12488 Exome Sequencing Unravels New Susceptibility Genes For Pheochromocytomas And Paragangliomas
Notice bibliographique
Résumé
Abstract Disclosure: G.F. Fagundes: None. F.F. Castro: None. L.S. Santana: None. A.F. Afonso: None. A.W. Maciel: None. F.L. Ledesma: None. C.A. Pereira: None. I.C. Soares: None. D.M. Lourenço Junior: None. M.A. Pereira: None. V. Srougi: None. F.Y. Tanno: None. J.L. Chambo: None. M.C. Fragoso: None. A.O. Hoff: None. B.B. Mendonca: None. A. Latronico: None. M.Q. Almeida: None. Background: Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors with a high association with hereditary disease, affecting 40% of the cases. PPGL susceptibility genes are categorized into three clusters based on their pathophysiological and metabolomic mechanisms. Somatic oncogenic variants are identified in 30% of the tumors. Most of the germline and somatic drivers are mutually exclusive in PPGLs. Thus, 30% of the PPGLs remain without known genetic causes. Aim: To investigate new susceptibility genes for PPGLs using whole exome sequencing. Methods: We included 145 index patients with PPGLs (93 female and 52 male) with 91 pheochromocytomas (PHEO) and 60 paragangliomas, of which 43 (29.65%) were metastatic. A target next-generation sequencing panel for susceptibility genes was initially performed. Whole exome sequencing was performed in 56 patients with PPGLs (38 were paired with tumor DNA). Results:SDHB was the most frequently affected gene in 29 of 145 patients (20%). Germline SDHB exon 1 deletion was identified in 14 patients (48.27%). Germline variants were identified as follow: RET 22 (15.17%), VHL 13 (8.96%), SDHA 6 (4.14%), SDHD 5 (3.45%), NF1 5 (3.45%), FH 2 (1.38%), MAX 2 (1.38%), DLST 1 (0.69%), TMEM127 1 (0.69%), SDHC 1 (0.69%) and H3F3A 1 (0.69%) case. Somatic variants were identified in 21 tumors: NF1 6 (4.14%), HRAS 5 (3.45%), VHL 2 (1.38%), FGFR1 2 (1.38%), and RET 1 (0.69%). Six variants (five germline and one somatic) were identified in 3 new candidate genes: 1) Three very rare germline CHEK2 likely pathogenic or pathogenic variants (c.475T>C/ p.Tyr159His; c.362G>A/ p.Cys121Tyr; c.319+2T>A) in one metastatic PHEO and two PGLs (one metastatic). The metastatic PGL did not harbor any somatic oncogenic variant, while exome sequencing of a metastatic lesion from the PHEO had a somatic likely oncogenic HRAS variant; 2) Two very rare germline BRCA2 pathogenic variants (c.3680_3681delTG/ p.Leu1227fs; c.7806-2A>C) in a 33-year-old man with non-metastatic PHEO and in a 25-year-old man with metastatic PGL. All germline variants have not been reported in the Brazilian genomic variant repository. Exome sequencing did not reveal any somatic oncogenic driver in both tumors; 3) The somatic GNAS likely oncogenic variant c.601C>T/ p.Arg201Cys in a pheochromocytoma. The prevalence of CHEK2 and BRCA2 pathogenic or likely pathogenic variants in our cohort were significantly higher compared with those in the gnomAD population database (p < 0.0001 and p = 0.0004, respectively). Co-occurrence of germline and somatic drivers were found in 3 cases: FH and FGFR1, DLST and NF1, and CHEK2 and HRAS. In summary, germline and somatic diagnosis were reached in 63.45% and 15.18% of the PPGLs in our cohort, respectively. Conclusion: Our findings support CHEK2, BRCA2 and GNAS as novel susceptibility genes for PPGLs. Support: Sao Paulo Research Foundation (FAPESP) grant 2019/15873-6. Presentation: 6/2/2024
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».