Kidney tumoroid characterisation by spatial mass spectrometry with same-section multiplex immunofluorescence uncovers...

Renal cell carcinoma (RCC) incidence is rising, and treatment remains challenging unless surgery is curative. Tumour heterogeneity contributes to resistance against both chemotherapy and immune checkpoint inhibitors, underscoring the need to better understand the complex tumour microenvironment (TME). While tumour models derived from cancer tissue from patients have advanced cancer research, they often fail to capture functional RCC heterogeneity and key TME components. We developed a 3D model system with a high success rate from resected tumour, retaining cancer, stromal, and immune cell populations. This system is fully compatible with advanced imaging technologies, including mass spectrometry imaging (MSI) and live-cell multiplex imaging. By integrating static spatial analysis with dynamic live-cell visualisation, our system provides unique insights into tumour heterogeneity, microenvironment metabolic crosstalk, and real-time cellular responses. Phenotypic characterization of the tumoroids showed strong histological resemblance to the original resected tissue, indicating that the tumoroids are reflective of the tumour in vivo and suitable as a representative model system. Additionally, DESI-MSI revealed distinct lipidomic profiles within patient-derived ccRCC tumoroids, capturing spatial metabolic heterogeneity reflective of the primary tissue. Lipid signatures varied across tumour regions, with phospholipid subclasses distinguishing epithelial, endothelial, and highly proliferative cell populations. Notably, non-clear cell regions exhibited reduced lipid droplet and fatty acid content, aligning with aggressive tumour phenotypes.