Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes

<div><p>Background</p><p>Carriers of mutations in hereditary cancer predisposition genes represent a small but clinically important subgroup of oncology patients. The identification of causal germline mutations determines follow-up management, treatment options and genetic counselling in patients’ families. Targeted next-generation sequencing-based analyses using cancer-specific panels in high-risk individuals have been rapidly adopted by diagnostic laboratories. While the use of diagnosis-specific panels is straightforward in typical cases, individuals with unusual phenotypes from families with overlapping criteria require multiple panel testing. Moreover, narrow gene panels are limited by our currently incomplete knowledge about possible genetic dispositions.</p><p>Methods</p><p>We have designed a multi-gene panel called CZECANCA (CZEch CAncer paNel for Clinical Application) for a sequencing analysis of 219 cancer-susceptibility and candidate predisposition genes associated with frequent hereditary cancers.</p><p>Results</p><p>The bioanalytical and bioinformatics pipeline was validated on a set of internal and commercially available DNA controls showing high coverage uniformity, sensitivity, specificity and accuracy. The panel demonstrates a reliable detection of both single nucleotide and copy number variants. Inter-laboratory, intra- and inter-run replicates confirmed the robustness of our approach.</p><p>Conclusion</p><p>The objective of CZECANCA is a nationwide consolidation of cancer-predisposition genetic testing across various clinical indications with savings in costs, human labor and turnaround time. Moreover, the unified diagnostics will enable the integration and analysis of genotypes with associated phenotypes in a national database improving the clinical interpretation of variants.</p></div

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 7

<p><b>Comparison of variant detection (shown as values of variant allelic fraction; AF) in DNA reference standards</b> (NA12878, NA24149, NA24385, NA24631 and NA24143) obtained from CZECANCA analysis (x-axis) and AF from VCF files for these standards downloaded from <a href="http://jimb.stanford.edu/giab/" target="_blank">http://jimb.stanford.edu/giab/</a> (y-axis). The graph shows all variants with GATK quality >100 reached in CZECANCA analysis (including FP variants) and undetected (FN) variants. Heterozygote variants clustered in the center, while homozygote variants in right upper corner. Variant distribution was partially influenced by the differences in mean sequencing coverage targeting 100X and 300X in CZECANCA and DNA reference standards VCFs, respectively. The number of TP, TN, FP, FN, and total number of variant (= CZECANCA target) was used to calculate of sensitivity, specificity, and accuracy of CZECANCA analysis.</p

Identification of c.661_662delinsTA double substitution (p.Val221*) in <i>PALB2</i> (NM_024675).

<p>The BAM file displayed in IGV shows the <i>cis</i>-position of both substitutions in approximately 50% of forward (pink bars) and reverse (blue bars) reads, respectively.</p

Coverage (y-axis) of coding sequences (x-axis) of 219 CZECANCA target genes from a routine, randomly selected run targeting 100X coverage.

<p>Note: Fully covered genes are depicted in green letters, genes with coverage <20X in a single exon are in orange letters, and genes with uncovered regions exceeding single exon or >10% of coding sequence are in red letters. Green horizontal bars (below individual graphs constructed using “Boudalyzer” script) indicate coverage ≥ 20X; red horizontal bars indicate regions covered <20X and uncovered regions.</p

CNV detection is influenced by a DNA preparation method.

<p>Panels show analyses of remaining ACMG genes (not shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.g005" target="_blank">Fig 5B and 5C</a>) from four runs performed in laboratory 1 (116 DNA samples fragmented by ultrasound) and laboratory 3 (125 DNA samples fragmented enzymatically). The numbers in parentheses express number of samples with possible CNVs from all analyzed samples in contributing laboratories. *indicate samples analyzed by MLPA negatively (FP–black) or positively (TP–red). Bin set covering exon 1 in <i>RET</i> was excluded from the analysis due to the large coverage variability.</p

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 4

<p><b>Analysis of intra-run (A), inter-run (B), and inter-laboratory (C) replicates.</b> The panels show sequencing coverages (y-axis) of the identified variants arranged according to chromosomal localizations (x-axis). We used moving average curves (average of 3 values) to compare trends in coverages. Panel (A) describes the results of an analysis of three independently processed intra-run replicates from an identical DNA sample pooled in 33 ng (considered as 100%), 24.75 ng (75%), and 16.5 ng (50%), respectively. Panel (B) demonstrates variant coverages identified in two independent inter-run (run 8 and 14) replicates. All coverage values of sample #3647 in run 14 were corrected by a factor of 1.3880 to normalize coverages between samples (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.s004" target="_blank">S4 Table</a>). Panel (C) shows coverages of variants identified in an inter-laboratory control sequenced in four laboratories (Lab) participating in panel validation (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195761#pone.0195761.s005" target="_blank">S5 Table</a>). The coverages of variants identified in Lab 2, 3, and 4 were normalized to the average coverage of Lab 1 for better comparisons of coverages.</p

