Why Space Matters
Standard scRNA-seq dissociates tissues, losing spatial context. Spatial transcriptomics technologies preserve the physical location of gene expression, revealing how cells communicate within their native tissue architecture.
Technology Landscape
| Platform | Resolution | Approach |
|---|---|---|
| 10x Visium | ~55 µm spots | Capture-based |
| MERFISH | Subcellular | Imaging-based |
| Slide-seq | ~10 µm beads | Capture-based |
| CODEX | Single-cell (protein) | Imaging-based |
Applications in Cancer
- Tumor-immune interface mapping — Identifying spatial patterns of immune infiltration and exclusion
- Tertiary lymphoid structures — Characterizing organized immune aggregates associated with immunotherapy response
- Invasion fronts — Transcriptional programs at the leading edge of tumor expansion
- Cell-cell communication — Ligand-receptor analysis with spatial constraints
Computational Challenges
Spatial data require specialized tools: Squidpy for spatial statistics, cell2location and DestVI for deconvolution, and NICHE-NET for spatially-aware cell communication inference.
Outlook
As spatial technologies achieve higher resolution and multiplexing, they will become essential for understanding treatment resistance and designing combination therapies.