SpottedPy quantifies relationships between spatial transcriptomic hotspots and uncovers new environmental cues of epithelial-mesenchymal plasticity in cancer

Abstract

Spatial transcriptomics is revolutionising our ability to explore intratissue heterogeneity in cancer, but methods that can effectively capture cancer cell niches and explore their relationships with the tumour microenvironment at various spatial scales remain limited. Here we present SpottedPy, a Python package designed to identify tumour hotspots and map spatial interactions within the cancer ecosystem. We employ SpottedPy to examine epithelial-mesenchymal plasticity in breast cancer and highlight locally stable niches associated with angiogenic and hypoxic regions, and shielded by myCAFs, macrophages and perivascular cell populations. Hybrid and mesenchymal hotspot distribution followed transformation gradients within the tissue reflecting progressive immunosuppression. Our method offers the flexibility to explore spatial relationships at different scales, from immediate neighbours to broader tissue modules, providing new insights into the spatial dynamics of the tumour microenvironment.