Inhibition of Peroxisome Proliferation-Activated Receptor Delta (PPARδ) Selectively Kills Acute Myeloid Leukemia Cells
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is a devastating hematological malignancy with limited therapeutic options and poor survival outcomes. Therefore, developing novel and selective anti-AML therapies are needed. Our group recently identified 6-methoxydihydroavicine (6ME), a benzophenanthridine alkaloid commonly found in the Papaveraceae family, as a novel and selective anti-AML drug that binds to and inhibits peroxisome proliferation-activated receptor delta (PPARδ). PPARδ, along with the other two PPAR isoforms, PPARα and PPARγ, belongs to a family of ligand-dependent transcription factors that regulate a variety of important genes involved in various biological pathways, including glucose and lipid homeostasis, inflammation, proliferation, and differentiation. While PPARα and PPARγ have been extensively characterized in leukemia, little is known about PPARδ. Here, we show that 6ME is a novel and selective anti-AML molecule that targets the PPARδ-FAO pathway, suggesting PPARδ may be a potential therapeutic target for AML treatment. 6ME suppressed clonogenic growth of patient-derived AML cells (IC50: 2.025 ± 0.187 μM) while having no effect on normal hematopoietic cells. In mouse engraftment studies, where patient-derived AML cells are engrafted into the mouse bone, 6ME (5 mg/kg, three times/week for 4 weeks) was given after a 3-week post-transplantation of patient cells into immunocompromised mice, once bone marrow aspirate engraftment was confirmed. The subsequent 4-week treatment with 6ME significantly reduced patient-derived AML cell engraftment in mouse bone marrow by about 45% (p<0.0001) without imparting toxicity. Using published computational methods, the family of PPAR transcription factors were identified as potential targets of 6ME. To confirm this potential mechanism, cell-based luciferase reporter assays, immunoblotting and co-immunoprecipitation (co-IP) coupled with ultra-high performance liquid chromatography (UHPLC) assay were performed to confirm that 6ME bound to PPARδ and inhibited its activity. To further study this interaction, we quantified downstream targets of PPARδ-transcriptional activity in 6ME-treated AML cells by immunoblotting; this showed that PPARδ-related genes including CD36, CPT2, UCP3, and PPARδ itself were significantly reduced by 6ME. Finally, shRNA-mediated PPARδ knockdown (KD) AML cells were created to probe the functional impact of PPARδ in AML cells. As expected, PPARδ KD AML cells were much less sensitive to 6ME, and those cells with reduced PPARδ resulted in a similar pattern of protein changes to that of 6ME-treated cells. As 6ME reduced levels of CD36, CPT2, UCP3, and PPARδ, which are all essential proteins involved in fatty acid oxidation (FAO), we measured FAO in AML cells using high-resolution respirometry. When provided with an FAO substrate (palmitate-BSA), 6ME significantly hindered oxygen flux of intact AML cells, indicating that 6ME impairs FAO-supported mitochondrial respiration. Similarly, treatment with a PPARδ antagonist (i.e., GSK0660) but not an agonist (i.e., GW0742), also resulted in the inhibition of FAO-supported intact AML cell respiration, suggesting 6ME targets PPARδ to impair mitochondrial FAO. Taken together, our 6ME targets the PPARδ-FAO pathway and may open a new avenue for therapeutic targeting in the treatment of AML.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".