Cytoprotective effects of IAPs revealed by a small molecule antagonist
Bibliographic record
Abstract
Deregulated expression of members of the IAP (inhibitor of apoptosis) family has been identified in a wide variety of neoplastic cells, and synthetic IAP antagonists represent a promising novel class of chemotherapeutic agents. Early work focused on the ability of these compounds to block the caspase-inhibitory function of XIAP (X-linked IAP). However, recent studies have shown that IAP antagonists, although primarily designed to target XIAP, trigger ubiquitin-mediated degradation of two related proteins, c-IAP (cellular IAP) 1 and c-IAP2, and through this process potentiates the death of tumour cells via autocrine cellular-signalling pathways. In this context, the relative contribution of XIAP as a target of this class of compounds is unclear. In the present study, we examine the involvement of XIAP using a recently described synthetic IAP antagonist, AEG40730, and through comparison of a human XIAP-depleted tumour cell line with its isogenic wild-type control line. Treatment with nanomolar concentrations of AEG40730 resulted in the loss of both XIAP and c-IAP1 proteins, albeit with different kinetics. Although XIAP-deficient HCT116 cells retained some sensitivity to external apoptotic stimuli, the results suggest that IAP antagonists, such as AEG40730, exert their apoptosis-enhancing effects through XIAP in addition to the c-IAPs. These results indicate that IAP antagonists can target multiple IAPs to augment distinct pro-apoptotic signalling pathways, thereby revealing the potential for these compounds in cancer therapy and underscoring the promise of IAP-targeted therapies.
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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 | 0.000 |
| 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".