AI Article Synopsis
- Bladder cancer has a poor prognosis partly due to the absence of effective biomarkers for predicting disease progression.
- Researchers analyzed three GEO datasets and identified 1516 differentially expressed genes (DEGs) linked to non-muscle invasive vs. muscle invasive bladder cancer.
- Seven genes were highlighted for their strong prognostic value, and a specific 3-panel gene set showed 95.5% sensitivity and 100% specificity in predicting bladder cancer progression.
Article Abstract
Bladder cancer prognosis remains dismal due to lack of appropriate biomarkers that can predict its progression. The study aims to identify novel prognostic biomarkers associated with the progression of bladder cancer by utilizing three Gene Expression Omnibus (GEO) datasets to screen differentially expressed genes (DEGs). A total of 1516 DEGs were identified between non-muscle invasive and muscle invasive bladder cancer specimens. To identify genes of prognostic value, we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A total of seven genes, including , , , , , , and were confirmed with strong prognostic values in bladder cancer and validated by qRT-PCR conducted in various human bladder cancer cells representing stage-specific disease progression. ULCAN, human protein atlas and The Cancer Genome Atlas datasets were used to confirm the predictive value of these genes in bladder cancer progression. Moreover, Kaplan-Meier analysis and Cox hazard ratio analysis were performed to determine the prognostic role of these genes. Univariate analysis performed on a validation set identified a 3-panel gene set viz. , and with 95.5% sensitivity and 100% specificity in predicting bladder cancer progression. In summary, our study screened and confirmed a 3-panel biomarker that could accurately predict the progression and prognosis of bladder cancer.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8656554 | PMC |
| http://dx.doi.org/10.3390/cancers13235931 | DOI Listing |
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