A possible genetic association between obesity and colon cancer in females.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37711894", "kind": "science-record", "revision": 4, "content_hash": "sha256:a3a62916363267eeda4d2731f96a770cc84184d555b4613df0aff691cfefc04c", "created_at": "2026-11-01T19:02:32Z", "updated_at": "2026-11-01T22:10:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A possible genetic association between obesity and colon cancer in females.", "doi": "10.3389/fendo.2023.1189570", "pmid": "37711894", "authors": ["Xiao-Li Zhang", "Xin-Feng Zhang", "Yuan Fang", "Meng-Li Li", "Ruo Shu", "Yi Gong", "Hua-You Luo", "Yan Tian"], "journal": "Frontiers in endocrinology", "year": 2023, "abstract": "Object: There is mounting clinical evidence that an increase in obesity is linked to an increase in cancer incidence and mortality. Although studies have shown a link between obesity and colon cancer, the particular mechanism of the interaction between obesity and colon cancer in females remains unknown. The goal of this work is to use bioinformatics to elucidate the genetic link between obesity and colon cancer in females and to investigate probable molecular mechanisms.\nMethods: GSE44076 and GSE199063 microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. In the two microarray datasets and healthy controls, the online tool GEO2R was utilized to investigate the differential genes between obesity and colon cancer. The differential genes (DEGs) identified in the two investigations were combined. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment studies were performed on the DEGs. The STRING database and Cytoscape software were then used to build protein-protein interaction (PPI) networks to discover hub genes. NetworkAnalyst was also used to build networks of target microRNAs (miRNAs) and hub genes, as well as networks of transcriptions.\nResults: Between the two datasets, 146 DEGs were shared. The DEGs are primarily enriched in inflammatory and immune-related pathways, according to GO analysis and KEGG. 14 hub genes were identified via PPI building using the Cytoscape software's MCODE and CytoNCA plug-ins: TYROBP, CD44, BGN, FCGR3A, CD53, CXCR4, FN1, SPP1, IGF1, CCND1, MMP9, IL2RG, IL6 and CTGF. Key transcription factors for these hub genes include WRNIP1, ATF1, CBFB, and NR2F6. Key miRNAs for these hub genes include hsa-mir-1-3p, hsa-mir-26b-5p, hsa-mir-164a-5p and hsa-mir-9-5p.\nConclusion: Our research provides evidence that changed genes are shared by female patients with colon cancer and obesity. Through pathways connected to inflammation and the immune system, these genes play significant roles in the emergence of both diseases. We created a network between hub genes and miRNAs that target transcription factors, which may offer suggestions for future research in this area.", "claims": [{"id": "claim-method", "statement": "Using the online biometric analysis tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), which is available on the official GEO website, differentially expressed genes in the two datasets were analyzed.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37711894", "locator": "sections[4] \"Screening of differential genes between the two datasets\" paragraph 2", "quote": "Using the online biometric analysis tool GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/), which is available on the official GEO website, differentially expressed genes in the two datasets were analyzed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material .", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37711894", "locator": "sections[19] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/ Supplementary Material ."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The two datasets shared 146 differentially expressed genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37711894", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Between the two datasets, 146 DEGs were shared."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The two datasets shared 146 differentially expressed 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:37711894"], "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:GSE199063"], "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:GSE199063"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37711894", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2023.1189570", "sha256": "sha256:9a366f23f61706cb01b86fce496fbd0680b307bbc22ec33ac7eb8a812aa39abe", "bytes": 36690, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2023.1189570", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10497871", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE199063", "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=GSE199063", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE199063", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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