Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Choong, Lee Yee, Lim, Simin, Chong, Poh Kuan, Wong, Chow Yin, Shah, Nilesh, Lim, Yoon Pin
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2010
Materias:
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
_version_ 1782182226965823488
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
work_keys_str_mv AT choongleeyee proteomewideprofilingofthemcf10atbreastcancerprogressionmodel
AT limsimin proteomewideprofilingofthemcf10atbreastcancerprogressionmodel
AT chongpohkuan proteomewideprofilingofthemcf10atbreastcancerprogressionmodel
AT wongchowyin proteomewideprofilingofthemcf10atbreastcancerprogressionmodel
AT shahnilesh proteomewideprofilingofthemcf10atbreastcancerprogressionmodel
AT limyoonpin proteomewideprofilingofthemcf10atbreastcancerprogressionmodel