Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:29588600", "kind": "science-record", "revision": 9, "content_hash": "sha256:20ce951901af8d846744e946b466806310c5b468e376ea1c8d06b2213fc6ad25", "created_at": "2026-11-01T15:40:32Z", "updated_at": "2026-11-01T22:43:19Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis.", "doi": "10.2147/OTT.S152238", "pmid": "29588600", "authors": ["Xiao Yang", "Shaoming Zhu", "Li Li", "Li Zhang", "Shu Xian", "Yanqing Wang", "Yanxiang Cheng"], "journal": "OncoTargets and therapy", "year": 2018, "abstract": "BACKGROUND: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms.\nRESULTS: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs) and were deeply analyzed by bioinformatics methods. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein-protein interaction (PPI) networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the tumor signaling pathway. The 17 most closely related genes among DEGs were identified from the PPI network.\nCONCLUSION: This study indicates that screening for DEGs and pathways in ovarian cancer using integrated bioinformatics analyses could help us understand the molecular mechanism underlying the development of ovarian cancer, be of clinical significance for the early diagnosis and prevention of ovarian cancer, and provide effective targets for the treatment of ovarian cancer.", "claims": [{"id": "claim-method", "statement": "Gene differential expression analysis was performed using the limma package in the Bioconductor package (available online: http://www.bioconductor.org/). The related operating instruction codes were put into R, and the DEGs in ovarian cancer and normal ovarian samples of the three microarray datasets were analyzed by the limma software package. Samples with a corrected P-value of <0.05 and log fold change (FC) >2 were considered DEGs. Using the keywords “ovarian cancer geo accession” to search on the GEO DataSets database (https://www.ncbi.nlm.nih.gov/geo/), the gene expression profiles of GDS3592,9 GSE54388,10 and GSE66957 (Cheng et al, unpublished data, 2015) were downloaded.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29588600", "locator": "sections[4] \"Screening for DEGs\" paragraph 2", "quote": "Gene differential expression analysis was performed using the limma package in the Bioconductor package (available online: http://www.bioconductor.org/)."}, {"asset": "source:pmid:29588600", "locator": "sections[4] \"Screening for DEGs\" paragraph 2", "quote": "The related operating instruction codes were put into R, and the DEGs in ovarian cancer and normal ovarian samples of the three microarray datasets were analyzed by the limma software package."}, {"asset": "source:pmid:29588600", "locator": "sections[4] \"Screening for DEGs\" paragraph 2", "quote": "Samples with a corrected P-value of <0.05 and log fold change (FC) >2 were considered DEGs."}, {"asset": "source:pmid:29588600", "locator": "sections[3] \"Microarray data\" paragraph 3", "quote": "Using the keywords “ovarian cancer geo accession” to search on the GEO DataSets database (https://www.ncbi.nlm.nih.gov/geo/), the gene expression profiles of GDS3592,9 GSE54388,10 and GSE66957 (Cheng et al, unpublished data, 2015) were downloaded."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The platform for GDS3592 is GPL570, [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2 Array, which includes 12 normal ovarian surface epithelial samples and 12 serous papillary ovarian adenocarcinomas specimens.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:29588600", "locator": "sections[3] \"Microarray data\" paragraph 3", "quote": "The platform for GDS3592 is GPL570, [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2 Array, which includes 12 normal ovarian surface epithelial samples and 12 serous papillary ovarian adenocarcinomas specimens."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study downloaded ovarian cancer microarray expression profiles from GEO, analyzed them with limma, integrated the three ranked datasets using RobustRankAggreg (RRA), and identified 190 DEGs, including 99 upregulated and 91 downregulated genes.", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "The three ovarian cancer gene expression microarray datasets were analyzed by the limma package and sorted according to logfold-change value and then analyzed by RRA (corrected P-value <0.05)."}, "evidence": [{"asset": "source:pmid:29588600", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples."}, {"asset": "source:pmid:29588600", "locator": "sections[10] \"Identification of DEGs in ovarian cancer using integrated bioinformatics\" paragraph 2", "quote": "The three ovarian cancer gene expression microarray datasets were analyzed by the limma package and sorted according to logfold-change value and then analyzed by RRA (corrected P-value <0.05)."}, {"asset": "source:pmid:29588600", "locator": "sections[10] \"Identification of DEGs in ovarian cancer using integrated bioinformatics\" paragraph 2", "quote": "Through rank analysis, we identified 190 DEGs, with 99 upregulated genes and 91 downregulated genes; the DEGs are shown in Table 2."