Identification and Validation of Prognostic Biomarker Signatures Associated with Overall Survival in Colorectal Cancer: Evidence from Bioinformatics Analysis and an in vivo Study.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41569184", "kind": "science-record", "revision": 3, "content_hash": "sha256:32aeaaa855575b6a0e64f6d2c52485677bbb8be49c50ce193deccb3afeb9cb7d", "created_at": "2026-11-01T20:31:32Z", "updated_at": "2026-11-01T22:15:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Prognostic Biomarker Signatures Associated with Overall Survival in Colorectal Cancer: Evidence from Bioinformatics Analysis and an in vivo Study.", "doi": "10.31557/APJCP.2026.27.1.163", "pmid": "41569184", "authors": ["Mohammad Bagher Jahantab", "Nasrin Amiri-Dashatan", "Mostafa Rezaei-Tavirani", "Mehdi Koushki"], "journal": "Asian Pacific journal of cancer prevention : APJCP", "year": 2026, "abstract": "BACKGROUND: Colorectal cancer (CRC) is one of the most common gastrointestinal cancers worldwide. Thus, genes targeting is useful for the prognosis and therapy of CRC. This study aimed to identify a promising and valuable signature model of prognostic biomarkers associated with overall survival (OS) in CRC.\nMETHODS: Two mRNA microarray datasets (GSE18105 and GSE113513) from the Gene Expression Omnibus (GEO) database were screened to extract key genes from differentially expressed genes (DEGs) to establish a multiscale embedded gene co-expression network, protein-protein interaction network, and survival analysis. Univariate Cox analysis was conducted to construct a prognostic signature for OS using Kaplan-Meier analysis. Then, we constructed and analyzed the protein-protein interaction network using STRING and Cytoscape, respectively to establish the key genes. Finally, the selected potential prognostic genes were validated in tissue samples of CRC by quantitative real-time PCR (qRT-PCR).\nRESULTS: In the present study, among 340 identified DEGs, four key genes (SPP1, CHEK1, KIF18A, and MAD2L1) were detected. The prognostic gene signature model demonstrated strong performance in the prognosis of CRC (AUC > 0.9). Moreover, the four key genes were also used to construct a risk-score prognostic model for OS and the findings showed that the prognostic gene signature model was highly effective in predicting the OS in CRC patients. The Gene Ontology (GO) enrichment analysis indicated the key genes were significantly associated with several CRC-related signaling pathways such as calcium-independent cell-cell adhesion. Finally, the results of qRT-PCR showed that the upregulation of SPP1, CHEK1, KIF18A, and MAD2L1 was associated with poor prognosis and served as risk factors for CRC patients compared to controls.\nCONCLUSION: The findings of the present study provided a set of four key genes with valid clinical utility that can serve as an alternative tool for prognosis and identification of new targets in CRC treatment.", "claims": [{"id": "claim-method", "statement": "Univariate Cox analysis was conducted to construct a prognostic signature for OS using Kaplan–Meier analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41569184", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Univariate Cox analysis was conducted to construct a prognostic signature for OS using Kaplan–Meier analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41569184", "locator": "sections[22] \"ack\" paragraph 1", "quote": "The data used to support the findings of this study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The prognostic gene signature model demonstrated strong performance in the prognosis of CRC (AUC > 0.9).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41569184", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The prognostic gene signature model demonstrated strong performance in the prognosis of CRC (AUC > 0.9)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The prognostic gene signature model demonstrated strong performance in the prognosis of CRC (AUC > 0.9).", "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:41569184"], "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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METHODS: Two mRNA microarray datasets (GSE18105 and GSE113513) from the G"], "order_basis": "paper_text_order:462", "id": "assay:2"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ted in tissue samples of CRC by quantitative real-time PCR (qRT-PCR). RESULTS: In the present study, am", "rence genes (GAPDH) using the 2-∆∆Ct method. RT-qPCR results were analyzed using SPSS, and plots", "ce genes (GAPDH) using the 2-∆∆Ct method. RT-qPCR results were analyzed using SPSS, and plots", "employed reverse-transcription quantitative-real-time PCR (qRT-PCR) analyses to assess expression leve"], "order_basis": "paper_text_order:1114", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}