Development and Validation of a Six-Gene Prognostic Signature for Bladder Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34938313", "kind": "science-record", "revision": 4, "content_hash": "sha256:aa6e244fd5f4ec3169f9d2a97ed1eccb9384b6ae8236978ec2082aed078588a1", "created_at": "2026-11-01T17:36:39Z", "updated_at": "2026-11-01T22:05:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and Validation of a Six-Gene Prognostic Signature for Bladder Cancer.", "doi": "10.3389/fgene.2021.758612", "pmid": "34938313", "authors": ["Fei Xu", "Qianqian Tang", "Yejinpeng Wang", "Gang Wang", "Kaiyu Qian", "Lingao Ju", "Yu Xiao"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "Human bladder cancer (BCa) is the most common urogenital system malignancy. Patients with BCa have limited treatment efficacy in clinical practice. Novel biomarkers could provide more crucial information conferring to cancer diagnosis, treatment, and prognosis. Here, we aimed to explore and identify novel biomarkers associated with cancer-specific survival of patients with BCa to build a prognostic signature. Based on univariate Cox regression, Lasso regression, and multivariate Cox regression analysis, we conducted an integrated analysis in the training set (GSE32894) and established a six-gene signature to predict the cancer-specific survival for human BCa. The six genes were Cyclin Dependent Kinase 4 (CDK4), E2F Transcription Factor 7 (E2F7), Collagen Type XI Alpha 1 Chain (COL11A1), Bradykinin Receptor B2 (BDKRB2), Yip1 Interacting Factor Homolog B (YIF1B), and Zinc Finger Protein 415 (ZNF415). Then, we validated the prognostic value of the model by using two other datasets (GSE13507 and TCGA). Also, we conducted univariate and multivariate Cox regression analyses, and results indicated that the six-gene signature was an independent prognostic factor of cancer-specific survival of patients with BCa. Functional analysis was performed based on the differentially expressed genes of low- and high-risk patients, and we found that they were enriched in lipid metabolic and cell division-related biological processes. Meanwhile, the gene set enrichment analysis (GSEA) revealed that high-risk samples were enriched in cell cycle and cancer-related pathways [G2/M checkpoint, E2F targets, mitotic spindle, mTOR signaling, spermatogenesis, epithelial-mesenchymal transition (EMT), DNA repair, PI3K/AKT/mTOR signaling, unfolded protein response (UPR), and MYC targets V2]. Lastly, we detected the relative expression of each signature in BCa cell lines by quantitative real-time PCR (qRT-PCR). As far as we know, currently, the present study is the first research that developed and validated a cancer-specific survival prognostic index based on three independent cohorts. The results revealed that this six-gene signature has a predictive ability for cancer-specific prognosis. Moreover, we also verified the relative expression of these six signatures between the bladder cell line and four BCa cell lines by qRT-PCR. Nevertheless, experiments to further explore the function of six genes are lacking.", "claims": [{"id": "claim-method", "statement": "Univariate hazard Cox regression, LASSO regression, and multivariate hazard Cox regression analyses were performed to identify the prognostic factors and to establish a prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34938313", "locator": "sections[11] \"2.9 Statistical Analysis\" paragraph 2", "quote": "Univariate hazard Cox regression, LASSO regression, and multivariate hazard Cox regression analyses were performed to identify the prognostic factors and to establish a prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34938313", "locator": "sections[25] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study established and validated a six-gene signature as an independent prognostic indicator for cancer-specific survival in human bladder cancer.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34938313", "locator": "sections[1] \"1 Introduction\" paragraph 4", "quote": "Our study proved that the six-gene signature could function as the independent biomarkers for the cancer-specific prognosis of human BCa and their potential roles in tumor progression."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study established and validated a six-gene signature as an independent prognostic indicator for cancer-specific survival in human bladder cancer.", "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:34938313"], "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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