SpottedPy quantifies relationships between spatial transcriptomic hotspots and uncovers environmental cues of epithelial-mesenchymal plasticity in breast cancer
Spatial transcriptomics is revolutionizing the exploration of intratissue heterogeneity in cancer, yet capturing cellular niches and their spatial relationships remains challenging. We introduce SpottedPy, a Python package designed to identify tumor hotspots and map spatial interactions within the cancer ecosystem. Using SpottedPy, we examine epithelial-mesenchymal plasticity in breast cancer and highlight stable niches associated with angiogenic and hypoxic regions, shielded by CAFs and macrophages. Hybrid and mesenchymal hotspot distribution follows transformation gradients reflecting progressive immunosuppression. Our method offers flexibility to explore spatial relationships at different scales, from immediate neighbors to broader tissue modules, providing new insights into tumor microenvironment dynamics.
Authors
- Eloise Withnell (ORCID: https://orcid.org/0000-0002-7368-5149)
- Maria Secrier (ORCID: https://orcid.org/0000-0003-2758-1741)
Institutions
- University College London (GB)
Publication Details
- Journal
- Genome biology
- Published
- 2024-11-11
- DOI
- https://doi.org/10.1186/s13059-024-03428-y
- Citations
- 13
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 3.04
Funders
- Alan Turing Institute
- UK Research and Innovation
- Biotechnology and Biological Sciences Research Council