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JMD 2005, Vol. 7, No. 1
Copyright © 2005 American Society for Investigative Pathology & Association for Molecular Pathology

Reproducibility, Fidelity, and Discriminant Validity of mRNA Amplification for Microarray Analysis from Primary Hematopoietic Cells

Liang Li^*, Joe Roden, Bruce E. Shapiro, Barbara J. Wold, Smita Bhatia, Stephen J. Forman^* and Ravi Bhatia^*

From the Divisions of Hematology and Bone Marrow Transplantation * and Pediatrics, City of Hope National Medical Center, Duarte; the Machine Learning Systems Group, Jet Propulsion Laboratory, Pasadena; and the Division of Biology, California Institute of Technology, Pasadena, California

Analysis of gene expression in clinical samples poses special challenges, including limited RNA availability and poor RNA quality. Quantitative information regarding reliability of RNA amplification methodologies applied to primary cells and representativeness of resulting gene expression profiles is limited. We evaluated four protocols for RNA amplification from peripheral blood mononuclear cells. Results obtained with 100 ng or 10 ng of RNA amplified using two rounds of cDNA synthesis and in vitro transcription were compared with control 2.5-µg RNA samples processed using a single round of in vitro transcription. Samples were hybridized to Affymetrix HG-U133A arrays. Considerable differences in results were obtained with different protocols. The optimal protocol resulted in highly reproducible gene expression profiles from amplified samples (r = 0.98) and good correlation between amplified and control samples (r = 0.94). Using the optimal protocol dissimilarities of gene expression between mononuclear cells from a normal individual and a patient with myelodysplastic syndrome were primarily maintained after amplification compared with controls. We conclude that small variations in methodology introduce considerable distortion of gene expression profiles obtained after RNA amplification from clinical samples and too strong a focus on a very small number of genes picked from an array analysis could be unduly influenced by seemingly acceptable methodologies. However, it is possible to obtain reproducible and representative results using optimized protocols.

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