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0This research introduces Renoir, a sophisticated computational framework designed to map cell-cell communication within the spatial architecture of tissues. By integrating single-cell transcriptomics with spatial data, Renoir tracks how ligands influence downstream target genes across specific neighborhood niches. The system outperforms existing methods by reducing false positives through the inclusion of receptor expression and spatial proximity in its activity scoring. Researchers successfully applied Renoir to diverse contexts, including mouse brain structures, breast cancer microenvironments, and human fetal liver development. Notably, the tool identified a critical interaction in hepatocellular carcinoma where onco-fetal cells reprogram bipotent stem-like cells via interleukin signaling. Renoir ultimately provides a high-resolution lens for discovering therapeutically relevant cellular crosstalk in complex biological systems.
References:
Rao N, Kumar T, Kazemi D, et al. Charting spatial ligand-target activity using Renoir[J]. Nature Communications, 2026, 17(1): 3983.
