Single-cell protein profiling defines cell populations associated with triple-negative breast cancer aggressiveness Journal Article


Authors: Kvokačková, B.; Fedr, R.; Kužílková, D.; Stuchlý, J.; Vávrová, A.; Navrátil, J.; Fabian, P.; Ondruššek, R.; Ovesná, P.; Remšík, J.; Bouchal, J.; Kalina, T.; Souček, K.
Article Title: Single-cell protein profiling defines cell populations associated with triple-negative breast cancer aggressiveness
Abstract: Triple-negative breast cancer (TNBC) is an aggressive and complex subtype of breast cancer that lacks targeted therapy. TNBC manifests characteristic, extensive intratumoral heterogeneity that promotes disease progression and influences drug response. Single-cell techniques in combination with next-generation computation provide an unprecedented opportunity to identify molecular events with therapeutic potential. Here, we describe the generation of a comprehensive mass cytometry panel for multiparametric detection of 23 phenotypic markers and 13 signaling molecules. This single-cell proteomic approach allowed us to explore the landscape of TNBC heterogeneity, with particular emphasis on the tumor microenvironment. We prospectively profiled freshly resected tumors from 26 TNBC patients. These tumors contained phenotypically distinct subpopulations of cancer and stromal cells that were associated with the patient's clinical status at the time of surgery. We further classified the epithelial-mesenchymal plasticity of tumor cells, and molecularly defined phenotypically diverse populations of tumor-associated stroma. Furthermore, in a retrospective tissue-microarray TNBC cohort, we showed that the level of CD97 at the time of surgery has prognostic potential. © 2022 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.
Keywords: triple-negative breast cancer; tumor heterogeneity; phenotypic plasticity; mass cytometry; single-cell profiles; unsupervised machine learning algorithm
Journal Title: Molecular Oncology
Volume: 17
Issue: 6
ISSN: 1878-0261
Publisher: FEBS Press  
Date Published: 2023-06-01
Start Page: 1024
End Page: 1040
Language: English
DOI: 10.1002/1878-0261.13365
PUBMED: 36550781
PROVIDER: scopus
PMCID: PMC10257414
DOI/URL:
Notes: Article -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Jan Remsik
    25 Remsik