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Gene Expression Profiling in Cancer Using cDNA Microarrays

  • Protocol
Molecular Analysis of Cancer

Part of the book series: Methods in Molecular Medicine ((MIMM,volume 68))

Abstract

The principle of cDNA microarray hybridization takes advantage of the property of DNA to form duplex structures between two complementary strands. In this technique (Fig. 1), the cDNA probes, which are arrayed onto a glass slide and represent the sequence of known genes or expressed sequence tags (ESTs), interrogate fluorescently labeled cDNA targets synthesized from extracted mRNA. In two-color microarray experiments, the differentially labeled cDNA targets (e.g., from tumor and normal tissue) hybridize to their respective cDNA probe sequences tethered to the slide. After imaging the microarray slide for signal intensities in each color channel, the relative expression ratio for each arrayed gene can be determined. In contrast to traditional gene-by-gene expression monitoring (such as Northerns), the cDNA microarray technique is limited only by the number of genes printed on the slide and, therefore; allows the analysis of gene expression on a truly genomewide scale (see Note 1).

The entire microarray process is summarized. (1) Plasmid DNA is extracted from the bacterial clones, and the cDNA insert PCR amplified using vector primers. The products are purified and printed onto immobilized slides using robots. Expression arrays containing up to 30,000 genes can be printed onto a microscope glass slide. (2) Total RNA extracted from test and reference cells is fluorescently labeled using oligo dT-primed reverse transcription by utilizing nucleotides tagged with either Cy3 or Cy5, respectively. (3) The probe mixture is hybridized to the microarray on the glass slides. (4) Fluorescence intensities at the immobilized targets are measured using laser confocal microscopes with the appropriate excitation lasers and emission filters. Each of the images is arbitrarily assigned a pseudo-color (i.e., Cy5 = red and Cy3 = green). A normalization process is performed to compensate for differential efficiencies of labeling and detection of Cy3 and Cy5. The two fluorescent images thus constitute the raw data from which differential gene expression ratio values are calculated. (5) Data mining tools are being developed depending on the experimental design. For instance, template-based clustering can identify genes sequentially expressed in time. Multidimensional scaling allows visualization of the similarity of expression profiles between experiments where the distance between the experiments correspond as closely as possible to 1 minus the Pearson correlation coefficient of the gene expression. Similarly, the relationships between genes and experiments can also be visualized by hierarchical clustering.

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Author information

Authors and Affiliations

  1. Oncogenomics Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD

    Javed Khan

  2. Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD

    Lao H. Saal, Michael L. Bittner, Yuan Jiang, Gerald C. Gooden, Arthur A. Glatfelter & Paul S. Meltzer

Authors
  1. Javed Khan
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  2. Lao H. Saal
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  3. Michael L. Bittner
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  4. Yuan Jiang
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  5. Gerald C. Gooden
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  6. Arthur A. Glatfelter
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  7. Paul S. Meltzer
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Editor information

Editors and Affiliations

  1. Leukaemia Research Fund Molecular Haematology Unit, University of Oxford, NDCLS, John Radcliffe Hospital, Oxford, UK

    Jacqueline Boultwood  & Carrie Fidler  & 

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© 2002 Humana Press Inc.

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Khan, J. et al. (2002). Gene Expression Profiling in Cancer Using cDNA Microarrays. In: Boultwood, J., Fidler, C. (eds) Molecular Analysis of Cancer. Methods in Molecular Medicine, vol 68. Humana Press. https://doi.org/10.1385/1-59259-135-3:205

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  • DOI: https://doi.org/10.1385/1-59259-135-3:205

  • Publisher Name: Humana Press

  • Print ISBN: 978-0-89603-622-2

  • Online ISBN: 978-1-59259-135-0

  • eBook Packages: Springer Protocols

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