Validation of a next-generation sequencing assay for clinical molecular oncology

Abstract

Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancer-associated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (≥ 1000× average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI = 83.4-100.0 for sensitivity and 94.2-100.0 for specificity) or whole-genome sequencing (95% CI = 89.1-100.0 for sensitivity and 99.9-100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI = 93.2-100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of ≥ 15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management.

Figure 1

The Washington University Cancer Mutation Profiling (WUCaMP) gene set includes NGS analysis of 25 genes with relevance across multiple tumor types. As supplements to the set, ALK and MLL are assessed by FISH for rearrangements. The choice of genes for the set was based on direct clinical actionability of the target mutations, as determined by consensus between pathologists and oncologists at our institution.

Figure 2

Schematic view of the WUCaMP assay workflow. DNA is extracted from tumor tissue (1) derived from fresh or FFPE specimens and fragmented by sonication (2). Libraries are prepared and amplified via limited-cycle PCR (3) and enriched for WUCaMP genes by fluid phase hybridization to custom cRNA capture reagents (4). The hybridized product is amplified (5) and sequenced on an Illumina HiSeq 2000 or Illumina MiSeq instrument (6). Paired-end reads are aligned to the genome (7), PCR duplicates are removed (8), and variant calls are made (9). Variants are annotated and classified by our internally developed CGW application, using publicly available and proprietary databases, and the case is reviewed and interpreted by a clinical genomicist for sign-out in CGW (10). A report is then issued to the medical record (11).

Figure 3

Distribution of unique coverage depth across the full WUCaMP capture region. The percentage of targeted WUCaMP positions (including both coding and flanking intronic sequence) that achieve unique coverage depth on the HiSeq instrument greater than or equal to that shown on the x axis is plotted. Rectangles (dashed lines) indicate the unique coverage depth achieved at 95% of positions and at 50% of positions (median unique coverage). On the y-axis scale, 1.0 indicates 100%.

Figure 4

Distribution of unique coverage depth across the 25 genes in the WUCaMP panel. Unique coverage data across 119 validation tumor specimen data sets from HiSeq sequencing are plotted by gene. Each box represents the interquartile range, with the midline as the median unique coverage; whiskers represent exon coverage for a given sequencing run within 2 SD of the median. Outlier exons for a sequencing run are plotted as independent dots.

Figure 5

Distribution of unique coverage depth across exons in JAK2, one gene of the WUCaMP panel. Unique coverage data across 119 validation tumor specimen data sets from HiSeq sequencing are plotted by exon. Box–whisker plots are defined as for Figure 4, except that unique coverage level is considered by position rather than averaged across an exon. The red horizontal line near the x axis indicates 50× unique coverage. JAK2 coverage was slightly below average, relative to other WUCaMP genes (data not shown).

Figure 6

Low VAF detection. For all target regions (top row) and for coding regions only (bottom row), sensitivity, false positives, and PPV are presented for one sample with a 50% mix proportion and a second sample with a 20% mix proportion. Error bars indicate the 95% binomial confidence interval for each point estimate. Top row: n = 109 variants (50% mix); n = 95 variants (20% mix). Bottom row: n = 11 variants (50% mix); n = 14 variants (20% mix). PPV = TP/(TP+FP).

Figure 7

Sensitivity for low VAF detection as a function of coverage depth. Synthetic mixed samples were generated from two individual HapMap samples in silico, with mix proportions of 50%, 20%, 10%, and 2% and mean coverage levels across the entire target region of 1000×, 750×, 500×, and 250×. Each mixed sample had 95 heterozygous variants unique to the minor sample present at mean observed VAFs of 23.8%, 10.6%, 5.8%, and 1.1%, respectively. Data indicate the sensitivity (percent detected) for variants with observed coverage in bins of 100. Error bars indicate the 95% binomial confidence interval for each point estimate.