Somatic neurofibromatosis type 1 (NF1) inactivation characterizes NF1-associated pilocytic astrocytoma
Bibliographic record
Abstract
Low-grade brain tumors (pilocytic astrocytomas) arising in the neurofibromatosis type 1 (NF1) inherited cancer predisposition syndrome are hypothesized to result from a combination of germline and acquired somatic NF1 tumor suppressor gene mutations. However, genetically engineered mice (GEM) in which mono-allelic germline Nf1 gene loss is coupled with bi-allelic somatic (glial progenitor cell) Nf1 gene inactivation develop brain tumors that do not fully recapitulate the neuropathological features of the human condition. These observations raise the intriguing possibility that, while loss of neurofibromin function is necessary for NF1-associated low-grade astrocytoma development, additional genetic changes may be required for full penetrance of the human brain tumor phenotype. To identify these potential cooperating genetic mutations, we performed whole-genome sequencing (WGS) analysis of three NF1-associated pilocytic astrocytoma (PA) tumors. We found that the mechanism of somatic NF1 loss was different in each tumor (frameshift mutation, loss of heterozygosity, and methylation). In addition, tumor purity analysis revealed that these tumors had a high proportion of stromal cells, such that only 50%-60% of cells in the tumor mass exhibited somatic NF1 loss. Importantly, we identified no additional recurrent pathogenic somatic mutations, supporting a model in which neuroglial progenitor cell NF1 loss is likely sufficient for PA formation in cooperation with a proper stromal environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".