Abstract PR001: Discovery of Etrumadenant, a first-in-class dual A2a and A2b adenosine receptor antagonist for cancer immunotherapy
Bibliographic record
Abstract
Abstract High levels of adenosine are generated in the tumor microenvironment (TME) by sequential hydrolysis of extracellular ATP by the ecto-nucleotidases CD39 (ATP→AMP) and CD73 (AMP→adenosine). Adenosine activates A2a and A2b adenosine receptors on immune cells, resulting in immunosuppression. Since A2aR is expressed by a variety of lymphocytes, the suppressive effects of adenosine on this cell type can be potentially reversed by blocking the A2aR. In contrast, myeloid cells that have comparable expression of A2aR and A2bR require dual A2a/bR blockade for full reversal of the immunosuppressive effects of adenosine. The first generation of adenosine antagonists deployed in oncology were repurposed CNS drug candidates with properties that were deemed less than optimal for anti-tumor efficacy (e.g., A2aR-selective, good BBB permeability, not optimized for minimal plasma protein binding, etc.). We sought to design a potent and selective dual antagonist of A2aR and A2bR to effectively block the high concentrations of adenosine found in tumors, with diminished brain penetration, and minimal non-specific binding to plasma proteins. Using a pharmacophore mapping approach, we discovered potent A2aR antagonists with favorable PK profile in rats, good selectivity, and moderate potency against A2bR. Systematic SAR studies led to improvement in A2bR potency, which ultimately resulted in Etrumadenant (AB928). Etrumadenant inhibits both A2aR and A2bR with similar potencies (KB: 1.4 nM and 2 nM, respectively), and is highly selective against other targets in the adenosine pathway with minimal penetration across the blood brain barrier. Etrumadenant provides superior dendritic cell activity compared to A2aR antagonist alone. Its combination with immunogenic chemotherapy enhances immune activity and suppresses tumor growth and metastasis in vivo. These data support our rational design of a dual A2a and A2b adenosine receptor antagonist to impact adenosine biology on multiple cell types within the TME. Etrumadenant is currently undergoing phase 2 clinical trials in colorectal and lung cancer patients. Citation Format: Ehesan U. Sharif, Dillon H. Miles, Brandon R. Rosen, Joel Beatty, Jenna L. Jeffrey, Laurent P. P. Debien, Rhiannon Thomas-Tran, Debashis Mandal, Dan Direnzo, Sachie Marubayashi, Kristen Zhang, Ferdie Soriano, Elaine Ginn, Divyank Soni, Pei-Yu Chen, Lixia Jin, Steve W. Young, Matt J. Walters, Manmohan R. Leleti, Jay P. Powers. Discovery of Etrumadenant, a first-in-class dual A2a and A2b adenosine receptor antagonist for cancer immunotherapy. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr PR001
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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 | 0.000 |
| 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".