Chapter title |
Harvesting Human Prostate Tissue Material and Culturing Primary Prostate Epithelial Cells
|
---|---|
Chapter number | 12 |
Book title |
The Nuclear Receptor Superfamily
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3724-0_12 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3722-6, 978-1-4939-3724-0
|
Authors |
Fiona M. Frame, Davide Pellacani, Anne T. Collins, Norman J. Maitland, Frame, Fiona M., Pellacani, Davide, Collins, Anne T., Maitland, Norman J. |
Abstract |
In order to fully explore the biology of a complex solid tumor such as prostate cancer, it is desirable to work with patient tissue. Only by working with cells from a tissue can we take into account patient variability and tumor heterogeneity. Cell lines have long been regarded as the workhorse of cancer research and it could be argued that they are of most use when considered within a panel of cell lines, thus taking into account specified mutations and variations in phenotype between different cell lines. However, often very different results are obtained when comparing cell lines to primary cells cultured from tissue. It stands to reason that cells cultured from patient tissue represents a close-to-patient model that should and does produce clinically relevant data. This chapter aims to illustrate the methods of processing, storing and culturing cells from prostate tissue, with a description of potential uses. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 38% |
Student > Ph. D. Student | 4 | 31% |
Student > Bachelor | 2 | 15% |
Lecturer > Senior Lecturer | 1 | 8% |
Professor | 1 | 8% |
Other | 0 | 0% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 31% |
Medicine and Dentistry | 3 | 23% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
Psychology | 1 | 8% |
Agricultural and Biological Sciences | 1 | 8% |
Other | 0 | 0% |
Unknown | 3 | 23% |