Lovastatin Induces a Pronounced Differentiation Response in Acute Myeloid Leukemias
Bibliographic record
Abstract
We recently identified HMG-CoA reductase, the rate-limiting enzyme of the mevalonate pathway, as a potential therapeutic target of various retinoic acid responsive cancers. Lovastatin, a competitive inhibitor of HMG-CoA reductase, induced a retinoic acid-like differentiation response followed by extensive apoptosis in neuroblastoma cell lines at relatively low concentrations (<20 microM) of this agent. More recently, we demonstrated that acute myeloid leukemias but not acute lymphocytic leukemias also displayed increased sensitivity to lovastatin-induced apoptosis. In this study, we examined the ability of lovastatin to induce differentiation of acute myeloid leukemic cells and to evaluate the role differentiation may hold in the anti-leukemic properties of this agent. Increased expression of the leukocyte integrins CD11b and CD18 as well as down-regulation of the anti-apoptotic gene bcl-2 are associated with late stage differentiation of the myeloid lineage and retinoic acid induced maturation of acute myeloid leukemic cells. Lovastatin exposure induced increased expression of CD11b and CD18 markers similar to retinoic acid treatment. Following 24 hrs exposure to 20 microM lovastatin, all 7 acute myeloid leukemia cell lines tested showed a decrease in bcl-2 mRNA expression while only 1/5 acute lymphocytic leukemia cell lines showed a similar response. A role for bcl-2 in the apoptotic response of acute myeloid leukemia cells to lovastatin was demonstrated as exogenous constitutive expression of bcl-2 in the AML-5 cell line inhibited apoptosis in a time and dose dependent manner. Thus, lovastatin exposure of acute myeloid leukemia cells induced a differentiation response that may contribute to the therapeutic potential of this agent in the treatment of this disease.
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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 | 0.001 |
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".