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Epigenomics-Guided Multi-Omics Integration Uncovers a Lipid-Metabolic Signature with Translational Utility in Bladder
Yu-De Wang1,2, Yo-Liang Lai3,4, Chia-Hsin Liu5
1Department of Urology, China Medical University Hospital, Taichung, Taiwan.
Computational and Structural Biotechnology Journal
|July 25, 2026
Summary
A new 25-gene signature integrating epigenomics and transcriptomics helps predict bladder cancer (BLCA) patient outcomes. This lipid-centric biomarker stratifies risk, guides treatment, and reveals immune interactions for precision oncology.
Area of Science:
- Oncology
- Genomics
- Epigenetics
- Metabolomics
Background:
- Bladder cancer (BLCA) is heterogeneous, with current prognostics and treatments limited.
- Epigenetic and metabolic changes are key drivers of BLCA.
- Need for biomarkers that integrate epigenomic data and have functional relevance.
Purpose of the Study:
- Identify epigenomically informed biomarkers for BLCA prognosis and treatment.
- Develop a multi-omics framework for precision oncology in BLCA.
Main Methods:
- Integrated epigenome (DNA methylation) and transcriptome (RNA sequencing) data from BLCA and normal samples.
- Utilized a survival-oriented machine learning framework to derive a 25-gene signature.
- Validated the signature in independent BLCA cohorts and performed functional assays.
Main Results:
- The 25-gene signature stratified BLCA patients into high- and low-risk groups, independent of clinical factors.
- Low-risk tumors showed immune-inflamed phenotypes, while high-risk tumors had lower immune engagement.
- Inhibition of key lipid metabolism genes (FASN, SCD) reduced BLCA cell proliferation and migration.
Conclusions:
- A lipid-centric 25-gene signature provides stage-independent prognostication for BLCA.
- The signature elucidates tumor-immune interactions and identifies potential therapeutic targets.
- This multi-omics approach advances precision oncology for bladder cancer.
