Response to histone deacetylase inhibition of novel PML/RARα mutants detected in retinoic acid–resistant APL cells
Bibliographic record
Abstract
Resistance to all-trans retinoic acid (ATRA) remains a clinical problem in the treatment of acute promyelocytic leukemia (APL) and provides a model for the development of novel therapies. Molecular alterations in the ligand-binding domain (LBD) of the PML/RARalpha fusion gene that characterizes APL constitute one mechanism of acquired resistance to ATRA. We identified missense mutations in PML/RARalpha from an additional ATRA-resistant patient at relapse and in a novel ATRA-resistant cell line, NB4-MRA1. These cause altered binding to ligand and transcriptional coregulators, leading to a dominant-negative block of transcription. These mutations are in regions of the LBD that appear to be mutational hot spots occurring repeatedly in ATRA-resistant APL patient cells. We evaluated whether histone deacetylase (HDAC) inhibition could overcome the effects of these mutations on ATRA-induced gene expression. Cotreatment with ATRA and TSA restored RARbeta gene expression in NB4-MRA1 cells, whose PML/RARalpha mutation is in helix 12 of the LBD, but not in an APL cell line harboring the patient-derived PML/RARalpha mutation, which was between helix 5 and 6. Furthermore, ATRA combined with TSA increases histone 4 acetylation on the RARbeta promoter only in NB4-MRA1 cells. Consistent with these results, the combined treatment induces differentiation of NB4-MRA1 only. Thus, the ability of an HDAC inhibitor to restore ATRA sensitivity in resistant cells may depend on their specific molecular defects. The variety of PML/RARalpha mutations arising in ATRA-resistant patients begins to explain how APL patients in relapse may differ in response to transcription therapy with HDAC inhibitors.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".