Diosmetin: An Anti‐Leukemic Flavonoid Targeting the Estrogen Receptor β
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is an aggressive hematological malignancy resulting from the accumulation of immature myeloid cells in the peripheral blood and bone marrow. It is associated with poor prognosis, especially in older patients where the 2‐year survival rate is approximately 10%. Leukemia stem cells (LSCs) are the cells responsible for AML development. To prevent relapse and improve patient prognosis, new therapies targeting LSCs are needed. Thus, to identify novel anti‐AML agents, we created a unique library consisting of food‐derived bioactive compounds (i.e., nutraceuticals). We screened this library (n= 288) using the MTS assay against TEX cells, a surrogate LSC line. Among the 288 compounds, diosmetin, a flavonoid derived from various citrus fruits, was found to be the most potent (EC50: 6.1 ± 0.5 μM, p<0.001). Most importantly, diosmetin did not affect the non‐LSC K562 cells, suggesting that diosmetin may selectively target leukemia stem cells. This was further demonstrated by clonogenic growth assays which showed that diosmetin (10 μM) reduced clonogenic growth in primary AML patient samples (n=6) but not in CD34+ normal hematopoietic cells (n=3). Finally, AML mouse xenografts showed that, compared to vehicle control, diosmetin treated mice had slower tumor growth and reduced tumor weights up on sacrifice (p<0.01). Collectively, this highlights diosmetin as a novel and selective anti‐AML agent. Diosmetin induced caspase 3 mediated apoptosis, as determined by caspase activation, Annexin V/Propidium iodide and DNA fragmentation assays. To identify diosmetin's molecular target we utilized online bioinformatics tools (e.g., protein data base, PoSSuM and DAVID tool), which identified the estrogen receptor (ER) as diosmetin's potential molecular target. To assess the cell and molecular role of ERs, we measured ERα and ERβ levels in diosmetin sensitive and insensitive cell lines. Interestingly, diosmetin sensitive cell lines (TEX, LP1) display significantly elevated ERβ protein and mRNA levels (4 fold, as determined by Western blotting and qtPCR, respectively) compared to diosmetin insensitive cell lines (K562, DU145). This pattern was not observed for ERα. Furthermore, this ER expression pattern was also observed in patient‐derived AML cells, as cells sensitive to diosmetin displayed elevated ERβ, but not ERα, mRNA. Genetic knockdown using shRNA confirmed that ERβ is diosmetin's target, as cells lacking ERβ were resistant to diosmetin. Finally, ER reporter assays demonstrated that diosmetin binds and acts as an agonist in ERβ but not ERα reporter cells. Together, these results show that diosmetin binds to ERβ and that ERβ is functionally important to diosmetin's activity. In summary, these studies highlight diosmetin binding to ERβ as a potential novel strategy for the treatment of AML. Support or Funding Information Stem Cell Network, University of Waterloo
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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) | 0.001 | 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".