P35-M Quantitative Measurement of Gene Expression from Formalin-Fixed Tissue Providing Identical Results as Fresh Tissue: Biomarker Validation using Clinical Samples.

Journal of biomolecular techniques(2007)

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摘要
The measurement of gene expression from formalin-fixed paraffin-embedded (FFPE) tissue has proven to be problematic. Consequently, archives of FFPE samples remain unexploited in the quest to elucidate and validate the molecular mechanisms of diseases, cellular processes, and drug activity/safety. We validated the measurement of gene expression from FFPE tissue by a new multiplexed assay, the quantitative nuclease protection assay (qNPA). qNPA measures the RNA cross-linked to tissue without its having to be solubilized, plus the soluble RNA pool—i.e., the total RNA contained in the FFPE sample. This is likely one explanation of qNPA success where methods that measure only soluble RNA have failed. Cross-linked RNA is the major pool in FPE samples, and the fraction it makes up varies from sample to sample, presumably due to differences in fixation time or sample age. Consistent with the observation that qNPA measures the total RNA in fixed tissue, and the fact that it measures the total RNA in fresh samples, is the result that identical quantitative levels of gene expression are measured from fresh fixed and 18-y-old FFPE tissue and from matched fresh or fixed tissue. The expression level for a set of low to moderately expressed genes from fresh vs. FFPE tissue correlated with an R2 = 0.99, slope = 1. Gene expression measurements in FFPE tissue provided average CVs <10%. A retrospective study using clinical diffuse large B-cell lymphoma samples was carried out, validating prognostic biomarkers of disease, disease subtype, and survival. The levels of gene expression measured by qNPA correlated with protein product levels measured by IHC. These results validate that qNPA provides a high-quality gene expression assay of FFPE tissue, enabling research and clinical assays not previously possible.
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biomedical research,bioinformatics
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