Parallel DNA/RNA NGS Using an Identical Target Enrichment Panel in the Analysis of Hereditary Cancer Predisposition

Abstract

Germline DNA testing using the next-gene­ration sequencing (NGS) technology has become the analytical standard for the diagnostics of hereditary diseases, including cancer. Its increasing use places high demands on correct sample identification, independent confirmation of prioritized variants, and their functional and clinical interpretation. To streamline these processes, we introduced parallel DNA and RNA capture-based NGS using identical capture panel CZECANCA, which is routinely used for DNA analysis of hereditary cancer predisposition. Here, we present the analytical workflow for RNA sample processing and its analytical and diagnostic performance. Parallel DNA/RNA analysis allowed credible sample identification by calculating the kinship coefficient. The RNA capture-based approach enriched transcriptional targets for the majority of clinically relevant cancer predisposition genes to a degree that allowed analysis of the effect of identified DNA variants on mRNA processing. By comparing the panel and whole-exome RNA enrichment, we demonstrated that the tissue-specific gene expression pattern is independent of the capture panel. Moreover, technical replicates confirmed high reproducibility of the tested RNA analysis. We concluded that parallel DNA/RNA NGS using the identical gene panel is a robust and cost-effective diagnostic strategy. In our setting, it allows routine analysis of 48 DNA/RNA pairs using NextSeq 500/550 Mid Output Kit v2.5 (150 cycles) in a single run with sufficient coverage to analyse 226 cancer predisposition and candidate ge­nes. This approach can replace laborious Sanger confirmatory sequencing, increase testing turnaround, reduce analysis costs, and improve interpretation of the impact of variants by analysing their effect on mRNA processing.

A comprehensive analysis of germline predisposition to early-onset ovarian cancer

“…Interestingly, CHEK2 GPV identified in 6/123 (4.9%) early-onset OC patients were significantly associated with earlier age at diagnosis compared to previously analyzed OC patients negative for GPV in HBOP cancer predisposition genes 6 . It is noteworthy that one CHEK2 deep intronic variant was identified only by RNA NGS which underlines the importance of RNA analysis 47 . Furthermore, GPV in CHEK2 have been identified in early-onset OC patients by other studies 6 , 10 , 48 , 49 , the most prevalently by Carter et al 10 who identified CHEK2 GPV in 5/147 (3.4%) early-onset OC patients.…”