RNA Silencing of Mcl-1 Enhances ABT-737-Mediated Apoptosis in Melanoma: Role for a Caspase-8-Dependent Pathway
Bibliographic record
Abstract
BACKGROUND: Malignant melanoma is resistant to almost all conventional forms of chemotherapy. Recent evidence suggests that anti-apoptotic proteins of the Bcl-2 family are overexpressed in melanoma and may contribute to melanoma's striking resistance to apoptosis. ABT-737, a small-molecule inhibitor of Bcl-2, Bcl-xl and Bcl-w, has demonstrated efficacy in several forms of leukemia, lymphoma as well as solid tumors. However, overexpression of Mcl-1, a frequent observance in melanoma, is known to confer ABT-737 resistance. METHODOLOGY/PRINCIPAL FINDINGS: Here we report that knockdown of Mcl-1 greatly reduces cell viability in combination with ABT-737 in six different melanoma cell lines. We demonstrate that the cytotoxic effect of this combination treatment is due to apoptotic cell death involving not only caspase-9 activation but also activation of caspase-8, caspase-10 and Bid, which are normally associated with the extrinsic pathway of apoptosis. Caspase-8 (and caspase-10) activation is abrogated by inhibition of caspase-9 but not by inhibitors of the death receptor pathways. Furthermore, while caspase-8/-10 activity is required for the full induction of cell death with treatment, the death receptor pathways are not. Finally, we demonstrate that basal levels of caspase-8 and Bid correlate with treatment sensitivity. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that the combination of ABT-737 and Mcl-1 knockdown represents a promising, new treatment strategy for malignant melanoma. We also report a death receptor-independent role for extrinsic pathway proteins in treatment response and suggest that caspase-8 and Bid may represent potential markers of treatment sensitivity.
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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) | 0.002 | 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".