Comprehensive analysis of immune related lncRNAs in the tumor microenvironment of stage II-III colorectal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34790388", "kind": "science-record", "revision": 3, "content_hash": "sha256:847d00fdbd0c8efd2eb1aa4d2ec521bde63cae45b5ac31f3afb9442135efafa7", "created_at": "2026-11-01T17:36:29Z", "updated_at": "2026-11-01T21:26:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of immune related lncRNAs in the tumor microenvironment of stage II-III colorectal cancer.", "doi": "10.21037/jgo-21-594", "pmid": "34790388", "authors": ["Zan Zhang", "Yixin Wu", "Changyuan Yu", "Zhengtai Li", "Lida Xu"], "journal": "Journal of gastrointestinal oncology", "year": 2021, "abstract": "BACKGROUND: Long non-coding RNAs (lncRNAs) associated with immunological function have increasingly been found to act as effective prognostic biomarkers of the overall survival (OS) of colorectal cancer (CRC) patients. We sought to identify a signature of immune-related lncRNAs that offered value as a tool for the prospective prognostic evaluation of patients with stage II-III CRC.\nMETHODS: The clinical and gene expression data of CRC patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases was obtained and separated into a training cohort composed of 202 samples, a test cohort of 124 samples from the GSE72970 dataset, and a validation cohort of 91 samples from the GSE143985 dataset.\nRESULTS: We firstly evaluated intratumoral immune cell infiltration by conducting a Single-sample gene set enrichment analyses (ssGSEA) analysis to separate patient tumors into those with low immune cell infiltration and those with high immune cell infiltration. We then compared lncRNA and mRNA expression profiles between these two tumor types, leading us to focus on eight lncRNAs identified within the resultant mRNA-lncRNA co-expression network. Multivariate Cox regression models were then utilized to detect an immune-associated lncRNA signature that offered value for prognostic model construction. Functional analyses revealed this lncRNA signature to be associated with key immunological pathways including the JAK-STAT signaling, T cell receptor signaling, and Rap1 signaling pathways.\nCONCLUSIONS: Together, our results suggest that our immune-related 4 lncRNA signature can reliably predict stage II-III CRC patient prognosis, thereby guiding efforts to better understand this disease and to effectively treat it.", "claims": [{"id": "claim-method", "statement": "We firstly evaluated intratumoral immune cell infiltration by conducting a Single-sample gene set enrichment analyses (ssGSEA) analysis to separate patient tumors into those with low immune cell infiltration and those with high immune cell infiltration. We then compared lncRNA and mRNA expression profiles between these two tumor types, leading us to focus on eight lncRNAs identified within the resultant mRNA-lncRNA co-expression network. Multivariate Cox regression models were then utilized to detect an immune-associated lncRNA signature that offered value for prognostic model construction.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34790388", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We firstly evaluated intratumoral immune cell infiltration by conducting a Single-sample gene set enrichment analyses (ssGSEA) analysis to separate patient tumors into those with low immune cell infiltration and those with high immune cell infiltration. We then compared lncRNA and mRNA expression profiles between these two tumor types, leading us to focus on eight lncRNAs identified within the resultant mRNA-lncRNA co-expression network. Multivariate Cox regression models were then utilized to detect an immune-associated lncRNA signature that offered value for prognostic model construction."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The clinical and gene expression data of CRC patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases was obtained and separated into a training cohort composed of 202 samples, a test cohort of 124 samples from the GSE72970 dataset, and a validation cohort of 91 samples from the GSE143985 dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34790388", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The clinical and gene expression data of CRC patients in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases was obtained and separated into a training cohort composed of 202 samples, a test cohort of 124 samples from the GSE72970 dataset, and a validation cohort of 91 samples from the GSE143985 dataset."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Together, our results suggest that our immune-related 4 lncRNA signature can reliably predict stage II–III CRC patient prognosis, thereby guiding efforts to better understand this disease and to effectively treat it.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34790388", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Together, our results suggest that our immune-related 4 lncRNA signature can reliably predict stage II–III CRC patient prognosis, thereby guiding efforts to better understand this disease and to effectively treat it."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Together, our results suggest that our immune-related 4 lncRNA signature can reliably predict stage II–III CRC patient prognosis, thereby guiding efforts to better understand this disease and to effectively treat it.", "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:34790388"], "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. 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