Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD 20993 USA.
BMC Biotechnol. 2011 Apr 12;11:38. doi: 10.1186/1472-6750-11-38.
Molecular biomarkers that are based on mRNA transcripts are being developed for the diagnosis and treatment of a number of diseases. DNA microarrays are one of the primary technologies being used to develop classifiers from gene expression data for clinically relevant outcomes. Microarray assays are highly multiplexed measures of comparative gene expression but have a limited dynamic range of measurement and show compression in fold change detection. To increase the clinical utility of microarrays, assay controls are needed that benchmark performance using metrics that are relevant to the analysis of genomic data generated with biological samples.
Ratiometric controls were prepared from commercial sources of high quality RNA from human tissues with distinctly different expression profiles and mixed in defined ratios. The samples were processed using six different target labeling protocols and replicate datasets were generated on high density gene expression microarrays. The area under the curve from receiver operating characteristic plots was calculated to measure diagnostic performance. The reliable region of the dynamic range was derived from log(2) ratio deviation plots made for each dataset. Small but statistically significant differences in diagnostic performance were observed between standardized assays available from the array manufacturer and alternative methods for target generation. Assay performance using the reliable range of comparative measurement as a metric was improved by adjusting sample hybridization conditions for one commercial kit.
Process improvement in microarray assay performance was demonstrated using samples prepared from commercially available materials and two metrics - diagnostic performance and the reliable range of measurement. These methods have advantages over approaches that use a limited set of external controls or correlations to reference sets, because they provide benchmark values that can be used by clinical laboratories to help optimize protocol conditions and laboratory proficiency with microarray assays.
基于 mRNA 转录本的分子生物标志物正在被开发用于许多疾病的诊断和治疗。DNA 微阵列是用于从基因表达数据中开发与临床相关结果分类器的主要技术之一。微阵列分析是对比较基因表达的高度多重测量，但测量的动态范围有限，并且在折叠变化检测中显示压缩。为了提高微阵列的临床实用性，需要使用与使用生物样品生成的基因组数据分析相关的指标来基准性能的检测对照。
从具有明显不同表达谱的人类组织中的商业来源高质量 RNA 制备了比率对照，并以定义的比例混合。使用六种不同的靶标标记方案处理样品，并在高密度基因表达微阵列上生成重复数据集。使用接收者操作特征图的曲线下面积来测量诊断性能。从每个数据集的对数（2）比偏差图中得出可靠的动态范围。在标准化阵列制造商提供的检测与替代靶标生成方法之间观察到诊断性能的微小但具有统计学意义的差异。通过调整一种商业试剂盒的样品杂交条件，使用可靠的比较测量范围作为指标的检测性能得到了改善。
使用商业可获得材料和两个指标 - 诊断性能和可靠的测量范围制备的样品，证明了微阵列检测性能的改进。与使用有限数量的外部对照或与参考集的相关性的方法相比，这些方法具有优势，因为它们提供了基准值，临床实验室可以使用这些值来帮助优化微阵列检测的协议条件和实验室熟练程度。
