Global gene expression profiling of a mouse model of ovarian clear cell carcinoma caused by ARID1A and PIK3CA mutations implicates a role for inflammatory cytokine signaling.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:26484281", "kind": "science-record", "revision": 8, "content_hash": "sha256:f61dc5fee804b54c3f54b05a47b60d5352def3fb957d19086056f99d7ec89ddc", "created_at": "2026-11-01T15:40:13Z", "updated_at": "2026-11-01T22:42:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Global gene expression profiling of a mouse model of ovarian clear cell carcinoma caused by ARID1A and PIK3CA mutations implicates a role for inflammatory cytokine signaling.", "doi": "10.1016/j.gdata.2015.06.027", "pmid": "26484281", "authors": ["Ronald L Chandler", "Jesse R Raab", "Mike Vernon", "Terry Magnuson", "Jonathan C Schisler"], "journal": "Genomics data", "year": 2015, "abstract": "Ovarian clear-cell carcinoma (OCCC) is an aggressive form of epithelial ovarian cancer (EOC). OCCC represents 5-25% of all EOC incidences and is the second leading cause of death from ovarian cancer (Glasspool and McNeish, 2013) [1]. A recent publication by Chandler et al. reported the first mouse model of OCCC that resembles human OCCC both genetically and histologically by inducing a localized deletion of ARID1A and the expression of the PIK3CA(H1047R) substitution mutation (Chandler et al., 2015) [2]. We utilized Affymetrix Mouse Gene 2.1 ST arrays for the global gene expression profiling of mouse primary OCCC tumor samples and animal-matched normal ovaries to identify cancer-dependent gene expression. We describe the approach used to generate the differentially expressed genes from the publicly available data deposited at the Gene Expression Omnibus (GEO) database under the accession number GSE57380. These data were used in cross-species comparisons to publically available human OCCC gene expression data and allowed the identification of coordinately regulated genes in both mouse and human OCCC and supportive of a role for inflammatory cytokine signaling in OCCC pathogenesis (Chandler et al., 2015) [2].", "claims": [{"id": "claim-method", "statement": "The data as descried thus far was used in Chandler et al. to identify expression changes (normal versus tumor tissue) by using Linear Models for Microarray Data Analysis (LIMMA) or Significance Analysis of Microarray (SAM) analysis [2].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26484281", "locator": "sections[11] \"Detecting differential gene expression\" paragraph 2", "quote": "The data as descried thus far was used in Chandler et al. to identify expression changes (normal versus tumor tissue) by using Linear Models for Microarray Data Analysis (LIMMA) or Significance Analysis of Microarray (SAM) analysis [2]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Direct link to deposited data\nhttp://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57380", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26484281", "locator": "sections[2] \"Direct link to deposited data\" paragraphs 1-2", "quote": "Direct link to deposited data\nhttp://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57380"}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study used LIMMA or SAM to identify differential expression, with SAM identifying 3,646 differentially expressed probes at a false discovery rate of 0.0%, using publicly available GEO data under accession GSE57380.", "kind": "quantitative", "target": {"value": 0.0, "unit": "per cent", "tolerance": null, "source": "SAM identified 3646 probes that were differentially expressed at a false discovery rate of 0.0% (Fig. 2E)."}, "evidence": [{"asset": "source:pmid:26484281", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We describe the approach used to generate the differentially expressed genes from the publicly available data deposited at the Gene Expression Omnibus (GEO) database under the accession number GSE57380."}, {"asset": "source:pmid:26484281", "locator": "sections[11] \"Detecting differential gene expression\" paragraph 2", "quote": "The data as descried thus far was used in Chandler et al. to identify expression changes (normal versus tumor tissue) by using Linear Models for Microarray Data Analysis (LIMMA) or Significance Analysis of Microarray (SAM) analysis [2]."}, {"asset": "source:pmid:26484281", "locator": "sections[11] \"Detecting differential gene expression\" paragraph 2", "quote": "SAM identified 3646 probes that were differentially expressed at a false discovery rate of 0.0% (Fig. 2E)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study used LIMMA or SAM to identify differential expression, with SAM identifying 3,646 differentially expressed probes at a false discovery rate of 0.0%, using publicly available GEO data under accession GSE57380.", "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:26484281"], "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. 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