Chapter title |
Purification of Distinct Subsets of Epithelial Cells from Normal Human Breast Tissue.
|
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Chapter number | 13 |
Book title |
Mammary Gland Development
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6475-8_13 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6473-4, 978-1-4939-6475-8
|
Authors |
Mona Shehata, John Stingl |
Editors |
Finian Martin, Torsten Stein, Jillian Howlin |
Abstract |
The mammary epithelium is composed of a variety of specialized cell types that function in a coordinated fashion to produce and eject milk through multiple cycles of pregnancy. The ability to identify and purify these subsets of cells in order to interrogate their growth and differentiation capacities, as well as to characterize the molecular mechanisms that regulate their behavior, is essential in identifying the processes associated with breast cancer initiation and progression. This methods chapter outlines the step-by-step methods for dissociating human breast reduction specimens to a single cell suspension of viable cells. As well, strategies for purifying four distinct subsets of epithelial cells by using fluorescence-activated cell sorting and protocols for interrogating the growth and differentiation properties of these purified cells at clonal densities in adherent culture are also described. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 3 | 21% |
Researcher | 2 | 14% |
Student > Doctoral Student | 1 | 7% |
Student > Bachelor | 1 | 7% |
Lecturer | 1 | 7% |
Other | 4 | 29% |
Unknown | 2 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 4 | 29% |
Medicine and Dentistry | 3 | 21% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
Veterinary Science and Veterinary Medicine | 1 | 7% |
Biochemistry, Genetics and Molecular Biology | 1 | 7% |
Other | 1 | 7% |
Unknown | 3 | 21% |