The objective of this study was to design and validate a next-generation sequencing assay (NGS) to detect BRCA1 and BRCA2 mutations. We developed an assay using random shearing of genomic DNA ...followed by RNA bait tile hybridization and NGS sequencing on both the Illumina MiSeq and Ion Personal Gene Machine (PGM). We determined that the MiSeq Reporter software supplied with the instrument could not detect deletions greater than 9 base pairs. Therefore, we developed an alternative alignment and variant calling software, Quest Sequencing Analysis Pipeline (QSAP), that was capable of detecting large deletions and insertions. In validation studies, we used DNA from 27 stem cell lines, all with known deleterious BRCA1 or BRCA2 mutations, and DNA from 67 consented control individuals who had a total of 352 benign variants. Both the MiSeq/QSAP combination and PGM/Torrent Suite combination had 100% sensitivity for the 379 known variants in the validation series. However, the PGM/Torrent Suite combination had a lower intra- and inter-assay precision of 96.2% and 96.7%, respectively when compared to the MiSeq/QSAP combination of 100% and 99.4%, respectively. All PGM/Torrent Suite inconsistencies were false-positive variant assignments. We began commercial testing using both platforms and in the first 521 clinical samples MiSeq/QSAP had 100% sensitivity for BRCA1/2 variants, including a 64-bp deletion and a 10-bp insertion not identified by PGM/Torrent Suite, which also suffered from a high false-positive rate. Neither the MiSeq nor PGM platform with their supplied alignment and variant calling software are appropriate for a clinical laboratory BRCA sequencing test. We have developed an NGS BRCA1/2 sequencing assay, MiSeq/QSAP, with 100% analytic sensitivity and specificity in the validation set consisting of 379 variants. The MiSeq/QSAP combination has sufficient performance for use in a clinical laboratory.
ABSTRACT
We developed a rules‐based scoring system to classify DNA variants into five categories including pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, and ...benign. Over 16,500 pathogenicity assessments on 11,894 variants from 338 genes were analyzed for pathogenicity based on prediction tools, population frequency, co‐occurrence, segregation, and functional studies collected from internal and external sources. Scores were calculated by trained scientists using a quantitative framework that assigned differential weighting to these five types of data. We performed descriptive and comparative statistics on the dataset and tested interobserver concordance among the trained scientists. Private variants defined as variants found within single families (n = 5,182), were either VUS (80.5%; n = 4,169) or likely pathogenic (19.5%; n = 1,013). The remaining variants (n = 6,712) were VUS (38.4%; n = 2,577) or likely benign/benign (34.7%; n = 2,327) or likely pathogenic/pathogenic (26.9%, n = 1,808). Exact agreement between the trained scientists on the final variant score was 98.5% 95% confidence interval (CI) (98.0, 98.9) with an interobserver consistency of 97% 95% CI (91.5, 99.4). Variant scores were stable and showed increasing odds of being in agreement with new data when re‐evaluated periodically. This carefully curated, standardized variant pathogenicity scoring system provides reliable pathogenicity scores for DNA variants encountered in a clinical laboratory setting.
The article by Karbassi et al. describes a standardized DNA variant scoring system that uses multiple lines of evidence, three subclasses of VUS, technical training procedures, and weighted rules‐based scoring to produce reliable and consistent clinical grade variant interpretations. This carefully curated scoring system provides the first roadmap to accurately process complex genetic information in diagnostics.
