From cancer treatment strategies to survivorship care: Advances in integrating multi-omics and artificial intelligence

Abstract

Advances in oncology are successfully shifting clinical focus beyond initial tumor control to address the complex, lifelong needs of a growing survivor population. This review examines the evolution of therapeutic paradigms, dissecting the mechanistic underpinnings and clinical impact of modern immunotherapies and gene-based modalities. It further addresses the multifaceted challenges in survivorship care, from managing persistent morbidity and psychological distress to overcoming systemic barriers in care coordination. Central to this discussion is the promise of multi-omics—which offers a high-resolution lens into tumor and host biology—to enable preemptive risk profiling. Concurrently, artificial intelligence (AI) emerges as the computational engine to distill these complex datasets into actionable intelligence for personalized surveillance. Furthermore, this review explores the translational hurdles facing AI, with a critical examination of inherent vulnerabilities, such as algorithmic bias, model opacity, and ethical pitfalls, in clinical deployment. By synthesizing these domains, this article provides a conceptual framework to steer the evolution of evidence-based, equitable, and patient-focused survivorship care.

Keywords

Cancer treatment strategy / Cancer survivorship care / Multi-omics / Artificial intelligence / Personalized medicine

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