Pathology-oriented multiplexing enables integrative disease mapping

Protein expression and location within tissues represent key determinants of health and disease. While advances in multiplexed imaging have expanded the number of proteins that can be spatially assessed, its potential use to integrate different biological layers (i.e., cell structure, subcellular domains and signal activity) remains unclear. Available methods are mainly restricted by the composition of antibody panels and image resolution, limiting the applications and development of computational image analysis tools. Here, we present <strong><strong>Patho</strong></strong>logy-oriented multi<strong><strong>Plex</strong></strong>ing (PathoPlex), a scalable, quality-controlled, and interpretable framework that combines deep multiplexed imaging at subcellular resolution with an open-source software package to extract, interpret and model protein co-expression patterns (clusters) that represent the integration of multiple biological layers. PathoPlex provides simple 3D printing solutions to simultaneously process up to 40 archival formalin-fixed paraffin-embedded biopsies (approx. 4000 mm²) using conventional inverted fluorescent light microscopes. We validated PathoPlex in 95 iterative cycles, mapping at least 142 commercial antibodies at 80 nm per pixel, which generated over half a trillion pixels. As proof-of-concept, we identified epithelial c-Jun activity as a key switch in immune-mediated kidney disease, demonstrating that PathoPlex-derived clusters represent functional pathological features. Next, PathoPlex was used to dissect human diabetic kidney disease (DKD), defining clusters associated with organ function, patient stratification, and therapeutic potential (i.e., calcium-mediated stress in proximal tubuli). Then, PathoPlex revealed clusters linked to renal stress in patients with type 2 diabetes (T2D) without DKD, providing tissue-based readouts to assess response to short-term administration of sodium-glucose cotransporter-2 inhibitors (SGLT2i). Finally, we proposed a cluster-based model connecting early T2D with DKD in patients without SGLT2i and evaluated the potential of SGLT2i to modify DKD development and progression. In summary, PathoPlex paves the way to democratize access to multiplexed imaging and support the development and interpretation of next-generation pathology atlases.