Literature DB >> 19018728

Use of diagnostic accuracy as a metric for evaluating laboratory proficiency with microarray assays using mixed-tissue RNA reference samples.

P S Pine1, M Boedigheimer, B A Rosenzweig, Y Turpaz, Y D He, G Delenstarr, B Ganter, K Jarnagin, W D Jones, L H Reid, K L Thompson.   

Abstract

Effective use of microarray technology in clinical and regulatory settings is contingent on the adoption of standard methods for assessing performance. The MicroArray Quality Control project evaluated the repeatability and comparability of microarray data on the major commercial platforms and laid the groundwork for the application of microarray technology to regulatory assessments. However, methods for assessing performance that are commonly applied to diagnostic assays used in laboratory medicine remain to be developed for microarray assays. A reference system for microarray performance evaluation and process improvement was developed that includes reference samples, metrics and reference datasets. The reference material is composed of two mixes of four different rat tissue RNAs that allow defined target ratios to be assayed using a set of tissue-selective analytes that are distributed along the dynamic range of measurement. The diagnostic accuracy of detected changes in expression ratios, measured as the area under the curve from receiver operating characteristic plots, provides a single commutable value for comparing assay specificity and sensitivity. The utility of this system for assessing overall performance was evaluated for relevant applications like multi-laboratory proficiency testing programs and single-laboratory process drift monitoring. The diagnostic accuracy of detection of a 1.5-fold change in signal level was found to be a sensitive metric for comparing overall performance. This test approaches the technical limit for reliable discrimination of differences between two samples using this technology. We describe a reference system that provides a mechanism for internal and external assessment of laboratory proficiency with microarray technology and is translatable to performance assessments on other whole-genome expression arrays used for basic and clinical research.

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Year:  2008        PMID: 19018728     DOI: 10.2217/14622416.9.11.1753

Source DB:  PubMed          Journal:  Pharmacogenomics        ISSN: 1462-2416            Impact factor:   2.533


  5 in total

Review 1.  Standards affecting the consistency of gene expression arrays in clinical applications.

Authors:  Steven A Enkemann
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-03-23       Impact factor: 4.254

2.  An adaptable method using human mixed tissue ratiometric controls for benchmarking performance on gene expression microarrays in clinical laboratories.

Authors:  P Scott Pine; Barry A Rosenzweig; Karol L Thompson
Journal:  BMC Biotechnol       Date:  2011-04-12       Impact factor: 2.563

3.  Summarizing performance for genome scale measurement of miRNA: reference samples and metrics.

Authors:  P Scott Pine; Steven P Lund; Jerod R Parsons; Lindsay K Vang; Ashish A Mahabal; Luca Cinquini; Sean C Kelly; Heather Kincaid; Daniel J Crichton; Avrum Spira; Gang Liu; Adam C Gower; Harvey I Pass; Chandra Goparaju; Steven M Dubinett; Kostyantyn Krysan; Sanford A Stass; Debra Kukuruga; Kendall Van Keuren-Jensen; Amanda Courtright-Lim; Karol L Thompson; Barry A Rosenzweig; Lynn Sorbara; Sudhir Srivastava; Marc L Salit
Journal:  BMC Genomics       Date:  2018-03-06       Impact factor: 3.969

4.  Learning from microarray interlaboratory studies: measures of precision for gene expression.

Authors:  David L Duewer; Wendell D Jones; Laura H Reid; Marc Salit
Journal:  BMC Genomics       Date:  2009-04-08       Impact factor: 3.969

5.  Cell-based reference samples designed with specific differences in microRNA biomarkers.

Authors:  P Scott Pine; Steven P Lund; Sanford A Stass; Debra Kukuruga; Feng Jiang; Lynn Sorbara; Sudhir Srivastava; Marc Salit
Journal:  BMC Biotechnol       Date:  2018-03-20       Impact factor: 2.563

  5 in total

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