Enhanced Antitumor Efficacy of Clinical-Grade Vasculature-Targeted Liposomal Doxorubicin
Bibliographic record
Abstract
PURPOSE: In vivo evaluation of good manufacturing practice-grade targeted liposomal doxorubicin (TVT-DOX), bound to a CD13 isoform expressed on the vasculature of solid tumors, in human tumor xenografts of neuroblastoma, ovarian cancer, and lung cancer. EXPERIMENTAL DESIGN: Mice were implanted with lung, ovarian, or neuroblastoma tumor cells via the pulmonary, peritoneal, or orthotopic (adrenal gland) routes, respectively, and treated, at different days post inoculation, with multiple doses of doxorubicin, administered either free or encapsulated in untargeted liposomes (Caelyx) or in TVT-DOX. The effect of TVT-DOX treatment on tumor cell proliferation, viability, apoptosis, and angiogenesis was studied by immunohistochemical analyses of neoplastic tissues and using the chick embryo chorioallantoic membrane assay. RESULTS: Compared with the three control groups (no doxorubicin, free doxorubicin, or Caelyx), statistically significant improvements in survival was seen in all three animal models following treatment with 5 mg/kg (maximum tolerated dose) of TVT-DOX, with long-term survivors occurring in the neuroblastoma group; increased survival was also seen at a dose of 1.7 mg/kg in mice bearing neuroblastoma or ovarian cancer. Minimal residual disease after surgical removal of neuroblastoma primary mass, and the enhanced response to TVT-DOX, was visualized and quantified by bioluminescence imaging and with magnetic resonance imaging. When treated with TVT-DOX, compared with Caelyx, all three tumor models, as assayed by immunohistochemistry and chorioallantoic membrane, showed statistically significant reductions in cell proliferation, blood vessel density, and microvessel area, showing increased cell apoptosis. CONCLUSION: TVT-DOX should be evaluated as a novel angiostatic strategy for adjuvant therapy of solid tumors.
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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 | 0.000 |
| 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".