Beyond the Hype: Structuring the Future of Applied Multi-Omics in Oncology

Multi-omics integration represents one of the most profound shifts in the architecture of modern medicine, nowhere more urgently than in oncology. The convergence of high-dimensional biological data with advanced machine learning has opened the door to a new class of precision tools capable of unraveling the layered complexity of cancer. Yet, as this field accelerates, its clinical impact remains constrained by a set of largely unresolved technical and ethical challenges.This review critically examines the dual nature of applied multi-omics in oncology: a disruptive promise tethered to fragile foundations. While AI-enabled platforms increasingly demonstrate potential in biomarker discovery, patient stratification, and therapeutic targeting, they are often built on pipelines that lack methodological transparency, reproducibility, and rigorous benchmarking. Integration strategies, ranging from early and late fusion to more sophisticated kernel and graph-based architectures, are frequently applied without alignment to biological structure or data type specificity. Moreover, the absence of longitudinal modeling frameworks means that most applications remain static snapshots, incapable of capturing the temporal evolution of disease or treatment response. Equally pressing are the questions of data governance, interpretability, and clinical-grade validation, without which, even the most elegant models remain inert in real-world oncology settings.Drawing on current literature and translational insights from platform-level development, we propose a structured roadmap for realizing the clinical potential of multi-omics. We argue that without a shift toward reproducible, temporally-aware, and ethically-aligned integration architectures, the field risks building castles on sand. Precision oncology demands more than computational ingenuity. It requires a rethinking of how we structure, validate, and apply the biological data that defines human disease.