A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38306023", "kind": "science-record", "revision": 3, "content_hash": "sha256:de8a7b0362e1920d1218aee11d3fd309b6c8700026a1bf224283b13daa29f909", "created_at": "2026-11-01T19:20:14Z", "updated_at": "2026-11-01T22:11:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer.", "doi": "10.3233/CBM-230216", "pmid": "38306023", "authors": ["Zhi Yi Zhao", "Yin Cao", "Hong Liang Wang", "Ling Yun Liu"], "journal": "Cancer biomarkers : section A of Disease markers", "year": 2024, "abstract": "OBJECTIVES: We aimed to analyze lncRNAs, miRNAs, and mRNA expression profiles of bladder cancer (BC) patients, thereby establishing a gene signature-based risk model for predicting prognosis of patients with BC.\nMETHODS: We downloaded the expression data of lncRNAs, miRNAs and mRNA from The Cancer Genome Atlas (TCGA) as training cohort including 19 healthy control samples and 401 BC samples. The differentially expressed RNAs (DERs) were screened using limma package, and the competing endogenous RNAs (ceRNA) regulatory network was constructed and visualized by the cytoscape. Candidate DERs were screened to construct the risk score model and nomogram for predicting the overall survival (OS) time and prognosis of BC patients. The prognostic value was verified using a validation cohort in GSE13507.\nRESULTS: Based on 13 selected. lncRNAs, miRNAs and mRNA screened using L1-penalized algorithm, BC patients were classified into two groups: high-risk group (including 201 patients ) and low risk group (including 200 patients). The high-risk group's OS time ( hazard ratio [HR], 2.160; 95% CI, 1.586 to 2.942; P= 5.678e-07) was poorer than that of low-risk groups' (HR, 1.675; 95% CI, 1.037 to 2.713; P= 3.393 e-02) in the training cohort. The area under curve (AUC) for training and validation datasets were 0.852. Younger patients (age ⩽ 60 years) had an improved OS than the patients with advanced age (age > 60 years) (HR 1.033, 95% CI 1.017 to 1.049; p= 2.544E-05). We built a predictive model based on the TCGA cohort by using nomograms, including clinicopathological factors such as age, recurrence rate, and prognostic score.\nCONCLUSIONS: The risk model based on 13 DERs patterns could well predict the prognosis for patients with BC.", "claims": [{"id": "claim-method", "statement": "What’s more, penalized package (Version 0.9–50) [25] was applied to screen the optimized DERs with Cox-PH model [26].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38306023", "locator": "sections[6] \"Prognosis related RNAs screening\" paragraph 2", "quote": "What’s more, penalized package (Version 0.9–50) [25] was applied to screen the optimized DERs with Cox-PH model [26]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analysed during the current study are available in the NCBI repository, https://www.ncbi.nlm.nih.gov/geo/. Accession number: GSE13507.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38306023", "locator": "sections[16] \"Data availability statement\" paragraph 2", "quote": "The datasets generated and/or analysed during the current study are available in the NCBI repository, https://www.ncbi.nlm.nih.gov/geo/. Accession number: GSE13507."}], "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:38306023"], "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:GSE13507"], "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": {"hazard_ratio": "ts older than 60 years (HR 1"}, "inputs": ["data:geo:GSE13507"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38306023", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3233/CBM-230216", "sha256": "sha256:2814baf6517ef05a24244030d305d324a111edf91b57301daaa294a6adafbe6e", "bytes": 29671, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3233/CBM-230216", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11091654", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE13507", "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=GSE13507", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE13507", "version": null, "note": "The datasets generated and/or analysed during the current study are available in the NCBI repository, https://www.ncbi.nlm.nih.gov/geo/. 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