Validation Strategy for Ultrasensitive Mutation Detection

Background: Ultrasensitive detection of low-abundance DNA point mutations is a challenging molecular biology problem, because nearly identical mutant and wild-type molecules exhibit crosstalk. Reliable ultrasensitive point mutation detection will facilitate early detection of cancer and therapeutic monitoring of cancer patients. Objective: The objective of this study was to develop a method to correct errors in low-level cell line mixes. Materials and Methods: We tested sample mixes with digital-droplet PCR (ddPCR) and next-generation sequencing. Results: We introduced two corrections: baseline variant allele frequency (VAF) in the parental cell line was used to correct for copy number variation; and haplotype counting was used to correct errors in cell counting and pipetting. We found ddPCR to have better correlation for detecting low-level mutations without applying any correction (R² = 0.80) and be more linear after introducing both corrections (R² = 0.99). Conclusions: The VAF correction was found to be more significant than haplotype correction. It is imperative that various technologies be evaluated against each other and laboratories be provided with defined quality control samples for proficiency testing.