Identification of genomic mutations by molecular testing plays an important role in diagnosis, prognosis, and treatment of myeloid neoplasms. Next-generation sequencing (NGS) is an efficient method ...for simultaneous detection of clinically significant genomic mutations with high sensitivity. Various NGS based in-house developed and commercial myeloid neoplasm panels have been integrated into routine clinical practice. However, some genes frequently mutated in myeloid malignancies are particularly difficult to sequence with NGS panels (e.g., CEBPA, CARL, and FLT3). We report development and validation of a 48-gene NGS panel that includes genes that are technically challenging for molecular profiling of myeloid neoplasms including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Target regions were captured by hybridization with complementary biotinylated DNA baits, and NGS was performed on an Illumina NextSeq500 instrument. A bioinformatics pipeline that was developed in-house was used to detect single nucleotide variations (SNVs), insertions/deletions (indels), and FLT3 internal tandem duplications (FLT3-ITD). An analytical validation study was performed on 184 unique specimens for variants with allele frequencies ≥5%. Variants identified by the 48-gene panel were compared to those identified by a 35-gene hematologic neoplasms panel using an additional 137 unique specimens. The developed assay was applied to a large cohort (n = 2,053) of patients with suspected myeloid neoplasms. Analytical validation yielded 99.6% sensitivity (95% CI: 98.9-99.9%) and 100% specificity (95% CI: 100%). Concordance of variants detected by the 2 tested panels was 100%. Among patients with suspected myeloid neoplasms (n = 2,053), 54.5% patients harbored at least one clinically significant mutation: 77% in AML patients, 48% in MDS, and 45% in MPN. Together, these findings demonstrate that the assay can identify mutations associated with diagnosis, prognosis, and treatment options of myeloid neoplasms even in technically challenging genes.
We report the frequency, positive rate, and type of mutations in 14 genes (PMP22, GJB1, MPZ, MFN2, SH3TC2, GDAP1, NEFL, LITAF, GARS, HSPB1, FIG4, EGR2, PRX, and RAB7A) associated with ...Charcot–Marie–Tooth disease (CMT) in a cohort of 17,880 individuals referred to a commercial genetic testing laboratory. Deidentified results from sequencing assays and multiplex ligation‐dependent probe amplification (MLPA) were analyzed including 100,102 Sanger sequencing, 2338 next‐generation sequencing (NGS), and 21,990 MLPA assays. Genetic abnormalities were identified in 18.5% (n = 3312) of all individuals. Testing by Sanger and MLPA (n = 3216) showed that duplications (dup) (56.7%) or deletions (del) (21.9%) in the PMP22 gene accounted for the majority of positive findings followed by mutations in the GJB1 (6.7%), MPZ (5.3%), and MFN2 (4.3%) genes. GJB1 del and mutations in the remaining genes explained 5.3% of the abnormalities. Pathogenic mutations were distributed as follows: missense (70.6%), nonsense (14.3%), frameshift (8.7%), splicing (3.3%), in‐frame deletions/insertions (1.8%), initiator methionine mutations (0.8%), and nonstop changes (0.5%). Mutation frequencies, positive rates, and the types of mutations were similar between tests performed by either Sanger (n = 17,377) or NGS (n = 503). Among patients with a positive genetic finding in a CMT‐related gene, 94.9% were positive in one of four genes (PMP22, GJB1, MPZ, or MFN2).
In a testing cohort of 17,880 individuals, we report that duplications (dup) (56.7%) or deletions (del) (21.9%) in the PMP22 gene accounted for the majority of positive findings followed by mutations in the GJB1 (6.7%), MPZ (5.3%), and MFN2 (4.3%) genes.
We evaluated performance characteristics of a laboratory-developed, non-invasive prenatal screening (NIPS) assay for fetal aneuploidies. This assay employs massively parallel shotgun sequencing with ...full automation. GC sequencing bias correction and statistical smoothing were performed to enhance discrimination of affected and unaffected pregnancies. Maternal plasma samples from pregnancies with known aneuploidy status were used for assay development, verification, and validation. Assay verification studies using 2,085 known samples (1873 unaffected, 69 trisomy 21, 20 trisomy 18, 17 trisomy 13) demonstrated complete discrimination between autosomal trisomy (Z scores >8) and unaffected (Z scores <4) singleton pregnancies. A validation study using 552 known samples (21 trisomy 21, 10 trisomy 18, 1 trisomy 13) confirmed complete discrimination. Twin pregnancies showed similar results. Follow-up of abnormal results from the first 10,000 clinical samples demonstrated PPVs of 98% (41/42) for trisomy 21, 92% (23/25) for trisomy 18, and 69% (9/13) for trisomy 13. Adjustment for causes of false-positive results identified during clinical testing (eg, maternal duplications) improved PPVs to 100% for trisomy 21 and 96% for trisomy 18. This NIPS test demonstrates excellent discrimination between trisomic and unaffected pregnancies. The PPVs obtained in initial clinical testing are substantially higher than previously reported NIPS methods.
