Laser-capture microdissection

Center for Applied Proteomics and Molecular Medicine, George Mason University, 10900 University Blvd. MS 4E3, Manassas, Virginia, USA.
Nature Protocol (Impact Factor: 9.67). 02/2006; 1(2):586-603. DOI: 10.1038/nprot.2006.85
Source: PubMed


Deciphering the cellular and molecular interactions that drive disease within the tissue microenvironment holds promise for discovering drug targets of the future. In order to recapitulate the in vivo interactions thorough molecular analysis, one must be able to analyze specific cell populations within the context of their heterogeneous tissue microecology. Laser-capture microdissection (LCM) is a method to procure subpopulations of tissue cells under direct microscopic visualization. LCM technology can harvest the cells of interest directly or can isolate specific cells by cutting away unwanted cells to give histologically pure enriched cell populations. A variety of downstream applications exist: DNA genotyping and loss-of-heterozygosity (LOH) analysis, RNA transcript profiling, cDNA library generation, proteomics discovery and signal-pathway profiling. Herein we provide a thorough description of LCM techniques, with an emphasis on tips and troubleshooting advice derived from LCM users. The total time required to carry out this protocol is typically 1-1.5 h.

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    • "Commercial UV-LCM microscopes are available from Zeiss (PALM; Bernried, Germany), Leica (LMD6500/7000; Wetzlar, Germany) and Arcturus (Veritas). For a recent review of the different LCM techniques , their potential and technical details the reader is referred to [43] [44]. LCM was successfully applied to separate tumor cells from stromal compartments and normal cells [45] [46] followed by subsequent molecular analysis [47] [48] [49]. "
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    ABSTRACT: Solid cancers are not simple accumulations of malignant tumor cells but rather represent complex organ-like structures. Despite a more chaotic general appearance as compared to the highly organized setup of healthy tissues, cancers still show highly differentiated structures and a close interaction with and dependency on the interwoven connective tissue. This complexity within cancers is not known in detail at the molecular level so far. The first part of this article will shortly describe the technology and strategies to quantify and dissect the heterogeneity in human solid cancers. Moreover, there is urgent need to better understand human cancer biology since the development of novel anti-cancer drugs is far from being efficient, predominantly due to the scarcity of predictive preclinical models. Hence, in vivo and in vitro models were developed, which better recapitulate the complexity of human cancers, by their intrinsic three-dimensional nature and the cellular heterogeneity and allow functional intervention for hypothesis testing. Therefore, in the second part 3D in vitro cancer models are presented that analyze and depict the heterogeneity in human cancers. Advantages and drawbacks of each model are highlighted and their suitability to preclinical drug testing is discussed. Copyright © 2015. Published by Elsevier Ltd.
    Seminars in Cancer Biology 08/2015; DOI:10.1016/j.semcancer.2015.08.007 · 9.33 Impact Factor
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    • "The quantity of RNA obtained after LCM is typically in the order of several picograms to a few nanograms, depending on the amount and type of cells captured. A quantity of 10 pg of total RNA per cell is commonly quoted, (e.g., Espina et al., 2006), and "
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    ABSTRACT: Laser capture microdissection (LCM) facilitates the isolation of individual cells from tissue sections, and when combined with RNA amplification techniques, it is an extremely powerful tool for examining genome-wide expression profiles in specific cell-types. LCM has been widely used to address various biological questions in both animal and plant systems, however, no attempt has been made so far to transfer LCM technology to macroalgae. Macroalgae are a collection of widespread eukaryotes living in fresh and marine water. In line with the collective effort to promote molecular investigations of macroalgal biology, here we demonstrate the feasibility of using LCM and cell-specific transcriptomics to study development of the brown alga Ectocarpus siliculosus. We describe a workflow comprising cultivation and fixation of algae on glass slides, laser microdissection, and RNA amplification. To illustrate the effectiveness of the procedure, we show qPCR data and metrics obtained from cell-specific transcriptomes generated from both upright and prostrate filaments of Ectocarpus.
    Frontiers in Plant Science 02/2015; 6(54). DOI:10.3389/fpls.2015.00054 · 3.95 Impact Factor
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    • "Some multicellular organisms , such as Caenorhabditis elegans (Sulston et al. 1983) and zebra fish (Aanes et al. 2011, 2014), have known numbers of cells at defined developmental stages. Laser capture microdissection enables the number of cells used for RNA extraction to be determined when working with solid tissues (Espina et al. 2006). In such cases, heterologous RNA (e.g., External RNA Fig. 4 Distribution of gene dosage responses in G. dolichocarpa. "
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    ABSTRACT: The number of RNA molecules per cell (transcriptome size) is highly variable, differing among and within cell types depending on cell size, stage of the cell cycle, ploidy level, age, disease state, and growth condition. Such variation has been observed at the level of total RNA, ribosomal RNA, messenger RNA (mRNA), and the polyadenylated fraction of mRNA, and these distinct RNA species can also vary in abundance with respect to each other. This variation in transcriptome size has been largely ignored or overlooked, and in fact, standard data normalization procedures for transcript profiling experiments implicitly assume that mRNA transcriptome size is constant. Consequently, variation in transcriptome size has important technical implications for such experiments, as well as profound biological implications for the affected cells and underlying genomes. Here, we review what is known about transcriptome size variation, explore how ignoring this variation introduces systematic bias into standard expression profiling experiments, and present examples of how such biases have led to erroneous conclusions in expression studies of sex chromosome dosage compensation, cancer, Rett syndrome, embryonic development, aging, and polyploidy. We also discuss how quantifying transcriptome size will help to elucidate the selective forces underlying patterns of gene and genome evolution and review the evidence that cells exert tight control over transcriptome size in order to maintain cell size homeostasis and to optimize chemical reactions within the cell, such that loss of control over transcriptome size is associated with cancer and aging. Thus, transcriptome size is an important phenotype in its own right. Finally, we discuss strategies for quantifying transcriptome size and individual gene dosage responses in order to account for and better understand this important biological phenomenon.
    Chromosoma 11/2014; 124(1). DOI:10.1007/s00412-014-0496-3 · 4.60 Impact Factor
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