Abstract 6710: AVID200, a first-in-class selective TGF-beta 1 and -beta 3 inhibitor, sensitizes tumors to immune checkpoint blockade therapies
Bibliographic record
Abstract
Abstract AVID200 is a first-in-class rationally designed receptor ectodomain trap that selectively neutralizes TGF-beta 1 and -beta 3 with pM potency while sparing TGF-beta 2, thereby reducing the potential for toxicities associated with neutralization of this isoform. A Phase 1 dose-escalation clinical study of AVID200 monotherapy has recently been completed and established that the agent was well tolerated and exhibited target engagement at all dose levels tested without reaching a maximally tolerated dose. To explore the potential of AVID200 as a combination agent with immunotherapy, expression analysis of TGF-beta isoforms across various solid tumors has been carried out and the ability of AVID200 to increase anti-tumor immunity as a single agent and in combination has been explored in vivo. Analysis of >10,000 tumor samples from TCGA revealed that TGF-beta1 and -beta3 are the predominant isoforms expressed in solid tumors, with TGF-beta2 showing only minimal expression. This corroborates the attractiveness of TGF-beta1 and -beta3 as promising anti-cancer targets and emphasizes the need to target both isoforms simultaneously. Furthermore, AVID200 increased T-cell-mediated cytotoxicity as a single agent as well as potentiating the efficacy of immune checkpoint inhibitors (ICI) in syngeneic mouse tumor models. In line with these observations, we have found that AVID200 increases the infiltration of T-cells in the tumor microenvironment. In conclusion, AVID200, a first-in-class, potent and selective TGF-beta trap, enhances the activity of ICI agents in vivo and holds promise as a potential novel immunotherapy combination regimen which warrants exploration in patients with solid tumor malignancies. Phase 1 clinical trials are underway in various indications. Citation Format: Gilles Tremblay, Tina Gruosso, Jean-François Denis, Rene Figueredo, Jim Koropatnick, Maureen O'Connor-McCourt. AVID200, a first-in-class selective TGF-beta 1 and -beta 3 inhibitor, sensitizes tumors to immune checkpoint blockade therapies [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6710.
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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) | 0.005 | 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".