2024
Procházková, Jiřina; Fedr, Radek; Hradilová, Barbora; Kvokačková, Barbora; Slavík, Josef; Kováč, Ondrej; Machala, Miroslav; Fabian, Pavel; Navrátil, Jiří; Kráčalíková, Simona; Levková, Monika; Ovesná, Petra; Bouchal, Jan; Souček, Karel
In: Journal of lipid research, vol. 65, no. 9, pp. 100609, 2024, ISSN: 1539-7262 0022-2275, (Place: United States).
Abstract | Links | BibTeX | Tags: *Breast Neoplasms/metabolism/pathology, *Epithelial-Mesenchymal Transition, *Glycosphingolipids/metabolism/analysis, *Single-Cell Analysis/methods, Breast cancer, Epithelial Cells, Female, Glycosphingolipids, Humans, Phenotype, phenotypic plasticity, stromal-like cells, surface profiling
@article{prochazkova_single-cell_2024,
title = {Single-cell profiling of surface glycosphingolipids opens a new dimension for deconvolution of breast cancer intratumoral heterogeneity and phenotypic plasticity.},
author = {Jiřina Procházková and Radek Fedr and Barbora Hradilová and Barbora Kvokačková and Josef Slavík and Ondrej Kováč and Miroslav Machala and Pavel Fabian and Jiří Navrátil and Simona Kráčalíková and Monika Levková and Petra Ovesná and Jan Bouchal and Karel Souček},
doi = {10.1016/j.jlr.2024.100609},
issn = {1539-7262 0022-2275},
year = {2024},
date = {2024-09-01},
journal = {Journal of lipid research},
volume = {65},
number = {9},
pages = {100609},
abstract = {Glycosylated sphingolipids (GSLs) are a diverse group of cellular lipids typically reported as being rare in normal mammary tissue. In breast cancer (BCa), GSLs have emerged as noteworthy markers associated with breast cancer stem cells, mediators of phenotypic plasticity, and contributors to cancer cell chemoresistance. GSLs are potential surface markers that can uniquely characterize the heterogeneity of the tumor microenvironment, including cancer cell subpopulations and epithelial-mesenchymal plasticity (EMP). In this study, mass spectrometry analyses of the total sphingolipidome in breast epithelial cells and their mesenchymal counterparts revealed increased levels of Gb3 in epithelial cells and significantly elevated GD2 levels in the mesenchymal phenotype. To elucidate if GSL-related epitopes on BCa cell surfaces reflect EMP and cancer status, we developed and rigorously validated a 12-color spectral flow cytometry panel. This panel enables the simultaneous detection of native GSL epitopes (Gb3, SSEA1, SSEA3, SSEA4, and GD2), epithelial-mesenchymal transition markers (EpCAM, TROP2, and CD9), and lineage markers (CD45, CD31, and CD90) at the single-cell level. Next, the established panel was used for the analysis of BCa primary tumors and revealed surface heterogeneity in SSEA1, SSEA3, SSEA4, GD2, and Gb3, indicative of native epitope presence also on non-tumor cells. These findings further highlighted the phenotype-dependent alterations in GSL surface profiles, with differences between epithelial and stromal cells in the tumor. This study provides novel insights into BCa heterogeneity, shedding light on the potential of native GSL-related epitopes as markers for EMP and cancer status in fresh clinical samples. The developed single-cell approach offers promising avenues for further exploration.},
note = {Place: United States},
keywords = {*Breast Neoplasms/metabolism/pathology, *Epithelial-Mesenchymal Transition, *Glycosphingolipids/metabolism/analysis, *Single-Cell Analysis/methods, Breast cancer, Epithelial Cells, Female, Glycosphingolipids, Humans, Phenotype, phenotypic plasticity, stromal-like cells, surface profiling},
pubstate = {published},
tppubtype = {article}
}
Glycosylated sphingolipids (GSLs) are a diverse group of cellular lipids typically reported as being rare in normal mammary tissue. In breast cancer (BCa), GSLs have emerged as noteworthy markers associated with breast cancer stem cells, mediators of phenotypic plasticity, and contributors to cancer cell chemoresistance. GSLs are potential surface markers that can uniquely characterize the heterogeneity of the tumor microenvironment, including cancer cell subpopulations and epithelial-mesenchymal plasticity (EMP). In this study, mass spectrometry analyses of the total sphingolipidome in breast epithelial cells and their mesenchymal counterparts revealed increased levels of Gb3 in epithelial cells and significantly elevated GD2 levels in the mesenchymal phenotype. To elucidate if GSL-related epitopes on BCa cell surfaces reflect EMP and cancer status, we developed and rigorously validated a 12-color spectral flow cytometry panel. This panel enables the simultaneous detection of native GSL epitopes (Gb3, SSEA1, SSEA3, SSEA4, and GD2), epithelial-mesenchymal transition markers (EpCAM, TROP2, and CD9), and lineage markers (CD45, CD31, and CD90) at the single-cell level. Next, the established panel was used for the analysis of BCa primary tumors and revealed surface heterogeneity in SSEA1, SSEA3, SSEA4, GD2, and Gb3, indicative of native epitope presence also on non-tumor cells. These findings further highlighted the phenotype-dependent alterations in GSL surface profiles, with differences between epithelial and stromal cells in the tumor. This study provides novel insights into BCa heterogeneity, shedding light on the potential of native GSL-related epitopes as markers for EMP and cancer status in fresh clinical samples. The developed single-cell approach offers promising avenues for further exploration.
2023
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
Single-cell protein profiling defines cell populations associated with triple-negative breast cancer aggressiveness. Journal Article
In: Molecular oncology, vol. 17, no. 6, pp. 1024–1040, 2023, ISSN: 1878-0261 1574-7891, (Place: United States).
Abstract | Links | BibTeX | Tags: *Triple Negative Breast Neoplasms/metabolism, Cell Line, Humans, mass cytometry, phenotypic plasticity, Proteomics, Retrospective Studies, Signal Transduction, single-cell profiles, Stromal Cells/metabolism, triple-negative breast cancer, Tumor, tumor heterogeneity, Tumor microenvironment, unsupervised machine learning algorithm
@article{kvokackova_single-cell_2023,
title = {Single-cell protein profiling defines cell populations associated with triple-negative breast cancer aggressiveness.},
author = {Barbora Kvokačková and Radek Fedr and Daniela Kužílková and Jan Stuchlý and Adéla Vávrová and Jiří Navrátil and Pavel Fabian and Róbert Ondruššek and Petra Ovesná and Ján Remšík and Jan Bouchal and Tomáš Kalina and Karel Souček},
doi = {10.1002/1878-0261.13365},
issn = {1878-0261 1574-7891},
year = {2023},
date = {2023-06-01},
journal = {Molecular oncology},
volume = {17},
number = {6},
pages = {1024–1040},
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.},
note = {Place: United States},
keywords = {*Triple Negative Breast Neoplasms/metabolism, Cell Line, Humans, mass cytometry, phenotypic plasticity, Proteomics, Retrospective Studies, Signal Transduction, single-cell profiles, Stromal Cells/metabolism, triple-negative breast cancer, Tumor, tumor heterogeneity, Tumor microenvironment, unsupervised machine learning algorithm},
pubstate = {published},
tppubtype = {article}
}
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.