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pmid:36643693

Bioinformatics analysis of key biomarkers for bladder cancer.

Wentao Liu · Yuxin Xu · Shengbin Bai · Libin Liao

Biomedical reports · 2023 doi:10.3892/br.2022.1596

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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2026-11-01T19:01:12Z
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title
Bioinformatics analysis of key biomarkers for bladder cancer.
doi
10.3892/br.2022.1596
pmid
36643693
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[0]
Wentao Liu
[1]
Yuxin Xu
[2]
Shengbin Bai
[3]
Libin Liao
journal
Biomedical reports
year
2023
abstract
Bladder cancer (BC) is one of the most prevalent genitourinary cancers. Despite the growing research interest in BC, the molecular mechanisms underlying its carcinogenesis remain poorly understood. The microarray datasets GSE38264 and GSE61615 obtained from the Gene Expression Omnibus (GEO) database were analyzed and differentially expressed genes (DEGs) were identified, which were then verified using a dataset from The Cancer Genome Atlas (TCGA). By taking the intersection of the two microarray datasets, the common DEGs were identified and these were selected as candidate genes associated with BC. The DEGs were further subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and the protein-protein interaction network was constructed. Further module analysis was performed using STRING and Cytoscape. A total of 362 DEGs were identified, including 13 hub genes, and the GO analysis revealed that these genes were mainly enriched in extracellular matrix organization, positive regulation of cell proliferation, angiogenesis and peptidyl-tyrosine phosphorylation. The expression changes of PTPRC, PDGFRA, CASQ2, TGFBI, KLRD1 and MT1X in the different datasets indicated that these genes were involved in the development of BC. Next, the differential expression of these genes was verified in the TCGA dataset, and ultimately, these 13 genes were determined to be related to the occurrence and development of BC. Finally, the cancer tissues and adjacent tissues of patients with BC were collected and subjected to reverse transcription-quantitative PCR, the results of which were consistent with the bioinformatics prediction. The present findings provide several vital genes for the clinical diagnosis and treatment of BC.
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GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to screen DEGs between BC and non-cancerous samples.
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sections[4] "Identification of DEGs" paragraph 2
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GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to screen DEGs between BC and non-cancerous samples.
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TCGA mRNA expression and clinical data were downloaded from the TCGA public database (https://portal.gdc.cancer.gov/) and the GEO mRNA expression and clinical data were downloaded from the GEO public database (https://www.ncbi.nlm.nih.gov/geo/).
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The analysis identified 362 common differentially expressed genes between the two bladder-cancer microarray datasets.
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sections[15] "Identification of DEGs in BC" paragraph 2
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After standardizing gene expression values in the GeneChip datasets GSE38264 and GSE6165, 4,414 and 494 DEGs were screened, respectively. As indicated in the Venn diagram (Fig. 1A), the overlap between the two datasets contained 362 genes.
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The analysis identified 362 common differentially expressed genes between the two bladder-cancer microarray datasets.
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In vivo disruption of Rb-E2F-Ezh2 signaling loop causes bladder cancer development
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TCGA mRNA expression and clinical data were downloaded from the TCGA public database (https://portal.gdc.cancer.gov/) and the GEO mRNA expression and clinical data were downloaded from the GEO public database (https://www.ncbi.nlm.nih.gov/geo/).
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GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to screen DEGs between BC and non-cancerous samples.
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carcinogenesis remain poorly understood. The microarray datasets GSE38264 and GSE61615 obtained from
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36643693", "kind": "science-record", "revision": 3, "content_hash": "sha256:164de6060b831fe88aa98464424322de44b11bfd49cf85fc61357a732bd20904", "created_at": "2026-11-01T19:01:12Z", "updated_at": "2026-11-01T22:08:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics analysis of key biomarkers for bladder cancer.", "doi": "10.3892/br.2022.1596", "pmid": "36643693", "authors": ["Wentao Liu", "Yuxin Xu", "Shengbin Bai", "Libin Liao"], "journal": "Biomedical reports", "year": 2023, "abstract": "Bladder cancer (BC) is one of the most prevalent genitourinary cancers. Despite the growing research interest in BC, the molecular mechanisms underlying its carcinogenesis remain poorly understood. The microarray datasets GSE38264 and GSE61615 obtained from the Gene Expression Omnibus (GEO) database were analyzed and differentially expressed genes (DEGs) were identified, which were then verified using a dataset from The Cancer Genome Atlas (TCGA). By taking the intersection of the two microarray datasets, the common DEGs were identified and these were selected as candidate genes associated with BC. The DEGs were further subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and the protein-protein interaction network was constructed. Further module analysis was performed using STRING and Cytoscape. A total of 362 DEGs were identified, including 13 hub genes, and the GO analysis revealed that these genes were mainly enriched in extracellular matrix organization, positive regulation of cell proliferation, angiogenesis and peptidyl-tyrosine phosphorylation. The expression changes of PTPRC, PDGFRA, CASQ2, TGFBI, KLRD1 and MT1X in the different datasets indicated that these genes were involved in the development of BC. Next, the differential expression of these genes was verified in the TCGA dataset, and ultimately, these 13 genes were determined to be related to the occurrence and development of BC. Finally, the cancer tissues and adjacent tissues of patients with BC were collected and subjected to reverse transcription-quantitative PCR, the results of which were consistent with the bioinformatics prediction. The present findings provide several vital genes for the clinical diagnosis and treatment of BC.", "claims": [{"id": "claim-method", "statement": "GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to screen DEGs between BC and non-cancerous samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36643693", "locator": "sections[4] \"Identification of DEGs\" paragraph 2", "quote": "GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) was used to screen DEGs between BC and non-cancerous samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "TCGA mRNA expression and clinical data were downloaded from the TCGA public database (https://portal.gdc.cancer.gov/) and the GEO mRNA expression and clinical data were downloaded from the GEO public database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36643693", "locator": "sections[24] \"Availability of data and materials\" paragraph 2", "quote": "TCGA mRNA expression and clinical data were downloaded from the TCGA public database (https://portal.gdc.cancer.gov/) and the GEO mRNA expression and clinical data were downloaded from the GEO public database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 362 common differentially expressed genes between the two bladder-cancer microarray datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36643693", "locator": "sections[15] \"Identification of DEGs in BC\" paragraph 2", "quote": "After standardizing gene expression values in the GeneChip datasets GSE38264 and GSE6165, 4,414 and 494 DEGs were screened, respectively. 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