Advertisement

Laser Capture Microdissection for Analysis of Gene Expression in Formalin-Fixed Paraffin-Embedded Tissue

  • Ru Jiang
  • Rona S. Scott
  • Lindsey M. Hutt-FletcherEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 755)

Abstract

A combination of laser capture microdissection and reverse transcriptase real-time quantitative PCR ­provides a powerful tool for the analysis of relative gene expression in archived tissue specimens. This chapter describes standard methodologies that can be used to determine the relative levels of gene expression in individual cells captured from formalin-fixed paraffin-embedded tissues.

Key words

Formalin-fixed tissues Laser capture microdissection Gene expression Reverse transcription Real-time quantitative PCR 

Notes

Acknowledgments

This work was supported by grants DE 016669 and CA114416.

References

  1. 1.
    Curran, S., McKay, J. A., McLeod, H. L., Murray, G. I. (2000) Laser capture microscopy. Journal of Clinical Pathology 53, 64–68.Google Scholar
  2. 2.
    Fend, F., Emmert-Buck, M. R., Chuaqui, R., Cole, K., Lee, J., Liotta, L. A., Raffeld, M. (1999) Immuno-LCM: laser capture microdissection of immunostained frozen sections for mRNA anal­ysis. American Journal of Pathology 154, 61–66.Google Scholar
  3. 3.
    Livak, K. J., Schmittgen, T. D. (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods 25, 402–408.Google Scholar
  4. 4.
    Pfaffl, M. W. (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Research 29, e45.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Ru Jiang
    • 1
  • Rona S. Scott
    • 1
  • Lindsey M. Hutt-Fletcher
    • 1
    Email author
  1. 1.Department of Microbiology and Immunology, Center for Molecular and Tumor Virology and Feist-Weiller Cancer CenterLouisiana State University Health Sciences CenterShreveportUSA

Personalised recommendations