Abstract 4371: Integrated molecular characterization of pheochromocytoma and paraganglioma including a novel, recurrent and prognostic fusion gene
Bibliographic record
Abstract
Abstract Pheochromocytomas (PCC) and paragangliomas (PGL) are tumors of the autonomic nervous system; 25% are metastatic or locally aggressive. Characterization of the inherited basis of disease has identified a variety of underlying germline mutations; however, understanding of somatic alterations remains limited. As part of The Cancer Genome Atlas, we performed the most comprehensive genomic characterization of PCC/PGL to date, by applying eight genomic profiling assays to 173 patients. Despite having a low overall mutation rate per tumor, we observed remarkable diversity in genomic alterations. 27% of patients had a pathogenic germline mutation among eight known familial PCC/PGL susceptibility genes, thus making PCC/PGL the tumor type with the greatest rate of germline mutations in The Cancer Genome Atlas. 38% of patients possessed a somatic driver mutation across 12 genes. RET, NF1 and VHL were affected by both germline and somatic mutation, albeit with different mutation site tendencies. We identified a new somatic driver gene, CSDE1, which had coordinated intron splicing defects, DNA copy number loss, and RNA under-expression, suggesting a loss of function consequence. Most notably, we discovered the first fusion genes in PCC/PGL from RNA and DNA sequencing (7% of patients), demonstrating for the first time that inter-chromosomal translocation and gene fusion is a method of molecular pathogenesis in this disease. Recurrent, novel MAML3 fusion genes spanned three isoforms and were activating based on over-expression of MAML3 and on fusion transcript exonic expression. MAML3 fusion positive tumors had concomitant dual focal DNA amplification of the fusion gene partners and a significantly divergent methylation profile. Another novel driver gene in PCC/PGL, BRAF, was affected by a hotspot somatic mutation and by an activating fusion gene. Through integrated platform analysis, four statistically significant molecular subtypes of PCC/PGL were detected and found to represent divergent molecular etiology – the kinase signaling subtype, the pseudohypoxia subtype, the Wnt-altered subtype, and the cortical admixture subtype. In particular, MAML3 fusions and CSDE1 mutations defined the new Wnt-altered expression subtype of PCC. Adding to the limited set of prognostic markers in PCC/PGL, three molecular markers were positively associated with clinically aggressive disease: germline mutations in SDHB, somatic mutations in ATRX and fusions involving MAML3. Nearly all somatic driver mutations, germline driver mutations and fusion genes were mutually exclusive across the cohort and covered a large portion of the cohort (69%). Our study provides important novel insights into PCC/PGL biology and identifies potential markers for aggressive disease and therapeutic intervention. Citation Format: Lauren Fishbein, Ignaty Leshchiner, Vonn Walter, Ludmila Danilova, A Gordon Robertson, Amy Johnson, Tara Lichtenberg, Bradley A. Murray, Hanse K. Ghayee, Tobias Else, Shiyun Ling, Stuart R. Jefferys, Aguirre A. de Cubas, Brandon Wenz, Esther Korpershoek, Antonio L. Amelio, Liza Makowski, W Kimryn Rathmell, Anne-Paule Gimenez-Roqueplo, Thomas J. Giordano, Sylvia L. Asa, Arthur S. Tischler, The Cancer Genome Atlas Pheochromocytoma and Paraganglioma Analysis Working Group, Karel Pacak, Katherine L. Nathanson, Matthew D. Wilkerson. Integrated molecular characterization of pheochromocytoma and paraganglioma including a novel, recurrent and prognostic fusion gene. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4371.
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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 | 0.000 |
| 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".