Hereditary cancer syndromes are a set of complex diseases, often presenting with diverse clinical phenotypes, involving multiple genes of interest with variable penetrance. Large scale genomic sequencing of multi-gene panels has become the standard of care. However, this approach identifies a multitude of novel variants, encompassing a wide range of variant types from duplications and deletions to single nucleotide variants. Interrogating and classifying these variants with respect to pathogenicity or inherent risk for a suspected hereditary cancer syndrome requires the review of an abundance of information, from population data to evolutionary conservation assessment to functional studies and literature reviews.

In this webinar, we show how Alamut Visual Plus has the computational power to pull data sources together, allowing for a consolidated and consistent approach to genomic variant interpretation in the context of hereditary cancers. In addition, we give a brief overview of the Mastermind genomic search engine and how the AI-powered tool reduces turnaround time, increases diagnostic yield and accelerates throughput for genomic variant interpretation.