ABSTRACT
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.
Subject(s)
DNA Mutational Analysis , Mutation , DNA Mutational Analysis/methods , HLA-A Antigens/genetics , Haplotypes , Humans , Polymerase Chain Reaction/methods , Polymorphism, Single Nucleotide , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
OBJECTIVES: To validate next-generation sequencing (NGS) technology for clinical diagnosis and to determine appropriate read depth. METHODS: We validated the KRAS, BRAF, and EGFR genes within the Ion AmpliSeq Cancer Hotspot Panel using the Ion Torrent Personal Genome Machine (Life Technologies, Carlsbad, CA). RESULTS: We developed a statistical model to determine the read depth needed for a given percent tumor cellularity and number of functional genomes. Bottlenecking can result from too few input genomes. By using 16 formalin-fixed, paraffin-embedded (FFPE) cancer-free specimens and 118 cancer specimens with known mutation status, we validated the six traditional analytic performance characteristics recommended by the Next-Generation Sequencing: Standardization of Clinical Testing Working Group. Baseline noise is consistent with spontaneous and FFPE-induced C:GâT:A deamination mutations. CONCLUSIONS: Redundant bioinformatic pipelines are essential, since a single analysis pipeline gave false-negative and false-positive results. NGS is sufficiently robust for the clinical detection of gene mutations, with attention to potential artifacts.
