Copy number variants in clinical next-generation sequencing data can define the relationship between simultaneous tumors in an individual patient

Targeted next-generation sequencing (NGS) cancer panels have become a popular method for the identification of clinically predictive mutations in cancer. Such methods typically detect single nucleotide variants (SNVs) and small insertions/deletions (indels) in known cancer genes and can provide further information regarding diagnosis in challenging surgical pathology cases, as well as identify therapeutic targets and prognostically significant mutations. However, in addition to SNVs and indels, other mutation classes, including copy number variants (CNVs) and translocations, can be simultaneously detected from targeted NGS data. Here, as proof of methods, we present clinical data which demonstrate that targeted NGS panels can separate synchronous liver tumors based on CNV status, in the absence of distinct SNVs and indels. Such CNV-based analysis can be performed without additional cost using existing targeted cancer panel data and publically available software.