Bivalent binding properties of epidermal growth factor receptor targeted monoclonal antibodies: Factors contributing to differences in observed clinical profiles.
Bibliographic record
Abstract
A36 Emerging evidence suggests that the ability of antibodies to bind bivalently (or with both antibody arms) is essential for maintaining prolonged residence in tumors and an important feature for inhibiting tumor cell proliferation (1-4). Formation of bivalent bonds is dependent on target density and antibody association and dissociation rates. Nimotuzumab is an EGFR-targeted monoclonal antibody that has demonstrated anti-tumor activity in preclinical and clinical trials in absence of side-effects commonly seen with other anti-EGFR antibodies, cetuximab and panitumumab. We investigated whether the differences in monovalent/bivalent binding profiles is one of the characteristics that distinguishes between the therapeutics. Cetuximab and nimotuzumab binding to EGFR-expressing cell lines including A431 (106 EGFR/cell), H125 (105 EGFR/cell) and MDA-MB231 (103 EGFR/cell) was analyzed by FACS. Cells were incubated with increasing concentrations of nimotuzumab, cetuximab, and monovalent fragments (Fab) of these antibodies. The binding patterns of nimotuzumab and cetuximab to cell lines with medium to high receptor expression (H125, A431) were remarkably similar at all dose levels. Cetuximab binding to the cell line with the low level of EGFR expression (MDA-MB23) was preserved and increased with escalating concentrations. In contrast, nimotuzumab binding was not detectable on MDA-MB23 regardless of concentration. Cetuximab Fab bound to all cell lines and the level of binding increased proportionately with dose. In contrast, nimotuzumab Fab binding to H125, MDA-MB23 was not detected, regardless of the Fab dose. Only marginal nimotuzumab Fab binding to A431 was detected at the highest doses. In-vitro binding kinetics of cetuximab, nimotuzumab and panitumumab are being investigated by SPR (Biacore 3000). The CM5 chip surface was coated with varying densities of EGFR, Fc-EGFR dimer and the antibodies via amine coupling. Nimotuzumab binding kinetics exhibited fast association and dissociation rates under monovalent binding conditions. Under conditions allowing bivalent attachment (Fc-EGFR dimer), nimotuzumab dissociation rate was significantly reduced. The effects of changing surface conditions (monovalent vs bivalent) on the binding kinetics of cetuximab and panitumumab were less significant. Nimotuzumab bound to Fc-EGFR dimer at a faster rate than cetuximab. These findings are consistent with the FACS data and support the preference for bivalent binding by nimotuzumab. Taken together, these observations suggest that, in contrast to other anti-EGFR antibodies, the intrinsic properties of nimotuzumab favor bivalent binding as the primary mode for attachment, which would lead to nimotuzumab attaching discriminately to cells that express moderate to high EGFR levels. This targeting property of the antibody may in part be responsible for sparing of healthy tissues by nimotuzumab observed in clinical studies and may have other important clinical implications that deserve further evaluation. Additional experimental data exploring these differences will be presented. References 1. Bueren et al, PNAS 2008. 105:6109 - 14 2. Yoshida et al, Int J Cancer 2008. 122:1530-8 3. Perez-Torres et al, J Biol Chem 2006. 281:40183-92 4. Fan et al, J Biol Chem 1994. 269:27595-02
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".