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pmid:33563317

Prospective pathway signaling and prognostic values of MicroRNA-9 in ovarian cancer based on gene expression omnibus (GEO): a bioinformatics analysis.

Li Zuo · Xiaoli Li · Yue Tan · Hailong Zhu · Mi Xiao

Journal of ovarian research · 2021 doi:10.1186/s13048-021-00779-z

Paper

complete

Experiment

partial

Data

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Analysis

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pmid:33563317
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title
Prospective pathway signaling and prognostic values of MicroRNA-9 in ovarian cancer based on gene expression omnibus (GEO): a bioinformatics analysis.
doi
10.1186/s13048-021-00779-z
pmid
33563317
authors array · 5 items
[0]
Li Zuo
[1]
Xiaoli Li
[2]
Yue Tan
[3]
Hailong Zhu
[4]
Mi Xiao
journal
Journal of ovarian research
year
2021
abstract
OBJECTIVE: MicroRNAs (miRNAs) play a vital role in the development of ovarian cancer (OC). The aim of this study to investigate the prognostic value and potential signaling pathways of hsa-miR-9-5p (miR-9) in OC through literature review and bioinformatics methods. METHODS: The expression of miR-9 in OC was assessed using the public datasets from the Gene Expression Omnibus (GEO) database. And a literature review was also performed to investigate the correlation between miR-9 expression and the OC prognosis. Two mRNA datasets (GSE18520 and GSE36668) of OC tissues and normal ovarian tissues (NOTs) were downloaded from GEO to identify the differentially expressed genes (DEGs). The target genes of hsa-miR-9-5p (TG-miR-9-5p) were predicted using miRWALK3.0 and TargetScan. Then the gene overlaps between DEGs in OC and the predicted TG-miR-9-5p were confirmed using a Venn diagram. After that, overlapping genes were subjected to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the impact of hub genes on OC prognosis was analyzed. RESULTS: It was found that OC patients with miR-9 low expression had poor prognosis. A total of 107 DEGs related to both OC and miR-9 were identified. Dozens of DEGs were enriched in developmental process, extracellular matrix structural constituent, cell junction, axon guidance. In the PPI network analysis, 5 of the top 10 hub genes was significantly associated with decreased overall survival of OC patients, namely FBN1 (HR = 1.64, P < 0.05), PRRX1 (HR = 1.76, P < 0.05), SMC2 (HR = 1.22, P < 0.05), SMC4 (HR = 1.31, P < 0.05), and VCAN (HR = 1.48, P < 0.05). CONCLUSION: Low expression of miR-9 indicates poor prognosis of OC patients. MiR-9 plays a crucial role in the biological process of OC by binding to target genes, thus affecting the prognosis of patients.
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A fixed-effects model was used for the pooled analysis of these prognostic indicators.
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The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
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Functional and pathway enrichment analysis of hsa-miR-9-5p related differentially expressed genes in Ovarian Cancer
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GO and KEGG analysis of miR-9-related DEGs in ovarian cancer
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Functional and pathway enrichment analysis of hsa-miR-9-5p related differentially expressed genes in Ovarian Cancer
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[1]
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GO:0048856
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GO:0071840
[1]
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GO:0016043
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[3]
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GO:0007275
[1]
multicellular organism development
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GO:0005201
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5
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GO:0030054
[1]
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0.0181
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Hsa-1,474,244
[1]
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8
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[1]
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section[12]/table-wrap[1]#Tab3
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A fixed-effects model was used for the pooled analysis of these prognostic indicators.
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fixed_effects_pool
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GSE47841
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GSE83693
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GSE53829
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GSE18520
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GSE36668
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[0]
GSE47841
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GSE83693
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GSE53829
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GSE23338
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GSE18520
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GSE36668
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[0]
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
basis
The paper names GSE47841, GSE83693, GSE53829, GSE23338, GSE18520, GSE36668 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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source:pmid:33563317
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data:geo:GSE18520
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asset:table:pmid:33563317:2
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asset:table:pmid:33563317:3
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data:geo:GSE18520
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pmid:33563317
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agent:minimax-reader
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data:geo:GSE18520
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agent:corpus-assay-engine
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data processing. MiR-9 expression levels in microarray datasets downloaded from GEO were expressed
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33563317", "kind": "science-record", "revision": 7, "content_hash": "sha256:908f391ef3ae1055caacc3e94539a17a0fb654dd75018f7d69b215dee9026f39", "created_at": "2026-11-01T15:41:24Z", "updated_at": "2026-11-01T22:03:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prospective pathway signaling and prognostic values of MicroRNA-9 in ovarian cancer based on gene expression omnibus (GEO): a bioinformatics analysis.", "doi": "10.1186/s13048-021-00779-z", "pmid": "33563317", "authors": ["Li Zuo", "Xiaoli Li", "Yue Tan", "Hailong Zhu", "Mi Xiao"], "journal": "Journal of ovarian research", "year": 2021, "abstract": "OBJECTIVE: MicroRNAs (miRNAs) play a vital role in the development of ovarian cancer (OC). The aim of this study to investigate the prognostic value and potential signaling pathways of hsa-miR-9-5p (miR-9) in OC through literature review and bioinformatics methods.\nMETHODS: The expression of miR-9 in OC was assessed using the public datasets from the Gene Expression Omnibus (GEO) database. And a literature review was also performed to investigate the correlation between miR-9 expression and the OC prognosis. Two mRNA datasets (GSE18520 and GSE36668) of OC tissues and normal ovarian tissues (NOTs) were downloaded from GEO to identify the differentially expressed genes (DEGs). The target genes of hsa-miR-9-5p (TG-miR-9-5p) were predicted using miRWALK3.0 and TargetScan. Then the gene overlaps between DEGs in OC and the predicted TG-miR-9-5p were confirmed using a Venn diagram. After that, overlapping genes were subjected to Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, a protein-protein interaction (PPI) network was constructed using STRING and Cytoscape, and the impact of hub genes on OC prognosis was analyzed.\nRESULTS: It was found that OC patients with miR-9 low expression had poor prognosis. A total of 107 DEGs related to both OC and miR-9 were identified. Dozens of DEGs were enriched in developmental process, extracellular matrix structural constituent, cell junction, axon guidance. In the PPI network analysis, 5 of the top 10 hub genes was significantly associated with decreased overall survival of OC patients, namely FBN1 (HR = 1.64, P < 0.05), PRRX1 (HR = 1.76, P < 0.05), SMC2 (HR = 1.22, P < 0.05), SMC4 (HR = 1.31, P < 0.05), and VCAN (HR = 1.48, P < 0.05).\nCONCLUSION: Low expression of miR-9 indicates poor prognosis of OC patients. MiR-9 plays a crucial role in the biological process of OC by binding to target genes, thus affecting the prognosis of patients.", "claims": [{"id": "claim-method", "statement": "A fixed-effects model was used for the pooled analysis of these prognostic indicators.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33563317", "locator": "sections[7] \"Statistical analysis\" paragraph 2", "quote": "A fixed-effects model was used for the pooled analysis of these prognostic indicators."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33563317", "locator": "sections[21] \"Availability of data and materials\" paragraph 2", "quote": "The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "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:33563317"], "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:GSE18520"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:fixed_effects_pool", "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:GSE18520"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:fixed_effects_pool"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33563317", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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