Transcriptomic screening to identify hub genes and drug signatures for PCOS based on RNA-Seq data in granulosa cells.
Drug repositioning
Granulosa cells
Network construction
PCOS
Polypharmacology
Transcriptomic screening
Journal
Computers in biology and medicine
ISSN: 1879-0534
Titre abrégé: Comput Biol Med
Pays: United States
ID NLM: 1250250
Informations de publication
Date de publication:
03 2023
03 2023
Historique:
received:
22
11
2022
revised:
14
01
2023
accepted:
22
01
2023
pubmed:
5
2
2023
medline:
25
2
2023
entrez:
4
2
2023
Statut:
ppublish
Résumé
Polycystic ovary syndrome (PCOS) is one of the most incident reproductive diseases, and remains the main cause of female infertility. Granulosa cells play a critical role in normal follicle development and steroid hormones synthesis. In spite of extensive research, no sole medication has been approved by FDA to treat PCOS. This study aimed to investigate the novel therapeutics targets in PCOS, focusing on granulosa cells transcriptome functional analysis with a drug repositioning approach. PCOS microarray and RNA-Seq datasets in granulosa cells were screened and reanalyzed. KEGG pathway enrichment and interaction network analyses were performed and followed by a set of drug signature screening and Poly-pharmacology survey. 545 deregulated genes were identified via filters including p Results of the current study represent approved, investigational and experimental drug signatures according to the differentially expressed genes in granulosa cells with supported literature reviews. This data might be useful for researchers and clinicians to pave the way for better management of PCOS.
Sections du résumé
BACKGROUND
Polycystic ovary syndrome (PCOS) is one of the most incident reproductive diseases, and remains the main cause of female infertility. Granulosa cells play a critical role in normal follicle development and steroid hormones synthesis. In spite of extensive research, no sole medication has been approved by FDA to treat PCOS. This study aimed to investigate the novel therapeutics targets in PCOS, focusing on granulosa cells transcriptome functional analysis with a drug repositioning approach.
METHODS
PCOS microarray and RNA-Seq datasets in granulosa cells were screened and reanalyzed. KEGG pathway enrichment and interaction network analyses were performed and followed by a set of drug signature screening and Poly-pharmacology survey.
RESULTS
545 deregulated genes were identified via filters including p
CONCLUSION
Results of the current study represent approved, investigational and experimental drug signatures according to the differentially expressed genes in granulosa cells with supported literature reviews. This data might be useful for researchers and clinicians to pave the way for better management of PCOS.
Identifiants
pubmed: 36738709
pii: S0010-4825(23)00066-5
doi: 10.1016/j.compbiomed.2023.106601
pii:
doi:
Substances chimiques
Steroids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
106601Informations de copyright
Copyright © 2023 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.