Telomere-related gene risk model for prognosis prediction in colorectal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39145075", "kind": "science-record", "revision": 3, "content_hash": "sha256:3ee8ed3c980a0db9d8e1f6042632d6156af541835c145aa50616cfb13c9d951c", "created_at": "2026-11-01T20:29:16Z", "updated_at": "2026-11-01T22:12:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Telomere-related gene risk model for prognosis prediction in colorectal cancer.", "doi": "10.21037/tcr-24-43", "pmid": "39145075", "authors": ["Hao Chen", "Yuhao Pan", "Chenhui Lv", "Wei He", "Dingting Wu", "Qijia Xuan"], "journal": "Translational cancer research", "year": 2024, "abstract": "Background: Colorectal cancer (CRC) is the third-most prevalent cancer globally. The biological significance of telomeres in CRC carcinogenesis and progression is underscored by accumulating data. Nevertheless, not much is known about how telomere-related genes (TRGs) affect CRC prognosis. Therefore, the aim of this study was to investigate the role of TRGs in CRC prognosis.\nMethods: We retrospectively obtained the expression profiles and clinical data of CRC patients from public databases. Utilizing least absolute shrinkage and selection operator (LASSO) regression analysis, we created a telomere-related risk model to predict survival outcomes, identifying ten telomere-related differentially expressed genes (TRDEGs). Based on TRDEGs, we stratified patients from The Cancer Genome Atlas (TCGA) into low- and high-risk subsets. Subsequently, we conducted comprehensive analyses, including survival assessment, immune cell infiltration, drug sensitivity, and prediction of molecular interactions using Kaplan-Meier curves, ESTIMATE, CIBERSORT, OncoPredict, and other approaches.\nResults: The model showed exceptional predictive accuracy for survival. Significant differences in survival were observed between the two groups of participants grouped according to the model (P<0.001), and this difference was further confirmed in the external validation set (GSE39582) (P=0.004). Additionally, compared to the low-risk group, the high-risk group exhibited significantly advanced tumor node metastasis (TNM) stages, lower proportions of activated CD4+ T cells, effector memory CD4+ T cells, and memory B cells, but increased ratios of M2 macrophages and regulatory T cells (Tregs), elevated tumor immune dysfunction and exclusion (TIDE) scores, and diminished sensitivity to dabrafenib, lapatinib, camptothecin, docetaxel, and telomerase inhibitor IX, reflecting the signature's capacity to distinguish clinical pathological characteristics, immune environment, and drug efficacy. Finally, we validated the expression of the ten TRDEGs (ACACB, TPX2, SRPX, PPARGC1A, CD36, MMP3, NAT2, MMP10, HIGD1A, and MMP1) through quantitative real-time polymerase chain reaction (qRT-PCR) and found that compared to normal cells, the expression levels of ACACB, HIGD1A, NAT2, PPARGC1A, and TPX2 in CRC cells were elevated, whereas those of CD36, SRPX, MMP1, MMP3, and MMP10 were reduced.\nConclusions: Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction.", "claims": [{"id": "claim-method", "statement": "To assess the prognostic significance of the thirteen TRDEGs, a prognostic model was developed using LASSO regression (Figure 6A).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39145075", "locator": "sections[25] \"Construction and validation of TRDEG’s prognostic model\" paragraph 2", "quote": "To assess the prognostic significance of the thirteen TRDEGs, a prognostic model was developed using LASSO regression (Figure 6A)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We downloaded the CRC dataset (TCGA-COADREAD) from The Cancer Genome Atlas (TCGA) using the TCGAbiolinks package (19).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39145075", "locator": "sections[4] \"Data download\" paragraph 2", "quote": "We downloaded the CRC dataset (TCGA-COADREAD) from The Cancer Genome Atlas (TCGA) using the TCGAbiolinks package (19)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39145075", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Overall, we constructed a telomere-related biomarker capable of predicting prognosis and treatment response in CRC individuals, offering potential guidance for drug therapy selection and prognosis prediction.", "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:39145075"], "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:GSE25070"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_mann_whitney", "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:GSE25070"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_mann_whitney"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39145075", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-24-43", "sha256": "sha256:d14d26d31bf0061c55a4fb298cb9ef1d6c8b27afac5b056325577f6b1533fe9f", "bytes": 56438, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tcr-24-43", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11319979", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE25070", "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=GSE25070", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE25070", "version": null, "note": "We downloaded the CRC dataset (TCGA-COADREAD) from The Cancer Genome Atlas (TCGA) using the TCGAbiolinks package (19).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We downloaded the CRC dataset (TCGA-COADREAD) from The Cancer Genome Atlas (TCGA) using the TCGAbiolinks package (19).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM615865", "GSM615866", "GSM615867", "GSM615868", "GSM615869", "GSM615870", "GSM615871", "GSM615872", "GSM615873", "GSM615874", "GSM615875", "GSM615876", "GSM615877", "GSM615878", "GSM615879", "GSM615880", "GSM615881", "GSM615882", "GSM615883", "GSM615884", "GSM615885", "GSM615886", "GSM615887", "GSM615888", "GSM615889", "GSM615890", "GSM615891", "GSM615892", "GSM615893", "GSM615894", "GSM615895", "GSM615896", "GSM615897", "GSM615898", "GSM615899", "GSM615900", "GSM615901", "GSM615902", "GSM615903", "GSM615904", "GSM615905", "GSM615906", "GSM615907", "GSM615908", "GSM615909", "GSM615910", "GSM615911", "GSM615912", "GSM615913", "GSM615914", "GSM615915", "GSM615916"], "sample_count": 52, "group_sizes": null, "group_sizes_basis": null, "platform": "6883", "taxon": "Homo sapiens", "title": "Gene expression analysis of colorectal tumors and matched adjacent non-tumor colorectal tissues.", "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": "We downloaded the CRC dataset (TCGA-COADREAD) from The Cancer Genome Atlas (TCGA) using the TCGAbiolinks package (19).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", 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