Bortezomib induces apoptosis via Bim and Bik up-regulation and synergizes with cisplatin in the killing of head and neck squamous cell carcinoma cells
Bibliographic record
Abstract
Head and neck squamous cell carcinomas (HNSCC) are characterized by resistance to chemotherapy and overexpression of antiapoptotic Bcl-2 family members, including Bcl-X(L) and Bcl-2. Molecular targeting of Bcl-X(L) and/or Bcl-2 in HNSCC cells has been shown to promote apoptosis signaling and to sensitize cells to chemotherapy drugs, including cisplatin, which is commonly used in the treatment of HNSCC. We report that induction of HNSCC apoptosis by the proteasome inhibitor bortezomib is accompanied by up-regulation of the proapoptotic proteins Bik and Bim, natural cellular inhibitors of Bcl-X(L) and Bcl-2. Additionally, bortezomib treatment of HNSCC cells caused up-regulation of antiapoptotic Mcl-1L. Inhibition of Bik or Bim up-regulation using small interfering RNA markedly attenuated bortezomib-induced cell death. By contrast, small interfering RNA-mediated inhibition of Mcl-1L expression resulted in enhanced killing by bortezomib. Further investigation showed that the combination of bortezomib and cisplatin led to synergistic killing of HNSCC cells, with calculated combination indexes well below 1.0. Taken together, these results delineate a novel mechanism of HNSCC killing by bortezomib that involves up-regulation of Bik and Bik. Moreover, our findings suggest that the combination of bortezomib plus cisplatin, or bortezomib plus an inhibitor of Mcl-1L, may have therapeutic value in the treatment of HNSCC.
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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) | 0.001 | 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".