Advances in our understanding of genetic markers and targeted therapies for pediatric LCH
Bibliographic record
Abstract
INTRODUCTION: Langerhans cell histiocytosis (LCH) is a rare myeloid neoplasm, encompassing a diverse clinical spectrum ranging from localized bone or skin lesions to a multisystemic life-threatening condition. Over the past decade, there has been an expansion in understanding the molecular biology of LCH, which translated into innovative targeted therapeutic approaches. AREAS COVERED: In this article, we will review the molecular alterations observed in pediatric LCH and the relationship between these molecular changes and the clinical phenotype, as well as targeted therapies in LCH. EXPERT OPINION: Mitogen-activated protein kinase (MAPK) pathway mutation is a hallmark of LCH and is identified in 80% of the cases. Notably, BRAFV600E mutation is seen in ~50-60% of the cases, ~30% has other MAPK pathway mutations, while 15-20% have no detected mutations. While the first line therapeutic approach is vinblastine and prednisone, targeted therapies - specifically BRAF/MEK inhibitors - emerged as a promising second-line salvage strategy, particularly when a mutation is identified. Most patients respond to BRAF/MEK inhibitors but at least 75% reactivate after stopping, however, most patients respond again when restarting inhibitors.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".