The aging-related risk signature in colorectal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33658390", "kind": "science-record", "revision": 8, "content_hash": "sha256:ef0aa2a2d6db5a2a52edbe030e363b398a63a6883e9be581d78f23e7e0ced0d7", "created_at": "2026-11-01T15:41:26Z", "updated_at": "2026-11-01T22:03:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The aging-related risk signature in colorectal cancer.", "doi": "10.18632/aging.202589", "pmid": "33658390", "authors": ["Taohua Yue", "Shanwen Chen", "Jing Zhu", "Shihao Guo", "Zhihao Huang", "Pengyuan Wang", "Shuai Zuo", "Yucun Liu"], "journal": "Aging", "year": 2021, "abstract": "BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. The opening of the TCGA and GEO databases has promoted the progress of CRC prognostic assessment, while the aging-related risk signature has never been mentioned.\nMETHODS: R software packages, GSEA software, Venn diagram, Metascape, STRING, Cytoscape, cBioPortal, TIMER and GeneMANIA website were used in this study.\nRESULTS: Aging-related gene sets, GO_AGING, GO_CELL_AGING and GO_CELLULAR_SENESCENCE, were activated significantly in CRC tissues. We constructed an aging-related risk signature using LASSO COX regression in training group TCGA and validated in testing group GSE39582. The risk score was significantly associated with the overall survival of CRC patients, whose stability was clarified by stratified survival analysis and accuracy was demonstrated using the ROC curve. The risk score was significantly increased in the advanced stage, T3-4, N1-3 and M1 and positively correlated with the richness of immune cell infiltration in the tumor microenvironment. We further investigated the molecular characteristics of 15 hub genes at the DNA and protein levels and performed GSEA between high- and low-risk groups.\nCONCLUSIONS: The aging-related signature is a reliable prognostic analysis model and can predict the severity and immune cell infiltration of CRC patients.", "claims": [{"id": "claim-method", "statement": "Univariate COX and LASSO-penalized COX regression were used to construct optimal prognostic risk signatures for CRC samples in the training group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33658390", "locator": "sections[23] \"Development of the prognostic signature based on the LASSO COX regression\" paragraph 2", "quote": "Univariate COX and LASSO-penalized COX regression were used to construct optimal prognostic risk signatures for CRC samples in the training group."}], "state": "complete"}, {"id": "claim-data-access", "statement": "In this study, the transcriptome profiling data and corresponding clinical information of colorectal cancer (CRC) were downloaded from The Cancer Genome Atlas (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:33658390", "locator": "sections[18] \"Data collection\" paragraph 2", "quote": "In this study, the transcriptome profiling data and corresponding clinical information of colorectal cancer (CRC) were downloaded from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/)."}], "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:33658390"], "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:33658390", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.202589", "sha256": 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and genes in colorectal cancer data set.", "rows": [["Data sets", "Numbers of genes", "Normal tissues", "Tumor tissues"], ["TCGA", "56753", "44", "568"], ["GSE39582", "21655", "19", "566"], ["GSE87211", "21754", "160", "203"]], "row_count": 4, "column_count": 4, "numeric_cells": 11, "header_rows": 0, "locator": "section[3]/table-wrap[1]#t1"}}, {"id": "asset:table:pmid:33658390:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:78f4dbe4c5ea058b311dc42fc935109d44f2b37e6610702fabeac12852f23c14", "bytes": 2140, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[4]/table-wrap[1]#t2", "version": null, "note": "Aging-related gene sets included in this study.", "structure": {"pmcid": "PMC7993742", "section_index": 4, "section_title": "Identification of aging-related genes", "row_count": 40, "column_count": 2}, "table": {"label": "Table 2", "caption": "Aging-related gene sets included in this study.", "rows": [["Name (Number of genes)"], ["DEMAGALHAES_AGING_DN (16)", "DEMAGALHAES_AGING_UP (54)"], ["GO_AGING (323)", "GO_CELL_AGING (117)"], ["KIM_HYPOXIA (19)", "GO_CELLULAR_SENESCENCE (78)"], ["KYNG_DNA_DAMAGE_DN (184)", "KYNG_DNA_DAMAGE_UP (209)"], ["KYNG_NORMAL_AGING_DN (18)", "KYNG_NORMAL_AGING_UP (15)"], ["LY_AGING_MIDDLE_DN (16)", "LY_AGING_MIDDLE_UP (14)"], ["LY_AGING_OLD_DN (56)", "LY_AGING_OLD_UP (7)"], ["LY_AGING_PREMATURE_DN (30)", "GO_MUSCLE_ATROPHY (12)"], ["RODWELL_AGING_KIDNEY_DN (146)", "RODWELL_AGING_KIDNEY_UP (500)"], ["KYNG_WERNER_SYNDROM_DN (18)", "KYNG_WERNER_SYNDROM_UP (15)"], ["KYNG_WERNER_SYNDROM_AND_NORMAL_AGING_DN (194)"], ["KYNG_WERNER_SYNDROM_AND_NORMAL_AGING_UP (80)"], ["RODWELL_AGING_KIDNEY_NO_BLOOD_DN (147)"], ["RODWELL_AGING_KIDNEY_NO_BLOOD_UP (223)"], ["WEIGEL_OXIDATIVE_STRESS_BY_HNE_AND_H2O2 (36)"], ["WEIGEL_OXIDATIVE_STRESS_BY_HNE_AND_TBH (59)"], ["WEIGEL_OXIDATIVE_STRESS_BY_TBH_AND_H2O2 (35)"], 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["KYNG_ENVIRONMENTAL_STRESS_RESPONSE_UP (53)"], ["MA_PITUITARY_FETAL_VS_ADULT_UP (0)"]], "row_count": 40, "column_count": 2, "numeric_cells": 49, "header_rows": 0, "locator": "section[4]/table-wrap[1]#t2"}}, {"id": "asset:table:pmid:33658390:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:a80d563059a115e5cbfc2381ff581f90d6bb590e8d13e9d727db380e0774c373", "bytes": 855, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[9]/table-wrap[1]#t3", "version": null, "note": "Clinical characteristics of the training group TCGA and the testing group GSE39582.", "structure": {"pmcid": "PMC7993742", "section_index": 9, "section_title": "Stratified survival assays", "row_count": 15, "column_count": 4}, "table": {"label": "Table 3", "caption": "Clinical characteristics of the training group TCGA and the testing group GSE39582.", "rows": [["Clinical 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