Preclinical Characterization of AEG35156/GEM 640, a Second-Generation Antisense Oligonucleotide Targeting X-Linked Inhibitor of Apoptosis
Bibliographic record
Abstract
PURPOSE: Cancer cells can use X-linked inhibitor of apoptosis (XIAP) to evade apoptotic cues, including chemotherapy. The antitumor potential of AEG35156, a novel second-generation antisense oligonucleotide directed toward XIAP, was assessed in human cancer models when given as a single agent and in combination with clinically relevant chemotherapeutics. EXPERIMENTAL DESIGN: AEG35156 was characterized for its ability to cause dose-dependent reductions of XIAP mRNA and protein in vitro and in vivo, to sensitize cancer cell lines to death stimuli, and to exhibit antitumor activity in multiple human cancer xenograft models as a single agent or in combination with chemotherapy. RESULTS: AEG35156 reduced XIAP mRNA levels with an EC50 of 8 to 32 nmol/L and decreased XIAP protein levels by >80%. Loss of XIAP protein correlated with increased sensitization to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-mediated apoptosis in Panc-1 pancreatic carcinoma cells. AEG35156 exhibited potent antitumor activity relative to control oligonucleotides in three human cancer xenograft models (prostate, colon, and lung) and was capable of inducing complete tumor regression when combined with taxanes. Antitumor effects of AEG35156 correlated with suppression of tumor XIAP levels. CONCLUSIONS: AEG35156 reduces XIAP levels and sensitizes tumors to chemotherapy. AEG35156 is presently under clinical assessment in multiple phase I trials in cancer patients as a single agent and in combination with docetaxel in solid tumors or cytarabine/idarubicin in leukemia.
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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 | 0.000 | 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".