Toward Clinical Adoption of Spatial Omics and Computational Pathology in Oncology

Spatial omics technologies map molecular information within intact tissue architecture, revealing how cellular organization and interactions shape tumor biology, therapeutic responses, resistance, and relapse. Advances in artificial intelligence and computational pathology are bridging research discovery and clinical practice, enabling prognostic extraction from routine histology and cost-effective molecular inference. Nevertheless, barriers including high costs, protocol complexity, and lack of standardized workflows remain. We outline how these converging fields can deliver translational value in oncology and identify key enablers for clinical adoption.