DNA damage repair molecular subtype derived immune signature applicable for the prognosis and immunotherapy response prediction in colon cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37969400", "kind": "science-record", "revision": 3, "content_hash": "sha256:e98e9fac13e5dbe768ed3bcffdff4bb1c849b1cf995786acf43c00d5aeec266b", "created_at": "2026-11-01T19:02:53Z", "updated_at": "2026-11-01T22:10:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "DNA damage repair molecular subtype derived immune signature applicable for the prognosis and immunotherapy response prediction in colon cancer.", "doi": "10.21037/tcr-23-747", "pmid": "37969400", "authors": ["Zhen Shang", "Ze Wang", "Yongtao Zhang", "Shanglong Liu"], "journal": "Translational cancer research", "year": 2023, "abstract": "Background: The DNA damage repair (DDR) pathway is one of the pathways of tumor pathogenesis, but its relationship with the immunophenotype has not been clarified in colon cancer (CC).\nMethods: We identified the differentially expressed immune-related genes (DEIRGs) between two DDR molecular subtypes, namely, C1 and C2, and used univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct the risk score in the training cohort [n=1,009, a combination of The Cancer Genome Atlas (TCGA) and GSE39582]. Regarding the median risk score as the unified cutoff to classify the patients into high- and low-risk groups. Two independent cohorts (GSE17538, n=232; GSE38832, n=122) were used for external validation of the prognostic value of the risk score. The IMvigor210 cohort (n=348) was used to test the predictive value of the risk score for immunotherapy response. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to discover the underlying mechanism. Immune cell infiltration was quantified by the single sample gene set enrichment analysis (ssGSEA) algorithm.\nResults: The high-risk group showed significantly reduced overall survival (OS), disease-specific survival (DSS), disease-free survival (DFS), progression-free survival (PFS), and relapse-free survival (RFS) compared to the low-risk group, and the two groups differed significantly in lymphatic invasion, American Joint Committee on Cancer (AJCC) TNM stage, preoperative carcinoembryonic antigen (CEA) level, etc. The enrichment levels of pathways related to colorectal cancer, epithelial-mesenchymal transition (EMT), angiogenesis, hypoxia, P53, TGF-β, KRAS signaling, etc., were upregulated in the high-risk group, but DDR-related pathways were defective in the high-risk group. The immunophenotypes of the high-risk group tended to be desert and excluded, and the risk score of patients who responded to immunotherapy was significantly lower than that of patients who did not respond to immunotherapy. The higher the infiltration levels of gamma delta T cells (γδ T cells), immature dendritic cells, and T follicular helper (Tfh) cells, the more significant adverse impact on the prognosis of CC patients was exhibited and an obviously positive correlation with the risk score was showed.\nConclusions: An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression analysis was performed in the training cohort (n=1,009), the PRGs were defined as the genes with a P value <0.001. The overfitting between the PRGs was removed by the least absolute shrinkage and selection operator (LASSO) algorithm with penalty parameter (λ) determined by the lowest partial likelihood deviance based on the R package “glmnet” (22).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37969400", "locator": "sections[8] \"Construction and validation of the prognostic risk score\" paragraph 2", "quote": "Univariate Cox regression analysis was performed in the training cohort (n=1,009), the PRGs were defined as the genes with a P value <0.001. The overfitting between the PRGs was removed by the least absolute shrinkage and selection operator (LASSO) algorithm with penalty parameter (λ) determined by the lowest partial likelihood deviance based on the R package “glmnet” (22)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Four large-sample independent CC cohorts, namely, The Cancer Genome Atlas (TCGA)-colon adenocarcinoma (COAD) (n=430), GSE39582 (n=579), GSE17538 (n=232), and GSE38832 (n=122), were included in the research. The clinical and mRNA expression data are available from TCGA (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37969400", "locator": "sections[6] \"Data acquisition\" paragraph 2", "quote": "Four large-sample independent CC cohorts, namely, The Cancer Genome Atlas (TCGA)-colon adenocarcinoma (COAD) (n=430), GSE39582 (n=579), GSE17538 (n=232), and GSE38832 (n=122), were included in the research. The clinical and mRNA expression data are available from TCGA (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An immune gene risk score associated with the DDR molecular subtype was built and verified and is applicable to prognosis and immunotherapy response prediction in colon cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37969400", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "An immune gene risk score associated with the DDR molecular subtype was built and verified herein; that is applicable to the prognosis and immunotherapy response prediction in CC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An immune gene risk score associated with the DDR molecular subtype was built and verified and is applicable to prognosis and immunotherapy response prediction in colon cancer.", "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:37969400"], "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:GSE17538"], "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:GSE17538"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37969400", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-23-747", "sha256": "sha256:78dd9aff814bfec380448957f53ba4a3659066abda06a211947a1eff867029ae", "bytes": 50523, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tcr-23-747", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10643980", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17538", "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=GSE17538", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17538", "version": null, "note": "Four large-sample independent CC cohorts, namely, The Cancer Genome Atlas (TCGA)-colon adenocarcinoma (COAD) (n=430), GSE39582 (n=579), GSE17538 (n=232), and GSE38832 (n=122), were included in the research. 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expression Classification of Colon Cancer defines six molecular subtypes with distinct 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}}], "gaps": ["asset:data:geo:GSE17538 not downloaded", "asset:data:geo:GSE17538 licence not read", "asset:data:geo:GSE38832 not downloaded", "asset:data:geo:GSE38832 licence not read", "asset:data:geo:GSE39582 not downloaded", "asset:data:geo:GSE39582 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Univariate Cox regression analysis was performed in the training cohort (n=1,009), the PRGs were defined as the genes with a P value <0.001. The overfitting between the PRGs was removed by the least absolute shrinkage and selection operator (LASSO) algorithm with penalty parameter (λ) determined by the lowest partial likelihood deviance based on the R package “glmnet” (22)."}}, {"id": "method-2", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-3", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Kaplan-Meier"}}, {"id": "method-4", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "log-rank"}}, {"id": "method-5", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "chi-square"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE39582", "GSE17538", "GSE38832"], "resolved_accessions": ["GSE39582", "GSE17538", "GSE38832"], "statements": ["Four large-sample independent CC cohorts, namely, The Cancer Genome Atlas (TCGA)-colon adenocarcinoma (COAD) (n=430), GSE39582 (n=579), GSE17538 (n=232), and GSE38832 (n=122), were included in the research. The clinical and mRNA expression data are available from TCGA (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/)."], "basis": "The paper names GSE39582, GSE17538, GSE38832 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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