Abstract
Spatial transcriptomics enables investigation of cell–cell communication (CCC) while preserving spatial context, yet large-scale resources that organize spatial CCC results across studies and make them readily searchable, visualizable, and comparable remain limited. Here, we present CCCView, a knowledge platform integrating 699 spatial transcriptomics samples and 7,473,444 inferred CCC interactions across 24 tissues, 182 annotated cell types, and 27 biological conditions in human and mouse. CCCView uses a unified cell-type annotation workflow and organizes results from three complementary CCC-inference approaches—COMMOT, CellNEST, and SpatialDM—while preserving method-specific outputs. The platform provides interactive search, browsing, visualization, disease-oriented exploration, data download, and online analysis functions. For cross-sample exploration, CCCView also includes MuCIA, a Tweedie regression-based statistical module for comparing inferred interaction strength across user-defined sample groups. A glioblastoma use case illustrates how CCCView can connect spatial cell-type context, inferred communication patterns, and condition-associated signals to generate biologically interpretable hypotheses. CCCView provides an integrated resource for systematic exploration of spatial transcriptomic CCC and for reuse of precomputed communication results across heterogeneous datasets.