Structure-guided design fine-tunes pharmacokinetics, tolerability, and antitumor profile of multispecific frizzled antibodies
Bibliographic record
Abstract
Aberrant activation of Wnt/β-catenin signaling occurs frequently in cancer. However, therapeutic targeting of this pathway is complicated by the role of Wnt in stem cell maintenance and tissue homeostasis. Here, we evaluated antibodies blocking 6 of the 10 human Wnt/Frizzled (FZD) receptors as potential therapeutics. Crystal structures revealed a common binding site for these monoclonal antibodies (mAbs) on FZD, blocking the interaction with the Wnt palmitoleic acid moiety. However, these mAbs displayed gastrointestinal toxicity or poor plasma exposure in vivo. Structure-guided engineering was used to refine the binding of each mAb for FZD receptors, resulting in antibody variants with improved in vivo tolerability and developability. Importantly, the lead variant mAb significantly inhibited tumor growth in the HPAF-II pancreatic tumor xenograft model. Taken together, our data demonstrate that anti-FZD cancer therapeutic antibodies with broad specificity can be fine-tuned to navigate in vivo exposure and tolerability while driving therapeutic efficacy.
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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) | 0.001 | 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".