Construction of an lncRNA model for prognostic prediction of bladder cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36514150", "kind": "science-record", "revision": 4, "content_hash": "sha256:c2da338aee12b32ab53c8f4609fb2d2a8c95f464e2221598d4c84031df4f4a5b", "created_at": "2026-11-01T19:01:01Z", "updated_at": "2026-11-01T22:50:49Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction of an lncRNA model for prognostic prediction of bladder cancer.", "doi": "10.1186/s12920-022-01414-6", "pmid": "36514150", "authors": ["Changlong Shi", "Yifei Li", "Enming Wan", "Enchong Zhang", "Li Sun"], "journal": "BMC medical genomics", "year": 2022, "abstract": "OBJECTIVE: We aimed to investigate the role and potential mechanisms of long non-coding RNAs (lncRNAs) in bladder cancer (BC), as well as determine their prognostic value.\nMETHODS: LncRNA expression data and clinical data from BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to carry out principal component analysis (PCA), differential analysis, and prognostic analysis. Lasso regression and multivariate Cox regression analyses were performed to identify potential prognostic genes. The expression of five identified genes and their correlation with prognosis were verified using TCGA and GSE13507 datasets. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm the expression of these five genes in cell lines (two human BC cell lines and one human bladder epithelial cell line) and tissues (84 pairs of BC tissues and the corresponding paracancerous tissues). Risk scores that had been generated from the five genes and their prognostic ability were assessed by receiver operating characteristic (ROC) and Kaplan-Meier (KM) curves. Co-expressed genes were screened by WGCNA and analyzed by GO and KEGG, while functional enrichment and immune infiltration analyses were performed using STRING ( https://cn.string-db.org/ ) and TIMER2.0 ( http://timer.cistrome.org/ ) online tools, respectively.\nRESULTS: CYP4F8, FAR2P1, LINC01518, LINC01764, and DTNA were identified as potential prognostic genes. We found that these five genes were differentially expressed in BC tissue, as well as in BC cell lines, and were significantly correlated with the prognosis of BC patients. KM analysis considering risk scores as independent parameters revealed differences in overall survival (OS) by subgroups. The ROC curve revealed that a combined model consisting of all five genes had good predictive ability at 1, 3, and 5 years. GO and KEGG analyses of 567 co-expressed genes revealed that these genes were significantly associated with muscle function.\nCONCLUSION: LncRNAs can be good predictors of BC development and prognosis, and may act as potential tumor markers and therapeutic targets that may be beneficial in helping clinicians decide the most effective treatment strategies.", "claims": [{"id": "claim-method", "statement": "R software was used to carry out principal component analysis (PCA), differential analysis, and prognostic analysis. Lasso regression and multivariate Cox regression analyses were performed to identify potential prognostic genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36514150", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "R software was used to carry out principal component analysis (PCA), differential analysis, and prognostic analysis. Lasso regression and multivariate Cox regression analyses were performed to identify potential prognostic genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All the data in the results of this study can be reasonably obtained from the corresponding authors. All data in the article is obtained from bioinformatics mining. The rawdata has been exposed on the https://figshare.com/ public resource platform, there are links in the article. There are no restrictions on data access in this article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36514150", "locator": "sections[22] \"notes\" paragraph 1", "quote": "All the data in the results of this study can be reasonably obtained from the corresponding authors. All data in the article is obtained from bioinformatics mining. The rawdata has been exposed on the https://figshare.com/ public resource platform, there are links in the article. There are no restrictions on data access in this article."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The combined five-gene model had good predictive ability at 1, 3, and 5 years, with AUC values of 0.79, 0.74, and 0.74, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36514150", "locator": "sections[13] \"Construction and evaluation of a 5-gene prognostic model\" paragraph 2", "quote": "ROC analysis indicated that a combined model consisting of all five genes had good predictive ability at 1 year (ACU value = 0.79), 3 years (ACU value = 0.74) and 5 years (ACU value = 0.74)"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The combined five-gene model had good predictive ability at 1, 3, and 5 years, with AUC values of 0.79, 0.74, and 0.74, respectively.", "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:36514150"], "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": {}, "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:36514150", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-022-01414-6", "sha256": "sha256:4f2a3b5aa253d968a8dfd0371f77a8cdf148264188acd0371cea1729a3295013", "bytes": 31426, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-022-01414-6", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9749389", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "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": "All the data in the results of this study can be reasonably obtained from the corresponding authors. All data in the article is obtained from bioinformatics mining. The rawdata has been exposed on the https://figshare.com/ public resource platform, there are links in the article. There are no restrictions on data access in this article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "All the data in the results of this study can be reasonably obtained from the corresponding authors. All data in the article is obtained from bioinformatics mining. The rawdata has been exposed on the https://figshare.com/ public resource platform, there are links in the article. 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