A nine-gene signature to improve prognosis prediction of colon carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33985413", "kind": "science-record", "revision": 5, "content_hash": "sha256:eed0b8817618c2ae8e8caa451e381b2e1d7718d9e021d2e80e9a53f8938199ab", "created_at": "2026-11-01T17:35:16Z", "updated_at": "2026-11-01T22:46:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A nine-gene signature to improve prognosis prediction of colon carcinoma.", "doi": "10.1080/15384101.2021.1919827", "pmid": "33985413", "authors": ["Jinlai Zhao", "Yigang Wang", "Jianchao Gao", "Yang Wang", "Xuan Zhong", "Xiaotang Wu", "Hua Li"], "journal": "Cell cycle (Georgetown, Tex.)", "year": 2021, "abstract": "This study aims to establish a gene model that can robustly and effectively predict the prognosis of colon carcinoma patients via bioinformatics. Data along with clinical information in GSE39582 Series Matrix were firstly downloaded from Gene Expression Omnibus (GEO) database. Next, differentially expressed genes (DEGs) were obtained through \"edgeR\" analysis. Finally, a risk predication model was established through a series of regression analyses, and then prognostic performance of the model was comprehensively evaluated though Kaplan-Meier and receiver operating characteristic (ROC) analysis. Gene set enrichment analysis (GSEA) was further performed. Totally, 846 DEGs were obtained by analyzing the gene expression data in GSE39582 dataset. A 9-gene signature-based risk predication model was established via regression analyses, and the model-based risk score was formulated as: Riskscore = (-0.1214) * TNFRSF11A + (-0.2617) * TMEM97 + (-0.1041) * LGR5 + 0.0973 * KLK10 + 0.1655 * HOXB8 + 0.227 * FKBP10 + (-0.1312) * CXCL13 + (-0.1316) * CXCL10 + 0.2593 * CD36. Kaplan-Meier curve showed that colon carcinoma patients in the high-risk group had a lower survival rate. GSEA showed that high-risk group and low-risk group displayed significant difference in biological pathways including ECM RECEPTOR INTERACTION. Besides, correlation analysis between the riskscore of the model and clinical features of patients revealed that the model could effectively predict the prognosis of patients in different ages (age>65, age<65) and stages (tumor_stage I/II, tumor_stage III/IV, T3&T4, N0&N1, N2&N3, M0). This study provides a robust model for the prognosis prediction of colon carcinoma, and lays a basis for researching the molecular mechanism underlying the development of colon carcinoma.", "claims": [{"id": "claim-method", "statement": "Next, differentially expressed genes (DEGs) were obtained through “edgeR” analysis. 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Gene set enrichment analysis (GSEA) was further performed."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data along with clinical information in GSE39582 Series Matrix were firstly downloaded from Gene Expression Omnibus (GEO) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33985413", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Data along with clinical information in GSE39582 Series Matrix were firstly downloaded from Gene Expression Omnibus (GEO) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A 9-gene signature-based risk predication model was established via regression analyses.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:33985413", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A 9-gene signature-based risk predication model was established via regression analyses"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A 9-gene signature-based risk predication model was established via regression analyses.", "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:33985413"], "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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