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Detecting heterogeneity in and between breast cancer cell lines
BACKGROUND: Cellular heterogeneity in tumor cells is a well-established phenomenon. Genetic and phenotypic cell-to-cell variability have been observed in numerous studies both within the same type of cancer cells and across different types of cancers. Another known fact for metastatic tumor cells is...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997265/ https://www.ncbi.nlm.nih.gov/pubmed/32090168 http://dx.doi.org/10.1186/s41236-020-0010-1 |
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author | Shen, Yang Schmidt, B. U. Sebastian Kubitschke, Hans Morawetz, Erik W. Wolf, Benjamin Käs, Josef A. Losert, Wolfgang |
author_facet | Shen, Yang Schmidt, B. U. Sebastian Kubitschke, Hans Morawetz, Erik W. Wolf, Benjamin Käs, Josef A. Losert, Wolfgang |
author_sort | Shen, Yang |
collection | PubMed |
description | BACKGROUND: Cellular heterogeneity in tumor cells is a well-established phenomenon. Genetic and phenotypic cell-to-cell variability have been observed in numerous studies both within the same type of cancer cells and across different types of cancers. Another known fact for metastatic tumor cells is that they tend to be softer than their normal or non-metastatic counterparts. However, the heterogeneity of mechanical properties in tumor cells are not widely studied. RESULTS: Here we analyzed single-cell optical stretcher data with machine learning algorithms on three different breast tumor cell lines and show that similar heterogeneity can also be seen in mechanical properties of cells both within and between breast tumor cell lines. We identified two clusters within MDA-MB-231 cells, with cells in one cluster being softer than in the other. In addition, we show that MDA-MB-231 cells and MDA-MB-436 cells which are both epithelial breast cancer cell lines with a mesenchymal-like phenotype derived from metastatic cancers are mechanically more different from each other than from non-malignant epithelial MCF-10A cells. CONCLUSION: Since stiffness of tumor cells can be an indicator of metastatic potential, this result suggests that metastatic abilities could vary within the same monoclonal tumor cell line. |
format | Online Article Text |
id | pubmed-6997265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-69972652020-02-19 Detecting heterogeneity in and between breast cancer cell lines Shen, Yang Schmidt, B. U. Sebastian Kubitschke, Hans Morawetz, Erik W. Wolf, Benjamin Käs, Josef A. Losert, Wolfgang Cancer Converg Research BACKGROUND: Cellular heterogeneity in tumor cells is a well-established phenomenon. Genetic and phenotypic cell-to-cell variability have been observed in numerous studies both within the same type of cancer cells and across different types of cancers. Another known fact for metastatic tumor cells is that they tend to be softer than their normal or non-metastatic counterparts. However, the heterogeneity of mechanical properties in tumor cells are not widely studied. RESULTS: Here we analyzed single-cell optical stretcher data with machine learning algorithms on three different breast tumor cell lines and show that similar heterogeneity can also be seen in mechanical properties of cells both within and between breast tumor cell lines. We identified two clusters within MDA-MB-231 cells, with cells in one cluster being softer than in the other. In addition, we show that MDA-MB-231 cells and MDA-MB-436 cells which are both epithelial breast cancer cell lines with a mesenchymal-like phenotype derived from metastatic cancers are mechanically more different from each other than from non-malignant epithelial MCF-10A cells. CONCLUSION: Since stiffness of tumor cells can be an indicator of metastatic potential, this result suggests that metastatic abilities could vary within the same monoclonal tumor cell line. Springer International Publishing 2020-02-03 2020 /pmc/articles/PMC6997265/ /pubmed/32090168 http://dx.doi.org/10.1186/s41236-020-0010-1 Text en © The Author(s) 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Shen, Yang Schmidt, B. U. Sebastian Kubitschke, Hans Morawetz, Erik W. Wolf, Benjamin Käs, Josef A. Losert, Wolfgang Detecting heterogeneity in and between breast cancer cell lines |
title | Detecting heterogeneity in and between breast cancer cell lines |
title_full | Detecting heterogeneity in and between breast cancer cell lines |
title_fullStr | Detecting heterogeneity in and between breast cancer cell lines |
title_full_unstemmed | Detecting heterogeneity in and between breast cancer cell lines |
title_short | Detecting heterogeneity in and between breast cancer cell lines |
title_sort | detecting heterogeneity in and between breast cancer cell lines |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997265/ https://www.ncbi.nlm.nih.gov/pubmed/32090168 http://dx.doi.org/10.1186/s41236-020-0010-1 |
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