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.

Amplicon-based targeted next-generation sequencing assays are used widely to test for clinically relevant somatic mutations in cancer. However, accurate detection of large insertions and deletions (indels) via these assays remains challenging. Sequencing reads that cover these anomalies are, by definition, different from the reference sequence, and lead to variable performance of alignment algorithms. Reads with large indels may be aligned incorrectly, causing incorrect calls, or may remain unmapped and essentially ignored by downstream informatics pipeline sub-processes. Herein, we describe Amplicon Indel Hunter (AIH), a novel large (>5-bp) indel detection method that is reference genome independent and highly sensitive for the identification of somatic indels in amplicon-based, paired-end, next-generation sequencing data. We validated the algorithm for sensitivity and specificity using a set of clinical cancer samples with Clinical Laboratory Improvement Amendment-confirmed indels as well as in silico mutated data sets. The AIH detected 100% of tested large indels with relatively higher mutant allele frequencies compared with a variety of traditional aligners, which showed variably reduced sensitivity and specificity by comparison. The AIH especially outperformed alignment-based methods for detection of all tested FLT3 internal tandem duplications up to 102 bp. Because AIH runs in parallel to traditional alignment-based informatics pathways, it can be readily incorporated into nearly any analysis pipeline for somatic mutation detection in paired-end amplicon-based data.

- The morphologic similarity and RAS mutations in FAs, NIFTPs, and IE-PTC-FVs supports the genetic similarity of those follicular neoplasms in contrast to the unique presence of BRAF V600E mutations in PTC-EFGs. Using strict diagnostic criteria supported by molecular testing, tumors with extensive follicular growth can be classified into follicular type or RAS-like (FA, NIFTP, IE-PTC-FV) versus papillary type or BRAF V600E-like (PTC-EFG).

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