Novel Neutralizing Hedgehog Antibody MEDI-5304 Exhibits Antitumor Activity by Inhibiting Paracrine Hedgehog Signaling
Bibliographic record
Abstract
The hedgehog pathway has been implicated in the tumorigenesis, tumor progression, and metastasis of numerous human cancers. We generated the first fully human hedgehog antibody MEDI-5304 and characterized its antitumor activity and preclinical toxicology. MEDI-5304 bound sonic hedgehog (SHH) and Indian hedgehog (IHH) with low picomolar affinity and neutralized SHH and IHH activity in cellular mGLI1 reporter assays. The antibody inhibited transcription of hedgehog target genes and osteoblast differentiation of C3H10T1/2 cells. We evaluated the activity of MEDI-5304 in vivo in model systems that allowed us to evaluate two primary hypotheses of hedgehog function in human cancer, paracrine signaling between tumor and stromal cells and cancer stem cell (CSC) self-renewal. MEDI-5304 displayed robust pharmacodynamic effects in stromal cells that translated to antitumor efficacy as a single agent in an HT-29/MEF coimplantation model of paracrine hedgehog signaling. MEDI-5304 also improved responses to carboplatin in the HT-29/MEF model. The antibody, however, had no effect as a single agent or in combination with gemcitabine on the CSC frequency or growth of several primary pancreatic cancer explant models. These findings support the conclusion that hedgehog contributes to tumor biology via paracrine tumor-stromal signaling but not via CSC maintenance or propagation. Finally, the only safety study finding associated with MEDI-5304 was ondontodysplasia in rats. Thus, MEDI-5304 represents a potent dual hedgehog inhibitor suitable for continued development to evaluate efficacy and safety in human patients with tumors harboring elevated levels of SHH or IHH.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".