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TruaceTracing the truth around AIWednesday, August 5, 2026
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TRV-2026-0569Certified recordPeer-reviewed

Epigenomics-Guided Multi-Omics Integration Uncovers a Lipid-Metabolic Signature with Translational Utility in Bladder Cancer

Background: Bladder cancer (BLCA) exhibits marked heterogeneity, and current classifiers provide limited guidance for prognosis or treatment. Because epigenetic reprogramming and metabolic rewiring jointly shape BLCA biology, we sought to identify epigenomically informed biomarkers with functional relevance. Methods: Epigenome (genome-wide promoter DNA methylation) and matched transcriptome (RNA sequencing) profiles from tumor and adjacent normal samples were integrated to identify genes with concordant differen…

Health · G Space — documented gain · certified 2026-07-26 · v1 · article view · machine-readable

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A survival-oriented machine learning framework distilled epigenomic and transcriptomic data into a 25-gene lipid-metabolic signature that stratified bladder cancer patients by risk across multiple cohorts and identified FASN and SCD as inhibitable drivers of proliferation and migration in cell models.

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Truvace Impact Record TRV-2026-0569, v1: “Epigenomics-Guided Multi-Omics Integration Uncovers a Lipid-Metabolic Signature with Translational Utility in Bladder Cancer.” Truvace, 2026-07-26. /record/TRV-2026-0569 (accessed at citation time). sha256 f609e66d0ef10095…

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