Unveiling Key Biomarkers and Therapeutic Drugs in Polycystic Ovary Syndrome (PCOS) Through Pathway Enrichment Analysis and Hub Gene-miRNA Networks.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38444712", "kind": "science-record", "revision": 5, "content_hash": "sha256:1f16ade01a200543802aa65c425c1b30323ebd5f249e7b7f8ecb2cbcc710908c", "created_at": "2026-11-01T19:20:23Z", "updated_at": "2026-11-01T22:53:48Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Unveiling Key Biomarkers and Therapeutic Drugs in Polycystic Ovary Syndrome (PCOS) Through Pathway Enrichment Analysis and Hub Gene-miRNA Networks.", "doi": "10.5812/ijpr-139985", "pmid": "38444712", "authors": ["Roozbeh Heidarzadehpilehrood", "Maryam Pirhoushiaran", "Malina Binti Osman", "King-Hwa Ling", "Habibah Abdul Hamid"], "journal": "Iranian journal of pharmaceutical research : IJPR", "year": 2023, "abstract": "Background: Polycystic ovary syndrome (PCOS) affects women of reproductive age globally with an incidence rate of 5% - 26%. Growing evidence reports important roles for microRNAs (miRNAs) in the pathophysiology of granulosa cells (GCs) in PCOS.\nObjectives: The objectives of this study were to identify the top differentially expressed miRNAs (DE-miRNAs) and their corresponding targets in hub gene-miRNA networks, as well as identify novel DE-miRNAs by analyzing three distinct microarray datasets. Additionally, functional enrichment analysis was performed using bioinformatics approaches. Finally, interactions between the 5 top-ranked hub genes and drugs were investigated.\nMethods: Using bioinformatics approaches, three GC profiles from the gene expression omnibus (GEO), namely gene expression omnibus series (GSE)-34526, GSE114419, and GSE137684, were analyzed. Targets of the top DE-miRNAs were predicted using the multiMiR R package, and only miRNAs with validated results were retrieved. Genes that were common between the \"DE-miRNA prediction results\" and the \"existing tissue DE-mRNAs\" were designated as differentially expressed genes (DEGs). Gene ontology (GO) and pathway enrichment analyses were implemented for DEGs. In order to identify hub genes and hub DE-miRNAs, the protein-protein interaction (PPI) network and miRNA-mRNA interaction network were constructed using Cytoscape software. The drug-gene interaction database (DGIdb) database was utilized to identify interactions between the top-ranked hub genes and drugs.\nResults: Out of the top 20 DE-miRNAs that were retrieved from the GSE114419 and GSE34526 microarray datasets, only 13 of them had \"validated results\" through the multiMiR prediction method. Among the 13 DE-miRNAs investigated, only 5, namely hsa-miR-8085, hsa-miR-548w, hsa-miR-612, hsa-miR-1470, and hsa-miR-644a, demonstrated interactions with the 10 hub genes in the hub gene-miRNA networks in our study. Except for hsa-miR-612, the other 4 DE-miRNAs, including hsa-miR-8085, hsa-miR-548w, hsa-miR-1470, and hsa-miR-644a, are novel and had not been reported in PCOS pathogenesis before. Also, GO and pathway enrichment analyses identified \"pathogenic E. coli infection\" in the Kyoto encyclopedia of genes and genomes (KEGG) and \"regulation of Rac1 activity\" in FunRich as the top pathways. The drug-hub gene interaction network identified ACTB, JUN, PTEN, KRAS, and MAPK1 as potential targets to treat PCOS with therapeutic drugs.\nConclusions: The findings from this study might assist researchers in uncovering new biomarkers and potential therapeutic drug targets in PCOS treatment.", "claims": [{"id": "claim-method", "statement": "Top miRNAs and mRNAs from three microarray datasets were analyzed for differential expression analysis in the GCs of PCOS and healthy participants using the R software package limma.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38444712", "locator": "sections[5] \"3.2. Statistical Analysis and Preprocessing of Microarray Data for Integration\" paragraph 2", "quote": "Top miRNAs and mRNAs from three microarray datasets were analyzed for differential expression analysis in the GCs of PCOS and healthy participants using the R software package limma."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data presented in this study were uploaded during submission through the manuscript file and are openly available for readers. Microarray data were deposited into the gene expression omnibus database under accession numbers GSE34526, GSE114419, and GSE137684.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38444712", "locator": "sections[23] \"Data Reproducibility:\" paragraph 2", "quote": "The data presented in this study were uploaded during submission through the manuscript file and are openly available for readers. Microarray data were deposited into the gene expression omnibus database under accession numbers GSE34526, GSE114419, and GSE137684."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 352 differentially expressed genes were identified between PCOS subjects and healthy controls.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38444712", "locator": "sections[13] \"4.2. Identification of Differentially Expressed Genes\" paragraph 2", "quote": "Hence, using the provided definition and referring to the Venn diagram, a total of “352” DEGs were found to be differentially expressed between PCOS subjects and healthy controls (Figure 1A, overlapping segment of Venn diagram: “352”)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 352 differentially expressed genes were identified between PCOS subjects and healthy controls.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:38444712"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE114419"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE114419"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38444712", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.5812/ijpr-139985", "sha256": "sha256:f415f81199ebc1b4bff5b2670cae7d681af010eceb81aa542d071be522f9ba77", "bytes": 39463, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.5812/ijpr-139985", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10912876", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE114419", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE114419", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE114419", "version": null, "note": "The data presented in this study were uploaded during submission through the manuscript file and are openly available for readers. 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