4.8 Article

The single-cell pathology landscape of breast cancer

期刊

NATURE
卷 578, 期 7796, 页码 615-+

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/s41586-019-1876-x

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资金

  1. SNSF R'Equip grant
  2. SNSF Assistant Professorship grant
  3. SystemsX Transfer Project `Friends and Foes'
  4. SystemX grant Metastasix
  5. NIH [UC4 DK108132]
  6. SystemX grant PhosphoNEtX
  7. CRUK IMAXT Grand Challenge
  8. European Research Council (ERC) under the European Union's Seventh Framework Program (FP/2007-2013)
  9. ERC [336921]
  10. SystemsX Transitional Post-Doctoral Fellowship
  11. Canadian Institute of Health Research Post-Doctoral Fellowship
  12. Cancer Research Society
  13. European Research Council (ERC) [336921] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Single-cell analyses have revealed extensive heterogeneity between and within human tumours(1-4), but complex single-cell phenotypes and their spatial context are not at present reflected in the histological stratification that is the foundation of many clinical decisions. Here we use imaging mass cytometry(5) to simultaneously quantify 35 biomarkers, resulting in 720 high-dimensional pathology images of tumour tissue from 352 patients with breast cancer, with long-term survival data available for 281 patients. Spatially resolved, single-cell analysis identified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity, and enabled the cellular architecture of breast cancer tissue to be characterized on the basis of cellular composition and tissue organization. Our analysis reveals multicellular features of the tumour microenvironment and novel subgroups of breast cancer that are associated with distinct clinical outcomes. Thus, spatially resolved, single-cell analysis can characterize intratumour phenotypic heterogeneity in a disease-relevant manner, with the potential to inform patient-specific diagnosis. A single-cell, spatially resolved analysis of breast cancer demonstrates the heterogeneity of tumour and stroma tissue and provides a more-detailed method of patient classification than the current histology-based system.

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