Kinetic analysis of novel mono‐ and multivalent VHH‐fragments and their application for molecular imaging of brain tumours
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The overexpression of epidermal growth factor receptor (EGFR) and its mutated variant EGFRvIII occurs in 50% of glioblastoma multiforme. We developed antibody fragments against EGFR/EGFRvIII for molecular imaging and/or therapeutic targeting applications. EXPERIMENTAL APPROACH: An anti-EGFR/EGFRvIII llama single-domain antibody (EG(2)) and two higher valency format constructs, bivalent EG(2)-hFc and pentavalent V2C-EG(2) sdAbs, were analysed in vitro for their binding affinities using surface plasmon resonance and cell binding studies, and in vivo using pharmacokinetic, biodistribution, optical imaging and fluorescent microscopy studies. KEY RESULTS: Kinetic binding analyses by surface plasmon resonance revealed intrinsic affinities of 55 nM and 97 nM for the monovalent EG(2) to immobilized extracellular domains of EGFR and EGFRvIII, respectively, and a 10- to 600-fold increases in apparent affinities for the multivalent binders, V2C-EG(2) and EG(2)-hFc, respectively. In vivo pharmacokinetic and biodistribution studies in mice revealed plasma half-lives for EG(2), V2C-EG(2) and EG(2)-hFc of 41 min, 80 min and 12.5 h, respectively, as well as a significantly higher retention of EG(2)-hFc compared to the other two constructs in EGFR/EGFRvIII-expressing orthotopic brain tumours, resulting in the highest signal in the tumour region in optical imaging studies. Time domain volumetric optical imaging fusion with high-resolution micro-computed tomography of microvascular brain network confirmed EG(2)-hFc selective accumulation/retention in anatomically defined tumour regions. CONCLUSIONS: Single domain antibodies can be optimized for molecular imaging applications by methods that improve their apparent affinity and prolong plasma half-life and, at the same time, preserve their ability to penetrate tumour parenchyma.
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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 | 0.001 | 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) | 0.000 | 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".