Rational "Error Elimination" Approach to Evaluating Molecular Barcoded Next-Generation Sequencing Data Identifies Low-Frequency Mutations in Hematologic Malignancies

Abstract

The emergence of highly sensitive molecular diagnostic approaches, such as droplet digital PCR, has allowed the accurate identification of low-frequency variant alleles in clinical specimens; however, the multiplex capabilities of droplet digital PCR for variant detection are inadequate. The incorporation of molecular barcodes or unique IDs into next-generation sequencing libraries through PCR has enabled the detection of low-frequency variant alleles across multiple genomic regions. However, rational library preparation and sequencing data analytic strategies that integrate molecular barcodes have rarely been applied to clinical settings. In this study, we evaluated the parameters that are crucial in the use of molecular barcodes in next-generation sequencing for genotyping clinical specimens from patients with hematologic malignancies. The uniform incorporation of molecular barcodes into DNA templates through PCR was found to be crucial, and the extent of uniformity was governed by multiple interdependent variables. An error elimination strategy was developed for removing sequencing background errors by using molecular barcode sequence information as an alternative to the conventional error correction approach. This approach was successfully used to identify mutations with frequencies as low as 0.15%, and the clonal heterogeneity of hematologic malignancies was revealed. These findings have implications for elucidating heterogeneity and temporal and spatial clonal evolution, evaluating response to therapy, and monitoring relapse in patients with hematologic malignancies.