Impact of PTEN abnormalities on outcome in pediatric patients with T-cell acute lymphoblastic leukemia treated on the MRC UKALL2003 trial
Bibliographic record
Abstract
PTEN gene inactivation by mutation or deletion is common in pediatric T-cell acute lymphoblastic leukemia (T-ALL), but the impact on outcome is unclear, particularly in patients with NOTCH1/FBXW7 mutations. We screened samples from 145 patients treated on the MRC UKALL2003 trial for PTEN mutations using heteroduplex analysis and gene deletions using single nucleotide polymorphism arrays, and related genotype to response to therapy and long-term outcome. PTEN loss-of-function mutations/gene deletions were detected in 22% (PTEN(ABN)). Quantification of mutant level indicated that 67% of mutated cases harbored more than one mutant, with up to four mutants detected, consistent with the presence of multiple leukemic sub-clones. Overall, 41% of PTEN(ABN) cases were considered to have biallelic abnormalities (mutation and/or deletion) with complete loss of PTEN in a proportion of cells. In addition, 9% of cases had N- or K-RAS mutations. Neither PTEN nor RAS genotype significantly impacted on response to therapy or long-term outcome, irrespective of mutant level, and there was no evidence that they changed the highly favorable outcome of patients with double NOTCH1/FBXW7 mutations. These results indicate that, for pediatric patients treated according to current protocols, routine screening for PTEN or RAS abnormalities at diagnosis is not warranted to further refine risk stratification.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".