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Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model
BACKGROUND: Mapping the expression changes during breast cancer development should facilitate basic and translational research that will eventually improve our understanding and clinical management of cancer. However, most studies in this area are challenged by genetic and environmental heterogeneit...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2882958/ https://www.ncbi.nlm.nih.gov/pubmed/20543960 http://dx.doi.org/10.1371/journal.pone.0011030 |
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author | Choong, Lee Yee Lim, Simin Chong, Poh Kuan Wong, Chow Yin Shah, Nilesh Lim, Yoon Pin |
author_facet | Choong, Lee Yee Lim, Simin Chong, Poh Kuan Wong, Chow Yin Shah, Nilesh Lim, Yoon Pin |
author_sort | Choong, Lee Yee |
collection | PubMed |
description | BACKGROUND: Mapping the expression changes during breast cancer development should facilitate basic and translational research that will eventually improve our understanding and clinical management of cancer. However, most studies in this area are challenged by genetic and environmental heterogeneities associated with cancer. METHODOLOGY/PRINCIPAL FINDINGS: We conducted proteomics of the MCF10AT breast cancer model, which comprises of 4 isogenic xenograft-derived human cell lines that mimic different stages of breast cancer progression, using iTRAQ-based tandem mass spectrometry. Of more than 1200 proteins detected, 98 proteins representing at least 20 molecular function groups including kinases, proteases, adhesion, calcium binding and cytoskeletal proteins were found to display significant expression changes across the MCF10AT model. The number of proteins that showed different expression levels increased as disease progressed from AT1k pre-neoplastic cells to low grade CA1h cancer cells and high grade cancer cells. Bioinformatics revealed that MCF10AT model of breast cancer progression is associated with a major re-programming in metabolism, one of the first identified biochemical hallmarks of tumor cells (the “Warburg effect”). Aberrant expression of 3 novel breast cancer-associated proteins namely AK1, ATOX1 and HIST1H2BM were subsequently validated via immunoblotting of the MCF10AT model and immunohistochemistry of progressive clinical breast cancer lesions. CONCLUSION/SIGNIFICANCE: The information generated by this study should serve as a useful reference for future basic and translational cancer research. Dysregulation of ATOX1, AK1 and HIST1HB2M could be detected as early as the pre-neoplastic stage. The findings have implications on early detection and stratification of patients for adjuvant therapy. |
format | Text |
id | pubmed-2882958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28829582010-06-11 Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model Choong, Lee Yee Lim, Simin Chong, Poh Kuan Wong, Chow Yin Shah, Nilesh Lim, Yoon Pin PLoS One Research Article BACKGROUND: Mapping the expression changes during breast cancer development should facilitate basic and translational research that will eventually improve our understanding and clinical management of cancer. However, most studies in this area are challenged by genetic and environmental heterogeneities associated with cancer. METHODOLOGY/PRINCIPAL FINDINGS: We conducted proteomics of the MCF10AT breast cancer model, which comprises of 4 isogenic xenograft-derived human cell lines that mimic different stages of breast cancer progression, using iTRAQ-based tandem mass spectrometry. Of more than 1200 proteins detected, 98 proteins representing at least 20 molecular function groups including kinases, proteases, adhesion, calcium binding and cytoskeletal proteins were found to display significant expression changes across the MCF10AT model. The number of proteins that showed different expression levels increased as disease progressed from AT1k pre-neoplastic cells to low grade CA1h cancer cells and high grade cancer cells. Bioinformatics revealed that MCF10AT model of breast cancer progression is associated with a major re-programming in metabolism, one of the first identified biochemical hallmarks of tumor cells (the “Warburg effect”). Aberrant expression of 3 novel breast cancer-associated proteins namely AK1, ATOX1 and HIST1H2BM were subsequently validated via immunoblotting of the MCF10AT model and immunohistochemistry of progressive clinical breast cancer lesions. CONCLUSION/SIGNIFICANCE: The information generated by this study should serve as a useful reference for future basic and translational cancer research. Dysregulation of ATOX1, AK1 and HIST1HB2M could be detected as early as the pre-neoplastic stage. The findings have implications on early detection and stratification of patients for adjuvant therapy. Public Library of Science 2010-06-09 /pmc/articles/PMC2882958/ /pubmed/20543960 http://dx.doi.org/10.1371/journal.pone.0011030 Text en Choong et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Choong, Lee Yee Lim, Simin Chong, Poh Kuan Wong, Chow Yin Shah, Nilesh Lim, Yoon Pin Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model |
title | Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model |
title_full | Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model |
title_fullStr | Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model |
title_full_unstemmed | Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model |
title_short | Proteome-Wide Profiling of the MCF10AT Breast Cancer Progression Model |
title_sort | proteome-wide profiling of the mcf10at breast cancer progression model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2882958/ https://www.ncbi.nlm.nih.gov/pubmed/20543960 http://dx.doi.org/10.1371/journal.pone.0011030 |
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