Abstract 218: AVID100 is an anti-EGFR ADC that promotes DM1-meditated cytotoxicity on cancer cells but not on normal cells
Bibliographic record
Abstract
Abstract AVID100 is a novel rationally designed antibody drug conjugate (ADC) that specifically targets the epidermal growth factor receptor (EGFR). EGFR is highly expressed on a variety of cancers making it a promising target for ADCs. However, due to the presence of EGFR on normal skin cells, on-target off-tumor toxicity is a concern. AVID100 is an anti-EGFR-DM1 conjugate exhibiting high potency against cancer cells relative to unconjugated antibodies, while not exhibiting increased toxicity on normal cells. In a series of in vitro and in vivo experiments, we provide mechanistic evidence rationalizing why AVID100 shows higher cytotoxicity on tumor cells compared to normal cells. The antibody moiety of AVID100, denoted MAB100, was shown to have a high affinity for EGFR (approximately 2nM) and to compete with EGF for binding to the EGFR. Also, MAB100 prevented downstream signalling from EGFR. In addition to exhibiting full antagonist activity, MAB100 effectively delivered the microtubule inhibitor DM1 to tumor cells, as demonstrated by an increase in apoptosis in AVID100-treated tumor cells relative to MAB100-treated tumor cells. AVID100 was very effective on tumor cell lines derived from breast, head and neck, and lung cancers with the cytotoxic IC50 values generally correlating with the number of EGFR molecules on the cell surface. Importantly, on keratinocytes, AVID100 did not exhibit increased cytotoxicity relative to MAB100. We hypothesized that this lack of increase in cytotoxicity on keratinocytes is due to the antagonistic effect of MAB100 on EGFR signalling. Blocking the EGFR pathway in keratinocytes strongly inhibits their proliferation, which should protect them against the cytotoxic action of DM1. To address this hypothesis, we compared the effect of AVID100 to that of a non-antagonistic anti-EGFR ADC, huML66-DM1. As expected, both ADCs were highly effective at killing MDA-MB-468 cancer cells, confirming their ability to deliver DM1. In contrast, keratinocytes exhibited a significantly higher level of apoptosis in response to huML66-DM1 as compared to AVID100. These results confirm that the antagonistic nature of the antibody moiety of AVID100 plays a critical role in protecting keratinocytes from the cytotoxic effect of DM1. Finally, the activity of AVID100 was investigated in multiple mouse xenograft studies, including in MDA-MB-468 human breast adenocarcinoma, H292 NSCLC, and FaDu SSCHN models. AVID100 treatment significantly reduced tumor growth and caused tumor regressions in some of the mice, even when administered as a single dose. Toxicology studies in cynomolgus monkeys demonstrated that AVID100 was well tolerated at up to 4 weekly doses of 10mg/kg. AVID100 has completed a Phase 1 clinical trial with the recommended Phase 2 dose having been determined. The Phase 2 trial of AVID100 is ongoing. Citation Format: Michael J. Thwaites, Rene Figueredo, Gilles Tremblay, James Koropatnick, Victor Goldmacher, Maureen O’Connor-McCourt. AVID100 is an anti-EGFR ADC that promotes DM1-meditated cytotoxicity on cancer cells but not on normal cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 218.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".