Prognostic significance and identification of basement membrane-associated lncRNA in bladder cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36300088", "kind": "science-record", "revision": 3, "content_hash": "sha256:8fe2bb112d2f28d94ec59f6417805bcee780218c8f5861c4120b04452990dfa1", "created_at": "2026-11-01T18:15:43Z", "updated_at": "2026-11-01T21:29:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prognostic significance and identification of basement membrane-associated lncRNA in bladder cancer.", "doi": "10.3389/fonc.2022.994703", "pmid": "36300088", "authors": ["Lixiang Feng", "Jun Yang", "Wei Zhang", "Xiong Wang", "Lili Li", "Min Peng", "Pengcheng Luo"], "journal": "Frontiers in oncology", "year": 2022, "abstract": "Based on the importance of basement membrane (BM) in cancer invasion and metastasis, we constructed a BM-associated lncRNA risk model to group bladder cancer (BCa) patients. Transcriptional and clinical data of BCa patients were downloaded from The Cancer Genome Atlas (TCGA), and the expressed genes of BM-related proteins were obtained from the BM-BASE database. We download the GSE133624 chip data from the GEO database as an external validation dataset. We screened for statistically different BM genes between tumors and adjacent normal tissues. Co-expression analysis of lncRNAs and differentially expressed BM genes was performed to identify BM-related lncRNAs. Then, differentially expressed BM-related lncRNAs (DEBMlncRNAs) between tumor and normal tissues were identified. Univariate/multivariate Cox regression analysis was performed to select lncRNAs for risk assessment. LASSO analysis was performed to build a prognostic model. We constructed a model containing 8 DEBMlncRNAs (AC004034.1, AL662797.1, NR2F1-AS1, SETBP1-DT, AC011503.2, AC093010.2, LINC00649 and LINC02321). The prognostic risk model accurately predicted the prognosis of BCa patients and revealed that tumor aggressiveness and distant metastasis were associated with higher risk scores. In this model, we constructed a nomogram to assist clinical decision-making based on clinicopathological characteristics such as age, T, and N. The model also showed good predictive power for the tumor microenvironment and mutational burden. We validated the expression of eight lncRNAs using the dataset GSE133624 and two human bladder cancer cell lines (5637, BIU-87) and examined the expression and cellular localization of LINC00649 and AC011503.2 using a human bladder cancer tissue chip. We found that knockdown of LINC00649 expression in 5637 cells promoted the proliferation of 5637 cells.Our eight DEBMlncRNA risk models provide new insights into predicting prognosis, tumor invasion, and metastasis in BCa patients.", "claims": [{"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: The data are available at the TCGA (https://tcga-data.nci.nih.gov/tcga/) and BM-BASE database (https://bmbase.manchester.ac.uk).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36300088", "locator": "sections[31] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: The data are available at the TCGA (https://tcga-data.nci.nih.gov/tcga/) and BM-BASE database (https://bmbase.manchester.ac.uk)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study used LASSO Cox and multivariate Cox regression to develop an eight-lncRNA basement membrane-associated risk model for bladder cancer from TCGA and BM-BASE data, with expression validated using GSE133624 and bladder cancer cell lines.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36300088", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Transcriptional and clinical data of BCa patients were downloaded from The Cancer Genome Atlas (TCGA), and the expressed genes of BM-related proteins were obtained from the BM-BASE database."}, {"asset": "source:pmid:36300088", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We download the GSE133624 chip data from the GEO database as an external validation dataset."}, {"asset": "source:pmid:36300088", "locator": "sections[20] \"Development of a prognostic risk model\" paragraph 2", "quote": "Ultimately, eight DEBMlncRNAs (AC004034.1, AL662797.1, NR2F1-AS1, SETBP1-DT, AC011503.2, AC093010.2, LINC00649 and LINC02321) were identified to develop a risk model (Figures 2A, B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study used LASSO Cox and multivariate Cox regression to develop an eight-lncRNA basement membrane-associated risk model for bladder cancer from TCGA and BM-BASE data, with expression validated using GSE133624 and bladder cancer cell lines.", "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:36300088"], "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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