A possible role for methotrexate in the treatment of childhood acute myeloid leukaemia, in particular for acute monocytic leukaemia
Bibliographic record
Abstract
Acute myeloid leukaemia (AML) is thought to be methotrexate (MTX)-resistant. However, a small study suggested that acute monocytic leukemia (AML-M5) is sensitive to MTX. We measured MTX accumulation/polyglutamylation in 20 AML-nonM5, 37 AML-M5 and 83 common/preB-acute lymphoblastic leukaemia (c/preB-ALL) samples. Membrane transport was determined in 11 childhood AMLs (including 3 AML-M5) and in 25 c/preB-ALL samples. MTX sensitivity was determined in 23 AML-nonM5, 15 AML-M5 and 63 common/preB-ALL samples using the thymidylate synthase (TS) inhibition assay. MTX transport was higher in AML samples compared with c/preB-ALL precluding a transport defect in AML. Accumulation of long-chain polyglutamates MTX-Glu(4-6) was 3-fold lower for AML-nonM5 compared with c/preB-ALL cells (median 268 versus 889 pmol MTX-Glu(4-6)/10(9) cells; P < or = 0.001); for AML-M5 samples, median accumulation of MTX-Glu(4-6) was 0 pmol/10(9) cells (P < or = 0.001). After short-term MTX exposure, AML-nonM5 was 6-fold more resistant to MTX compared with c/preB-ALL cells (2.16 versus 0.39 microM; P < 0.001), while AML-M5 was 2-fold more resistant (P = 0.02). In both AML-nonM5 and AML-M5 cells, MTX resistance was circumvented by continuous MTX exposure (median TSI(50) values: 0.052 and 0.041 microM, respectively) compared with a c/preB-ALL value of 0.066 microM. In conclusion, AML-M5 is relatively sensitive to MTX compared with other AML-subtypes even though polyglutamylation of MTX is poor. Using continuous exposure, AML-nonM5 and AML-M5 cells were at least as sensitive to MTX as c/preB-ALL cells. This report suggests that MTX might be an overlooked drug in the treatment of childhood AML.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".