Analysis of individual patient pathway coordination in a cross-species single-cell kidney atlas

Abstract

The use of single-cell RNA sequencing in clinical and translational research is limited by the challenge of identifying cell-type-specific, targetable molecular changes in individual patients and cross-species differences. Here we created an integrated single-cell kidney atlas including over 1 million cells from 140 samples, defining more than 70 conserved cell states in human and rodent models. We developed CellSpectra, a computational tool that quantifies changes in gene expression coordination across cellular functions, which we applied to kidney and lung cancer data. This tool powers our patient-level single-cell functional profiling report, which highlights cell-type-specific changes in the coordination of pathway gene expression in individuals. Our cross-species atlas facilitates the selection of a rodent model that closely reflects the cellular and pathway-level signatures observed in patient samples, advancing the application of single-cell methodologies in clinical precision medicine. Finally, using experimental models, we demonstrate how our informatics approach can be applied for the potential selection of suitable therapeutics. CellSpectra identifies functionally relevant changes in cellular pathways when analyzing single samples in comparison to a reference atlas, here applied to rodent models and patient samples of kidney disease.