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0The paper introduces TERRA, a spatial foundation model pretrained on 112 million human cells using a joint-embedding predictive architecture to analyze imaging-based spatial transcriptomics. By tokenizing each cell alongside its local environment, the model simultaneously generates gene-, cell-, and neighborhood-level embeddings from a single pretrained backbone without requiring task-specific fine-tuning. This multi-scale framework supports zero-shot tissue analysis, cross-platform transfer, and in silico gene perturbations that predict cellular and microenvironmental responses to injury or therapeutic intervention. Furthermore, the sources demonstrate TERRA's practical utility by uncovering a developmental precursor of islet microvasculature during pancreas organogenesis, predicting a checkpoint-blockade injury program in the human kidney, and cataloging conserved macrophage niche archetypes across multiple organs and disease states.
References:
Birk S, Sanian M V, Vahidi A, et al. Multi-scale modeling of human tissues from spatial transcriptomics with TERRA[J]. BioRxiv, 2026: 2026.07. 29.741565.
