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Record W1586602460 · doi:10.1158/1538-7445.am2014-2657

Abstract 2657: Utilization of the Angiopep platform to enable brain penetration of therapeutic mAbs or Antibody-Drug Conjugates for treatment of brain tumors

2014· article· en· W1586602460 on OpenAlexaff
Michel Demeule, Jean E. Lachowicz, Sasmita Tripathy, Giogang Yang, Sanjoy K. Das, Christian Ché, Jean-Christophe Currie, Simon Lord‐Dufour, Anthony Régina, Jean‐Paul Castaigne

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversité de MontréalAngiochem (Canada)
Fundersnot available
KeywordsTranscytosisLRP1Monoclonal antibodyBlood–brain barrierIn vitroCancer researchAntibodyPharmacologyReceptorTumor microenvironmentBiologyChemistryImmunologyBiochemistryEndocrinologyCentral nervous systemLipoproteinLDL receptorEndocytosis

Abstract

fetched live from OpenAlex

Abstract Monoclonal antibodies directed against receptor tyrosine kinases such as HER2 have been demonstrated to reduce tumor size and increase survival. However, these agents achieve little to no brain penetration, making them ineffective against metastatic brain tumors. The blood-brain barrier (BBB), efficient at restricting entry of proteins such as mAbs into the brain, is comprised of capillary endothelial cells with tight junctions and efflux pumps. 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. Conjugation of the Angiopep-2 (An2) to confer brain permeability has been validated for small molecules (ANG 1005, Phase II), peptides and proteins. For example, therapeutic concentrations of an anti-HER2 mAb have been achieved with An2 conjugation. This Angiopep-Antibody Conjugate, ANG4043, 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. Mice intracranially implanted with BT-474 human breast cancer cells showed reduced brain tumor size when dosed with ANG4043 compared to controls and increased mice survival. Here, we also describe the chemical conjugation between a brain penetrant Angiopep, a cytotoxic agent and a mAb directed against HER2. This new peptide-antibody-drug-conjugate shows a much higher in vitro anti-proliferative potency against HER2+ BT-474 cells than the native antibody. Furthermore, this new peptide-drug-antibody-conjugate demonstrates a high rate of entry into the brain when compared to the unconjugated antibody. Overall, these data demonstrate that the addition of an Angiopep to therapeutic mAbs or Antibody Drug Conjugates (ADCs) can improve their brain penetration. These results extend the validation of Angiopep conjugation beyond small molecules and peptides to include larger molecules such as therapeutic mAbs or ADCs for development of new brain-penetrant antitumor therapeutics. Citation Format: Michel Demeule, Jean E. Lachowicz, Sasmita Tripathy, Giogang Yang, Sanjoy Das, Christian Che, Jean-Christophe Currie, Simon Lord-Dufour, Anthony Regina, Jean-Paul Castaigne. Utilization of the Angiopep platform to enable brain penetration of therapeutic mAbs or Antibody-Drug Conjugates for treatment of brain tumors. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2657. doi:10.1158/1538-7445.AM2014-2657

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.115
GPT teacher head0.409
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

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