Single‐cell protein profiling defines cell populations associated with triple‐negative breast cancer aggressiveness

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‐...

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Veröffentlicht in:Molecular oncology Jg. 17; H. 6; S. 1024 - 1040
Hauptverfasser: Kvokačková, Barbora, Fedr, Radek, Kužílková, Daniela, Stuchlý, Jan, Vávrová, Adéla, Navrátil, Jiří, Fabian, Pavel, Ondruššek, Róbert, Ovesná, Petra, Remšík, Ján, Bouchal, Jan, Kalina, Tomáš, Souček, Karel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States John Wiley & Sons, Inc 01.06.2023
John Wiley and Sons Inc
Wiley
Schlagworte:
Antibodies
Bar codes
Breast Cancer
Cells
Cloning
Cytometry
Fibroblasts
Glycerol
mass cytometry
Metastasis
Patients
phenotypic plasticity
Proteins
Proteomics
Single-cell protein
single‐cell profiles
Stromal cells
Surgery
triple‐negative breast cancer
Tumor cells
tumor heterogeneity
Tumor microenvironment
Tumors
unsupervised machine learning algorithm
United States > US
Germany
unsupervised machine learning algorithm
triple-negative breast cancer
phenotypic plasticity
mass cytometry
single-cell profiles
tumor heterogeneity
ISSN:1574-7891, 1878-0261, 1878-0261
Online-Zugang:Volltext
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Zusammenfassung: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. The extensive heterogeneity of triple‐negative breast cancer (TNBC) affects disease progression and therapeutic response. To investigate TNBC heterogeneity in more detail, we profiled 26 treatment‐naïve primary TNBC at the single‐cell level using mass cytometry. We introduced a new clinically relevant Ki‐67+LNR index and identified distinct tumor and stromal populations associated with clinical observations.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1574-7891
1878-0261
1878-0261
DOI:10.1002/1878-0261.13365