Homoharringtonine interacts synergistically with bortezomib in NHL cells through MCL-1 and NOXA-dependent mechanisms
Bibliographic record
Abstract
BACKGROUND: Interactions between the protein synthesis inhibitor homoharringtonine (HHT) and the proteasome inhibitor bortezomib were investigated in DLBCL and mantle cell lymphoma cells (MCL). METHODS: Various DLBCL and MCL cells were exposed to HHT and bortezomib alone or together after which apoptosis and signaling pathway perturbations were monitored by flow cytometry and Western blot analysis. Xenograft mouse models were used to assess tumor growth and animal survival. RESULTS: HHT and bortezomib co-administration synergistically induced apoptosis in GC-, ABC- and double-hit DLBCL cells. Similar interactions were observed in MCL cells and in primary lymphoma cells. HHT/bortezomib co-administration diminished binding of MCL-1 to both BAK and NOXA. Knock-down of NOXA significantly diminished lethality whereas MCL-1 knock-down or ectopic NOXA expression increased cell death. Notably, HHT/bortezomib lethality was dramatically reduced in BAK knockout or knockdown cells. Finally, HHT/bortezomib co-administration significantly improved survival compared to single agents in GC- and ABC- xenograft models while exhibiting little toxicity. CONCLUSIONS: These findings indicate that HHT and bortezomib cooperate to kill DLBCL and MCL cells through a process involving MCL-1 down-regulation, NOXA up-regulation, and BAK activation. They also suggest that a strategy combining HHT with bortezomib warrants attention in DLBCL and MCL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".