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• W4317821569 endingPage "106601" @default.
• W4317821569 startingPage "106601" @default.
• W4317821569 abstract "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 padj < 0.05 and |log2FC| > 1. Amongst the top 15 KEGG pathways significantly enriched, metabolism of xenobiotics by cytochrome P450, steroid hormone biosynthesis and ovarian steroidogenesis were observed. The Protein-Protein Interaction network identified 18 hub genes amongst this set. Interestingly, most candidate drug signatures have been introduced by databases are either FDA approved or entered into clinical trials, including melatonin, resveratrol and raloxifene. Investigational or experimental introduced drugs obey rules of drug-likeness with almost safe and acceptable ADMET properties. Notably, 21 top target genes of the final drug set were also included in the granulosa significant differentially expressed genes. 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." @default.
• W4317821569 created "2023-01-24" @default.
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• W4317821569 date "2023-03-01" @default.
• W4317821569 modified "2023-10-03" @default.
• W4317821569 title "Transcriptomic screening to identify hub genes and drug signatures for PCOS based on RNA-Seq data in granulosa cells" @default.
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• W4317821569 doi "https://doi.org/10.1016/j.compbiomed.2023.106601" @default.
• W4317821569 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36738709" @default.
• W4317821569 hasPublicationYear "2023" @default.
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