Department of Genetics, Evolution and Environment, UCL Genetics Institute, University College London, London, WC1E 6BT, UK.
Genome Biol. 2024 Nov 11;25(1):289. doi: 10.1186/s13059-024-03428-y.
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.
空间转录组学正在彻底改变对癌症组织内异质性的探索，但捕捉细胞生态位及其空间关系仍然具有挑战性。我们引入了 SpottedPy，这是一个专为识别肿瘤热点并绘制癌症生态系统内空间相互作用而设计的 Python 包。使用 SpottedPy，我们研究了乳腺癌中的上皮-间充质可塑性，并强调了与血管生成和缺氧区域相关的稳定生态位，这些区域受到 CAFs 和巨噬细胞的保护。混合和间充质热点的分布遵循反映渐进性免疫抑制的转化梯度。我们的方法提供了在不同尺度上探索空间关系的灵活性，从紧邻的邻居到更广泛的组织模块，为肿瘤微环境动力学提供了新的见解。
