Antibody recognition of a unique tumor-specific glycopeptide antigen
Bibliographic record
Abstract
Aberrant glycosylation and the overexpression of certain carbohydrate moieties is a consistent feature of cancers, and tumor-associated oligosaccharides are actively investigated as targets for immunotherapy. One of the most common aberrations in glycosylation patterns is the presentation of a single O-linked N-acetylgalactosamine on a threonine or serine residue known as the "Tn antigen." Whereas the ubiquitous nature of Tn antigens on cancers has made them a natural focus of vaccine research, such carbohydrate moieties are not always tumor-specific and have been observed on embryonic and nonmalignant adult tissue. Here we report the structural basis of binding of a complex of a monoclonal antibody (237mAb) with a truly tumor-specific glycopeptide containing the Tn antigen. In contrast to glycopeptide-specific antibodies in complex with simple peptides, 237mAb does not recognize a conformational epitope induced in the peptide by sugar substitution. Instead, 237mAb uses a pocket coded by germ-line genes to completely envelope the carbohydrate moiety itself while interacting with the peptide moiety in a shallow groove. Thus, 237mAb achieves its striking tumor specificity, with no observed physiological cross-reactivity to the unglycosylated peptide or the free glycan, by a combination of multiple weak but specific interactions to both the peptide and to the glycan portions of the antigen.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".