The BRCA1 and BRCA2 genes epitomize the modern understanding of cancer molecular genetics. Today, identifying germline and somatic mutations in BRCA1/2 has become routine practice, especially for hereditary cancer studies. However, the highly-fragmented nature of traditional sample to insight workflows can make the identification and classification of all pathogenic and actionable variants in BRCA1/2 particularly challenging. In this webinar, we explore these challenges and present solutions for streamlined, standardized, and accurate detection, interpretation, and reporting of challenging BRCA mutations, such as exon-level copy number variants (CNVs), splicing variants, and variants in homopolymer regions.
In the first half of the webinar, we will introduce a fully-integrated Sample to Insight NGS clinical research workflow for the detection of BRCA1/2 mutations. Designed as an integrated part of the GeneReader NGS System, the QIAact BRCA1/2 and the BRCA Advanced Panel leverages unique molecular index (UMI) technology to detect single nucleotide variants (SNVs), exon-level CNVs, even those at low-frequency, ensuring consideration of all variants within the sample.
In the second half of the webinar, we will present a concordance study demonstrating the accuracy of QIAGEN Clinical Insight (QCI®), QIAGEN’s clinical decision support software for the interpretation and reporting of NGS data. The study compares QCI’s automated variant classification of over 6,000 BRCA1/2 variants to the human-derived variant classifications from expert panels (the ENIGMA consortium and ClinGen). QCI achieves extremely high concordance (99.6%) and provides automated tiered classifications according to all 28 ACMG guidelines with full transparency to the underlying evidence.
1. QIAGEN’s GeneReader workflows are pre-optimized sample to insight solutions able to overcome the challenges of a fragmented NGS workflow
2. The BRCA ½ and the BRCA Advanced Panels coupled with the GeneReader enable comprehensive profiling of mutations within BRCA, including challenging mutations such as large Indels and exon-level CNVs, and with UMI technology, even those of low allele frequency
3. QCI Interpret as part of the GeneReader solution automates variant classification using all 28 ACMG criteria, while transparently providing the supporting evidence for variant assessment
4. In compelling concordance study, QCI-Interpret used to automatically classify >6000 BRCA1 and BRCA2 variants, demonstrating the extremely high concordance (99.6%) between automated tiered classification with this clinical decision support platform and classifications by a panel of experts.
Clinical Genetic Molecular Biologist Scientist (Cgmbs)
Medical Laboratory Technician67%
Clinical Laboratory Scientist33%