An adaptable method using human mixed tissue ratiometric controls for benchmarking performance on gene expression...

Area of Science:

• Molecular biology
• Genomics
• Biomarker discovery

Background:

• mRNA transcript-based molecular biomarkers are crucial for disease diagnosis and treatment.
• DNA microarrays are key for developing gene expression classifiers for clinical outcomes.
• Current microarray assays have limitations in dynamic range and fold change detection, necessitating improved assay controls.

Purpose of the Study:

• To develop and validate ratiometric controls for benchmarking DNA microarray assay performance.
• To assess diagnostic performance and reliable measurement ranges using these novel controls.
• To demonstrate process improvements in microarray assays for clinical utility.

Main Methods:

• Prepared ratiometric controls from commercial human RNA with distinct expression profiles, mixed in defined ratios.
• Processed samples using six target labeling protocols and generated replicate datasets on high-density gene expression microarrays.
• Utilized receiver operating characteristic plots and log(2) ratio deviation plots to measure diagnostic performance and reliable dynamic range.

Main Results:

• Statistically significant differences in diagnostic performance were observed between standardized and alternative target generation methods.
• Assay performance, measured by the reliable range of comparative measurement, improved by adjusting hybridization conditions for a commercial kit.
• Ratiometric controls enabled the derivation of reliable dynamic range and diagnostic performance metrics.

Conclusions:

• Process improvements in microarray assay performance were demonstrated using commercially available materials and validated metrics.
• The developed methods provide benchmark values for optimizing protocols and laboratory proficiency in clinical settings.
• These controls offer advantages over limited external controls or reference set correlations for assay validation.