Frontiers in Neurology (Aug 2024)

Algorithm of genetic diagnosis for patients with head and neck paraganglioma—update

  • Katarzyna Radomska,
  • Zofia Leszczyńska,
  • Rafal Becht,
  • Monika Zaborek - Łyczba,
  • Anna Rzepakowska,
  • Jakub Lubiński,
  • Marcin Szymański

DOI
https://doi.org/10.3389/fneur.2024.1437027
Journal volume & issue
Vol. 15

Abstract

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Paragangliomas are rare tumors originating from the paraventricular bodies of the autonomic nervous system located in the adrenal glands, chest, abdomen, pelvis and head and neck. Tumors of this type account for 0.5% of head and neck cancers, 0.03% of all cancers and their incidence is estimated at 1–30/100,000 per year. Head and Neck Paragangliomas (HNPGL) are localized in carotid body, tympanic cavity or jugular foramen. It is established that HNPGL may be associated with mutations of the SDH complex, with SDHD being the most prevalent. However, SDHB, SDHC and SDHAF are also potential causes. The aforementioned mutations are influenced by various risk factors, including young age, a positive family history of paraganglioma, the presence of metastases and gender The purpose of this study is to summarize the results of genetic testing performed on patients with head and neck paraganglioma and to create an up-to-date genetic diagnosis algorithm for patients with HNPGL based on previous studies published in the literature that can be used in daily practice. Several papers observed that among SDHD mutation carriers, most or all of those studied had HNPGL, and SDHB mutations were more frequently found in the presence of metastasis. Based on the results, it was concluded that there is no basis for genetic testing for VHL in patients without a positive family history. In each algorithm proposed by different authors, proposals for rational genetic diagnosis were analyzed based on the studies cited by the author and the analyses included in our paper. For the analysis of the treatment algorithms, the following were included: Martin, Mannelli, Neumann, Gupta. Subsequently, publications related to the genetic diagnosis of HNPGL were analyzed to verify the proposed algorithms in light of the latest genetic studies and to establish an updated diagnostic management scheme.

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