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The SDHD :p.H102R Variant Is Frequent in Russian Patients with Head and Neck Paragangliomas and Associated with Loss of 11p15.5 Region and Hypermethylation of H19-DMR.

Anastasiya V SnezhkinaMaria S FedorovaAnastasiya KobelyatskayaDaria MarkovaMargarita LantsovaAnna Yu IkonnikovaMarina EmelyanovaDmitry V KalininElena PudovaNataliya V MelnikovaAlexey A DmitrievGeorge S KrasnovVladislav S PavlovAnna V Kudryavtseva
Published in: International journal of molecular sciences (2022)
Head and neck paragangliomas (HNPGLs) are rare neuroendocrine neoplasms derived from the parasympathetic paraganglia of the head and neck. At least 30% of HNPGLs are linked to germline mutations, predominantly in SDHx genes. In this study, we analyzed an extended cohort of Russian patients with HNPGLs using whole-exome sequencing and found a highly frequent missense variant p.H102R in the SDHD gene. We determined this variant in 34% of the SDHD mutation carriers. This variant was associated with somatic loss of the gene wild-type allele. Data from the B allele frequency method and microsatellite and microdeletion analysis indicated evident LOH at the 11p15.5 region and potential loss of the whole of chromosome 11. We found hypermethylation of H19-DMR in all tumors, whereas differential methylation of KvDMR was mostly retained. These findings do not support the paternal transmission of SDHD :p.H102R but are in agreement with the Hensen model. Using targeted sequencing, we also studied the variant frequency in a control cohort; we found SDHD :p.H102R in 1.9% of cases, allowing us to classify this variant as pathogenic. The immunohistochemistry of SDHB showed that the SDHD :p.H102R mutation, even in combination with wild-type allele loss, does not always lead to SDH deficiency. The obtained results demonstrate the frequent variant associated with HNPGLs in a Russian population and support its pathogenicity. Our findings help with understanding the mechanism of tumorigenesis and are also important for the development of cost-effective genetic screening programs.
Keyphrases
  • wild type
  • genome wide
  • copy number
  • dna methylation
  • escherichia coli
  • dna damage
  • single cell
  • staphylococcus aureus
  • big data
  • dna repair
  • deep learning
  • african american