Binding and internalization of NGR-peptide-targeted liposomal doxorubicin (TVT-DOX) in CD13-expressing cells and its antitumor effects
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Bibliographic record
Abstract
In an effort to develop new agents and molecular targets for the treatment of cancer, aspargine-glycine-arginine (NGR)-targeted liposomal doxorubicin (TVT-DOX) is being studied. The NGR peptide on the surface of liposomal doxorubicin (DOX) targets an aminopeptidase N (CD13) isoform, specific to the tumor neovasculature, making it a promising strategy. To further understand the molecular mechanisms of action, we investigated cell binding, kinetics of internalization as well as cytotoxicity of TVT-DOX in vitro. We demonstrate the specific binding of TVT-DOX to CD13-expressing endothelial [human umbilical vein endothelial cells (HUVEC) and Kaposi sarcoma-derived endothelial cells (SLK)] and tumor (fibrosarcoma, HT-1080) cells in vitro. Following binding, the drug was shown to internalize through the endosomal pathway, eventually leading to the localization of doxorubicin in cell nuclei. TVT-DOX showed selective toxicity toward CD13-expressing HUVEC, sparing the CD13-negative colon-cancer cells, HT-29. Additionally, the nontargeted counterpart of TVT-DOX, Caelyx, was less cytotoxic to the CD13-positive HUVECs demonstrating the advantages of NGR targeting in vitro. The antitumor activity of TVT-DOX was tested in nude mice bearing human prostate-cancer xenografts (PC3). A significant growth inhibition (up to 60%) of PC3 tumors in vivo was observed. Reduction of tumor vasculature following treatment with TVT-DOX was also apparent. We further compared the efficacies of TVT-DOX and free doxorubicin in the DOX-resistant colon-cancer model, HCT-116, and observed the more pronounced antitumor effects of the TVT-DOX formulation over free DOX. The potential utility of TVT-DOX in a variety of vascularized solid tumors is promising.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it