Pharmacology of the Novel Antiangiogenic Peptide ATN-161 (Ac-PHSCN-NH2): Observation of a U-Shaped Dose-Response Curve in Several Preclinical Models of Angiogenesis and Tumor Growth
Bibliographic record
Abstract
PURPOSE: ATN-161 (Ac-PHSCN-NH(2)) is an integrin-binding peptide that is currently in phase II trials in cancer patients. This peptide has been shown to have antitumor activity in a number of different preclinical models. EXPERIMENTAL DESIGN: In this study, we examined the binding, biodistribution, and dose and biomarker response of ATN-161 in several animal models. RESULTS: ATN-161 bound to the beta subunit of a number of different integrins implicated in tumor growth and progression, which depended on its cysteine thiol. The peptide had antiangiogenic activity in the Matrigel plug model, and this activity could be reversed by inhibitors of protein kinase A, an effector of alpha(5)beta(1)-dependent angiogenesis. A labeled analogue of ATN-161, ATN-453, localized to neovessels but not to preexisting vasculature in vivo. The half-life of the peptide when localized to a tumor was much longer than in plasma. Dose-response studies in the Matrigel plug model of angiogenesis or a Lewis lung carcinoma model of tumor growth showed a U-shaped dose-response curve with 1 to 10 mg/kg given thrice a week, being the optimal dose range of ATN-161. Two additional pharmacodynamic models of angiogenesis (dynamic contrast-enhanced magnetic resonance imaging and measurement of endothelial cell progenitors) also revealed U-shaped dose-response curves. CONCLUSIONS: The presence of a U-shaped dose-response curve presents a significant challenge to identifying a biologically active dose of ATN-161. However, the identification of biomarkers of angiogenesis that also exhibit this same U-shaped response should allow the translation of those biomarkers to the clinic, allowing them to be used to identify the active dose of ATN-161 in phase II studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".