Mapping Tumor Recurrence and Metastasis With Pan‐Cancer Multi‐Omics

Tumor recurrence and metastasis remain the leading causes of treatment failure and cancer‐related mortality. These processes arise from dynamic evolutionary interactions among genomic alterations, cellular plasticity, and tumor microenvironmental adaptation, which cannot be fully explained by single‐layer molecular analyses. Although recent reviews have summarized either pan‐cancer metastasis or multi‐omics technologies, a unified framework integrating shared biological mechanisms across cancer types with multi‐omics evidence and clinical translation is still lacking. In this review, we present a mechanism‐oriented pan‐cancer perspective on tumor recurrence and metastasis by integrating evidence from genomics, transcriptomics, proteomics, metabolomics, single‐cell, and spatial omics. Rather than describing individual technologies, we emphasize how each omics layer contributes complementary insights into common evolutionary programs, including clonal selection, cell‐state plasticity, immune and stromal remodeling, metabolic adaptation, and treatment‐induced evolution. We further discuss how multi‐omics integration can move beyond descriptive associations toward mechanistic understanding through longitudinal sampling, spatial analysis, and functional validation. Finally, we highlight the translational potential of multi‐omics for recurrence‐risk prediction, minimal residual disease monitoring, identification of therapeutic vulnerabilities, and development of perioperative intervention strategies. By linking shared pan‐cancer biological programs with clinically relevant applications, this review provides a conceptual framework for understanding recurrence and metastasis and outlines future directions for translating multi‐omics discoveries into precision oncology.