Lovastatin inhibits erythroleukemia progression through KLF2-mediated suppression of MAPK/ERK signaling
Bibliographic record
Abstract
Abstract Background Lovastatin, an HMG-CoA inhibitor and an effective cholesterol lowering drug, exhibits anti-neoplastic activity towards several types of cancer, although the underlying mechanism is still not fully understood. Herein, we investigated mechanism of growth inhibition of leukemic cells by lovastatin. Methods RNAseq analysis was used to explore the effect of lovastatin on gene expression in leukemic cells. An animal model of leukemia was used to test the effect of this statin in vivo. FAM83A and DDIT4 expression was knocked-downed in leukemia cells via lentivirus-shRNA. Western blotting, RT-qPCR, cell cycle analysis and apoptosis assays were used to determine the effect of lovastatin-induced growth suppression in leukemic cells in vitro. Results Lovastatin treatment strongly inhibited cancer progression in a mouse model of erythroleukemia induced by Friend virus. In tissue culture, lovastatin inhibited cell proliferation through induction of G1 phase cell cycle arrest and apoptosis. Interestingly, lovastatin induced most known genes associated with cholesterol biosynthesis in leukemic cells. Moreover, it suppressed ERK1/2 phosphorylation by downregulating FAM83A and DDIT4, two mediators of MAP-Kinase signaling. RNAseq analysis of lovastatin treated leukemic cells revealed a strong induction of the tumor suppressor gene KLF2. Accordingly, lentivirus-mediated knockdown of KLF2 antagonized leukemia cell suppression induced by lovastatin, associated with higher ERK1/2 phosphorylation compared to control. We further show that KLF2 induction by lovastatin is responsible for lower expression of the FAM83A and DDIT4 oncogenes, involved in the activation of ERK1/2. KLF2 activation by lovastatin also activated a subset of cholesterol biosynthesis genes that may further contribute to leukemia suppression. Conclusions These results implicate KLF2-mediated FAM83A/DDIT4/MAPK suppression and activation of cholesterol biosynthesis as the mechanism of leukemia cell growth inhibition by lovastatin.
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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".