ABSTRACT
As next‐generation sequencing increases access to human genetic variation, the challenge of determining clinical significance of variants becomes ever more acute. Germline variants in the ...BRCA1 and BRCA2 genes can confer substantial lifetime risk of breast and ovarian cancer. Assessment of variant pathogenicity is a vital part of clinical genetic testing for these genes. A database of clinical observations of BRCA variants is a critical resource in that process. This article describes BRCA Share™, a database created by a unique international alliance of academic centers and commercial testing laboratories. By integrating the content of the Universal Mutation Database generated by the French Unicancer Genetic Group with the testing results of two large commercial laboratories, Quest Diagnostics and Laboratory Corporation of America (LabCorp), BRCA Share™ has assembled one of the largest publicly accessible collections of BRCA variants currently available. Although access is available to academic researchers without charge, commercial participants in the project are required to pay a support fee and contribute their data. The fees fund the ongoing curation effort, as well as planned experiments to functionally characterize variants of uncertain significance. BRCA Share™ databases can therefore be considered as models of successful data sharing between private companies and the academic world.
BRCA ShareTM is an international alliance of academic centers and commercial testing laboratories. By integrating content of the Universal Mutation Database generated by the French Unicancer Genetic Group with the testing results of Quest Diagnostics and Laboratory Corporation of America (LabCorp), BRCA ShareTM has assembled one of the largest publicly accessible collections of BRCA variants with over 6,200 variants currently available.
In addition, to funding high quality curation, BRCA ShareTM seeks to support functional studies, targeting variants of uncertain significance.
The use of genetic testing to identify individuals with hereditary cancer syndromes has been widely adopted by clinicians for management of inherited cancer risk. The objective of this study was to ...develop and validate a 34-gene inherited cancer predisposition panel using targeted capture-based next-generation sequencing (NGS). The panel incorporates genes underlying well-characterized cancer syndromes, such as BRCA1 and BRCA2 (BRCA1/2), along with more recently discovered genes associated with increased cancer risk. We performed a validation study on 133 unique specimens, including 33 with known variant status; known variants included single nucleotide variants (SNVs) and small insertions and deletions (Indels), as well as copy-number variants (CNVs). The analytical validation study achieved 100% sensitivity and specificity for SNVs and small Indels, with 100% sensitivity and 98.0% specificity for CNVs using in-house developed CNV flagging algorithm. We employed a microarray comparative genomic hybridization (aCGH) method for all specimens that the algorithm flags as CNV-positive for confirmation. In combination with aCGH confirmation, CNV detection specificity improved to 100%. We additionally report results of the first 500 consecutive specimens submitted for clinical testing with the 34-gene panel, identifying 53 deleterious variants in 13 genes in 49 individuals. Half of the detected pathogenic/likely pathogenic variants were found in BRCA1 (23%), BRCA2 (23%), or the Lynch syndrome-associated genes PMS2 (4%) and MLH1 (2%). The other half were detected in 9 other genes: MUTYH (17%), CHEK2 (15%), ATM (4%), PALB2 (4%), BARD1 (2%), CDH1 (2%), CDKN2A (2%), RAD51C (2%), and RET (2%). Our validation studies and initial clinical data demonstrate that a 34-gene inherited cancer predisposition panel can provide clinically significant information for cancer risk assessment.
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