A non–RGD-based integrin binding peptide (ATN-161) blocks breast cancer growth and metastasis <i>in vivo</i>
Bibliographic record
Abstract
PURPOSE: Integrins are expressed by numerous tumor types including breast cancer, in which they play a crucial role in tumor growth and metastasis. In this study, we evaluated the ability of ATN-161 (Ac-PHSCN-NH2), a 5-mer capped peptide derived from the synergy region of fibronectin that binds to alpha5beta1 and alphavbeta3 in vitro, to block breast cancer growth and metastasis. EXPERIMENTAL DESIGN: MDA-MB-231 human breast cancer cells were inoculated s.c. in the right flank, or cells transfected with green fluorescent protein (MDA-MB-231-GFP) were inoculated into the left ventricle of female BALB/c nu/nu mice, resulting in the development of skeletal metastasis. Animals were treated with vehicle alone or by i.v. infusion with ATN-161 (0.05-1 mg/kg thrice a week) for 10 weeks. Tumor volume was determined at weekly intervals and tumor metastasis was evaluated by X-ray, microcomputed tomography, and histology. Tumors were harvested for histologic evaluation. RESULT: Treatment with ATN-161 caused a significant dose-dependent decrease in tumor volume and either completely blocked or caused a marked decrease in the incidence and number of skeletal as well as soft tissue metastases. This was confirmed histologically as well as radiographically using X-ray and microcomputed tomography. Treatment with ATN-161 resulted in a significant decrease in the expression of phosphorylated mitogen-activated protein kinase, microvessel density, and cell proliferation in tumors grown in vivo. CONCLUSION: These studies show that ATN-161 can block breast cancer growth and metastasis, and provides a rationale for the clinical development of ATN-161 for the treatment of breast cancer.
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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 | 0.001 |
| 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".