The study was supported in part by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Center for Cancer Research.

The described protocol was employed in accordance with NIH rules on the use of human tissue samples.
1. Tissue Preparation
<ol>
	<li>Prior to beginning, obtain human tissue specimens according to Institutional Review Board (IRB) protocols.</li>
	<li>Choose the type of tissue/cell block and corresponding processing method [formalin-fixed paraffin-embedded (FFPE), frozen, or ethanol-fixed paraffin-embedded (EFPE)]. Formalin fixation provides optimal histology, followed by ethanol fixation and ...

<ol>
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B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Contaminating+cells+alter+gene+signatures+in+whole+organ+versus+laser+capture+microdissected+tumors:+a+comparison+of+experimental+breast+cancers+and+their+lymph+node+metastases.">Contaminating cells alter gene signatures in whole organ versus laser capture microdissected tumors: a comparison of experimental breast cancers and their lymph node metastases.</a> Clinical &amp; experimental metastasis. 25, 81-88 (2008).</li><li>Rodriguez-Canales, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimal+molecular+profiling+of+tissue+and+tissue+components:+defining+the+best+processing+and+microdissection+methods+for+biomedical+applications.">Optimal molecular profiling of tissue and tissue components: defining the best processing and microdissection methods for biomedical applications.</a> Methods in molecular biology. 980, 61-120 (2013).</li><li>Silvestri, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+pathway+biomarker+analysis+of+human+cancer+reveals+requirement+for+upfront+cellular-enrichment+processing.">Protein pathway biomarker analysis of human cancer reveals requirement for upfront cellular-enrichment processing.</a> Laboratory investigation; a journal of technical methods and pathology. 90, 787-796 (2010).</li><li>Eberle, F. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunoguided+laser+assisted+microdissection+techniques+for+DNA+methylation+analysis+of+archival+tissue+specimens.">Immunoguided laser assisted microdissection techniques for DNA methylation analysis of archival tissue specimens.</a> The Journal of molecular diagnostics : JMD. 12, 394-401 (2010).</li><li>Kim, H. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Distinctions+in+gastric+cancer+gene+expression+signatures+derived+from+laser+capture+microdissection+versus+histologic+macrodissection.">Distinctions in gastric cancer gene expression signatures derived from laser capture microdissection versus histologic macrodissection.</a> BMC medical genomics. 4, 48 (2011).</li><li>Klee, E. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impact+of+sample+acquisition+and+linear+amplification+on+gene+expression+profiling+of+lung+adenocarcinoma:+laser+capture+micro-dissection+cell-sampling+versus+bulk+tissue-sampling.">Impact of sample acquisition and linear amplification on gene expression profiling of lung adenocarcinoma: laser capture micro-dissection cell-sampling versus bulk tissue-sampling.</a> BMC medical genomics. 2, 13 (2009).</li><li>Zheng, J., Garg, S., Wang, J., Loose, D. S., Hauer-Jensen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Laser+capture+microdissected+mucosa+versus+whole+tissue+specimens+for+assessment+of+radiation-induced+dynamic+molecular+and+pathway+changes+in+the+small+intestine.">Laser capture microdissected mucosa versus whole tissue specimens for assessment of radiation-induced dynamic molecular and pathway changes in the small intestine.</a> PloS one. 8, e53711 (2013).</li><li>Boone, D. R., Sell, S. L., Hellmich, H. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Laser+capture+microdissection+of+enriched+populations+of+neurons+or+single+neurons+for+gene+expression+analysis+after+traumatic+brain+injury.">Laser capture microdissection of enriched populations of neurons or single neurons for gene expression analysis after traumatic brain injury.</a> J Vis Exp. (74), (2013).</li><li>Iyer, E. P., Cox, D. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Laser+capture+microdissection+of+Drosophila+peripheral+neurons.">Laser capture microdissection of Drosophila peripheral neurons.</a> J Vis Exp. (39), (2010).</li><li>Hipp, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SIVQ-aided+laser+capture+microdissection:+A+tool+for+high-throughput+expression+profiling.">SIVQ-aided laser capture microdissection: A tool for high-throughput expression profiling.</a> Journal of pathology informatics. 2, 19 (2011).</li><li>Hipp, J. D., Cheng, J. Y., Toner, M., Tompkins, R. G., Balis, U. 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We present a protocol for the application of SIVQ-LCM to microdissect immunostained epithelial cells from FFPE human breast tissue. The use of an image analysis algorithm, such as SIVQ, reduces the amount of hands-on time required for the microdissection process. This is a potentially important advance for the field since operator time and effort is typically the rate-limiting step for the precise dissection of cells of interest. In the present protocol, we specifically adapted our procedure to the ArcturusXT instrument,...

