Abstract 864: ANG4043: A new brain-penetrant peptide-antibody conjugate that reduces tumor growth in a HER2-positive orthotopic tumor model.
Bibliographic record
Abstract
Abstract While monoclonal antibodies to receptor tyrosine kinases such as HER2 have been demonstrated to reduce tumor size and increase survival, these agents achieve little to no brain penetration, making them ineffective against metastatic brain tumors. The blood-brain barrier (BBB), which restricts entry of proteins such as mAbs into the brain, is comprised of capillary endothelial cells with tight junctions and efflux pumps. Brain entry of nutrients, hormones, and other required molecules is accomplished by processes such as receptor-mediated transcytosis. As low-density lipoprotein receptor-related protein 1 (LRP1) is known to perform this function in BBB endothelial cells, we have created a family of peptides (Angiopeps) designed for LRP1 recognition. These proprietary Angiopeps can be used to create novel Peptide-Drug Conjugates that successfully cross the BBB by LRP1-mediated transcytosis. Here we describe chemical conjugation of Angiopep-2 (An2) to a mAb against HER2. This Peptide-Antibody Conjugate, ANG 4043, displays HER2 binding affinity and in vitro cytotoxic potency similar to that of native anti-HER2. ANG4043 demonstrates a high rate of entry into the brain, consistent with achieving therapeutic concentrations. The plasma half-life of ANG4043 is similar to that of Anti-HER2 in mouse. Mice with intracranially implanted BT-474 cells showed reduced brain tumor size when dosed with ANG4043 compared to controls. Overall, these data demonstrate that a brain-penetrant Peptide-Antibody Conjugate is efficacious in a mouse HER2-positive tumor model. These results extend the validation of An2 conjugation beyond small molecules and peptides to include larger molecules such as therapeutic mAbs for development of new brain-penetrant antitumor therapeutics. Citation Format: Jean E. Lachowicz, Michel Demeule, Christian Che, Sasmita Tripathy, Jean-Christophe Currie, Anthony Regina, Tran Nguyen, Simon Lord-Dufour, Jean-Paul Castaigne. ANG4043: A new brain-penetrant peptide-antibody conjugate that reduces tumor growth in a HER2-positive orthotopic tumor model. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 864. doi:10.1158/1538-7445.AM2013-864
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 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".