Abstract 1124: The identification and characterization of a novel A3R agonist with potent anti-cancer properties

التفاصيل البيبلوغرافية
العنوان: Abstract 1124: The identification and characterization of a novel A3R agonist with potent anti-cancer properties
المؤلفون: Jana Kotulova, Sona Gurska, Barbora Liskova, Miroslav Popper, Katerina Jecmenova, Petr Dzubak, Marian Hajduch
المصدر: Cancer Research. 82:1124-1124
بيانات النشر: American Association for Cancer Research (AACR), 2022.
سنة النشر: 2022
مصطلحات موضوعية: Cancer Research, Oncology
الوصف: Introduction: G protein-coupled receptors (GPCRs) are among the most druggable targets. Adenosine receptors (ARs) belong to the class A GPCRs. The role of adenosine and ARs in tumorigenesis is increasingly appreciated. Moreover, novel studies also point out pro-tumor and anti-tumor effects of modulating ARs. Besides A2AR and A2BR in immune-oncology, A3R was shown to be overexpressed in tumor tissue and play an important role in cancer. Especially A3R agonists decrease proliferation, induce cell cycle arrest and cytotoxicity selectively in cancer cells. However, most compounds fail in clinical trials due to their insufficient efficacy or high occurrence of adverse effects. Here we introduce a novel A3R agonist with plausible anti-cancer properties. Material and methods: First, we developed a screening pipeline of AR agonists and antagonists, where the hits from the primary screen (aequorin luminescence assay) were evaluated in the counter-screen (calcium mobilization assay) and confirmed in concentration-response experiments. In parallel, the identified modulators were subjected to cytotoxicity screening against a panel of tumor and non-tumor cell lines. The selected lead compound with potent anti-cancer properties was biologically and pharmacologically compared to a reference A3R agonist, 2-Cl-IB-MECA, recently evaluated in a clinical trial against hepatocellular carcinoma. To assess the relevance of the in vitro assays, the lead compound was administered to mice and its in vivo efficacy was evaluated. Results: Our screening pipeline shows high reproducibility and robustness. We identified several potential hits among the newly synthesized nucleosides and selected an A3R agonist PNH173 with significant cytotoxic effects against several tumor cell types compared to the reference A3R agonist. PNH173 also demonstrates good pharmacological properties in non-clinical ADME tests, reduces tumor growth, and increases overall survival in vivo experiments. Conclusions: We set out to identify novel small molecule A3R agonists with strong anti-tumor effects using a screening campaign and subsequent series of biological assays. Our data indicate desired anti-cancer properties of a novel A3R agonist PNH173 in in vitro and in vivo experiments, with higher efficacy compared to the reference compound. In addition, PNH173 demonstrates biased signaling which could be further utilized against human malignancies. Funding: The European Regional Development Fund (Project ENOCH No. CZ.02.1.01/0.0/0.0/16_019/0000868), the Czech Ministry of Education, Youth and Sports (EATRIS-CZ, LM2018133, and CZ-OPENSCREEN, LM2018130), the Czech Science Foundation (GACR 19-08124S), the Technology Agency of the Czech Republic: Czech National Centres of Competence, project “PerMed” Personalized Medicine - Diagnostics and Therapy (TN01000013), and the Grant agency of Palacky University (IGA_LF_2021_036). Citation Format: Jana Kotulova, Sona Gurska, Barbora Liskova, Miroslav Popper, Katerina Jecmenova, Petr Dzubak, Marian Hajduch. The identification and characterization of a novel A3R agonist with potent anti-cancer properties [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1124.
تدمد: 1538-7445
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::8f905c7258ae3ef14d7abc486e33f10a
https://doi.org/10.1158/1538-7445.am2022-1124
رقم الأكسشن: edsair.doi...........8f905c7258ae3ef14d7abc486e33f10a
قاعدة البيانات: OpenAIRE