Validation of CZECANCA (CZEch CAncer paNel for Clinical Application) for targeted NGS-based analysis of hereditary cancer syndromes - Fig 3

<p><b>Coverage of selected genes from the CZECANCA (A-E) and TruSight Cancer sequencing (F) panels.</b> The pictures show coverage (at y-axis) alongside the coding sequences of <i>BRCA1</i> (NM_007294), <i>BRCA2</i> (NM_000059), <i>PALB2</i> (NM_024675), and <i>TP53</i> (NM_000546), the vertical lines represent exon boundaries. Panels A–D show results obtained from a CZECANCA NGS analysis of various samples performed in four participating laboratories using the ultrasound (A, B) or enzymatic (C, D) DNA fragmentation protocol. Examples of the identified CNV aberrations in the depicted genes (deletions in <i>BRCA1</i>, <i>BRCA2</i> and <i>TP53</i> and duplication in <i>PALB2</i>) are shown in panel E. For comparison, panel F demonstrates the uneven coverage of the depicted genes by sequencing using the TruSight Cancer panel (Illumina).</p

Multigene Panel Germline Testing of 1333 Czech Patients with Ovarian Cancer

Ovarian cancer (OC) is the deadliest gynecologic malignancy with a substantial proportion of hereditary cases and a frequent association with breast cancer (BC). Genetic testing facilitates treatment and preventive strategies reducing OC mortality in mutation carriers. However, the prevalence of germline mutations varies among populations and many rarely mutated OC predisposition genes remain to be identified. We aimed to analyze 219 genes in 1333 Czech OC patients and 2278 population-matched controls using next-generation sequencing. We revealed germline mutations in 18 OC/BC predisposition genes in 32.0% of patients and in 2.5% of controls. Mutations in BRCA1/BRCA2, RAD51C/RAD51D, BARD1, and mismatch repair genes conferred high OC risk (OR &gt; 5). Mutations in BRIP1 and NBN were associated with moderate risk (both OR = 3.5). BRCA1/2 mutations dominated in almost all clinicopathological subgroups including sporadic borderline tumors of ovary (BTO). Analysis of remaining 201 genes revealed somatic mosaics in PPM1D and germline mutations in SHPRH and NAT1 associating with a high/moderate OC risk significantly; however, further studies are warranted to delineate their contribution to OC development in other populations. Our findings demonstrate the high proportion of patients with hereditary OC in Slavic population justifying genetic testing in all patients with OC, including BTO

ENIGMA CHEK2gether Project : a comprehensive study identifies functionally impaired CHEK2 germline missense variants associated with increased breast cancer risk

Purpose: Germline pathogenic variants in CHEK2 confer moderately elevated breast cancer risk (odds ratio, OR ∼ 2.5), qualifying carriers for enhanced breast cancer screening. Besides pathogenic variants, dozens of missense CHEK2 variants of uncertain significance (VUS) have been identified, hampering the clinical utility of germline genetic testing (GGT). Experimental Design: We collected 460 CHEK2 missense VUS identified by the ENIGMA consortium in 15 countries. Their functional characterization was performed using CHEK2-complementation assays quantifying KAP1 phosphorylation and CHK2 autophosphorylation in human RPE1–CHEK2-knockout cells. Concordant results in both functional assays were used to categorize CHEK2 VUS from 12 ENIGMA case–control datasets, including 73,048 female patients with breast cancer and 88,658 ethnicity-matched controls. Results: A total of 430/460 VUS were successfully analyzed, of which 340 (79.1%) were concordant in both functional assays and categorized as functionally impaired (N = 102), functionally intermediate (N = 12), or functionally wild-type (WT)–like (N = 226). We then examined their association with breast cancer risk in the case–control analysis. The OR and 95% CI (confidence intervals) for carriers of functionally impaired, intermediate, and WT-like variants were 2.83 (95% CI, 2.35–3.41), 1.57 (95% CI, 1.41–1.75), and 1.19 (95% CI, 1.08–1.31), respectively. The meta-analysis of population-specific datasets showed similar results. Conclusions: We determined the functional consequences for the majority of CHEK2 missense VUS found in patients with breast cancer (3,660/4,436; 82.5%). Carriers of functionally impaired missense variants accounted for 0.5% of patients with breast cancer and were associated with a moderate risk similar to that of truncating CHEK2 variants. In contrast, 2.2% of all patients with breast cancer carried functionally wild-type/intermediate missense variants with no clinically relevant breast cancer risk in heterozygous carriers