Evaluation of Hybridization Capture Versus Amplicon-Based Methods for Whole-Exome Sequencing.

Next-generation sequencing has aided characterization of genomic variation. While whole-genome sequencing may capture all possible mutations, whole-exome sequencing remains cost-effective and captures most phenotype-altering mutations. Initial strategies for exome enrichment utilized a hybridization-based capture approach. Recently, amplicon-based methods were designed to simplify preparation and utilize smaller DNA inputs. We evaluated two hybridization capture-based and two amplicon-based whole-exome sequencing approaches, utilizing both Illumina and Ion Torrent sequencers, comparing on-target alignment, uniformity, and variant calling. While the amplicon methods had higher on-target rates, the hybridization capture-based approaches demonstrated better uniformity. All methods identified many of the same single-nucleotide variants, but each amplicon-based method missed variants detected by the other three methods and reported additional variants discordant with all three other technologies. Many of these potential false positives or negatives appear to result from limited coverage, low variant frequency, vicinity to read starts/ends, or the need for platform-specific variant calling algorithms. All methods demonstrated effective copy-number variant calling when evaluated against a single-nucleotide polymorphism array. This study illustrates some differences between whole-exome sequencing approaches, highlights the need for selecting appropriate variant calling based on capture method, and will aid laboratories in selecting their preferred approach.

Analytic validation and real-time clinical application of an amplicon-based targeted gene panel for advanced cancer.

Multiplex somatic testing has emerged as a strategy to test patients with advanced cancer. We demonstrate our analytic validation approach for a gene hotspot panel and real-time prospective clinical application for any cancer type. The TruSight Tumor 26 assay amplifies 85 somatic hotspot regions across 26 genes. Using cell line and tumor mixes, we observed that 100% of the 14,715 targeted bases had at least 1000x raw coverage. We determined the sensitivity (100%, 95% CI: 96-100%), positive predictive value (100%, 95% CI: 96-100%), reproducibility (100% concordance), and limit of detection (3% variant allele frequency at 1000x read depth) of this assay to detect single nucleotide variants and small insertions and deletions. Next, we applied the assay prospectively in a clinical tumor sequencing study to evaluate 174 patients with metastatic or advanced cancer, including frozen tumors, formalin-fixed tumors, and enriched peripheral blood mononuclear cells in hematologic cancers. We reported one or more somatic mutations in 89 (53%) of the sequenced tumors (167 passing quality filters). Forty-three of these patients (26%) had mutations that would enable eligibility for targeted therapies. This study demonstrates the validity and feasibility of applying TruSight Tumor 26 for pan-cancer testing using multiple specimen types.

Comparison of custom capture for targeted next-generation DNA sequencing.

Targeted, capture-based DNA sequencing is a cost-effective method to focus sequencing on a coding region or other customized region of the genome. There are multiple targeted sequencing methods available, but none has been systematically investigated and compared. We evaluated four commercially available custom-targeted DNA technologies for next-generation sequencing with respect to on-target sequencing, uniformity, and ability to detect single-nucleotide variations (SNVs) and copy number variations. The technologies that used sonication for DNA fragmentation displayed impressive uniformity of capture, whereas the others had shorter preparation times, but sacrificed uniformity. One of those technologies, which uses transposase for DNA fragmentation, has a drawback requiring sample pooling, and the last one, which uses restriction enzymes, has a limitation depending on restriction enzyme digest sites. Although all technologies displayed some level of concordance for calling SNVs, the technologies that require restriction enzymes or transposase missed several SNVs largely because of the lack of coverage. All technologies performed well for copy number variation calling when compared to single-nucleotide polymorphism arrays. These results enable laboratories to compare these methods to make informed decisions for their intended applications.