June 1, 2021

Highly sensitive and cost-effective detection of somatic cancer variants using single-molecule, real-time sequencing

Author(s): Sethuraman, Anand and Eng, Kevin and Baybayan, Primo and Heyrman, Lien and Del Favero, Jurgen and Huang, Catherine and Anakella, Bharathi and Kujawa, Steve

Next-Generation Sequencing (NGS) technologies allow for molecular profiling of cancer samples with high sensitivity and speed at reduced cost. For efficient profiling of cancer samples, it is important that the NGS methods used are not only robust, but capable of accurately detecting low-frequency somatic mutations. Single Molecule, Real-Time (SMRT) Sequencing offers several advantages, including the ability to sequence single molecules with very high accuracy (>QV40) using the circular consensus sequencing (CCS) approach. The availability of genetically defined, human genomic reference standards provides an industry standard for the development and quality control of molecular assays for studying cancer variants. Here we characterize SMRT Sequencing for the detection of low-frequency somatic variants using the Quantitative Multiplex DNA Reference Standards from Horizon Discovery, combined with amplification of the variants using the Multiplicom Tumor Hotspot MASTR Plus assay. First, we sequenced a reference standard containing precise allelic frequencies from 1% to 24.5% for major oncology targets verified using digital PCR. This reference material recapitulates the complexity of tumor composition and serves as a well-characterized control. The control sample was amplified using the Multiplicom Tumor Hotspot MASTR Plus assay that targets 252 amplicons (121-254 bp) from 26 relevant cancer genes, which includes all 11 variants in the control sample. Next, we sequenced control samples prepared by SeraCare Life Sciences, which contained a defined mutation at allelic frequencies from 10% down to 0.1%. The wild type and mutant amplicons were serially diluted, sequenced and analyzed using SMRT Sequencing to identify the variants and determine the observed frequency. The random error profile and high-accuracy CCS reads make it possible to accurately detect low-frequency somatic variants.

Organization: PacBio
Year: 2016

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