Anti-CD3 × Anti-Epidermal Growth Factor Receptor (EGFR) Bispecific Antibody Redirects T-Cell Cytolytic Activity to EGFR-Positive Cancers <i>In vitro</i> and in an Animal Model
Bibliographic record
Abstract
PURPOSE: Targeting epidermal growth factor receptor (EGFR) overexpressed by many epithelial-derived cancer cells with anti-EGFR monoclonal antibodies (mAb) inhibits their growth. A limited number of clinical responses in patients treated with the anti-EGFR mAb, (cetuximab), may reflect variability in EGFR type or signaling in neoplastic cells. This study combines EGFR-targeting with the non-MHC-restricted cytotoxicity of anti-CD3 activated T cells (ATC) to enhance receptor-directed cytotoxicity. EXPERIMENTAL DESIGN: ATC from normal and patient donors were expanded ex vivo. Specific cytolytic activity of ATC armed with anti-CD3 x anti-EGFR (EGFRBi) against EGFR-expressing cancer cells derived from lung, pancreas, colon, prostate, brain, skin, or EGFR-negative breast cancer cells was evaluated in (51)Cr release assays. In vivo studies comparing tumor growth delay induced by EGFRBi-armed ATCs or cetuximab were done in severe combined immunodeficient/Beige mice (SCID-Beige) bearing COLO 356/FG pancreatic and LS174T colorectal tumors. RESULTS: At effector/target ratios from 3.125 to 50, both EGFRBi-armed normal and patient ATC were significantly more cytotoxic, by 23% to 79%, against EGFR-positive cells over ATC, cetuximab, anti-CD3 alone, or ATC armed with irrelevant BiAb directed at CD20. EGFRBi-armed ATC also secreted significantly higher levels of some T(H1)/T(H2) cytokines compared with ATC alone. In mice, i.v. infusions of EGFRBi-armed ATC (0.001 mg equivalent/infusion) were equally effective as cetuximab (1 mg/infusion) alone for significantly delaying growth of established COLO 356/FG but not LS174T tumors compared with mice that received ATC alone or vehicle (P < 0.001). CONCLUSIONS: Combining EGFR antibody targeting with T cell-mediated cytotoxicity may overcome some limitations associated with EGFR-targeting when using cetuximab alone.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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".