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Assessment of normalization strategies for quantitative RT-PCR using microdissected tissue samples

  1. Author:
    Erickson, H. S.
    Albert, P. S.
    Gillespie, J. W.
    Wallis, B. S.
    Rodriguez-Canales, J.
    Linehan, W. M.
    Gonzalez, S.
    Velasco, A.
    Chuaqui, R. F.
    Emmert-Buck, M. R.
  2. Author Address

    NCI, Pathogenet Unit, Pathol Lab, Bethesda, MD 20892 USA. NCI, Urol Oncol Branch, NIH, Bethesda, MD 20892 USA. NCI, Biomet Res Branch, Div Canc Treatment & Diag, NIH, Bethesda, MD 20892 USA. NCI, SAIC Frederick Inc, Frederick, MD 21701 USA. Catholic Univ Chile, Dept Pathol, Santiago, Chile. Catholic Univ Chile, Dept Urol, Santiago, Chile.;Erickson, HS, NCI, Pathogenet Unit, Pathol Lab, Bethesda, MD 20892 USA.;HSE@nih.gov mbuck@helix.nih.gov
    1. Year: 2007
    2. Date: Sep
  1. Journal: Laboratory Investigation
    1. 87
    2. 9
    3. Pages: 951-962
  2. Type of Article: Article
  3. ISSN: 0023-6837
  1. Abstract:

    Gene expression measurement techniques such as quantitative reverse transcriptase (qRT)-PCR require a normalization strategy to allow meaningful comparisons across biological samples. Typically, this is accomplished through the use of an endogenous housekeeping gene that is presumed to show stable expression levels in the samples under study. There is concern regarding how precisely specific genes can be measured in limited amounts of mRNA such as those from microdissected (MD) tissues. To address this issue, we evaluated three different approaches for qRT-PCR normalization of dissected samples; cell count during microdissection, total RNA measurement, and endogenous control genes. The data indicate that both cell count and total RNA are useful in calibrating input amounts at the outset of a study, but do not provide enough precision to serve as normalization standards. However, endogenous control genes can accurately determine the relative abundance of a target gene relative to the entire cellular transcriptome. Taken together, these results suggest that precise gene expression measurements can be made from MD samples if the appropriate normalization strategy is employed.

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External Sources

  1. DOI: 10.1038/labinvest.3700659
  2. WOS: 000248943900010

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