12488 Exome Sequencing Unravels New Susceptibility Genes For Pheochromocytomas And Paragangliomas
Bibliographic record
Abstract
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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".