ArticlePathology oncology research : POR2020
Identifying Potential Prognostic Markers for Muscle-Invasive Bladder Urothelial Carcinoma by Weighted Gene Co-Expression Network Analysis.
Article in Pathology oncology research : POR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 16 citations in OpenAlex.
- Article
- PDLIM3 expression is implicated in the invasive behavior of glioblastoma stem cells and their ability to form neurospheres.microPublication biology · 2025Article
- Article
- JAM3: A prognostic biomarker for bladder cancer via epithelial-mesenchymal transition regulation.Biomolecules & biomedicine · 2024Article
- Review
- Identifying stage-associated hub genes in bladder cancer via weighted gene co-expression network and robust rank aggregation analyses.Medicine · 2022Article
- Comprehensive Analysis of PDLIM3 Expression Profile, Prognostic Value, and Correlations with Immune Infiltrates in Gastric Cancer.Journal of immunology research · 2022Article
- Article
- Identification of Lymph Node Metastasis-Related Key Genes and Prognostic Risk Model in Bladder Cancer by Co-Expression Analysis.Frontiers in molecular biosciences · 2021Article
- Identification of Key Gene and Pathways for the Prediction of Peritoneal Metastasis of Gastric Cancer by Co-expression Analysis.Journal of Cancer · 2020Article
- Integrated Transcriptomic Analysis Reveals the Molecular Mechanism of Meningiomas by Weighted Gene Coexpression Network Analysis.BioMed research international · 2020Article
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Authors and funding
5 authors at 4 institutions in 1 country.
Funding
Abstract
Muscle-invasive bladder urothelial carcinoma (MIBC) is characterized as a genetic heterogeneous cancer with a high percentage of recurrence and worse prognosis. Identify the prognostic potentials of novel genes for muscle-invasive urothelial bladder cancer could at least provide important information for early detection and clinical treatment. Weighted gene co-expression network analysis (WGCNA) algorithm, a powerful systems biology approach, was utilized to extract co-expressed gene networks from mRNA expression dataset to construct transcriptional modules in MIBC samples, which was associated with demographic and clinical traits of MIBC patients. The potential prognostic markers of MIBC were screened out in the discovery dataset and verified in an independent external validation dataset. A total of 8 co-expression modules were detected through the WGCNA algorithm in the discovery datasets based on 401 MIBC samples. One transcriptional module enriched in cell development was observed to be correlated with the MIBC prognosis in the discovery datasets (HR = 1.48, 95%CI = 1.04-2.11) and independently verified in an external dataset (HR = 3.59, 95%CI = 1.09-11.79). High expression of hub genes including discoidin domain receptor tyrosine kinase 2 (DDR2), PDZ and LIM domain 3 (PDLIM3), zinc finger protein 521 (ZNF521), methionine sulfoxide reductase B3 (MSRB3) were significantly associated with the unfavorable survival of MIBC patients. We identified and validated four novel potential biomarkers associated with prognosis of MIBC patients by constructing genes co-expression networks. The discovery of these genetic markers may provide a new target for the development of MIBC chemotherapeutic drugs.
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