Anderson, K. S.

Messenger RNA (mRNA) therapeutics have transformed vaccination and protein replacement strategies, yet efforts to improve their performance have focused largely on sequence engineering, nucleotide modification, and delivery vehicles. Here we show that mRNA function can be controlled by rational design of higher-order RNA architectures. We develop self-assembling mRNA origami (mRNA-OG), a class of unimolecular RNA nanostructures that encode protein-coding sequences within higher-order, programmable, and compact nucleic acid architectures. Using computational design and experimental validation, we demonstrate that mRNA-OG folds into well-defined nanostructures while remaining translationally competent in mammalian cells. Although folded mRNA-OG recruits ribosomes comparably to unfolded constructs, it produces lower protein output, indicating that RNA architecture can directly influence translational efficiency. The compact geometry of mRNA-OG also enhances encapsulation by cationic lipid delivery systems, suggesting a structural route to improved cargo packaging. Beyond its effects on translation, mRNA architecture modulates innate immune recognition. In primary human dendritic cells, folded and unfolded mRNA-OG elicit distinct cytokine programs and differential activation of stress-response pathways, including a modest induction of the integrated stress response that is not fully explained by canonical PKR signaling. Our results establish programmable structure as a new design parameter for mRNA therapeutics that can affect its functionality, delivery properties, and immune sensing.

Abstract Background: HPV16 (human papillomavirus) is a leading cause of oropharyngeal cancer (OPC) in the US. Antibodies to HPV16 early antigens are detectable in serum samples up to two decades before diagnosis and are potential biomarkers for early detection. In this study, we have developed and compared three custom HPV16 serology platforms for detection of OPC: MSD (Meso Scale Discovery) electrochemiluminescent detection, RAPID ELISA, and a novel semi-quantitative lateral flow assay (LFA) using a custom android application. Methods: For the MSD platform, recombinant HPV 16 antigens (E1, E2, E6, E7) were synthesized in mammalian cells and printed on multiplexed arrays. In RAPID ELISA, GST-tagged antigens (E1, E2, E6, E7) were expressed using mammalian in vitro transcription and translation and bound IgG detected. For the LFA, His-tagged recombinant proteins (HPV16 CE2 184-365aa and HPV16 E7) were synthesized, printed, and antibodies detected with protein G conjugated nanoparticles. Archived serum samples drawn from newly-diagnosed OPC patients (n = 60), with matching saliva samples (n=54, MSD assay only) were obtained from Mayo Clinic. Unmatched controls (n = 46) were obtained from AT Still. For the lateral flow assay, colorimetric image analysis was done using a titration curve of known concentration of monoclonal antibody. We optimized the biomarker panel (E2, E6, and E7 for MSD and ELISA, and for LFA E2, and E7) by using multiparametric analysis and plotting the receiver operating curves to the test performance, and assays were compared using the Cohen’s kappa statistic. Results: At 98% specificity, the MSD HPV16 serologic assay achieved 88% sensitivity, similar to RAPID ELISA, and the LFA assay at 85% sensitivity. The signal intensities for saliva samples were weaker at 24% sensitivity. The Cohen’s kappa value ranged from 0.74 to 0.78 for the comparison between all three assays. There was only one sample among all the cases that was negative by all three serology tests. Conclusion: All three assays have strong concordance for the detection of HPV16 early antigen serology. All the tests can facilitate large scale HPV serology research. Citation Format: Akshansh Kaushik, David Routman, Tej Patel, Joshua Eger, Padhmavathy Yuvaraj, Kathleen R. Bartemes, Marisa D. Griesel, Danielle E. Hunter, Katie Van Abel, Anu Mathew, Mingyue Wang, Leonid Dzantiev, Martin Stengelin, Jacob N. Wohlstadter, Ann Spolarich, Kristina R. Dahlstrom, Jennifer Blain Christen, Erich Sturgis, Karen Anderson. HPV serology for rapid detection of HPV positive oropharyngeal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5099.

Abstract Introduction: Accurate detection and prioritization of tumor-specific somatic variants is foundational to the development of personalized immunotherapies. Traditional pipelines for neoepitope identification rely heavily on short-read next-generation sequencing (NGS) and DNA-based variant calling, followed by RNA expression filtering and HLA-binding prediction. However, this approach is limited by time-intensive workflows, potential false positives from DNA-only calls, and poor capture of complex isoforms or RNA-level editing. Moreover, the accuracy of neoepitope prediction is constrained by conventional sequence-based HLA binding algorithms that do not account for structural and biophysical features of peptide-MHC interactions, particularly across underrepresented HLA alleles. Methods: To overcome these limitations, we developed a streamlined, sequencing-to-vaccine framework that leverages long-read RNA sequencing for direct detection of expressed somatic variants, including fusions, indels, and single nucleotide variants. Using Oxford Nanopore Technologies’ cDNA-PCR approach, we enable comprehensive, full-length transcript characterization from both fresh and frozen breast tumor samples. Our bioinformatic pipeline, NeoTarget, integrates alignment, variant calling, and neoepitope inference from tumor RNA in a single, modular workflow. A core innovation of this pipeline is HLA-Inception, a deep convolutional neural network trained to predict peptide-MHC class I binding using features derived from molecular dynamics-based modeling of electrostatic potential at the peptide-HLA interface, enhancing generalizability across diverse HLA subtypes. Results: Expanding on previous results, the current NeoTarget pipeline identifies, evaluates, and prioritizes single nucleotide variants, indels, and fusions. To validate this system, we used a set of 9 human breast cancer tumors benchmarked with short read sequencing. Identified neoantigens included most variants shown by clinical short read sequencing and also novel structural variants (i.e., fusions) only revealed with long read sequencing with high confidence. Conclusion: Here, we describe the design and performance of the NeoTarget pipeline, and show proof-of-concept feasibility of applying this fast and cost-effective workflow for HLA-restricted epitope discovery in breast tumors using long-read RNA sequencing. Overall, these methods can be applied to rapidly identify and prioritize neoantigens for personalized neoantigen-based immune therapies. Citation Format: F. Batalini, S. Henry, Y. Zhang, R. Foster, J. M. Gayton, A. Hostal, E. A. Wilson, A. Singharoy, M. Gustafson, B. Pockaj, J. Park, K. S. Anderson. Somatic variant detection using long read RNA sequencing reveals HLA-restricted targets for immunotherapy [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-06-08.