Chimeric Antibody c.8B6 to O-Acetyl-GD2 Mediates the Same Efficient Anti-Neuroblastoma Effects as Therapeutic ch14.18 Antibody to GD2 without Antibody Induced Allodynia
Bibliographic record
Abstract
BACKGROUND: Anti-GD2 antibody is a proven therapy for GD2-positive neuroblastoma. Monoclonal antibodies against GD2, such as chimeric mAb ch14.18, have become benchmarks for neuroblastoma therapies. Pain, however, can limit immunotherapy with anti-GD2 therapeutic antibodies like ch14.18. This adverse effect is attributed to acute inflammation via complement activation on GD2-expressing nerves. Thus, new strategies are needed for the development of treatment intensification strategies to improve the outcome of these patients. METHODOLOGY/PRINCIPAL FINDINGS: We established the mouse-human chimeric antibody c.8B6 specific to OAcGD2 in order to reduce potential immunogenicity in patients and to fill the need for a selective agent that can kill neuroblastoma cells without inducing adverse neurological side effects caused by anti-GD2 antibody immunotherapy. We further analyzed some of its functional properties compared with anti-GD2 ch14.18 therapeutic antibody. With the exception of allodynic activity, we found that antibody c.8B6 shares the same anti-neuroblastoma attributes as therapeutic ch14.18 anti-GD2 mAb when tested in cell-based assay and in vivo in an animal model. CONCLUSION/SIGNIFICANCE: The absence of OAcGD2 expression on nerve fibers and the lack of allodynic properties of c.8B6-which are believed to play a major role in mediating anti-GD2 mAb dose-limiting side effects-provide an important rationale for the clinical application of c.8B6 in patients with high-risk neuroblastoma.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".