ArticleJournal of translational medicine2026
A bladder cancer-associated gene signature for exploratory qPCR-based survival stratification in NAC-Treated muscle-invasive bladder cancer.
Article in Journal of translational medicine, 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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Abstract
backgroundMuscle-invasive bladder cancer (MIBC) is an aggressive and heterogeneous malignancy with limited biomarkers to guide patient stratification and response to neoadjuvant chemotherapy (NAC). We sought to define the biological basis and clinical utility of a bladder cancer-associated ten-gene signature for predicting prognosis and therapeutic response.
methodsBulk transcriptomic data from The Cancer Genome Atlas (TCGA) and single-nucleus RNA sequencing (snRNASeq) of primary MIBC tumors were integrated to characterize the cellular context of the ten-gene bladder cancer (BLCA) signature. Machine-learning approaches were applied to qPCR-derived expression data to develop an exploratory model for survival stratification.
resultsAn expression-based direction-weighted BLCA signature score was associated with worse OS, DSS, and PFI in TCGA-BLCA and marked a tumor state characterized by coordinated activation of oncogenic programs including EMT, cell-cycle, and MAPK/PI3K signaling. snRNASeq revealed enrichment of signature activity within the stromal compartment, marked by expansion of FAP
conclusionsTranslating these findings, qPCR-derived expression of the ten-gene panel was used to build an exploratory machine-learning model for survival stratification in the NAC-treated MIBC cohort. The selected StepCox (forward) + RSF model showed moderate internal discrimination after bootstrap optimism correction (optimism-corrected C-index = 0.695, 95% CI 0.628-0.792), supporting the feasibility of qPCR-based risk modeling while highlighting the need for external validation.
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