Near infrared imaging of epidermal growth factor receptor positive xenografts in mice with domain I/II specific antibody fragments
Bibliographic record
Abstract
Epidermal growth factor receptor (EGFR) is a transmembrane cell surface receptor that is frequently overexpressed and/or mutated in many cancers.Therapies targeting EGFR have poor outcomes due to the lack of reliable diagnostic tests to monitor EGFR.Current in vitro EGFR diagnostic methods are invasive, requiring biopsies, which limits tumor sampling and availability.EGFR molecular imaging provides non-invasive whole-body images capable of detecting primary tumors and metastases, which can be used to diagnose and monitor response to therapy.Methods: We evaluated properties of two anti-EGFR fragments, 8708 and 8709, as molecular-targeted imaging probes.8708 and 8709 are anti-EGFR antigen binding fragments (Fabs) that recognize domain I/II of EGFR, which is distinct from epitopes recognized by current anti-EGFR therapeutic antibodies.We used complementarity determining region sequences from 8708 and 8709 Fabs to generate an anti-EGFR IgG and (scFv)2 and scFv-Fc antibody fragments.We expressed, purified, and labeled the IgG and fragments with IRDye800CW and used them to image EGFR-positive and -negative xenografts in CD-1 nude mice.8709 scFv-Fc was also tested for competitive binding with the therapeutic anti-EGFR antibody nimotuzumab and for quantifying ratios of EGFR and EGFRvIII deletion mutant.Results: IRDye800CW-labeled 8708 (scFv)2 and 8709 scFv-Fc imaging probes showed high levels of accumulation and good retention in EGFR-positive xenografts, with peak accumulation occurring at 24 and 48 hours post injection, respectively.IRDye680RD-labeled 8709 scFv-Fc did not compete with IRDye800CW-labeled nimotuzumab for EGFR binding as assayed by flow cytometry using an EGFR-positive cell line.IRDye680RD-labeled 8709 scFv-Fc and IRDye800CW-labeled nimotuzumab used in combination were able to determine the ratio of cells expressing EGFR and a deletion mutant EGFRvIII.Conclusion: IRDye800CW-labeled 8708 (scFv)2 and 8709 scFv-Fc had desirable binding affinities, clearance times, and tumor accumulation to be used for imaging in combination with current EGFR targeted therapies.This study highlights the potential for using 8708 (scFv)2 and 8709 scFv-Fc as EGFR diagnostic and therapy monitoring tools.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".