Mutant <i>IDH1</i> cooperates with <i>NPM1c</i> or <i>FLT3</i> <sup>ITD</sup> to drive distinct myeloid diseases and molecular outcomes
Bibliographic record
Abstract
In human acute myeloid leukemia (AML), mutations of isocitrate dehydrogenase-1 ( IDH1 ) often co-occur with NPM1 mutations, and less frequently with FLT3 mutations. To investigate whether the effects of IDH1 mutation differ according to the specific co-occurring mutation, we generated two strains of double knock-in mutant mice. Idh1 R132H combined with Npm1c induced overt AML, whereas Idh1 R132H plus Flt3 ITD resulted in Flt3 ITD -driven myelo- or lymphoproliferation that was minimally affected by Idh1 R132H and rarely generated AML. Gene expression profiling revealed differences between Idh1 R132H ; Npm1c cells and Idh1 R132H ; Flt3 ITD cells and suggested altered heme metabolism and immune responses in the former. The profile of Idh1 R132H ; Npm1c cells corresponded to that of human IDH -mutated AML cells, particularly those resistant to inhibitors of mutant IDH. Compared to treatment with a menin inhibitor, IDH1-targeted therapy of Idh1 R132H ; Npm1c AML-bearing mice was less efficacious in improving cell differentiation and extending survival. The differential cooperation of Idh1 R132H with Npm1c vs. Flt3 ITD may have implications for the devising of subtype-specific treatments for human 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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".