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Titel: Hybrid neurofibroma/schwannoma in schwannomatosis : a diagnostically challenging benign peripheral nerve sheath tumour
Autor(en): Tippner, Daniel
Anokhin, Maxim
Scheffler, JonasIn der Gemeinsamen Normdatei der DNB nachschlagen
Hellmann, FabioIn der Gemeinsamen Normdatei der DNB nachschlagen
Plontke, Stefan K.-R.In der Gemeinsamen Normdatei der DNB nachschlagen
Leisz, SandraIn der Gemeinsamen Normdatei der DNB nachschlagen
Harder, AnjaIn der Gemeinsamen Normdatei der DNB nachschlagen
Erscheinungsdatum: 2025
Art: Artikel
Sprache: Englisch
Zusammenfassung: Hybrid neurofibroma/schwannoma tumors (HNS) represent a still underrecognized, yet clinically and diagnostically significant entity within the spectrum of schwannomatosis (SWN). While classical schwannomas have been well known for decades, HNS have only recently been described as a distinct histological pattern, composed of intermixed features typical of both schwannomas and neurofibromas. Differentiating HNS from pure neurofibroma (Nf) is critical, as misclassification may lead to an incorrect diagnosis of neurofibromatosis type 1 rather than SWN. The distinction of hybrid tumors (more precisely HNS) is especially important in SWN forms outside the neurofibromatosis type 2 (NF2) spectrum (NF2-SWN), where major diagnostic criteria are less well defined, making histological differentiation even more significant. At the molecular level, HNS frequently show alterations in the genes NF2, LZTR1, and SMARCB1, often accompanied by characteristic losses of chromosome 22q. In addition, recurrent somatic mutations have been identified in genes such as ERBB2, RET, KMT2A, and CTNNA3. Methylation profiling classifies HNS within the schwannoma spectrum, supporting the hypothesis that they may be a morphological variant rather than a distinct entity, although this has not yet been conclusively confirmed. Histologically, HNS are characterized by a combination of mostly schwannoma-associated Antoni A patterns, collagen-rich neurofibroma-like areas, lymphocytic infiltrates, and, in some cases, plexiform growth. Given the diagnostic challenges, artificial intelligence-based image analysis, such as whole-slide imaging and radiomics, may offer valuable tools for more accurate identification of these tumors in the future. Initial studies in related fields have shown that such approaches can even surpass human-level accuracy. Nevertheless, an accurate histological and, if necessary, molecular evaluation remains essential—particularly for the correct classification as SWN and for ensuring appropriate genetic counseling to affected individuals.
URI: https://opendata.uni-halle.de//handle/1981185920/123699
http://dx.doi.org/10.25673/121748
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY 4.0) Creative Commons Namensnennung 4.0 International(CC BY 4.0) Creative Commons Namensnennung 4.0 International
Journal Titel: Familial cancer
Verlag: Springer Science + Business Media B.V
Verlagsort: Dordrecht [u.a.]
Band: 24
Originalveröffentlichung: 10.1007/s10689-025-00505-4
Seitenanfang: 1
Seitenende: 11
Enthalten in den Sammlungen:Open Access Publikationen der MLU

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