Spatial TME communication

Use this workflow when tumor-region context matters for immuno-oncology signaling. It connects cell-cell communication results to spatial metadata such as tumor core, invasive margin, stroma, necrosis, immune-excluded regions, and TLS-adjacent neighborhoods so boundary-specific signaling can be reviewed directly.

Research question

Which tumor regions and boundaries concentrate ligand-receptor signaling across malignant, immune, stromal, endothelial, and TLS-adjacent compartments?

Use case

Use this for spatial transcriptomics or spatially annotated single-cell studies where the biological question depends on tumor core versus margin, stromal exclusion, TLS-adjacent immune activity, or tumor-stroma boundary signaling. The workflow is designed for research review of spatial communication evidence, not diagnostic spatial pathology.

Suggested path

1. Prepare expression and metadata tables with cell type labels, spatial coordinates, and region labels such as tumor core, invasive margin, stroma, necrosis, immune-excluded, or TLS-adjacent.
2. Run oncology cell_communication.
3. Review TME sender/receiver classes, spatial region summaries, centroid communication map edges, and tumor-immune or tumor-stroma boundary priorities.
4. Compare responder/non-responder or pre/post treatment conditions when metadata columns are available.
5. Use interpretation to summarize dominant spatial signaling axes with research caveats.

Outputs to cite

• spatial region cell counts
• region-specific cell-type profiles
• spatial communication map edge score
• boundary interaction priority
• IO pathway axis score
• top spatial boundary ligand-receptor pair