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Research Article

Optimized blood cell profiling method for genomic biomarker discovery using high-density microarray

, , , , , , , , , & show all
Pages 310-320
Received 22 Mar 2005
Published online: 08 Oct 2008

Abstract

High-quality biomarkers for disease progression, drug efficacy and toxicity liability are essential for improving the efficiency of drug discovery and development. The identification of drug-activity biomarkers is often limited by access to and the quantity of target tissue. Peripheral blood has increasingly become an attractive alternative to tissue samples from organs as source for biomarker discovery, especially during early clinical studies. However, given the heterogeneous blood cell population, possible artifacts from ex vivo activations, and technical difficulties associated with overall performance of the assay, it is challenging to profile peripheral blood cells directly for biomarker discovery. In the present study, Applied BioSystems’ blood collection system was evaluated for its ability to isolate RNA suitable for use on the Affymetrix microarray platform. Blood was collected in a TEMPUS tube and RNA extracted using an ABI-6100 semi-automated workstation. Using human and rat whole blood samples, it was demonstrated that the RNA isolated using this approach was stable, of high quality and was suitable for Affymetrix microarray applications. The microarray data were statistically analysed and compared with other blood protocols. Minimal haemoglobin interference with RNA labelling efficiency and chip hybridization was found using the TEMPUS tube and extraction method. The RNA quality, stability and ease of handling requirement make the TEMPUS tube protocol an attractive approach for expression profiling of whole blood to support target and biomarker discovery.

Acknowledgements

The authors are grateful to Jeff Fill and Mark Willey for help with blood collection. They thank Mark Rekhter, Peter Mitchell and members of the functional genomics group for helpful discussions. They also thank John Calley for gene annotation as well as IT support from the bioinformatics/IT group. J. S. and C. D. contributed equally to this study.

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