Spatial omics in cancer: decoding tumor heterogeneity, metabolic reprogramming and therapy resistance

Tumors are spatially organized ecosystems in which malignant cells, immune cells, stromal cells, vasculature, extracellular matrix and metabolites interact within structured tissue niches. Bulk RNA sequencing has clarified cancer-associated molecular programmes, and single-cell RNA sequencing has resolved cellular heterogeneity, but both approaches incompletely preserve the anatomical relationships that govern invasion, immune escape, metabolic competition and therapy resistance. Spatial omics addresses this gap by linking molecular measurements to tissue coordinates, histology and cellular neighbourhoods. In cancer research, spatial transcriptomics, spatial proteomics, multiplexed imaging and spatial metabolomics now allow investigators to resolve tumor heterogeneity across RNA, protein and metabolic layers. This review summarizes the technological landscape of spatial multi-omics and synthesizes its application to tumor microenvironment mapping, cell-cell communication, tertiary lymphoid structures, clonal evolution, metabolic reprogramming and treatment resistance. Particular emphasis is placed on spatial metabolic vulnerabilities, including lipid metabolism, amino acid competition, ferroptosis-associated states and pharmacological distribution within tumor tissue. We further discuss how spatial biomarkers, spatial pharmacokinetics and spatial pharmacodynamics may improve patient stratification and guide rational combination therapy. The field is moving from descriptive tissue mapping toward mechanism-driven, clinically interpretable spatial oncology. Its translational value will depend on robust multimodal integration, functional validation, standardized tissue workflows and collaboration among oncology, pathology, bioinformatics, pharmacology and engineering.