Advances and Applications of Spatial Proteomics: From Organellar Maps to Clinical Translation

Spatial proteomics has emerged as a powerful approach to systematically map the subcellular localization of thousands of proteins in parallel, providing insights into organelle composition, protein trafficking, and context-dependent relocalization events. Building on advances in mass spectrometry sensitivity, and acquisition as well as quantification strategies, organelle-resolved protein maps can now be generated with unprecedented depth and resolution, and recent workflows have expanded the applicability of spatial proteomics to diverse experimental and challenging contexts. Complementary bioinformatic pipelines enable the assignment of proteins to compartments, the detection of distribution shifts, and the integration of spatial data with other omics layers. Beyond fundamental cell biology, the technology holds great potential for clinical research, where limited input material and the complexity of primary samples pose specific challenges. Emerging low-input preparation methods, antibody-based organelle enrichment, and microscopy-guided approaches offer promising solutions, while robust, marker-independent data analysis will be essential to handle the biological variability of patient-derived samples. As protocols become more automated, low-input compatible, and bioinformatically standardized, spatial proteomics is poised to become a valuable tool for mechanistic disease research, biomarker discovery, and therapeutic target identification.