Characterisation of FLT3 alterations in childhood acute lymphoblastic leukaemia
Bibliographic record
Abstract
BACKGROUND: Alterations of FLT3 are among the most common driver events in acute leukaemia with important clinical implications, since it allows patient classification into prognostic groups and the possibility of personalising therapy thanks to the availability of FLT3 inhibitors. Most of the knowledge on FLT3 implications comes from the study of acute myeloid leukaemia and so far, few studies have been performed in other leukaemias. METHODS: A comprehensive genomic (DNA-seq in 267 patients) and transcriptomic (RNA-seq in 160 patients) analysis of FLT3 in 342 childhood acute lymphoblastic leukaemia (ALL) patients was performed. Mutations were functionally characterised by in vitro experiments. RESULTS: Point mutations (PM) and internal tandem duplications (ITD) were detected in 4.3% and 2.7% of the patients, respectively. A new activating mutation of the TKD, G846D, conferred oncogenic properties and sorafenib resistance. Moreover, a novel alteration involving the circularisation of read-through transcripts (rt-circRNAs) was observed in 10% of the cases. Patients presenting FLT3 alterations exhibited higher levels of the receptor. In addition, patients with ZNF384- and MLL/KMT2A-rearranged ALL, as well as hyperdiploid subtype, overexpressed FLT3. DISCUSSION: Our results suggest that specific ALL subgroups may also benefit from a deeper understanding of the biology of FLT3 alterations and their clinical implications.
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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 | 0.002 | 0.001 |
| 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".