Targeting the MTF2–MDM2 Axis Sensitizes Refractory Acute Myeloid Leukemia to Chemotherapy
Bibliographic record
Abstract
Abstract Deep sequencing has revealed that epigenetic modifiers are the most mutated genes in acute myeloid leukemia (AML). Thus, elucidating epigenetic dysregulation in AML is crucial to understand disease mechanisms. Here, we demonstrate that metal response element binding transcription factor 2/polycomblike 2 (MTF2/PCL2) plays a fundamental role in the polycomb repressive complex 2 (PRC2) and that its loss elicits an altered epigenetic state underlying refractory AML. Unbiased systems analyses identified the loss of MTF2–PRC2 repression of MDM2 as central to, and therefore a biomarker for, refractory AML. Thus, immature MTF2-deficient CD34+CD38− cells overexpress MDM2, thereby inhibiting p53 that leads to chemoresistance due to defects in cell-cycle regulation and apoptosis. Targeting this dysregulated signaling pathway by MTF2 overexpression or MDM2 inhibitors sensitized refractory patient leukemic cells to induction chemotherapeutics and prevented relapse in AML patient-derived xenograft mice. Therefore, we have uncovered a direct epigenetic mechanism by which MTF2 functions as a tumor suppressor required for AML chemotherapeutic sensitivity and identified a potential therapeutic strategy to treat refractory AML. Significance: MTF2 deficiency predicts refractory AML at diagnosis. MTF2 represses MDM2 in hematopoietic cells and its loss in AML results in chemoresistance. Inhibiting p53 degradation by overexpressing MTF2 in vitro or by using MDM2 inhibitors in vivo sensitizes MTF2-deficient refractory AML cells to a standard induction-chemotherapy regimen. Cancer Discov; 8(11); 1376–89. ©2018 AACR. See related commentary by Duy and Melnick, p. 1348. This article is highlighted in the In This Issue feature, p. 1333
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".