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The expanded CAG repeat number in HTT gene causes Huntington disease (HD), which is a severe, dominant neurodegenerative illness. The accurate determination of the expanded allele size is crucial to confirm the genetic status in symptomatic and presymptomatic at-risk subjects and avoid genetic polymorphism-related false-negative diagnoses. Precise CAG repeat number determination is critical to discriminate the cutoff between unexpanded and intermediate mutable alleles (IAs, 27–35 CAG) as well as between IAs and pathological, low-penetrance alleles (i.e., 36–39 CAG repeats), and it is also critical to detect large repeat expansions causing pediatric HD variants. We analyzed the HTT-CAG repeat number of 14 DNA reference materials and of a DNA collection of 43 additional samples carrying unexpanded, IAs, low and complete penetrance alleles, including large (&gt, 60 repeats) and very large (&gt, 100 repeats) expansions using a novel triplet-primed PCR-based assay, the AmplideX PCR/CE HTT Kit. The results demonstrate that the method accurately genotypes both normal and expanded HTT-CAG repeat numbers and reveals previously undisclosed and very large CAG expansions &gt, 200 repeats. We also show that this technique can improve genetic test reliability and accuracy by detecting CAG expansions in samples with sequence variations within or adjacent to the repeat tract that cause allele drop-outs or inaccuracies using other PCR methods.

Introduction: Mutation analysis of circulating tumor DNA (ctDNA) in blood-based liquid biopsies provides a minimally invasive approach to detect and monitor disease. Existing next-generation sequencing (NGS) liquid biopsy techniques have laborious and/or inefficient workflows, heuristic error-correction algorithms, and variable performance with clinical tumor-plasma samples. We describe a method that combines a kittable and efficient wet-bench workflow with accurate dry-bench analytics to reduce costs and turnaround time, and is relevant to clinical research and patient testing. Methods: We developed a comprehensive, targeted NGS technology to enable the ultra-sensitive detection of variants from liquid biopsy samples. Input DNA molecules from Seraseq™ ctDNA v2 reference materials (SeraCare) and >50 matched FFPE and plasma samples were uniquely tagged with a random molecular barcode (MBC), amplified in an efficient PCR protocol, and sequenced using a targeted panel covering >500 somatic mutation hotspots. Sequence-ready libraries were prepared from input DNA within 9 hours. Data were analyzed with a robust bioinformatics pipeline tailored to the library chemistry to correct for multiple background errors. Variants were identified with a site-specific model, which effectively eliminated recurring non-biological aberrations that remained despite MBC-facilitated error-suppression. We verified variant calls in plasma by Droplet Digital™ PCR (Bio-Rad). To evaluate the limit of detection, healthy control and mutation-positive plasma admixtures were prepared and sequenced. Results: Input template molecules were efficiently recovered. The median number of unique MBCs across all amplicons was >90% of expectation based on input DNA quantities for both the tumor-associated plasma and Seraseq™ ctDNA v2 material. SNVs and indels were recognized with >90% sensitivity and PPV at 0.5% allele frequency (AF) in the Seraseq™ ctDNA mutation mixes. In both neat plasma samples and plasma admixtures, we correctly identified tumor mutations down to ~0.1% AF while maintaining a low false-positive rate (sensitivity and PPV remained high for AF ≥0.1%). Reference ctDNA material and tumor-associated plasma had analogous template amplification and variant frequency rates. Conclusions: A fast, efficient, and sensitive NGS panel approach was developed and evaluated, and it demonstrated the reliable and specific detection of rare variants in liquid biopsy specimens. The method is able to distinguish a low frequency ctDNA signal from the overwhelming background noise in plasma cell-free DNA using a streamlined workflow and purpose-built bioinformatics pipeline. This technology may provide an easy-to-use, high-performance, and adaptable NGS diagnostic framework for disease detection and therapeutic intervention monitoring. Citation Format: Jessica L. Larson, Liangjing Chen, Lando Ringel, Blake Printy, Farol L. Tomson, Yves Konigshofer, Sarah Statt, Joseph K. Kaplan, Shobha Gokul, Jeffrey Shelton, Gary J. Latham, Brian C. Haynes. A comprehensive, targeted next-generation sequencing method that rapidly and accurately detects circulating tumor DNA variants at 0.1% frequency in plasma samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5574.