Abstract LB_A20: Overcoming cancer drug resistance with AI-designed RNA epigenetic inhibitors

Abstract

Abstract Background: Drug resistance is a major obstacle to successful treatment of cancer and leukemia. The role of RNA epigenetics in cancer drug resistance is largely unknown. Our previous studies demonstrated that specific RNA cytosine methyltransferases (RCMTs), namely NSUN1 (aka NOL1, NPO2) and NSUN2, mediate the formation of drug-resistant active chromatin structures (ACS) at nascent RNAs to regulate drug resistance in leukemia cells (Cheng, J.X. et al. Nat Commun, 2018). The Cancer Genome Atlas Program (TCGA) data demonstrate that elevated expression levels of NSUN1 and NSUN2 are correlated with significantly shorter patients’ survival in almost all cancer subtypes (https://www.proteinatlas.org/ENSG00000111641-NOP2/pathology). However, due to the lack of NSUN1 and NSUN2 proteins’ crystal structures, no NSUN1/2-targeting therapeutics have been developed yet. Methods: 1. Argonne artificial intelligence (AI)/supercomputer design of NSUN1/2-targeting small-molecule compound libraries, simulation of compound-protein interactions and analysis of structure activity relationship (SAR). 2. Novel RNA epigenetic technologies, including NSUN1/2-targeting fluorescence releasing assay (FRA), 5-ethynyl uridine click chemistry (EC) and proximity ligation rolling cycle amplification (PL-RCA)-coupled confocal microscopy (CM), flow cytometry (FCM) and RNA sequencing (RNA-seq). 3. Functional drug screening, H&E histology and immunohistochemistry (IHC). 4. Enforced NSUN1/2 expression and knockout (KO) cell lines and syngeneic AML mouse models. Results:1. Identification of the ligand-binding modules/surfaces in NSUN1 and NSUN2 proteins and generation of NSUN1/2-targeting small-molecule libraries by AI/supercomputing. 2. Identification of several NSUN1/2 inhibitors that effectively inhibit growth of the venetoclax-resistant human monocytic leukemia (SC), erythroid leukemia (K562) and lung cancer (H82) cells. 3. Demonstration of the lead inhibitors execute their effects through disruption of NSUN1/2-mediated (ACS) and translational complexes (TLC). 4. Characterization of the lead inhibitors’ binding modules with AI/supercomputing SAR analysis. 5. In vivo validation of the efficacies of the identified lead inhibitors using syngeneic AML mouse models. Conclusion:By leveraging the power of the Argonne AI/supercomputer and our functional assays, we identified several small-molecule inhibitors that can disrupt the NSUN1/2-mediated ACS and TLC to overcome venetoclax resistance in AML cell lines and syngeneic mice. This study has not only illustrated the importance of NSUN1 and NSUN2 in oncogenic bioprocesses and drug (venetoclax) resistance, but also paved the way to the development of novel RNA epigenetics-driven therapeutics for leukemia and other cancer subtypes. Citation Format: Jason X Cheng, Shaun Wood, Derrick Tang, Linda Degenstein, Andrzej Joachimiak, Rick Stevens. Overcoming cancer drug resistance with AI-designed RNA epigenetic inhibitors [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr LB_A20.