LncRNA profile study reveals a seven-lncRNA signature predicts the prognosis of patients with colorectal cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32128213", "kind": "science-record", "revision": 6, "content_hash": "sha256:21b491591e53aeaf36047bf0c82b9a8d346f61d54b559c1c30e98fa44bef5be8", "created_at": "2026-11-01T15:40:57Z", "updated_at": "2026-11-01T21:22:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "LncRNA profile study reveals a seven-lncRNA signature predicts the prognosis of patients with colorectal cancer.", "doi": "10.1186/s40364-020-00187-3", "pmid": "32128213", "authors": ["Rui Huang", "Lian Zhou", "Yue Chi", "Haibo Wu", "Lei Shi"], "journal": "Biomarker research", "year": 2020, "abstract": "BACKGROUND: The prognosis of colorectal cancer (CRC) is still challenging to evaluate or predict. Recently, long non-coding RNAs (lncRNAs) have been found to play an important role in tumorigenesis and prognosis, however, few lncRNAs have been identified in CRC progression. We aimed to establish a lncRNA signature to improve prognosis prediction of CRC.\nMETHODS: In the present study, we profiled lncRNA expression with a lncRNA-mining approach in two CRC data sets from Gene Expression Ominus (GEO) (GSE39582, N = 557 and GSE17538, N = 200). LncRNAs were analyzed to determine a prognostic signature by Cox regression and Robust likelihood-based survival model. We identified seven lncRNAs that significantly associated with the disease free survival (DFS) in the training group. A risk score formula was constructed to evaluate the performance of this lncRNA panel.\nRESULTS: A seven-lncRNA signature was established to predict prognosis of CRC patients. The prognostic value of this signature was verified in the training group, internal validation group and external validation cohort, respectively. Receiver operating characteristic (ROC) analysis suggested a powerful discrimination ability of the seven-gene signature. Finally, Cox regression analyzed this signature as an independent influencing factor and subsequent pathway or network analysis implicated a potential mechanism of these lncRNAs.\nCONCLUSIONS: In summary, the seven-lncRNA signature we identified can effectively classify patients. This risk score model could serve as an independent biomarker to predict prognosis of CRC patients.", "claims": [{"id": "claim-method", "statement": "LncRNAs were analyzed to determine a prognostic signature by Cox regression and Robust likelihood-based survival model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32128213", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "LncRNAs were analyzed to determine a prognostic signature by Cox regression and Robust likelihood-based survival model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data sets used and/or analyzed during the current study are publicly available data from Gene Expression Omnibus (GEO) databases (GSE39582, GSE17538). The figures and materials supporting the conclusions of this article are included within the article and its additional files).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32128213", "locator": "sections[28] \"Availability of data and materials\" paragraph 2", "quote": "The data sets used and/or analyzed during the current study are publicly available data from Gene Expression Omnibus (GEO) databases (GSE39582, GSE17538). The figures and materials supporting the conclusions of this article are included within the article and its additional files)."}], "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:32128213"], "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:32128213", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s40364-020-00187-3", "sha256": "sha256:b1197d6c12198f6b7d3253e855acd386ee6d72879e78a56cf6391aa20ca32ca2", "bytes": 58388, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s40364-020-00187-3", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7047379", "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": "The data sets used and/or analyzed during the current study are publicly available data from Gene Expression Omnibus (GEO) databases (GSE39582, GSE17538). 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1, "locator": "section[12]/table-wrap[1]#Tab1"}}, {"id": "asset:table:pmid:32128213:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:900b3e1a0955458fa60256ddfa710923af3da7172b0d39f813290493c1f31bbf", "bytes": 2682, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[13]/table-wrap[1]#Tab2", "version": null, "note": "Univariable and multivariable Cox regression analyses in each data set", "structure": {"pmcid": "PMC7047379", "section_index": 13, "section_title": "The seven lncRNA-based risk score model and the survival in the training group", "row_count": 34, "column_count": 7}, "table": {"label": "Table 2", "caption": "Univariable and multivariable Cox regression analyses in each data set", "rows": [["Variables", "Univariable modela", "Multivariable modela"], ["HR", "95% CI of HR", "P valueb", "HR", "95% CI of HR", "P valueb"], ["GSE39582 training 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