This paper details the introduction and validation of PathoPlex, a scalable and open-source framework for highly multiplexed imaging and analysis of formalin-fixed paraffin-embedded (FFPE) tissue specimens. This technology significantly advances spatial biology by enabling the detection of over 120 protein markers at subcellular resolution, exceeding the capabilities of existing commercial systems. PathoPlex combines iterative indirect immunofluorescence with a custom-built, low-cost 3D printing-based automation system for high-throughput sample processing and utilizes the accompanying spatiomic Python library for sophisticated pixel-level cluster analysis. The efficacy of PathoPlex is demonstrated through studies on mouse models of kidney disease and human clinical samples of diabetic kidney disease, revealing complex molecular and structural signatures associated with disease progression and therapeutic response. The framework aims to provide universal access to advanced multiplexed imaging, shifting the focus from solely cellular-level to integrative, pixel-based analysis of tissue pathology.
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