Literature DB >> 26332018

A quantitative proteomics analysis of MCF7 breast cancer stem and progenitor cell populations.

Song Nie1, Sean P McDermott2,3, Yadwinder Deol2,3, Zhijing Tan1, Max S Wicha2,3, David M Lubman1.   

Abstract

Accumulating evidence has demonstrated that breast cancers are initiated and develop from a small population of stem-like cells termed cancer stem cells (CSCs). These cells are hypothesized to mediate tumor metastasis and contribute to therapeutic resistance. However, the molecular regulatory networks responsible for maintaining CSCs in an undifferentiated state have yet to be elucidated. In this study, we used CSC markers to isolate pure breast CSCs fractions (ALDH+ and CD44+CD24- cell populations) and the mature luminal cells (CD49f-EpCAM+) from the MCF7 cell line. Proteomic analysis was performed on these samples and a total of 3304 proteins were identified. A label-free quantitative method was applied to analyze differentially expressed proteins. Using the criteria of greater than twofold changes and p value <0.05, 305, 322 and 98 proteins were identified as significantly different in three pairwise comparisons of ALDH+ versus CD44+CD24-, ALDH+ versus CD49f-EpCAM+ and CD44+CD24- versus CD49f-EpCAM+, respectively. Pathway analysis of differentially expressed proteins by Ingenuity Pathway Analysis (IPA) revealed potential molecular regulatory networks that may regulate CSCs. Selected differential proteins were validated by Western blot assay and immunohistochemical staining. The use of proteomics analysis may increase our understanding of the underlying molecular mechanisms of breast CSCs. This may be of importance in the future development of anti-CSC therapeutics.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Breast cancer; Cancer stem cell; LC-MS/MS; Pathway analysis; Quantitative proteomics; Systems biology

Mesh:

Substances:

Year:  2015        PMID: 26332018      PMCID: PMC4715579          DOI: 10.1002/pmic.201500002

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  46 in total

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