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Universal approaches for assessing the diagnostic performance of microarray assays are essential for the application of microarray technology to clinical and regulatory settings. Reference systems for diagnostic assays in laboratory medicine typically involve the utilization of reference samples, metrics, and reference datasets to ensure that measurements are comparable and true. For microarray performance evaluation and process improvement, reference samples can be composed of mixes of different tissue or cell line RNAs that contain tissue-selective analytes at defined target ratios. The diagnostic accuracy of detected changes in expression, measured as the area under the curve from receiver-operating characteristic plots, can provide a single commutable value for comparing assay specificity and sensitivity. Examples of applying this method for assessing overall performance are provided using public datasets generated on five commercial human whole genome microarray platforms for the MicroArray Quality Control project, a community-wide effort to address issues surrounding microarray data reliability.

The substrate specificity of the P-glycoprotein (P-170), a multidrug transporter, was studied using N-acylated daunorubicin derivatives and four MDR1 cDNA transfected cell lines. Results showed that N-acetyl-daunorubicin is a substrate, but the longer fatty acid derivatives, N-octanoyl and N-dodecanoyl daunorubicins, are not. This conclusion was reached by flow cytometric drug uptake assay, cell proliferation assays, and confocal microscopy. It was concluded that the longer fatty acid derivatives interact with plasma membranes in a way that affected P-glycoprotein function.