Project Summary Personal neoantigens have been conceptualized as optimal tumor antigens but their broad applicability across cancers has been limited by the variability in mutational burden across tumors. Recent clinical experiences in targeting neoantigens, such as by vaccination, in high and moderate mutation-rate tumors (e.g. melanoma, glioblastoma) have been promising, but such promise for low mutation burden cancers remains under evaluation. Chronic lymphocytic leukemia (CLL) is an example of such a low mutation burden malignancy where improved tumor antigen identification could open new therapeutic opportunities. Indeed, although a growing armamentarium of clinically active therapies is now available for CLL (i.e. targeted inhibitors, CAR-T cells, CPB), CLL remains largely incurable. While inherently immunogenic, as highlighted by evidence of spontaneous regression and its responsiveness to the graft-versus-leukemia (GvL) activity of allogeneic hematopoietic cell transplantation (allo-HCT), CLL patients demonstrate inconsistent ability to mount antigen-specific immunity. Notably, we have achieved several exciting technologic advances over the last 5 years that impact antigen discovery, including: (i) new understanding of the cancer genome and transcriptome, advanced by new sequencing technologies, yielding potential alternative sources of cancer neoantigens; (ii) establishment of a scalable approach to rapidly validate peptide-MHC interactions, providing essential experimental feedback to our prediction efforts; (iii) improvements in the sensitivity, throughput and analysis of immunopeptidome data; (iv) expanded computational infrastructure to rapidly incorporate findings into prediction models for HLA class I. In this application, we hypothesize that novel classes of neoantigens are discoverable in CLL and that antigen-specific interactions arising from recognition of these alternative neoantigens could contribute to leukemia control. We propose an integrative strategy for the discovery and validation of novel neoantigen species. This commences with detection analyses of alterations that could encode these alternative CLL neoantigens through long-read and ribosomal sequencing, that can be used to inform improvements on the analysis pipelines. It then proceeds with validation using new high throughput binding assays, immunopeptidome detection and T cell response assessments (Aim 1). Our strategy further involves systematic improvement of our class I prediction tools through generation of experimental data from which we can iteratively correct and refine the epitope predictions. We furthermore incorporate the feature of peptide-MHC stability, which has been increasingly identified as relevant in peptide-MHC immunogenicity (Aim 2). Finally, we propose to confirm the functional relevance of alternative tumor neoantigens through their evaluation in the context of variation in natural history of CLL in a newly-assembled cohort of >1000 molecular...