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Molecular characterization of breast cancer cell lines through multiple omic approaches
BACKGROUND: Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K)...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460504/ https://www.ncbi.nlm.nih.gov/pubmed/28583138 http://dx.doi.org/10.1186/s13058-017-0855-0 |
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author | Smith, Shari E. Mellor, Paul Ward, Alison K. Kendall, Stephanie McDonald, Megan Vizeacoumar, Frederick S. Vizeacoumar, Franco J. Napper, Scott Anderson, Deborah H. |
author_facet | Smith, Shari E. Mellor, Paul Ward, Alison K. Kendall, Stephanie McDonald, Megan Vizeacoumar, Frederick S. Vizeacoumar, Franco J. Napper, Scott Anderson, Deborah H. |
author_sort | Smith, Shari E. |
collection | PubMed |
description | BACKGROUND: Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated. METHODS: We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer. RESULTS: The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated in common or unique ways. CONCLUSIONS: These two new kinase or “Kin-OMIC” analyses add another dimension of important data about these frequently used breast cancer cell lines. This will assist researchers in selecting the most appropriate cell lines to use for breast cancer studies and provide context for the interpretation of the emerging results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-017-0855-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5460504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54605042017-06-07 Molecular characterization of breast cancer cell lines through multiple omic approaches Smith, Shari E. Mellor, Paul Ward, Alison K. Kendall, Stephanie McDonald, Megan Vizeacoumar, Frederick S. Vizeacoumar, Franco J. Napper, Scott Anderson, Deborah H. Breast Cancer Res Research Article BACKGROUND: Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated. METHODS: We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer. RESULTS: The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated in common or unique ways. CONCLUSIONS: These two new kinase or “Kin-OMIC” analyses add another dimension of important data about these frequently used breast cancer cell lines. This will assist researchers in selecting the most appropriate cell lines to use for breast cancer studies and provide context for the interpretation of the emerging results. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13058-017-0855-0) contains supplementary material, which is available to authorized users. BioMed Central 2017-06-05 2017 /pmc/articles/PMC5460504/ /pubmed/28583138 http://dx.doi.org/10.1186/s13058-017-0855-0 Text en © The Author(s). 2017 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. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Smith, Shari E. Mellor, Paul Ward, Alison K. Kendall, Stephanie McDonald, Megan Vizeacoumar, Frederick S. Vizeacoumar, Franco J. Napper, Scott Anderson, Deborah H. Molecular characterization of breast cancer cell lines through multiple omic approaches |
title | Molecular characterization of breast cancer cell lines through multiple omic approaches |
title_full | Molecular characterization of breast cancer cell lines through multiple omic approaches |
title_fullStr | Molecular characterization of breast cancer cell lines through multiple omic approaches |
title_full_unstemmed | Molecular characterization of breast cancer cell lines through multiple omic approaches |
title_short | Molecular characterization of breast cancer cell lines through multiple omic approaches |
title_sort | molecular characterization of breast cancer cell lines through multiple omic approaches |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460504/ https://www.ncbi.nlm.nih.gov/pubmed/28583138 http://dx.doi.org/10.1186/s13058-017-0855-0 |
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