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Article Abstract

Background: Epigenetic regulatory genes (epiRG) are pivotal in the epigenetic regulation of the human genome, primarily through DNA and histone modifications. These genes are frequently mutated in human cancers, particularly bladder cancer (BC). However, the functional impact of epiRG mutations on patient outcomes remains poorly understood.

Methods: In this study, we developed gene signatures for the most frequent genomic aberrations of epiRG using The Cancer Genome Atlas Bladder Carcinoma (TCGA-BLCA) dataset and validated these signatures with independent tumor expression profiles for prognostic relevance. Furthermore, we evaluated the role of these signature scores in the immune system within the tumor microenvironment (TME). Finally, we assessed the correlation between epiRG and global DNA methylation.

Results: Our results indicated that the inferred aberration-specific signature scores were more predictive of patient stratification than the genomic aberrations. Notably, certain signature scores were significantly associated with patient progression, whereas others correlated with the tumor immune microenvironment via interactions with the immune system. Patients with mutations had high signature scores in CREBBP-mut and EP300-mut, which revealed poor overall survival. Conversely, KDM6A-mut signatures showed an opposite trend, with low scores linking to favorable prognosis through enhanced immune activity. Also, other epiRG signature scores were strongly correlated with the immune system in TME and successfully predicted patients who responded to immunotherapy. Global methylation analysis revealed that high signature scores of KDM6A-mut are associated with hypomethylation.

Conclusions: These findings collectively establish epiRG signature scores as powerful biomarkers that integrate genomic, epigenetic, and immune microenvironment features for improved prognostic prediction in bladder cancer. This integrative approach not only advances our understanding of epigenetic mechanisms in BC but also offers potential for developing innovative prognostic tools and therapeutic strategies tailored to personalized medicine.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281021PMC
http://dx.doi.org/10.1002/cam4.71057DOI Listing

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