Spatial Multi-Omics in Cancers

Spatial omics allows for the simultaneous measurement of multiple “omics” layers (genomics, transcriptomics, proteomics, metabolomics). The analysis reveals significant advances in tumor microenvironment characterization, biomarker discovery, and clinical applications. Spatial Multiomics is particularly crucial in cancer research because tumors are highly heterogeneous, and the spatial relationships between cancer cells, immune cells, and stromal cells within the tumor microenvironment (TME) are critical for understanding disease progression, metastasis, and treatment response. The convergence of large-scale spatial omics data with artificial intelligence is powering the next revolution in oncology research. The clinical applications of spatial multi-omics are expanding rapidly, from patient stratification for precision oncology to the design of more efficient clinical trials. Developing interpretable models that can guide treatment decisions based on spatial patterns of gene and protein expression will be a key focus of future research.