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Cancer Gene Profiling

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Attention for Chapter 2: Tissue Microdissection.
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Chapter title
Tissue Microdissection.
Chapter number 2
Book title
Cancer Gene Profiling
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3204-7_2
Pubmed ID
Book ISBNs
978-1-4939-3203-0, 978-1-4939-3204-7
Authors

Anja Rabien Ph.D., Glen Kristiansen, Anja Rabien

Editors

Robert Grützmann, Christian Pilarsky

Abstract

The new opportunities of modern assays of molecular biology can only be exploited fully if the results can be accurately correlated to the tissue phenotype under investigation. This is a general problem of non-in situ techniques, whereas results from in situ techniques are often difficult to quantify. The use of bulk tissue, which is not precisely characterized in terms of histology, has long been the basis for molecular analysis. It has, however, become apparent, that this simple approach is not sufficient for a detailed analysis of molecular alterations, which might be restricted to a specific tissue phenotype (e.g., tumor or normal tissue, stromal or epithelial cells). Microdissection is a method to provide minute amounts of histologically characterized tissues for molecular analysis with non-in situ techniques and has become an indispensable research tool. If tissue diversity is moderate and negligible, manual microdissection can be an easy and cost-efficient method of choice. In contrast, the advantage of laser microdissection is a very exact selection down to the level of a single cell, but often with a considerable time exposure to get enough material for the following analyses. The latter issue and the method of tissue preparation needed for laser microdissection are the main problems to solve if RNA, highly sensitive to degradation, shall be analyzed. This chapter focuses on optimized procedures for manual microdissection and laser microdissection to analyze RNA of malignant and nonmalignant prostate tissue.

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The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 20%
Researcher 3 20%
Student > Master 3 20%
Student > Bachelor 2 13%
Professor 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 47%
Economics, Econometrics and Finance 2 13%
Neuroscience 2 13%
Medicine and Dentistry 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Other 0 0%
Unknown 2 13%