Multiplexed deep visual proteomics resolves spatial heterogeneity and rare endocrine states in human pancreatic...

Understanding tissue function requires connecting spatial cellular context with molecular depth, yet such integration remains challenging in complex organs like the pancreas. We develop multiplexed Deep Visual Proteomics (mxDVP), an end-to-end workflow combining high-plex imaging, automated computational analysis, and spatially guided ultra-sensitive mass spectrometry. Powered by PIPΣX, an open-source image analysis framework enabling whole-slide membrane-aware segmentation, annotation, and laser microdissection export, mxDVP achieves >6000 protein identifications from as few as 100 small islet cells. Applied to human pancreatic islets, mxDVP segments over 860,000 cells and resolves twelve endocrine subtypes, including rare polyhormonal and intermediate-state populations that exhibit spatial organization patterns, co-expression of INSM1 and SCG3, and hybrid α/β/δ signatures. These findings reveal a spectrum of endocrine heterogeneity and spatial organization. By integrating imaging and deep proteomics in an accessible framework, mxDVP enables discovery of rare cell states whose biological roles depend on tissue architecture.