While spatial transcriptomics has flourished, developing technologies for Spatial Omics presents distinct challenges due to the immense chemical diversity and dynamic range of the proteome. Mass-spectrometry imaging approaches like MALDI imaging have enabled spatially resolved protein detection but are limited in multiplexing capabilities. Hybrid methods are now pursuing spatially resolved multi-omic profiles combining proteomic and transcriptomic data. Emerging techniques based on DNA-encoded antibody libraries also promise highly multiplexed spatial protein profiling. As the field advances, spatial proteomics has the potential to reveal protein localization patterns and post-translational modifications influencing cell state and phenotype in healthy and pathological tissues.

Sustained progress will require continued collaboration between biologists, chemists, engineers, mathematicians, and computer scientists. Spatial omics is poised to generate enormous spatially resolved multi-omics datasets demanding interdisciplinary analytics and modeling capabilities. With multi-stakeholder efforts, spatial omics is expected to revolutionize our molecular understanding of biological systems in health and disease.

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