ovarian cancer: A hypothesis based on the weighted gene co-expression network analysis.


Journal

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
ISSN: 1950-6007
Titre abrégé: Biomed Pharmacother
Pays: France
ID NLM: 8213295

Informations de publication

Date de publication:
Feb 2022
Historique:
received: 01 10 2021
revised: 09 12 2021
accepted: 13 12 2021
pubmed: 19 12 2021
medline: 8 4 2022
entrez: 18 12 2021
Statut: ppublish

Résumé

Ovarian cancer (OC) is one of the worrisome gynecological cancers worldwide. Given its considerable mortality rate, it is necessary to investigate its oncogenesis. In this study, we used systems biology approaches to describe the key gene modules, hub genes, and regulatory drugs associated with serous OC as the novel biomarkers using weighted gene co-expression network analysis (WGCNA). Our findings have demonstrated that the blue module genes (r = 0.8, p-value = 1e-16) are involved in OC progression. Based on gene enrichment analysis, the genes in this module are frequently involved in biological processes such as the Cyclic adenosine monophosphate (cAMP) signaling pathway and the cellular response to transforming growth factor-beta stimulation. The co-expression network has been built using the correlated module's top hub genes, which are ADORA1, ANO9, CD24P4, CLDN3, CLDN7, ELF3, KLHL14, PRSS8, RASAL1, RIPK4, SERINC2, and WNT7A. Finally, a drug-target network has been built to show the interaction of the FDA-approved drugs with hub genes. Our results have discovered that ADORA1, ANO9, SERINC2, and KLHL14 are hub genes associated with serous OC. These genes can be considered as novel candidate target genes for treating OC.

Sections du résumé

BACKGROUND BACKGROUND
Ovarian cancer (OC) is one of the worrisome gynecological cancers worldwide. Given its considerable mortality rate, it is necessary to investigate its oncogenesis.
METHODS METHODS
In this study, we used systems biology approaches to describe the key gene modules, hub genes, and regulatory drugs associated with serous OC as the novel biomarkers using weighted gene co-expression network analysis (WGCNA).
FINDINGS RESULTS
Our findings have demonstrated that the blue module genes (r = 0.8, p-value = 1e-16) are involved in OC progression. Based on gene enrichment analysis, the genes in this module are frequently involved in biological processes such as the Cyclic adenosine monophosphate (cAMP) signaling pathway and the cellular response to transforming growth factor-beta stimulation. The co-expression network has been built using the correlated module's top hub genes, which are ADORA1, ANO9, CD24P4, CLDN3, CLDN7, ELF3, KLHL14, PRSS8, RASAL1, RIPK4, SERINC2, and WNT7A. Finally, a drug-target network has been built to show the interaction of the FDA-approved drugs with hub genes.
CONCLUSIONS CONCLUSIONS
Our results have discovered that ADORA1, ANO9, SERINC2, and KLHL14 are hub genes associated with serous OC. These genes can be considered as novel candidate target genes for treating OC.

Identifiants

pubmed: 34922114
pii: S0753-3322(21)01324-X
doi: 10.1016/j.biopha.2021.112537
pii:
doi:

Substances chimiques

CLDN7 protein, human 0
Claudins 0
Membrane Proteins 0
SERINC2 protein, human 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

112537

Informations de copyright

Copyright © 2021 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Auteurs

Samira Nomiri (S)

Department of Biochemistry, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran; Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran.

Hassan Karami (H)

Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran.

Behzad Baradaran (B)

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.

Darya Javadrashid (D)

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

Afshin Derakhshani (A)

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy.

Niloufar Sadat Nourbakhsh (NS)

Department of Genetics, Faculty of Basic Sciences, Kazerun branch, Islamic Azad University, Kazerun, Iran.

Mahdi Abdoli Shadbad (MA)

Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.

Antonio Giovanni Solimando (AG)

Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari, Bari, Italy.

Neda Jalili Tabrizi (NJ)

Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

Oronzo Brunetti (O)

IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy.

Saeed Nasseri (S)

Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran.

Vito Racanelli (V)

Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari, Bari, Italy.

Hossein Safarpour (H)

Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran. Electronic address: h.safarpour@bums.ac.ir.

Nicola Silvestris (N)

IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy; Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari, Bari, Italy. Electronic address: n.silvestris@oncologico.bari.it.

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Classifications MeSH