Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33557848", "kind": "science-record", "revision": 7, "content_hash": "sha256:00b48e20372b7880de523e49573cefbddd6493500c3116ea80e492d84612e68c", "created_at": "2026-11-01T15:41:24Z", "updated_at": "2026-11-01T22:03:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer.", "doi": "10.1186/s12935-021-01782-6", "pmid": "33557848", "authors": ["Xiaoye Jiang", "Zhongxiang Jiang", "Lichun Xiang", "Xuenuo Chen", "Jiao Wu", "Zheng Jiang"], "journal": "Cancer cell international", "year": 2021, "abstract": "BACKGROUND: Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT.\nMETHODS: A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors.\nRESULTS: In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy.\nCONCLUSIONS: Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy.", "claims": [{"id": "claim-method", "statement": "In univariate and multivariate Cox regression analyses, our model was associated with survival (P = 0.002).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33557848", "locator": "sections[18] \"Relationship between the CYT-related prognostic model and clinicopathological features\" paragraph 3", "quote": "In univariate and multivariate Cox regression analyses, our model was associated with survival (P = 0.002)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The obtained data were used according to the TCGA (https://portal.gdc.cancer.gov/repository), GTEx (http://commonfund.nih.gov/GTEx) and GEO (https://www.ncbi.nlm.nih.gov/geo/) data access policies. The mutation data, mRNA profile data and clinical feature data for CC are publicly obtainable and open access. All analyses were carried out based on pertinent guidelines and regulations.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33557848", "locator": "sections[31] \"notes\" paragraph 1", "quote": "The obtained data were used according to the TCGA (https://portal.gdc.cancer.gov/repository), GTEx (http://commonfund.nih.gov/GTEx) and GEO (https://www.ncbi.nlm.nih.gov/geo/) data access policies. The mutation data, mRNA profile data and clinical feature data for CC are publicly obtainable and open access. All analyses were carried out based on pertinent guidelines and regulations."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:33557848"], "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:GSE39582"], "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:GSE39582"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33557848", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12935-021-01782-6", "sha256": "sha256:d618db0a2e285411af228730356d3e9581d215a3216aaeac2c1d802b7acbe4ed", "bytes": 36238, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12935-021-01782-6", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7869500", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE39582", "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=GSE39582", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE39582", "version": null, "note": "The obtained data were used according to the TCGA (https://portal.gdc.cancer.gov/repository), GTEx (http://commonfund.nih.gov/GTEx) and GEO (https://www.ncbi.nlm.nih.gov/geo/) data access policies. The mutation data, mRNA profile data and clinical feature data for CC are publicly obtainable and open access. All analyses were carried out based on pertinent guidelines and regulations.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The obtained data were used according to the TCGA (https://portal.gdc.cancer.gov/repository), GTEx (http://commonfund.nih.gov/GTEx) and GEO (https://www.ncbi.nlm.nih.gov/geo/) data access policies. The mutation data, mRNA profile data and clinical feature data for CC are publicly obtainable and open access. 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clinical, molecular and survival characteristics [Expression]", "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:GSE41258", "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=GSE41258", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE41258", "version": null, "note": "The obtained data were used according to the TCGA (https://portal.gdc.cancer.gov/repository), GTEx (http://commonfund.nih.gov/GTEx) and GEO (https://www.ncbi.nlm.nih.gov/geo/) data access policies. The mutation data, mRNA profile data and clinical feature data for CC are publicly obtainable and open access. All analyses were carried out based on pertinent guidelines and regulations.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The obtained data were used according to the TCGA (https://portal.gdc.cancer.gov/repository), GTEx (http://commonfund.nih.gov/GTEx) and GEO (https://www.ncbi.nlm.nih.gov/geo/) data access policies. The mutation data, mRNA profile data and clinical feature data for CC are publicly obtainable and open access. 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