CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30633156", "kind": "science-record", "revision": 8, "content_hash": "sha256:e654c2139de6dc2c6fdfff35fe2492afdbd5ac419306fe91e336e2203d73a07d", "created_at": "2026-11-01T15:40:40Z", "updated_at": "2026-11-01T22:00:14Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CALD1, CNN1, and TAGLN identified as potential prognostic molecular markers of bladder cancer by bioinformatics analysis.", "doi": "10.1097/MD.0000000000013847", "pmid": "30633156", "authors": ["Yun Liu", "Xia Wu", "Guokun Wang", "Shisong Hu", "Yuandong Zhang", "Shenglong Zhao"], "journal": "Medicine", "year": 2019, "abstract": "BACKGROUND: Bladder cancer (BC) is one of the most common malignant neoplasms in the genitourinary tract. We employed the GSE13507 data set from the Gene Expression Omnibus (GEO) database in order to identify key genes related to tumorigenesis, progression, and prognosis in BC patients.\nMETHODS: The data set used in this study included 10 normal bladder mucosae tissue samples and 165 primary BC tissue samples. Differentially expressed genes (DEGs) in the 2 types of samples were identified by GEO2R. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the online website DAVID. The online website STRING was used to construct a protein-protein interaction network. Moreover, the plugins in MCODE and cytoHubba in Cytoscape were employed to find the hub genes and modules in these DEGs.\nRESULTS: We identified 154 DEGs comprising 135 downregulated genes and 19 upregulated genes. The GO enrichment results were mainly related to the contractile fiber part, extracellular region part, actin cytoskeleton, and extracellular region. The KEGG pathway enrichment results mainly comprised type I diabetes mellitus, asthma, systemic lupus erythematosus, and allograft rejection. A module was identified from the protein-protein interaction network. In total, 15 hub genes were selected and 3 of them comprising CALD1, CNN1, and TAGLN were associated with both overall survival and disease-free survival.\nCONCLUSION: CALD1, CNN1, and TAGLN may be potential biomarkers for diagnosis as well as therapeutic targets in BC patients.", "claims": [{"id": "claim-method", "statement": "The adjusted P values were used to reduce the false positive rate with the Benjamini and Hochberg false discovery rate method by default.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30633156", "locator": "sections[4] \"Data processing\" paragraph 2", "quote": "The adjusted P values were used to reduce the false positive rate with the Benjamini and Hochberg false discovery rate method by default."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We selected gene expression profiles from the GSE13507 data set in the GEO database, which is a free public database. The GSE13507 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, accessed December 6, 2017) gene expression profiles comprised 256 samples from the GPL6102 platform (Illumina human-6 v2.0 expression beadchip), with 10 normal bladder mucosae tissues, 165 primary BC tissues, 23 recurrent non-muscle invasive tumor tissues, and 58 normal-looking bladder mucosae surrounding cancer tissues.[10,11] In order to construct a reliable model, 165 primary BC samples and 10 normal bladder mucosae samples were selected for the analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30633156", "locator": "sections[3] \"Patient information\" paragraph 2", "quote": "We selected gene expression profiles from the GSE13507 data set in the GEO database, which is a free public database. The GSE13507 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, accessed December 6, 2017) gene expression profiles comprised 256 samples from the GPL6102 platform (Illumina human-6 v2.0 expression beadchip), with 10 normal bladder mucosae tissues, 165 primary BC tissues, 23 recurrent non-muscle invasive tumor tissues, and 58 normal-looking bladder mucosae surrounding cancer tissues.[10,11] In order to construct a reliable model, 165 primary BC samples and 10 normal bladder mucosae samples were selected for the analysis."}], "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:30633156"], "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:30633156", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1097/MD.0000000000013847", "sha256": "sha256:1f4421f8faf0f298543f1bc5a6366221f4925343c0359de24aa5916898304ce4", "bytes": 21631, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1097/MD.0000000000013847", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6336601", "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": "We selected gene expression profiles from the GSE13507 data set in the GEO database, which is a free public database. 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