GENT-36. THE GENOMIC LANDSCAPE OF SCHWANNOMA
Bibliographic record
Abstract
Schwannomas are common cranial and spinal nerve tumors that can cause significant debilitating morbidities. To date, clinical trials for schwannomas have yielded mixed to no benefits and this may be in part due to a lack of fully understanding the somatic alterations that occur in schwannoma. We performed an integrative multiplatform analysis to determine the genomic landscape of sporadic schwannomas. Exome sequence analysis with validation by targeted DNA-sequencing of 125 samples uncovered, in addition to expected NF2 disruption, recurrent mutations in ARID1A, ARID1B and DDR1. Genome wide methylation profiling revealed that schwannomas consists of two molecular subgroups with unique gene signatures and anatomical location. RNA sequencing revealed a recurrent in-frame gene fusion on chromosome 10q in 12/125 (10%) cases, and genomic analysis identified the mechanism to be from a balanced 19Mb chromosomal inversion. The presence of the fusion was associated with male gender predominance, occurring in one out of every six men with schwannoma. Expression of the fusion transcript in both schwannomas and normal schwann cells resulted in elevated phosphorylated-ERK, increased proliferation, increased invasion and resulted in the formation of in vivo xenografts. Targeting of the MEK/ERK pathway was effective in fusion-positive Schwann cells, suggesting a possible therapeutic approach for this subset of tumors. Our study provides rationale that integrative analysis approaches can identify novel therapies for schwannoma patients.
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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) | 0.001 | 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".