ArticleScientific reports2024
Identification and validation of prognostic signature genes of bladder cancer by integrating methylation and transcriptomic analysis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Article
- Identification and validation of novel inflammatory response-related diagnostic biomarkers in diabetic foot ulcers.Journal of diabetes investigation · 2026Article
- Itaconate-Related Gene Signatures as Prognostic Markers in Colon Cancer: Insights From Transcriptomic and Spatial Analysis.Human mutation · 2026Article
- A GRK5 centered prognostic framework for bladder cancer based on palmitoylation and epigenetic regulation.Discover oncology · 2025Article
- Integrative Analysis Reveals the Prognostic Effects of Epigenetic Regulators in Bladder Cancer.Cancer medicine · 2025Article
- Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification.Discover oncology · 2025Review
- Epigenetic Biomarkers as a New Diagnostic Tool in Bladder Cancer-From Early Detection to Prognosis.Journal of clinical medicine · 2024Review
- Molecular Landscape of Bladder Cancer: Key Genes, Transcription Factors, and Drug Interactions.International journal of molecular sciences · 2024Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Being a frequent malignant tumor of the genitourinary system, Bladder Urothelial Carcinoma (BLCA) has a poor prognosis. This study focused on identifying and validating prognostic biomarkers utilizing methylation, transcriptomics, and clinical data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA BLCA) cohort. The impact of altered differentially methylated hallmark pathway genes was subjected to clustering analysis to observe changes in the transcriptional landscape on BLCA patients and identify two subtypes of patients from the TCGA BLCA population where Subtype 2 was associated with the worst prognosis with a p-value of 0.00032. Differential expression and enrichment analysis showed that subtype 2 was enriched in immune-responsive and cancer-progressive pathways, whereas subtype 1 was enriched in biosynthetic pathways. Following, regression and network analyses revealed Epidermal Growth Factor Receptor (EGFR), Fos-related antigen 1 (FOSL1), Nuclear Factor Erythroid 2 (NFE2), ADP-ribosylation factor-like protein 4D (ARL4D), SH3 domain containing ring finger 2 (SH3RF2), and Cadherin 3 (CDH3) genes to be the most significant prognostic gene markers. These genes were used to construct a risk model that separated the BLCA patients into high and low-risk groups. The risk model was also validated in an external dataset by performing survival analysis between high and low-risk groups with a p-value < 0.001 and the result showed the high group was significantly associated with poor prognosis compared to the low group. Single-cell analyses revealed the elevated level of these genes in the tumor microenvironment and associated with immune response. High-grade patients also tend to have a high expression of these genes compared to low-grade patients. In conclusion, this research developed a six-gene signature that is pertinent to the prediction of overall survival (OS) and might contribute to the advancement of precision medicine in the management of bladder cancer.
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