Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection

• Published in: Biomarker Insights 2009-01, Vol.2009 (4), p.BMI.S2253-179
• Main Authors: Barker, Peter E., Murthy, Mahadev
• Format: Article
• Language: English
• ISSN: 1177-2719; 1177-2719
• DOI: 10.4137/BMI.S2253

Peter E. Barker1 and Mahadev Murthy21Bioassay Methods Group, Biochemical Sciences Division, Bldg 227/B248, NIST, 100 Bureau Drive, Gaithersburg, Maryland. 2Division of Aging Biology (DAB), National Institute on Aging, 7201 Wisconsin Ave., GW 2C231, Bethesda, MD 20892. AbstractThe anticipated biological and clinical utility of biomarkers has attracted significant interest recently. Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologies and specific biomarker analytes bear comparison. Mitochondrial DNA (mtDNA) as a biomarker in both biological models has been evaluated. However, it remains unclear whether mtDNA changes in aging and cancer represent biological relationships that are causal, incidental, or a combination of both. This article focuses on evaluation of mtDNA-based biomarkers, emerging strategies for quantitating mtDNA admixtures, and how current understanding of mtDNA in aging and cancer evolves with introduction of new technologies. Whether for cancer or aging, lessons from mtDNA based biomarker evaluations are several. Biological systems are inherently dynamic and heterogeneous. Detection limits for mtDNA sequencing technologies differ among methods for low-level DNA sequence admixtures in healthy and diseased states. Performance metrics of analytical mtDNA technology should be validated prior to application in heterogeneous biologically-based systems. Critical in evaluating biomarker performance is the ability to distinguish measurement system variance from inherent biological variance, because it is within the latter that background healthy variability as well as high-value, disease-specific information reside.