Published in

Wiley Open Access, Molecular Genetics and Genomic Medicine, 6(11), 2023

DOI: 10.1002/mgg3.2151

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Genome sequencing identifies complex structural MLH1 variant in unsolved Lynch syndrome

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

AbstractBackgroundLynch syndrome is one of the most common cancer predisposition syndromes. It is caused by inherited changes in the mismatch repair pathway. With current diagnostic approaches, a causative genetic variant can be found in less than 50% of cases. A correct diagnosis is important for ensuring that an appropriate surveillance program is used and that additional high‐risk family members are identified.MethodsWe used clinical genome sequencing on DNA from blood and subsequent transcriptome sequencing for confirmation. Data were analyzed using the megSAP pipeline and classified according to basic criteria in diagnostic laboratories. Segregation analyses in family members were conducted via breakpoint PCR.ResultsWe present a family with the clinical diagnosis of Lynch syndrome in which standard diagnostic tests, such as panel or exome sequencing, were unable to detect the underlying genetic variant. Genome sequencing in the index patient confirmed the previous diagnostic results and identified an additional complex rearrangement with intronic breakpoints involving MLH1 and its neighboring gene LRRFIP2. The previously undetected structural variant was classified as medically relevant. Segregation analysis in the family identified additional at‐risk individuals which were offered intensified cancer screening.Discussion and ConclusionsThis case illustrates the advantages of clinical genome sequencing in detecting structural variants compared with current diagnostic approaches. Although structural variants are rare in Lynch syndrome families, they seem to be underreported, in part because of technical challenges. Clinical genome sequencing offers a comprehensive genetic characterization detecting a wide range of genetic variants.