Large-scale synthesis and structural analysis of a synthetic glycopeptide dendrimer as an anti-cancer vaccine candidate
Bibliographic record
Abstract
T-cell epitopes. The synthetic process involves (i) the stepwise solid-phase assembly of protected amino acids, including the high value-added Tn building blocks with only 1.5 equivalents, (ii) a single isolated intermediate, and (iii) the simultaneous deprotection of 36 hindered protective groups. The resulting MAG-Tn3 was unambiguously characterized using a combination of techniques, including a structural analysis by nuclear magnetic resonance spectroscopy. The four peptidic chains are flexible in solution, with a more constrained but extended conformation at the Tn3 antigen motif. Finally, we demonstrate that, when injected into HLA-DR1-expressing transgenic mice, this vaccine induces Tn-specific antibodies that mediate the killing of human Tn-positive tumor cells. These studies led to a clinical batch of the MAG-Tn3, currently investigated in breast cancer patients (phase I clinical trial). The current study demonstrates the feasibility of the multigram-scale synthesis of a highly pure complex glycopeptide, and it opens new avenues for the use of synthetic glycopeptides as drugs in humans.
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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) | 0.001 | 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".