AI Article Synopsis

  • Metastatic disease is a major cause of cancer-related deaths, yet its tumor microenvironment is not well understood due to technical challenges in studying it.
  • This research created a comprehensive map of 67 tumor biopsies from 60 metastatic breast cancer patients, using advanced techniques like single-cell RNA sequencing and various spatial expression assays to analyze tumor characteristics.
  • Key findings included identifying different macrophage spatial patterns, three phenotypes of epithelial-to-mesenchymal transition, and gene expression linked to T cell presence or absence, highlighting the study's potential for clinical insights.

Article Abstract

Although metastatic disease is the leading cause of cancer-related deaths, its tumor microenvironment remains poorly characterized due to technical and biospecimen limitations. In this study, we assembled a multi-modal spatial and cellular map of 67 tumor biopsies from 60 patients with metastatic breast cancer across diverse clinicopathological features and nine anatomic sites with detailed clinical annotations. We combined single-cell or single-nucleus RNA sequencing for all biopsies with a panel of four spatial expression assays (Slide-seq, MERFISH, ExSeq and CODEX) and H&E staining of consecutive serial sections from up to 15 of these biopsies. We leveraged the coupled measurements to provide reference points for the utility and integration of different experimental techniques and used them to assess variability in cell type composition and expression as well as emerging spatial expression characteristics across clinicopathological and methodological diversity. Finally, we assessed spatial expression and co-localization features of macrophage populations, characterized three distinct spatial phenotypes of epithelial-to-mesenchymal transition and identified expression programs associated with local T cell infiltration versus exclusion, showcasing the potential of clinically relevant discovery in such maps.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11564109PMC
http://dx.doi.org/10.1038/s41591-024-03215-zDOI Listing

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