P2, N=30, Active, not recruiting, Washington University School of Medicine | Trial completion date: Dec 2029 --> Jun 2030 | Trial primary completion date: Oct 2025 --> Apr 2026
30 days ago
Trial completion date • Trial primary completion date
However, unlike blinatumomab, which tends to induce T cell exhaustion, we showed that the release of PBF-509 from NanoBiTE suppressed the A2AR pathway and substantially improved tumor cell killing induced by NanoBiTE. Moreover, NanoBiTE treatment led to substantially reduced tumor burden in vivo in a humanized mouse model. Our results demonstrate that NanoBiTE is a safe and potent bispecific therapy that can also reduce T cell exhaustion for cancer immunotherapy.
Compound 14a also effectively restored T cell proliferation suppressed by 5'-N-ethylcarboxamidoadenosine (NECA) and exhibited superior T cell-mediated cytotoxicity in coculture systems with A1R- and PD-L1-expressed cancer cells compared with ciforadenant (A2AR antagonist) and etrumadenant (A2AR/A2BR dual antagonist). Moreover, the combination of compound 14a with avelumab, an anti-PD-L1 antibody, resulted in enhanced infiltration of effector T cells and significantly increased the CD8+/Treg ratio in the CT26 syngeneic mouse model, substantially inhibiting tumor growth. Therefore, compound 14a is a promising candidate for multitargeted immunomodulation in cancer immunotherapy.
Furthermore, overexpression of PNP or using taminadenant, a A2aR-targeting inhibitor used in clinical trials, significantly enhances the EGFR-targeted therapeutic response in vitro, as well as in patient-derived organoids, cell-derived xenografts and mouse models bearing human EGFR-driven spontaneous lung tumor. Overall, our findings clarify the role of inosine metabolism in TKI resistance, highlighting a potential therapeutic strategy-targeting the inosine/A2aR axis-to counteract EGFR-TKI tolerance in LUAD treatment.
This resulted in the identification of the Food and Drug Administration-approved drugs isradipine, avanafil, and istradefylline as inhibitors of ENT1. We have screened over 1600 diverse molecules, allowing us to build machine learning models that in turn were further used to make predictions to validate the models. Our combined experimental and machine learning approach resulted in the identification of multiple Food and Drug Administration-approved medications as inhibitors of ENT1 or ENT2.
4 months ago
Journal
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SLC29A1 (Solute Carrier Family 29 Member 1) • SLC29A2 (Solute Carrier Family 29 Member 2)