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Mammary Stem Cells

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Cover of 'Mammary Stem Cells'

Table of Contents

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    Book Overview
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    Chapter 1 Breast Cancer Stem Cells: Current Advances and Clinical Implications
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    Chapter 2 A Protocol for Studying Embryonic Mammary Progenitor Cells During Mouse Mammary Primordial Development in Explant Culture
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    Chapter 3 FACS Sorting Mammary Stem Cells
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    Chapter 4 Side Population
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    Chapter 5 Single-cell genome and transcriptome processing prior to high-throughput sequencing.
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    Chapter 6 Shotgun proteomics on tissue specimens extracted with Acid guanidinium-thiocyanate-phenol-chloroform.
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    Chapter 7 Antibody-Based Capture of Target Peptides in Multiple Reaction Monitoring Experiments
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    Chapter 8 Lentiviral Transduction of Mammary Epithelial Cells
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    Chapter 9 The Transplantation of Mouse Mammary Epithelial Cells into Cleared Mammary Fat Pads
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    Chapter 10 Humanization of the Mouse Mammary Gland
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    Chapter 11 Lineage Tracing in the Mammary Gland Using Cre/lox Technology and Fluorescent Reporter Alleles
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    Chapter 12 Modeling the Breast Cancer Bone Metastatic Niche in Complex Three-Dimensional Cocultures
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    Chapter 13 Mammary Cancer Stem Cells Reinitiation Assessment at the Metastatic Niche: The Lung and Bone
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    Chapter 14 Nanomechanical Characterization of Living Mammary Tissues by Atomic Force Microscopy
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    Chapter 15 Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation
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    Chapter 16 Mammary Stem Cells: A Clinician’s View
Attention for Chapter 1: Breast Cancer Stem Cells: Current Advances and Clinical Implications
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Chapter title
Breast Cancer Stem Cells: Current Advances and Clinical Implications
Chapter number 1
Book title
Mammary Stem Cells
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2519-3_1
Pubmed ID
Book ISBNs
978-1-4939-2518-6, 978-1-4939-2519-3
Authors

Ming Luo, Shawn G. Clouthier, Yadwinder Deol, Suling Liu, Sunitha Nagrath, Ebrahim Azizi, Max S. Wicha, Luo, Ming, Clouthier, Shawn G., Deol, Yadwinder, Liu, Suling, Nagrath, Sunitha, Azizi, Ebrahim, Wicha, Max S.

Abstract

There is substantial evidence that many cancers, including breast cancer, are driven by a population of cells that display stem cell properties. These cells, termed cancer stem cells (CSCs) or tumor initiating cells, not only drive tumor initiation and growth but also mediate tumor metastasis and therapeutic resistance. In this chapter, we summarize current advances in CSC research with a major focus on breast CSCs (BCSCs). We review the prevailing methods to isolate and characterize BCSCs and recent evidence documenting their cellular origins and phenotypic plasticity that enables them to transition between mesenchymal and epithelial-like states. We describe in vitro and clinical evidence that these cells mediate metastasis and treatment resistance in breast cancer, the development of novel strategies to isolate circulating tumor cells (CTCs) that contain CSCs and the use of patient-derived xenograft (PDX) models in preclinical breast cancer research. Lastly, we highlight several signaling pathways that regulate BCSC self-renewal and describe clinical implications of targeting these cells for breast cancer treatment. The development of strategies to effectively target BCSCs has the potential to significantly improve the outcomes for patients with breast cancer.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 91 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 19%
Student > Bachelor 16 18%
Researcher 11 12%
Student > Ph. D. Student 8 9%
Professor > Associate Professor 7 8%
Other 17 19%
Unknown 15 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 31%
Medicine and Dentistry 20 22%
Agricultural and Biological Sciences 8 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Engineering 3 3%
Other 8 9%
Unknown 20 22%