Detection of large rearrangements in a hereditary pan-cancer panel using next-generation sequencing

Abstract

Abstract Background Healthcare providers increasingly use information about pathogenic variants in cancer predisposition genes, including sequence variants and large rearrangements (LRs), in medical management decisions. While sequence variant detection is typically robust, LRs can be difficult to detect and characterize and may be underreported as a cause for hereditary cancer risk. This report describes the outcomes of hereditary cancer genetic testing using a comprehensive strategy that employs next-generation sequencing (NGS) for LR detection, coupled with LR confirmation using repeat hybrid capture NGS, microarray comparative genomic hybridization (microarray-CGH), and/or multiplex ligation-dependent probe amplification (MLPA). Methods Sequencing and LR analysis were conducted in a consecutive series of 376,159 individuals who received clinical testing with a hereditary pan-cancer gene panel from September 2013 through May 2017. NGS dosage analysis was used to evaluate potential deletions or duplications, with controls in place to exclude pseudogene reads. Samples positive for a putative LR based on NGS were confirmed using a comprehensive approach that included targeted microarray-CGH and/or MLPA analysis, with further examination as needed to ascertain the nature of the LR. Results A total of 3461 LRs were identified and classified as a deleterious mutation (DM), suspected deleterious mutation (SDM) or variant of uncertain significance. Pathogenic LRs (DM/SDM) accounted for the majority of LRs (67.7%), the largest proportion of which were deletions (86.1%), followed by duplications (11.3%), insertions (1.8%), triplications (0.5%), and inversions (0.3%). Several cases presented illustrate that the laboratory approach employed here can ensure consistent identification and accurate characterization of LRs. In the absence of this comprehensive testing strategy, 9% of LRs identified in this testing population might have been missed, potentially leading to inappropriate medical management in as many as 210 individuals referred for hereditary cancer testing. Conclusions These data show that copy number analysis using NGS coupled with confirmatory testing reliably detects and characterizes LRs. Further, LRs comprise a substantial proportion (7.2%) of pathogenic variants identified by the test. A robust and accurate LR identification strategy is an essential component of a high-quality genetic testing program, enabling clinicians to optimize patient medical management decisions.