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Updated: Mar 12, 2026

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Clinical Validation of a Next-Generation Sequencing Genomic Oncology Panel via Cross-Platform Benchmarking against
Sabah Kadri1, Bradley C Long1, Ibro Mujacic1
1Division of Genomic and Molecular Pathology, The University of Chicago, Chicago, Illinois.
Abstract:
Next-generation sequencing (NGS) genomic oncology profiling assays have emerged as key drivers of personalized cancer care and translational research. However, validation of these assays to meet strict clinical standards has been historically problematic because of both significant assay complexity and a scarcity of optimal validation samples. Herein, we present the clinical validation of 76 genes from a novel 1212-gene large-scale hybrid capture cancer sequencing assay (University of Chicago Medicine OncoPlus) using full-data comparisons against multiple clinical NGS amplicon-based assays to yield dramatic increases in per-sample data comparison efficiency compared with previously published validations. Using a sample set of 104 normal, solid tumor, and hematopoietic malignancy specimens, head-to-head NGS data analyses allowed for 6.8 million individual clinical base call comparisons, including 2729 previously confirmed variants, with 100% sensitivity and specificity. University of Chicago Medicine OncoPlus showed excellent performance for detection of single-nucleotide variants, insertions/deletions up to 52 bp, and FLT3 internal tandem duplications of up to 102 bp or larger. Highly concordant copy number variant and ALK/RET/ROS1 gene fusion detection were also observed. In addition to underlining the efficiency of NGS validation via full-data benchmarking against existing clinical NGS assays, this study also highlights the degree of performance similarity between hybrid capture and amplicon assays that is attainable with the application of strict quality control parameters and optimized computational analytics.
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