Unique Biology of Mcl-1: Therapeutic Opportunities in Cancer
Bibliographic record
Abstract
Accumulating evidence suggests that Mcl-1 plays a critical pro-survival role in the development and maintenance of both normal and malignant tissues. Regulation of Mcl-1 expression occurs at multiple levels, allowing for either the rapid induction or elimination of the protein in response to different cellular events. This suggests that Mcl-1 can play an early role in response to signals directing either cell survival or cell death. Deregulation of pathways regulating Mcl-1 that result in its over-expression likely contribute to a cell's inability to properly respond to death signals possibly leading to cell immortalization and tumorigenic conversion. Correspondingly, Mcl-1 has been shown to be up-regulated in numerous hematological and solid tumor malignancies. Moreover, this up-regulation appears to be a factor in the resistance of some cancer types to conventional cancer therapies. Mechanisms that abrogate the pro-survival function of Mcl-1 either by diminishing its levels or inactivating its functional BH3 groove have shown promise for the combinational treatment with existing cancer therapies and as single agents in certain malignancies. Here we review the various pathways that regulate Mcl-1 expression and describe agents that are currently under development to modulate Mcl-1 activity for therapeutic benefit in oncology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".