| Chapter title |
Laser Capture Microdissection for Gene Expression Analysis
|
|---|---|
| Chapter number | 10 |
| Book title |
Apoptosis and Cancer
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-1661-0_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-1660-3, 978-1-4939-1661-0
|
| Authors |
Mallikarjun Bidarimath, Andrew K Edwards, Chandrakant Tayade, Andrew K. Edwards |
| Abstract |
Laser capture microdissection (LCM) is an excellent and perhaps the only platform to isolate homogeneous cell populations from specific microscopic regions of heterogeneous tissue section, under direct microscopic visualization. The basic operations of the LCM system are based on (a) microscopic visualization of phenotypically identified cells of interest, (b) selective adherence of cells to a melting thermolabile film/membrane using a low-energy infrared laser (IR system) or photovolatization of cells within a selected region (UV system), (c) capturing or catapulting of structurally intact cells from a stained tissue section. RNA/DNA or protein can be extracted from the cell or tissue fragments for downstream applications to quantitatively study gene expression. This method can be applied to many downstream analyses including but not limited to quantitative real-time polymerase chain reaction (PCR), microarray, DNA genotyping, RNA transcript profiling, generation of cDNA library, mass spectrometry analysis, and proteomic discovery.The application of LCM is described here to specifically and reliably obtain a homogeneous cell population in order to extract RNA to study microRNA expression by quantitative real-time PCR. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
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|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 27% |
| Student > Ph. D. Student | 3 | 20% |
| Student > Master | 2 | 13% |
| Student > Postgraduate | 2 | 13% |
| Professor > Associate Professor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 3 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 27% |
| Agricultural and Biological Sciences | 3 | 20% |
| Medicine and Dentistry | 3 | 20% |
| Neuroscience | 1 | 7% |
| Engineering | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 3 | 20% |