<i>BRAF-KIAA1549</i> Fusion Predicts Better Clinical Outcome in Pediatric Low-Grade Astrocytoma
Bibliographic record
Abstract
PURPOSE: Recent studies have revealed that the majority of pediatric low-grade astrocytomas (PLGA) harbor the BRAF-KIAA1549 (B-K) fusion gene resulting in constitutive activation of the RAS/MAPK pathway. However, the clinical significance of this genetic alteration is yet to be determined. We aimed to test the prognostic role of the B-K fusion in progression of incompletely resected PLGA. EXPERIMENTAL DESIGN: We retrospectively identified 70 consecutive patients with incompletely resected "clinically relevant" PLGA. We added 76 tumors diagnosed at our institution between 1985 and 2010 as controls. We examined BRAF alterations by reverse transcriptase PCR, FISH, and single-nucleotide polymorphism array analysis and correlated that with progression-free survival (PFS). RESULTS: Overall, 60% of tumors were B-K fusion positive. All patients with B-K fused PLGA are still alive. Five-year PFS was 61% ± 8% and 18% ± 8% for fusion positive and negative patients, respectively (P = 0.0004). B-K fusion resulted in similarly significant favorable PFS for patients who received chemotherapy. Multivariate analysis revealed that B-K fusion was the most significant favorable prognostic factor in incompletely resected PLGA and was independent of location, pathology, and age. In vitro, BRAF overexpression resulted in growth arrest associated with DNA damage (γH2AX expression). Five-year PFS was 68% ± 15% and 0% for patients with B-K fused and γH2AX-expressing PLGA versus negative tumors (P = 0.001). CONCLUSION: These data suggest that B-K fusion confers a less aggressive clinical phenotype on PLGA and may explain their tendency to growth arrest. Combined analysis of B-K fusion and γH2AX expression can determine prognosis and may be a powerful tool to tailor therapy for these patients.
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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 | 0.001 |
| 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 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".