Low‐dose triptolide enhances antitumor effect of JQ1 on acute myeloid leukemia through inhibiting RNA polymerase II in vitro and in vivo
Bibliographic record
Abstract
The bromodomain and extra-terminal (BET) domain inhibitor JQ1 exerts potent anticancer activity in various cancer cells. However, the resistance to BET inhibitors in leukemia stem cells limits its implication in acute myeloid leukemia (AML). High concentration of triptolide (TPL) presents anticancer activities but with adverse effects. Here, we investigated whether the combination of low-dose TPL with JQ1 could help to circumvent the dilemma of drug resistance and side effect in treating AML. AML cell lines, primary cells from 10 AML patients with different status, as well as AML mice model were subjected to different treatments and apoptotic related protein expression were evaluated. Data showed that low-dose TPL combined with JQ1 effectively killed AML cell lines and primary cells from AML patients without exerting significantly greater lethal activity against normal cells. Mechanism study revealed that low-dose TPL combined with JQ1 triggered reactive oxygen species production and induced mitochondrial-mediated apoptosis in AML cells, in which the inhibition of RNA polymerase II to downregulate c-Myc was mainly responsible for the enhanced activity of TPL in combination with JQ1. In vivo study presented that cotreatment with low-dose TPL and JQ1 significantly reduced tumor burden of the NOD/SCID mice engrafted with MOLM-13 cells. In conclusion, low-dose TPL enhanced the antitumor effect of JQ1 on AML without increasing the side effects, supporting a potential option for AML treatment.
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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 | 0.001 |
| 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".