Artificial intelligence meets epigenetics: a new frontier in precision oncology

Epigenetics involves heritable and stable changes in gene expression that occur without altering the DNA sequence, primarily through chemical modifications to DNA and alterations in chromatin structure. Dysregulation of these epigenetic processes is widely recognized as a hallmark of cancer, influencing tumor initiation, progression, and recurrence. Consequently, characterizing cancer-associated epigenetic alterations has become a major research focus, both to understand disease mechanisms and to identify therapeutic targets. Importantly, many epigenetic changes are reversible, making them attractive candidates for targeted therapies. However, the complexity and volume of epigenomic data; spanning DNA methylation, histone modifications, chromatin accessibility, and gene expression demanding advanced computational approaches for meaningful interpretation. Artificial intelligence (AI), particularly machine learning and deep learning, has emerged as a powerful solution for extracting biologically relevant patterns from such high-dimensional datasets. These approaches enable prediction of disease risk, classification of tumor subtypes, discovery of novel regulatory mechanisms, and development of patient-specific therapeutic strategies. Rather than simply enhancing traditional computational biology, AI fundamentally expands the analytical and predictive capabilities of epigenetic research. This review highlights current applications of AI in epigenomics-based precision oncology, along with ongoing challenges and future directions in integrating advanced computational modeling with biological insight.