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Nomiri S, Karami H, Baradaran B, et al. Exploiting systems biology to investigate the gene modules and drugs in ovarian cancer: A hypothesis based on the weighted gene co-expression network analysis. Biomed Pharmacother. 2021;146:112537doi: 10.1016/j.biopha.2021.112537.
Nomiri, S., Karami, H., Baradaran, B., Javadrashid, D., Derakhshani, A., Nourbakhsh, N. S., Shadbad, M. A., Solimando, A. G., Tabrizi, N. J., Brunetti, O., Nasseri, S., Racanelli, V., Safarpour, H., & Silvestris, N. (2021). Exploiting systems biology to investigate the gene modules and drugs in ovarian cancer: A hypothesis based on the weighted gene co-expression network analysis. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie, 146112537. https://doi.org/10.1016/j.biopha.2021.112537
Nomiri, Samira, et al. "Exploiting systems biology to investigate the gene modules and drugs in ovarian cancer: A hypothesis based on the weighted gene co-expression network analysis." Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie vol. 146 (2021): 112537. doi: https://doi.org/10.1016/j.biopha.2021.112537
Nomiri S, Karami H, Baradaran B, Javadrashid D, Derakhshani A, Nourbakhsh NS, Shadbad MA, Solimando AG, Tabrizi NJ, Brunetti O, Nasseri S, Racanelli V, Safarpour H, Silvestris N. Exploiting systems biology to investigate the gene modules and drugs in ovarian cancer: A hypothesis based on the weighted gene co-expression network analysis. Biomed Pharmacother. 2021 Dec 16;146:112537. doi: 10.1016/j.biopha.2021.112537. Epub 2021 Dec 16. PMID: 34922114.
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Biomed Pharmacother. 2021 Dec 16;146:112537. doi: 10.1016/j.biopha.2021.112537. Epub 2021 Dec 16.

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

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie

Samira Nomiri, Hassan Karami, Behzad Baradaran, Darya Javadrashid, Afshin Derakhshani, Niloufar Sadat Nourbakhsh, Mahdi Abdoli Shadbad, Antonio Giovanni Solimando, Neda Jalili Tabrizi, Oronzo Brunetti, Saeed Nasseri, Vito Racanelli, Hossein Safarpour, Nicola Silvestris

Affiliations

  1. Department of Biochemistry, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran; Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran.
  2. Student Research Committee, Birjand University of Medical Sciences, Birjand, Iran.
  3. Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
  4. Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
  5. Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy.
  6. Department of Genetics, Faculty of Basic Sciences, Kazerun branch, Islamic Azad University, Kazerun, Iran.
  7. Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran.
  8. Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari, Bari, Italy.
  9. IRCCS Istituto Tumori "Giovanni Paolo II" of Bari, Bari, Italy.
  10. Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran.
  11. Cellular and Molecular Research Center, Birjand University of Medical Sciences, Birjand, Iran. Electronic address: [email protected].
  12. 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: [email protected].

PMID: 34922114 DOI: 10.1016/j.biopha.2021.112537

Abstract

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: 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: 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: 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.

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

Keywords: Biomarker; Ovarian cancer; Transcriptome analysis; WGCNA

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