Originally developed in the mid-1990s, laser capture microdissection (LCM) enables the user to precisely capture specific cells or cellular regions from a histological tissue section via microscopic visualization1,2. Many studies comparing molecular analysis of LCM versus tissue scrapes illustrate the value of the method3-12. In addition, there are three video protocol publications on the technology that are available for viewing13,14. However, despite its proven value, LCM can be tedious and laborious when the target of interest is a dispersed cell population in a heterogeneous tissue section, or when large numbers of cells are required for specific downstream applications such as proteomics. The burden placed on the human operator led us to develop a semi-automated dissection approach for LCM by combining a powerful image analysis algorithm to guide the LCM process15.
In collaboration with the University of Michigan, our laboratory at the NIH extended the previously developed and reported Spatially invariant vector quantization (SIVQ) algorithm in a manner to allow it to semi-automate the tissue selection process intrinsic to guided microdissection, thus making available a tool with the pathologist or life scientist in mind. Spatially invariant vector quantization (SIVQ) is an algorithm that allows the user to simply &#8220;click&#8221; on a histological feature of interest to create a ring vector (predicate image feature) that can be used to search the entire histological image, adjusting the statistical threshold as needed16-21. The resultant heat map displays the quality of matches to the initial predicate image feature and is subsequently converted into a single color (red) annotation map that can be imported into the LCM instrument. The automated selection software, AutoScanXT, is then used to draw a map based on SIVQ&#39;s annotation guiding the capture of the target cells from the tissue sample. The detailed protocol below describes the implementation of SIVQ into the microdissection workflow.

<table border="0" cellpadding="0" cellspacing="0" width="586">
	<tbody>
		<tr height="43">
			<td height="43" style="height:43px;width:216px;">Positive Charged Glass Slides</td>
			<td style="width:84px;">Thermo Scientific</td>
			<td style="width:119px;">4951Plus-001</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:216px;">Xylenes, ACS reagent, &#8805;98.5% xylenes + ethylbenzene basis&#160;</td>
			<td style="width:84px;">Sigma Aldrich</td>
			<td style="width:119px;">247642</td>
			<td style="width:167px;">CAUTION: PLEASE USE PROPER SAFETY PROCEDURES.</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:216px;">Ethyl Alcohol, U.S.P. 200 Proof, Anhydrous</td>
			<td style="width:84px;">The Warner-Graham Company</td>
			<td style="width:119px;">6.505E+12</td>
			<td style="width:167px;">CAUTION: PLEASE USE PROPER SAFETY PROCEDURES.</td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:216px;">Arcturus CapSure Macro LCM Caps</td>
			<td style="width:84px;">Life Technologies</td>
			<td style="width:119px;">LCM0211</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:216px;">ArcturusXT Laser Microdissection Instrument</td>
			<td style="width:84px;">Life Technologies</td>
			<td style="width:119px;">ARCTURUSXT</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="127">
			<td height="127" style="height:127px;width:216px;">AutoScanXT Software</td>
			<td style="width:84px;">Life Technologies</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">An optional image analysis program for the ArcturusXT Laser Microdissection Device. This is software is required for SIVQ-LCM.</td>
		</tr>
		<tr height="169">
			<td height="169" style="height:169px;width:216px;">Spatially Invariant Vector Quantization (SIVQ)</td>
			<td style="width:84px;">University of Michigan</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">This tool suite is publicly available for academic collaborations. For access to the SIVQ algorithm, please contact Dr. Ulysses Balis [Ulysses@med.umich.edu]</td>
		</tr>
	</tbody>
</table>

sivq-lcm protocol for the arcturusxt instrument

SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process.&#160;It aims to create an advanced, rapidly customizable laser dissection platform technology. In this report, we describe the integration of the image analysis software Spatially Invariant Vector Quantization (SIVQ) onto the ArcturusXT instrument. The ArcturusXT system contains both an infrared (IR) and ultraviolet (UV) laser, allowing for specific cell or large area dissections. The principal goal is to improve the speed, accuracy, and reproducibility of the laser dissection to increase sample throughput. This novel approach facilitates microdissection of both animal and human tissues in research and clinical workflows.

A FFPE human breast tissue section was immunostained for cytokeratin AE1/AE3 using a standard IHC protocol23. After staining, the tissue slide was placed on the ArcturusXT stage and the SIVQ-LCM protocol was initiated as described above. Since the tissue cannot be coverslipped for microdissection, the IHC+ stained cells can be difficult to discern visually (Figure 1A). Thus, to provide better index matching and an improved image, xylenes were added to the tissue section to create a pseudo-cove...

Watch this Scientific Journal Video about SIVQ-LCM Protocol for the ArcturusXT Instrument at JoVE.com

SIVQ-LCM Protocol for the ArcturusXT Instrument

SIVQ-LCM is an innovative approach that harnesses a computer algorithm, Spatially Invariant Vector Quantization (SIVQ), to drive the laser capture microdissection (LCM) process. The SIVQ-LCM workflow greatly improves the speed and accuracy of microdissection, with applications in both the research and clinical settings.

SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process.&#160;It aims to create an ...

sivq-lcm-protocol-for-the-arcturusxt-instrument

Research

JoVE Journal

Biology

8.5K visualizações.  National Institutes of Health.  SIVQ-LCM é uma abordagem inovadora que utiliza um algoritmo de computador, espacialmente invariantes Quantização Vetorial (SIVQ), para conduzir o processo a laser microdissection captura (LCM). O fluxo de trabalho SIVQ-LCM melhora a velocidade e precisão da microdissecção, com aplicações tanto na pesquisa e na clínica. 