Abstract 139: The identification of potent inhibitor of apoptosis protein (IAP) inhibitors for clinical development
Bibliographic record
Abstract
Abstract The inhibitor of apoptosis proteins (IAPs) are important regulators of cell death. Over-expression of IAPs, including XIAP, cIAP1 and cIAP2, predicts poor patient outcome in several types of cancer. XIAP binds to and inhibits caspases 3, 7 and 9. Inhibition of IAP function can enhance cell death in tumor cells. Inhibition of IAPs is being explored clinically with XIAP anti-sense (AEG35156) and small molecule inhibitor (HGS1029) strategies. We describe small molecule inhibitors of the IAPs that have been designed to bind to the homologous BIR3 domains on the IAPs, which is the site of binding of second mitochondria-derived activator of caspase (SMAC). Structure-activity trends of IAP inhibitors were evaluated for binding potency and selectivity towards IAP BIR domains and analyzed for their ability to sensitize cancer cells to death alone or in conjunction with the agonistic TRAIL receptor 1 monoclonal antibody, mapatumumab, or chemotherapeutic agents. Bridging selected compounds at various sites led to compounds with binding affinities for IAPs in the picomolar range. In cellular assays, IAP inhibitor compounds caused rapid and robust loss of cIAP1, consistent with stimulation of E3 ligase activity. In vitro cytotoxicity assays demonstrated sensitization of tumor cell lines to co-treatment with mapatumumab or chemotherapy at low nanomolar concentrations. In vitro ADME studies were conducted in multiple species to select stable molecules which were negative in CYP and hERG binding assays. Selected compounds had high protein binding in plasma from multiple species. IV administration in mice resulted in Cmax values in excess of the EC50 required for cancer cell death in vitro. Efficacy of lead compounds was demonstrated against several xenograft tumor models as single agents and in combination with either mapatumumab or conventional chemotherapeutics. This led to the identification of a highly potent compound series from which a clinical development candidate, HGS1029, was selected. Solid tumor and lymphoid malignancies Phase 1 cancer trials with HGS1029 have been initiated. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 139.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".