Abstract

Introduction Malignant myeloid diseases are a group of blood cancers that arise from genetic changes in hematopoietic cells in the bone marrow or peripheral blood. The presence of measurable residual disease (MRD), or detection of abnormal cells in the body following completion of therapy, is associated with a higher risk of disease relapse, and decreased overall survival (Schuurhuis 2018). Next-generation sequencing (NGS) can be leveraged as a high-sensitivity, minimally invasive method for detection of MRD. The Ion Torrent Oncomine Myeloid MRD Assay (Myeloid MRD) is a targeted NGS assay designed for the detection of single nucleotide variants (SNVs) and insertions/deletions in a curated selection of clinically relevant myeloid disease-related genes at low limits of detection. Assay performance was evaluated using normal and diseased clinical blood and bone marrow samples and NGS reference materials. Methods The Myeloid MRD DNA panel targets hotspot regions across 33 genes and uses Ion AmpliSeq HD technology with unique molecular tagging to suppress sequencing artifacts and improve analytical sensitivity. Briefly, DNA was extracted from whole blood or bone marrow samples and 120 ng of nucleic acid was used as input for the assay. The DNA was divided between 2 polymerase chain reactions (PCR), where it served as the template for target amplifications, before combining reaction products by sample. Library preparation followed the standard Ion AmpliSeq HD protocol, where amplicons were partially enzymatically digested, and a second round of amplification was performed using barcoded primers. Following bead purification, the final library was measured by quantitative PCR (qPCR) to inform final library loading onto the sequencer. Six libraries were pooled and sequenced on an Ion 550 chip using the Ion GeneStudio S5 System. Primary and secondary analyses were performed using the Torrent Suite software, and results were exported to the Ion Reporter software for variant calling. From the variant calling results, a probit model was utilized to determine the variant allele frequency (VAF) at which the assay achieved 90% power to call an expected variant, defining the limit of detection (LoD). Other parameters evaluated included analytical sensitivity, analytical specificity, positive predictive value (PPV), accuracy, and precision. Results Overall, consistent, high quality on-target reads were observed across 22 sequencing runs with a median Ion Sphere Particle (ISP) loading of 90%, usable sequence of 59%, and over 130 million total reads per chip. When evaluating individual samples according to the vendor-recommended number of mapped reads (> 10 million), 98.3% of samples tested passed quality control (QC). Additional sample QC metrics established during assay validation included thresholds of > 80% reads on-target, > 80% uniformity of base coverage, and a mean read length of at least 80 base pairs. The estimated LoD for the assay was 0.1% VAF for small variants (SNVs, insertions/deletions).Above the LoD, the assay demonstrated 96.03% sensitivity, 99.89% accuracy of base-calling, 100% specificity, and 98.83% PPV.Additionally,a comparison was performed usingmatched whole blood and bone marrow samples collected from patients with acute myeloid leukemia (AML) to evaluate the concordance of variant calling. It was determined that the same variants were identified across both sample types, although at higher allele frequency in bone marrow compared to whole blood. Conclusion This evaluation of the Myeloid MRD assay demonstrates that it is a precise and accurate assay with sensitivity that is acceptable for MRD analysis. Notably, variant detection was concordant between whole blood and bone marrow sample types collected from AML patients, with bone marrow providing improved sensitivity for low-frequency variant detection. The user-friendly workflow and integrated informatics pipeline offer opportunities for streamlined testing and interpretation of results. The Ion Torrent Myeloid MRD DNA assay is a powerful new tool for MRD detection across a growing myeloid disease target landscape.

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