Inferring cellular communication through mapping cells in space using Tangram 2
Huang, H.; Andersson, A.; Wu, S. Z.; Scalia, G.; Collier, J.; Hoi, K. H.; Muller, S.; Heimberg, G.; Corrada Bravo, H.; Gaddam, S.; Huetter, J.-C.; Turley, S.; Richmond, D.; BenTaieb, A.; Biancalani, T.
Show abstract
Cell-to-cell communication (CCC) shapes development, immunity, and disease, yet current spatial transcriptomics (SRT) platforms rarely achieve both single-cell resolution and high-quality transcriptome-wide coverage to accurately characterize CCC in the tissue microenvironment. Tangram2 bridges this gap by integrating single-cell RNA sequencing (scRNA-seq) with SRT to identify genes whose expression changes as a function of neighboring cell types. By accurately mapping cells in tissue space, Tangram2 disentangles interaction-driven transcriptional shifts from intrinsic identity markers, yielding mechanistic CCC maps. Validation across diverse settings--including Slide-tags, co-cultured experiments, human lymph nodes, and simulations--demonstrates high accuracy. Applied to triple-negative breast cancer (TNBC) and cutaneous squamous cell carcinoma (cSCC), Tangram2 recapitulates known biology and uncovers new hypotheses, including various immunosuppressive mechanisms in TNBC and a macrophage-regulatory T-cell circuit associated with survival in cSCC.
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