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    Methods comparison for high-resolution transcriptional analysis of archival material on Affymetrix Plus 2.0 and Exon 1.0 microarrays.

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    Authors
    Linton, Kim M
    Hey, Yvonne
    Dibben, Sian
    Miller, Crispin J
    Freemont, Anthony J
    Radford, John A
    Pepper, Stuart D
    Affiliation
    Cancer Research UK Department of Medical Oncology, The Christie NHS Foundation Trust, Manchester, UK. kim.linton@christie.nhs.uk
    Issue Date
    2009-07
    
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    Abstract
    Microarray gene expression profiling of formalin-fixed paraffin-embedded (FFPE) tissues is a new and evolving technique. This report compares transcript detection rates on Affymetrix U133 Plus 2.0 and Human Exon 1.0 ST GeneChips across several RNA extraction and target labeling protocols, using routinely collected archival FFPE samples. All RNA extraction protocols tested (Ambion-Optimum, Ambion-RecoverAll, and Qiagen-RNeasy FFPE) provided extracts suitable for microarray hybridization. Compared with Affymetrix One-Cycle labeled extracts, NuGEN system protocols utilizing oligo(dT) and random hexamer primers, and cDNA target preparations instead of cRNA, achieved percent present rates up to 55% on Plus 2.0 arrays. Based on two paired-sample analyses, at 90% specificity this equalled an average 30 percentage-point increase (from 50% to 80%) in FFPE transcript sensitivity relative to fresh frozen tissues, which we have assumed to have 100% sensitivity and specificity. The high content of Exon arrays, with multiple probe sets per exon, improved FFPE sensitivity to 92% at 96% specificity, corresponding to an absolute increase of ~600 genes over Plus 2.0 arrays. While larger series are needed to confirm high correspondence between fresh-frozen and FFPE expression patterns, these data suggest that both Plus 2.0 and Exon arrays are suitable platforms for FFPE microarray expression analyses.
    Citation
    Methods comparison for high-resolution transcriptional analysis of archival material on Affymetrix Plus 2.0 and Exon 1.0 microarrays. 2009, 47 (1):587-96 BioTechniques
    Journal
    BioTechniques
    URI
    http://hdl.handle.net/10541/87535
    DOI
    10.2144/000113169
    PubMed ID
    19594443
    Type
    Article
    Language
    en
    ISSN
    1940-9818
    ae974a485f413a2113503eed53cd6c53
    10.2144/000113169
    Scopus Count
    Collections
    Applied Computational Biology and Bioinformatics
    All Paterson Institute for Cancer Research
    Medical Oncology
    Molecular Biology Core Facility

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