CD8+ T cell associated scoring model helps prognostic diagnosis and immunotherapy selection in patients with colon adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39386801", "kind": "science-record", "revision": 3, "content_hash": "sha256:1673069fef94d0a0e1cdc848be5da884b1cc9bd1e623f5648e21ac8b0d446b5b", "created_at": "2026-11-01T20:29:36Z", "updated_at": "2026-11-01T22:12:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CD8+ T cell associated scoring model helps prognostic diagnosis and immunotherapy selection in patients with colon adenocarcinoma.", "doi": "10.1016/j.heliyon.2024.e37998", "pmid": "39386801", "authors": ["Zheng Zhao", "Mingkai Chen", "Kuanxue Sun", "Xinqi Gu"], "journal": "Heliyon", "year": 2024, "abstract": "Objective: T cell-mediated immunity plays a crucial role in the immune response against tumors, with CD 8+ T cells playing a leading role in the eradication of cancer cells.\nMaterial and methods: A total of 5 datasets were included in this study. Single cell transcriptome data were used to discover CD8+ T cell marker genes, and Bulk transcriptome data from TCGA and GEO were jointly analyzed to screen candidate prognostic genes. lasso regression was performed to construct prognostic models. Immunotherapy cohort (IMvigor 210 and GSE78220) was applied to validate the diagnostic power of markers.\nResult: Single-cell transcriptome data identified 65 CD8+ T cell marker genes, highlighting their importance in T cell-mediated immune responses. Among these, 11 genes were identified as CD8+ T-associated differential genes through analysis of bulk data from TCGA and GEO. A prognostic model for 5 genes was identified based on Lasso regression, dividing colon adenocarcinoma (COAD) patients into high- and low-risk groups. This model exhibited higher prognostic accuracy compared to traditional clinicopathological characteristics (age, pathological stage, histological grading). Moreover, the risk score derived from this model successfully differentiated patient responses to immunotherapy, as validated in the IMvigor 210 and GSE78220 cohorts.\nConclusion: Our research introduces a novel prognostic signature based on CD8+ T cell marker genes, demonstrating significant predictive power for prognosis and immunotherapy response in COAD patients. This model offers a potential tool for improving patient stratification and personalizing treatment strategies.", "claims": [{"id": "claim-method", "statement": "Next, 10-fold cross-validated LASSO Cox regression analysis (Fig. 2B–C) was performed on the 11 candidate genes, and 5 genes (CXCL8, TIMP1, CPA3, SPP1, GLA) were screened for inclusion in the model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39386801", "locator": "sections[11] \"Establishment and validation of a 5-gene prognostic signature based on CD8+ T cell marker genes\" paragraph 2", "quote": "Next, 10-fold cross-validated LASSO Cox regression analysis (Fig. 2B–C) was performed on the 11 candidate genes, and 5 genes (CXCL8, TIMP1, CPA3, SPP1, GLA) were screened for inclusion in the model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data sets used in this study are public data sets. The datasets generated analyzed during the current study are available in the GEO and TCGA repository, including GSE146771, GSE39582, GSE78220, TCGA-COAD and IMvigor210. The raw data and code supporting this article can be obtained by contacting the corresponding author with a reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39386801", "locator": "sections[20] \"Data availability statement\" paragraph 2", "quote": "All data sets used in this study are public data sets. The datasets generated analyzed during the current study are available in the GEO and TCGA repository, including GSE146771, GSE39582, GSE78220, TCGA-COAD and IMvigor210. The raw data and code supporting this article can be obtained by contacting the corresponding author with a reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A prognostic model for 5 genes was identified based on Lasso regression, dividing colon adenocarcinoma (COAD) patients into high- and low-risk groups.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39386801", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A prognostic model for 5 genes was identified based on Lasso regression, dividing colon adenocarcinoma (COAD) patients into high- and low-risk groups."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A prognostic model for 5 genes was identified based on Lasso regression, dividing colon adenocarcinoma (COAD) patients into high- and low-risk groups.", "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:39386801"], "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:GSE146771"], "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:GSE146771"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39386801", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2024.e37998", "sha256": "sha256:af903f8074539ba27725e708af72ea7c11d4967a24f2408bfb8bee8371b8b690", "bytes": 39457, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.heliyon.2024.e37998", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11462492", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE146771", "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=GSE146771", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE146771", "version": null, "note": "All data sets used in this study are public data sets. The datasets generated analyzed during the current study are available in the GEO and TCGA repository, including GSE146771, GSE39582, GSE78220, TCGA-COAD and IMvigor210. The raw data and code supporting this article can be obtained by contacting the corresponding author with a reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All data sets used in this study are public data sets. The datasets generated analyzed during the current study are available in the GEO and TCGA repository, including GSE146771, GSE39582, GSE78220, TCGA-COAD and IMvigor210. The raw data and code supporting this article can be obtained by contacting the corresponding author with a reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4405613", "GSM4405614", "GSM4405615", "GSM4405616", "GSM4405617", "GSM4405618", "GSM4405619", "GSM4405620", "GSM4405621", "GSM4405622", "GSM4405623", "GSM4405624", "GSM4405625", "GSM4405626", "GSM4405627", "GSM4405628", "GSM4405629", "GSM4405630", "GSM4405631", "GSM4405632"], "sample_count": 20, "group_sizes": null, "group_sizes_basis": null, "platform": "20301", "taxon": "Homo sapiens", "title": "Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted therapies in colon cancer", "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: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": "All data sets used in this study are public data sets. 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