期刊
GENETICS IN MEDICINE
卷 -, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1038/s41436-020-0880-8
关键词
hereditary cancer; variant interpretation; structural variants; genome sequencing; long-read sequencing
资金
- Genome Canada
- Genome BC [202SEQ, 212SEQ, 12002]
- Canada Foundation for Innovation [20070, 30198, 30981, 33408]
- BC Knowledge Development Fund
- BC Cancer Foundation
- Genome British Columbia [B20POG]
- University of British Columbia Clinician Investigator Program
- Canadian Institutes for Health Research Postdoctoral Fellowship award
- Canadian Institutes of Health Research
- Michael Smith Foundation for Health Research
Purpose Structural variants (SVs) may be an underestimated cause of hereditary cancer syndromes given the current limitations of short-read next-generation sequencing. Here we investigated the utility of long-read sequencing in resolving germline SVs in cancer susceptibility genes detected through short-read genome sequencing. Methods Known or suspected deleterious germline SVs were identified using Illumina genome sequencing across a cohort of 669 advanced cancer patients with paired tumor genome and transcriptome sequencing. Candidate SVs were subsequently assessed by Oxford Nanopore long-read sequencing. Results Nanopore sequencing confirmed eight simple pathogenic or likely pathogenic SVs, resolving three additional variants whose impact could not be fully elucidated through short-read sequencing. A recurrent sequencing artifact on chromosome 16p13 and one complex rearrangement on chromosome 5q35 were subsequently classified as likely benign, obviating the need for further clinical assessment. Variant configuration was further resolved in one case with a complex pathogenic rearrangement affectingTSC2. Conclusion Our findings demonstrate that long-read sequencing can improve the validation, resolution, and classification of germline SVs. This has important implications for return of results, cascade carrier testing, cancer screening, and prophylactic interventions.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据