Functional Mimicry of an Anti‐idiotypic Antibody to Nominal Antigen on Cellular Response
Bibliographic record
Abstract
One concept for immune therapy of cancer involves induction of antigen mimic antibodies to trigger the immune system into a response against the tumor cells. Anti-idiotypic antibodies (Ab2) directed against the antigen-combining site of other antibodies (Ab1) may functionally and even structurally mimic antigen and induce anti-anti-idiotypic immune response. We report here the generation of murine monoclonal antibody (mAb) WJ02 (Ab2) raised against the murine monoclonal immunoglobulin MJ01 (Ab1), which defines ovarian cancer antigen CA125. In enzyme immunoassays the binding of Ab2 to the variable region of Ab1 could be inhibited by CA125. In addition, the mimicry of mAb WJ02 to CA125 on cellular immune response was detected by human peripheral blood cells. The T cells primed by mAb WJ02 or CA125 proliferated in the presence of CA125 or mAb WJ02, respectively. Furthermore, T cells specific to mAb WJ02 could lyse ovarian cancer cells OVCAR-3 that express CA125. Finally, we proved that a patient immunized with mAb MJ01 could induce T cells that recognize mAb WJ02. In summary, we conclude that mAb WJ02 mimics CA125 on cellular response and such functional mimicry is one of the most important criteria to select Ab2 for cancer therapy.
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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) | 0.002 | 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".