| Chapter title |
Using 3D Culture of Primary Mammary Epithelial Cells to Define Molecular Entities Required for Acinus Formation: Analyzing MAP Kinase Phosphatases.
|
|---|---|
| Chapter number | 9 |
| Book title |
Mammary Gland Development
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6475-8_9 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6473-4, 978-1-4939-6475-8
|
| Authors |
Malgorzata Gajewska Ph.D., D.Sc., Sara McNally, Malgorzata Gajewska |
| Editors |
Finian Martin, Torsten Stein, Jillian Howlin |
| Abstract |
Three-dimensional (3D) cell cultures on reconstituted basement membrane (rBM) enable the study of complex interactions between extracellular matrix (ECM) components and epithelial cells, which are crucial for the establishment of cell polarity and functional development of epithelia. 3D cultures of mammary epithelial cells (MECs) on Matrigel (a laminin-rich ECM derived from the Engelbreth-Holm-Swarm (EHS) murine tumor) promote interactions of MECs with the matrix via integrins, leading to formation of spherical monolayers of polarized cells surrounding a hollow lumen (acini). Acini closely resemble mammary alveoli found in the mammary gland. Thus, it is possible to study ECM-cell interactions and signalling pathways that regulate formation and maintenance of tissue-specific shape and functional differentiation of MECs in 3D under in vitro conditions. Here we present experimental protocols used to investigate the role of mitogen-activated protein kinase phosphatases (MKPs) during development of the alveoli-like structures by primary mouse mammary epithelial cells (PMMEC) cultured on Matrigel. We present detailed protocols for PMMEC isolation, and establishment of 3D cultures using an "on top" method, use of specific kinase and phosphatases inhibitors (PD98059 and pervanadate, respectively) administered at different stages of acinus development, and give examples of analyses carried out post-culture (Western blot, immunofluorescence staining, and confocal imaging). |
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Demographic breakdown
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|---|---|---|
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| Professor | 1 | 7% |
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| Unknown | 3 | 20% |