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study downloaded ovarian cancer microarray expression profiles from GEO, analyzed them with limma, integrated the three ranked datasets using RobustRankAggreg (RRA), and identified 190 DEGs, including 99 upregulated and 91 downregulated genes.", "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:29588600"], "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:GSE54388"], "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:GSE54388"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:29588600", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/OTT.S152238", "sha256": "sha256:c4ae8cecccaaeb4dd7a9e8675f5479d9e668a86dc9abc13a4d94d2752727b268", "bytes": 33914, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/OTT.S152238", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC5858852", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE54388", "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=GSE54388", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE54388", "version": null, "note": "The platform for GDS3592 is GPL570, [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2 Array, which includes 12 normal ovarian surface epithelial samples and 12 serous papillary ovarian adenocarcinomas specimens.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The platform for GDS3592 is GPL570, [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2 Array, which includes 12 normal ovarian surface epithelial samples and 12 serous papillary ovarian adenocarcinomas specimens.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1314222", "GSM1314223", "GSM1314224", "GSM1314225", "GSM1314226", "GSM1314227", "GSM1314228", "GSM1314229", "GSM1314230", "GSM1314231", "GSM1314232", "GSM1314233", "GSM1314234", "GSM1314235", "GSM1314236", "GSM1314237", "GSM1314238", "GSM1314239", "GSM1314240", "GSM1314241", "GSM1314242", "GSM1314243"], "sample_count": 22, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Identification of differentially expressed transcription factors in ovarian cancer", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE66957", "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=GSE66957", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE66957", "version": null, "note": "The platform for GDS3592 is GPL570, [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2 Array, which includes 12 normal ovarian surface epithelial samples and 12 serous papillary ovarian adenocarcinomas specimens.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The platform for GDS3592 is GPL570, [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2 Array, which includes 12 normal ovarian surface epithelial samples and 12 serous papillary ovarian adenocarcinomas specimens.", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM1634925", "GSM1634926", "GSM1634927", "GSM1634928", "GSM1634929", "GSM1634930", "GSM1634931", "GSM1634932", "GSM1634933", "GSM1634934", "GSM1634935", "GSM1634936", "GSM1634937", "GSM1634938", "GSM1634939", "GSM1634940", "GSM1634941", "GSM1634942", "GSM1634943", "GSM1634944", "GSM1634945", "GSM1634946", "GSM1634947", "GSM1634948", "GSM1634949", "GSM1634950", "GSM1634951", "GSM1634952", "GSM1634953", "GSM1634954", "GSM1634955", "GSM1634956", "GSM1634957", "GSM1634958", "GSM1634959", "GSM1634960", "GSM1634961", "GSM1634962", "GSM1634963", "GSM1634964", "GSM1634965", "GSM1634966", "GSM1634967", "GSM1634968", "GSM1634969", "GSM1634970", "GSM1634971", "GSM1634972", "GSM1634973", "GSM1634974", "GSM1634975", "GSM1634976", "GSM1634977", "GSM1634978", "GSM1634979", "GSM1634980", "GSM1634981", "GSM1634982", "GSM1634983", "GSM1634984", "GSM1634985", "GSM1634986", "GSM1634987", "GSM1634988", "GSM1634989", "GSM1634990", "GSM1634991", "GSM1634992", "GSM1634993"], "sample_count": 69, "group_sizes": null, "group_sizes_basis": null, "platform": "15048", "taxon": "Homo sapiens", "title": "Pathways of ovarian cancer development", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE54388 not downloaded", "asset:data:geo:GSE54388 licence not read", "asset:data:geo:GSE66957 not downloaded", "asset:data:geo:GSE66957 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "reordered", "quote": "Gene differential expression analysis was performed using the limma package in the Bioconductor package (available online: http://www.bioconductor.org/). The related operating instruction codes were put into R, and the DEGs in ovarian cancer and normal ovarian samples of the three microarray datasets were analyzed by the limma software package. Samples with a corrected P-value of <0.05 and log fold change (FC) >2 were considered DEGs. Using the keywords “ovarian cancer geo accession” to search on the GEO DataSets database (https://www.ncbi.nlm.nih.gov/geo/), the gene expression profiles of GDS3592,9 GSE54388,10 and GSE66957 (Cheng et al, unpublished data, 2015) were downloaded."}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "GO enrichment"}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "build_graph", "expected_value": 0.05, "unit": "p-value", "tolerance": null, "state": "complete", "note": "The threshold the paper applied to its own result, as the paper states it. 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Samples with a corrected P-value of <0.05 and log fold change (FC) >2 were considered DEGs. Using the keywords “ovarian cancer geo accession” to search on the GEO DataSets database (https://www.ncbi.nlm.nih.gov/geo/), the gene expression profiles of GDS3592,9 GSE54388,10 and GSE66957 (Cheng et al, unpublished data, 2015) were downloaded."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}