2026-05-06 スタンフォード大学
Nine cellular environments, or spatial ecotypes, are shown here in a melanoma tumor. Spatial ecotypes, defined by the cellular interactions and the gene expression patterns of their cells, give clues about effective treatment options. | Aaron Newman
＜関連情報＞
- https://news.stanford.edu/stories/2026/05/blood-test-cell-tumor-neighborhoods-cancer-research
- https://www.nature.com/articles/s41586-026-10452-4
空間生態型を用いた腫瘍微小環境の非侵襲的プロファイリング Non-invasive profiling of the tumour microenvironment with spatial ecotypes
Wubing Zhang,Erin L. Brown,Abul Usmani,Noah Earland,Minji Kang,Chibuzor Olelewe,Anushka Viswanathan,Pradeep S. Chauhan,Chloé B. Steen,Hyun Soo Jeon,Susanna Avagyan,Irfan Alahi,Nicholas P. Semenkovich,Janella C. Schwab,Chloe M. Sachs,Faridi Qaium,Peter K. Harris,Qingyuan Cai,Andrew J. Gentles,James Knight,Rondell P. Graham,Antonietta Bacchiocchi,Peter C. Lucas,Ryan C. Fields,… Aaron M. Newman
Nature Published:06 May 2026
DOI:https://doi.org/10.1038/s41586-026-10452-4
Abstract
Multicellular programs in the tumour microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and profile clinically1,2,3. Here, we present a machine-learning framework for multi-analyte profiling of spatially dependent cell states and multicellular ecosystems, termed spatial ecotypes (SEs). By integrating over 10 million single-cell and spot-level spatial transcriptomes from diverse human carcinomas and melanomas, we identified nine SEs with broad conservation, each of which has unique biology, geospatial features and clinical outcome associations, including several linked to immunotherapy response. Notably, SEs were distinguishable by DNA methylation profiling and were recoverable from plasma cell-free DNA (cfDNA) using deep learning. In cfDNA from nearly 100 patients with melanoma, SE levels exhibited striking associations with immunotherapy response. Our data reveal fundamental units of TME organization and demonstrate a multimodal platform for profiling solid and liquid TMEs, with implications for improved risk stratification and therapy personalization.
