Histone H3 Methylation Mediates All-Trans-Retinoic Acid Responsiveness in Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Abstract 224 During hematopoiesis, all-trans-retinoic acid (ATRA), a natural derivative of vitamin A, has been shown to induce both myelomonocytic progenitor/stem cell differentiation and self-renewal. Although these opposing effects are likely to be partly due to developmental differences, it has been shown that pro- and anti-differentiation effects of ATRA are mediated by distinct retinoic acid receptor isotypes (RARα and RARγ, respectively). With the exception of acute promyelocytic leukemia (APL), ATRA treatment as a single agent has not been successful in other types of acute myeloid leukemia (AML). We have previously hypothesized that one of the underlying reasons for poor response of non-APL AML to ATRA (pan-RAR agonist) is aberrant expression and/or activities of RAR isotypes favoring RARγ and cell growth versus differentiation. Consistently, we have reported that expression of RARα isoforms, particularly ATRA-inducible RARα2, are down-regulated in AML (Blood. 2008; 111:2374). Epigenetic analysis of patient samples revealed that relative to normal CD33+ cells, the loss of RARα2 in AML is associated with a diminution in levels of histone histone H3 lysine 4 dimethylation (H3K4me2) on the ATRA-responsive RARA2 promoter (a modification associated with transcriptional activation). Interestingly, the H3K4me1/me2 demethylase LSD1/KDM1 (AOF2) is highly expressed in AML patients (www.proteinatlas.org). A number of small molecules that target this enzyme (LSD1i) are in development and, collectively, these data predict that the use of LSD1i will facilitate induction of expression of genes that are required for differentiation of AML cells. In this study we used tranylcypromine (TCP, a monoamine oxidase used as an antidepressant and anxiolytic agent in the clinical treatment of mood and anxiety disorders, respectively), which functions a time-dependent, mechanism-based inhibitor of LSD1. Here we show that TCP unlocked the ATRA-driven therapeutic differentiation response in non-APL AML cell lines including the TEX cell line, which is derived from primitive human cord blood cells immortalized by expression of the TLS-ERG oncogene. TEX cells are >90% CD34+, respond poorly to ATRA and mimic features of primary human AML and leukemia initiating cells (Leukemia. 2005; 19:1794). Consistent with this, ATRA/TCP treatment increased differentiation in primary patient samples. ATRA alone had in general only small effects in primary AML samples and TCP showed minimal activity in most cases. Furthermore, shRNA-mediated knockdown of LSD1 confirmed a critical role for this enzyme in blocking the ATRA response in AML cells. The effects of ATRA/TCP on AML cell maturation were paralleled by enhanced induction of genes associated with myelomonocytic differentiation, including direct ATRA targets. LSD1i treatment did not lead to an increase in genome-wide H3K4me2, but did increase H3K4 dimethylation of myelomonocytic differentiation-associated genes. Importantly, treatment with ATRA/TCP dramatically diminished the clonogenic capacity of AML cells in vitro and engraftment of cells derived from AML patients in vivo, suggesting that ATRA/TCP may also target leukemic stem cells. These data strongly suggest that LSD1 may, at least in part, contribute to AML pathogenesis by inhibiting the normal function of ATRA in myelomonocytic development and pave the way for effective differentiation therapy of AML. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".