89Zr-Labeled Domain II-Specific scFv-Fc ImmunoPET Probe for Imaging Epidermal Growth Factor Receptor In Vivo
Bibliographic record
Abstract
Epidermal growth factor receptor I (EGFR) is overexpressed in many cancers. The extracellular domain of EGFR has four binding epitopes (domains I- IV). All clinically approved anti-EGFR antibodies bind to domain III. Imaging agents that bind to domains other than domain III of EGFR are needed for accurate quantification of EGFR, patient selection for anti-EGFR therapeutics and monitoring of response to therapies. We recently developed a domain II-specific antibody fragment 8709. In this study, we have evaluated the in vitro and in vivo properties of 89Zr-8709-scFv-Fc (105 kDa). We conjugated 8709-scFv-Fc with the deferoxamine (DFO) chelator and radiolabeled the DFO-8970-scFv with 89Zr. We evaluated the binding of 89Zr-DFO-8709-scFv-Fc in EGFR positive and negative cell lines DLD-1, MDA-MB-231 and MDA-MB-435, respectively, and in mouse xenograft models. Simultaneously, we have compared the binding of 89Zr-8709-scFv-Fc with 111In-nimotuzumab, a domain III anti-EGFR antibody. DFO-8709-scFv-Fc displayed similar cell binding specificity as 8709-scFv-Fc. Saturation cell binding assay and immunoreactive fraction showed that radiolabeling did not alter the binding of 8709-scFv-Fc. Biodistribution and microPET showed good uptake of 89Zr-8709-scFv-Fc in xenografts after 120 h post injection (p.i). and was domain-specific to EGFR domain II. 89Zr-8709-scFv-Fc did not compete for binding in vitro and in vivo with a known domain III binder nimotuzumab. The results show that 89Zr-8709-scFv-Fc is specific to domain II of EGFR making it favorable for quantification of EGFR in vivo, hence, patient selection and monitoring of response to treatment with anti-EGFR antibodies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".