A synthetic anti-Frizzled antibody engineered for broadened specificity exhibits enhanced anti-tumor properties
Bibliographic record
Abstract
Secreted Wnt ligands play a major role in the development and progression of many cancers by modulating signaling through cell-surface Frizzled receptors (FZDs). In order to achieve maximal effect on Wnt signaling by targeting the cell surface, we developed a synthetic antibody targeting six of the 10 human FZDs. We first identified an anti-FZD antagonist antibody (F2) with a specificity profile matching that of OMP-18R5, a monoclonal antibody that inhibits growth of many cancers by targeting FZD7, FZD1, FZD2, FZD5 and FZD8. We then used combinatorial antibody engineering by phage display to develop a variant antibody F2.A with specificity broadened to include FZD4. We confirmed that F2.A blocked binding of Wnt ligands, but not binding of Norrin, a ligand that also activates FZD4. Importantly, F2.A proved to be much more efficacious than either OMP-18R5 or F2 in inhibiting the growth of multiple RNF43-mutant pancreatic ductal adenocarcinoma cell lines, including patient-derived cells.
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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) | 0.001 | 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) | 0.001 | 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".