Molecular Genetics & Genomic Medicine (Sep 2023)

From variant of unknown significance to likely pathogenic: Characterization and pathogenicity determination of a large genomic deletion in the MLH1 gene

  • Ahmed Bouras,
  • Clementine Legrand,
  • Jihen Kourda,
  • Eric Ruano,
  • Chloé Grand‐Masson,
  • Cedrick Lefol,
  • Qing Wang

DOI
https://doi.org/10.1002/mgg3.2231
Journal volume & issue
Vol. 11, no. 9
pp. n/a – n/a

Abstract

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Abstract Background The MLH1 gene is one of the DNA mismatch repair genes (MMR), implicated in Lynch syndrome (LS), an autosomal dominant hereditary tumor susceptibility disease. The advent of next‐generation sequencing (NGS) technologies has accelerated the diagnosis of inherited diseases and increased the percentage of diagnosis of inherited cancers. However, some complex genomic alterations require the combination of several analytical strategies to allow correct biological interpretations. Here, we describe a novel MLH1 deletion and its pathogenicity determination in a patient suspected of LS. Methods The index case was a French 73‐year‐old man diagnosed with colorectal cancer displaying microsatellite instability and the loss of MLH1 and PMS2 expression. NGS analysis was used as the primary method for MMR genes screening. Long‐range PCR and reverse transcriptase polymerase chain reaction (RT‐PCR) were used for breakpoints and pathogenicity determinations. Results A large genomic deletion was detected which removed the last six nucleotides of MLH1 exon 11 together with a large part of intron 11. It was initially considered as a variant of unknown significance (VUS). Genomic breakpoints were subsequently characterized defining the deletion as c.1033_1039‐248del. Further RNA analysis demonstrated that this variant activated a cryptic donor splice site at the 5′ of the breakpoint, leading to a premature truncated protein: p.Thr345Alafs*13. Conclusion Our finding suggested that although NGS technologies have increased variant detection yield, combined approaches were still needed for complex variant characterization and pathogenicity assessment.

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