Linking Antibody Fc Domain to Endostatin Significantly Improves Endostatin Half-life and Efficacy
Bibliographic record
Abstract
PURPOSE: The half-life of the antiangiogenic molecule endostatin that has been used in clinical trial is short ( approximately 2 h). In addition, approximately 50% of the clinical grade endostatin molecules lack four amino acids at their NH(2) termini. Lack of these amino acids gives rise to a molecule that is devoid of zinc, resulting in no antitumor activity. Our goal was to develop a new version of endostatin that does not show such deficiency. EXPERIMENTAL DESIGN: A recombinant human endostatin conjugated to the Fc domain of IgG was constructed and expressed in mammalian cell culture. The presence of Fc has been shown by previous investigators to play a major role in increasing the half-life of the molecule. Fc-endostatin was tested in tumor-bearing mice, and its half-life was compared with the clinical grade endostatin. RESULTS: The antitumor dose of Fc-endostatin was found to be approximately 100 times less than the clinical grade endostatin. The half-life of Fc-endostatin in the circulation was found to be weeks rather than hours, as observed for endostatin alone. In addition, a U-shaped curve was observed for antitumor activity of endostatin as a function of endostatin concentration delivered to the animals. CONCLUSION: Fc-endostatin is a superior molecule to the original clinical endostatin. Due to its long half-life, the amount of protein required is substantially reduced compared with the clinically tested endostatin. Furthermore, in view of the U-shaped curve of efficacy observed for endostatin, we estimate that the requirement for Fc-endostatin is approximately 700-fold less than endostatin alone. The half-life of endostatin is similar to that of vascular endothelial growth factor-Trap and Avastin, two other antiangiogenic reagents. We conclude that a new clinical trial of endostatin, incorporating Fc, may benefit cancer patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".