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Abstract The tumor microenvironment (TME) is an immensely complex ecosystem^1,2. This complexity underlies difficulties in elucidating principles of spatial organization and using molecular profiling of the TME for clinical use³. Through statistical analysis of 96 spatial transcriptomic (ST-seq) datasets spanning twelve diverse tumor types, we found a conserved distribution of multicellular, transcriptionally covarying units termed ‘Spatial Groups’ (SGs). SGs were either dependent on a hierarchical local spatial context – enriched for cell-extrinsic processes such as immune regulation and signal transduction – or independent from local spatial context – enriched for cell-intrinsic processes such as protein and RNA metabolism, DNA repair, and cell cycle regulation. We used SGs to define a measure of gene spatial heterogeneity – ‘spatial lability’ – and categorized all 96 tumors by their TME spatial lability profiles. The resulting classification captured spatial variation in cell-extrinsic versus cell-intrinsic biology and motivated class-specific strategies for therapeutic intervention. Using this classification to characterize pre-treatment biopsy samples of 16 non-small cell lung cancer (NSCLC) patients outside our database distinguished responders and non-responders to immune checkpoint blockade while programmed death-ligand 1 (PD-L1) status and spatially unaware bulk transcriptional markers did not. Our findings show conserved principles of TME spatial biology that are both biologically and clinically significant.