Comparison of immunoscintigraphy, efficacy, and toxicity of conventional and pretargeted radioimmunotherapy in CD20-expressing human lymphoma xenografts.
Bibliographic record
Abstract
UNLABELLED: Pretargeted radioimmunotherapy (RIT) using streptavidin (sAv)-conjugated antibodies before radiolabeled-biotin is a promising approach to improve absorbed dose ratios and achieve high durable remission rates with diminished systemic toxicity. This study compared the immunoscintigraphy, toxicity, and therapeutic efficacy of pretargeted RIT with conventional RIT using an anti-CD20 antibody. METHODS: Athymic mice bearing Ramos human Burkitt's lymphoma xenografts were injected intraperitoneally with a 1F5-sAv conjugate followed 24 h later by a galactosylated, biotinylated clearing agent (CA) and, finally, 3 h later by (111)In- or (90)Y-labeled 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)-biotin. The comparison groups consisted of mice injected with conventional, directly labeled (111)In- or (90)Y-1F5. RESULTS: Rapid tumor uptake of radioactivity within 2 h was observed with the pretargeting approach, resulting in high-contrast tumor images at 24 h with minimal blood-pool radioactivity. Although conventional radiolabeled antibodies produced clear tumor images at 24 h, a large amount of radioactivity was present in the blood pool. The tumor-to-blood ratio was 3.5:1 with pretargeting compared with 0.4:1 with conventional (111)In-1F5. Pretargeted RIT with 29.6 MBq (800 micro Ci) (90)Y-DOTA-biotin cured 100% of mice with tolerable toxicity, whereas conventional RIT with (90)Y-1F5 at a dose of 14.8 MBq (400 micro Ci) produced no cures, induced profound pancytopenia, and was lethal to all mice. CONCLUSION: These results suggest that anti-CD20 pretargeted RIT may be superior to conventional radiolabeled antibodies in terms of radioimmunoscintigraphy, toxicity, and therapeutic efficacy for treatment of B-cell lymphomas.
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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) | 0.000 | 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 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".