Greater understanding of the gene expression and spatial organization of cells within the kidney is expected to aid understanding of normal and disease processes. However, the number of analyses that can be performed is restricted by the limited amount of biopsy tissue. In new research, Nikhil Singh and Lloyd Cantley overcome this limitation by using an imaging mass cytometry (IMC)-based approach to phenotype and quantify diverse cell types within biopsy samples. “Our aim was to develop a reference data set against which quantitative interrogation of diseased tissue could be compared,” says Singh.

IMC couples laser ablation of formalin-fixed paraffin-embedded tissue to time-of-flight mass spectrometry to generate high-resolution reconstructions of multiple markers on a single section of tissue. To define cell types within kidneys, the researchers assembled and validated a panel of 23 metal-conjugated markers, which were applied to kidney tissue samples that were considered histopathologically normal. They also developed a machine learning-based technique, termed Kidney-MAPPS, to quantify the cells. “Unsurprisingly, we found that proximal tubular cells are the most abundant cell type in the cortex, and that immune cells vary in their abundance from cortex to medulla,” says Singh. “We also identified rare and unexpected cell populations, including a subset of proximal tubule cells that express vimentin and may represent regenerating cells, as well as vascular cells that express WT1 and nestin.”

The researchers plan to use this methodology to test hypotheses about the mechanisms of cell death and regeneration and role of immune cells. “IMC coupled to Kidney-MAPPS can provide an immense amount of quantitative data from a single slide; we believe this methodology may unlock a wealth of previously inaccessible information contained in kidney biopsy repositories worldwide,” notes Singh.