Mcl-1 Down-regulation Potentiates ABT-737 Lethality by Cooperatively Inducing Bak Activation and Bax Translocation
Bibliographic record
Abstract
The Bcl-2 antagonist ABT-737 targets Bcl-2/Bcl-xL but not Mcl-1, which may confer resistance to this novel agent. Here, we show that Mcl-1 down-regulation by the cyclin-dependent kinase (CDK) inhibitor roscovitine or Mcl-1-shRNA dramatically increases ABT-737 lethality in human leukemia cells. ABT-737 induces Bax conformational change but fails to activate Bak or trigger Bax translocation. Coadministration of roscovitine and ABT-737 untethers Bak from Mcl-1 and Bcl-xL, respectively, triggering Bak activation and Bax translocation. Studies employing Bax and/or Bak knockout mouse embryonic fibroblasts (MEFs) confirm that Bax is required for ABT-737+/-roscovitine lethality, whereas Bak is primarily involved in potentiation of ABT-737-induced apoptosis by Mcl-1 down-regulation. Ectopic Mcl-1 expression attenuates Bak activation and apoptosis by ABT-737+roscovitine, whereas cells overexpressing Bcl-2 or Bcl-xL remain fully sensitive. Finally, Mcl-1 knockout MEFs are extremely sensitive to Bak conformational change and apoptosis induced by ABT-737, effects that are not potentiated by roscovitine. Collectively, these findings suggest down-regulation of Mcl-1 by either CDK inhibitors or genetic approaches dramatically potentiate ABT-737 lethality through cooperative interactions at two distinct levels: unleashing of Bak from both Bcl-xL and Mcl-1 and simultaneous induction of Bak activation and Bax translocation. These findings provide a mechanistic basis for simultaneously targeting Mcl-1 and Bcl-2/Bcl-xL in leukemia.
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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) | 0.001 | 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) | 0.002 | 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".