Evidence map›Paper›PMID 42470583›Full record

ArticleMolecular biology reports2026

Integrative analysis identifies candidate biomarkers for bladder cancer: evidence from genomic and clinical validation.

Sana Sajjadi, Amin Ramezani, Sajad Alavimanesh, Hojat Alipoor, Mohammad Ali Takhshid

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Article in Molecular biology reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Sana SajjadiDivision of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
Amin Ramezani *Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran. aramezani@sums.ac.ir.ORCID http://orcid.org/0000-0001-5655-8722
Sajad AlavimaneshCellular and Molecular Research Center, Basic Health Sciences Institute, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Hojat AlipoorDepartment of Urology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad Ali Takhshid *Division of Medical Biotechnology, Department of Laboratory Sciences, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran. takhshidma@sums.ac.ir.ORCID http://orcid.org/0000-0003-0246-3765

Funding

Vice-Chancellor for Research Affairs of Shiraz University of Medical Sciences 30994
6 · The paper itself

Abstract

backgroundBladder cancer (BCa) is a highly prevalent urological malignancy and one of the most frequently occurring cancers worldwide, necessitating the development of diagnostic and therapeutic biomarkers. This study aimed to explore candidate genes that may be involved in the carcinogenesis of BCa. MATERIALS AND

methodsBCa gene expression data from the Gene Expression Omnibus (GEO) database were analyzed. Both differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on datasets (GSE236932, GSE133624) to identify the key modules and hub genes. We subsequently extracted genes from the top modules positively correlated with tumor traits identified via WGCNA and intersected them with differentially expressed genes (DEGs) in each dataset. Finally, the overlapping genes were screened for their therapeutic potential as biomarkers in bladder cancer, and quantitative Real-Time PCR (qRT-PCR) was executed to validate the expression patterns of the most promising candidate genes in clinical tissue samples.

resultsIntegrative analysis revealed a set of hub genes potentially involved in bladder cancer, including PSMG3, ESRP1, GRHL2, MAL2, CDH1, AP1M2, PAFAH1B3, PRKCZ, MAPK13, and RAB25. Among these, PAFAH1B3 and PSMG3 emerged as notable novel candidates. qRT-PCR validation further underscored the significant overexpression of these genes in BCa samples, with approximately two-fold changes relative to normal tissues.

conclusionsThis study suggests that PAFAH1B3 and PSMG3 may serve as valuable biomarkers and potential therapeutic targets in bladder cancer. However, further investigations are needed to establish their biological function and clinical relevance.

Indexed as

Biomarkers, TumorUrinary Bladder NeoplasmsComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksGenomicsHumansBiomarkers, TumorBioinformatics analysisBiomarker identificationBladder cancerDifferential gene expressionqRT-PCRWeighted gene co-expression network analysis (WGCNA)

Identifiers

PMID42470583

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.