Pre-targeted radioimmunotherapy of human colon cancer xenografts in athymic mice using streptavidin-CC49 monoclonal antibody and 90Y-DOTA-biotin
Bibliographic record
Abstract
Radioimmunotherapy of solid malignancies using directly labelled 90Y-monoclonal antibodies has been associated in clinical trials with dose-limiting bone marrow toxicity. Our objective in this study was to evaluate the efficacy and toxicity of an alternative two-step pre-targeted radioimmunotherapy protocol for the treatment of human colon cancer. The two-step protocol consisted of administration of the tumour-associated glycoprotein (TAG-72) monoclonal antibody CC49 conjugated to streptavidin, followed by administration of 90Y-DOTA-biotin. Swiss nu/nu athymic mice bearing subcutaneous LS174T human colon cancer xenografts were injected intraperitoneally with streptavidin-CC49 (250 micrograms), followed 40 h later by an intravenous injection of 90Y-DOTA-biotin (900 microCi, 40 micrograms). Tumour growth was measured over 25 days and compared with that in control mice receiving no treatment. Bone marrow and normal tissue toxicity was determined by peripheral blood leucocyte counts and by monitoring the body weight of the animals. Pre-targeted radioimmunotherapy resulted in a modest (30-40%) decrease in the mean tumour growth rate in treated mice compared to control animals. There was no change in body weight following treatment and peripheral blood leucocyte counts remained within the normal range. Pre-targeted radioimmunotherapy was safe at administered amounts of 90Y radioactivity, which were at least nine-fold higher than those previously determined to be lethal using directly labelled 90Y-monoclonal antibodies. The results of this study are promising for the application of pre-targeted radioimmunotherapy using streptavidin-CC49 and 90Y-DOTA-biotin for the treatment of advanced colorectal cancer in humans.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".