Background Multiplex immunostaining combined with digital image analysis has become a central tool in hepatology research because it allows for the simultaneous visualisation and spatial mapping of multiple cellular markers within a single tissue section, providing critical insights into the complex, heterogeneous microenvironments of liver diseases like cholangiopathies, hepatocellular carcinoma, metabolic dysfunction-associated steatohepatitis or hepatic fibrosis. Nevertheless, significant barriers prevent the widespread adoption of most multiplexing platforms, including the technological complexity that necessitates specialised equipment and personnel. Additionally, several technologies remain incompatible with standard laboratory workflows and archival formalin-fixed paraffin-embedded (FFPE) tissue or in vitro culture samples. Methods We developed a customised immunofluorescence workflow based on sequential cycles of antibody stripping to generate multiplexed digital images from FFPE liver sections, intrahepatic cholangiocyte organoids and primary mouse liver cells cultured either in conventional two-dimensional systems or within a biliary niche-on-a-chip platform. Subsequent image processing and channel alignment were performed using an in-house and open-source, Python-based software tool. Results We demonstrate the functionality of a multiplex immunofluorescence protocol that can be readily adapted to a broad range of archival tissues and primary cell-based samples. This workflow allows the visualisation of antigen-expressing cells and protein–protein interactions using proximity ligation assays. This study also details the technical considerations necessary for its rapid integration into routine workflows in virtually any laboratory equipped for conventional immunohistochemistry. Conclusions This methodology integrates multiplex immunofluorescence into standard laboratory workflows, thereby enabling researchers to overcome challenges such as technological complexity and cost for transitioning from conventional to multiplexed microscopy.
Leonardi et al. (2026) studied this question.