Histone post-translational modifications (PTMs) have long been recognized as critical regulators of chromatin dynamics and gene expression, with aberrations in these processes driving tumorigenesis, immune escape, metastasis, and therapy resistance. While multi-omics technologies are generating ever more detailed maps of the histone landscape, translating these insights into clinical practice remains challenging. The ongoing convergence of high-throughput omics technologies and Artificial Intelligence (AI) is revolutionizing drug repositioning strategies, offering new precision tools to identify histone-targeted therapies for solid tumors. In this review, we explore how AI-driven multi-omics integration is currently reshaping therapeutic opportunities by uncovering novel drug-target-patient associations with unprecedented accuracy. Special focus is given to gynecologic and breast cancers, where chromatin remodeling dysregulation is particularly widespread, conventional therapeutic approaches have demonstrated substantial limitations and drug resistance represents a major clinical obstacle. These aggressive and lethal cancers exemplify areas where AI-powered repurposing of epi-drugs is making tangible clinical advances, enhancing tumor sensitivity to treatments like immunotherapy, but also offering new avenues to overcome challenging phenomena such as drug resistance and cancer relapse. We critically discuss these challenges and the effectiveness of a combination strategy approaches based on AI-driven patient stratification and biomarker-guided therapy optimization to maximize clinical benefits. In an era where precision oncology demands both specific drugs and the application of smarter strategies, the integration of AI, multi-omics, and targeting of chromatin remodelers may herald a transformative shift in the management of solid tumors, bridging the gap between biological insights and therapeutic innovation.
Salvati et al. (Fri,) studied this question.