Abstract 5718:Ex vivoATLAS-identification of neoantigens for personalized cancer immunotherapy in mouse melanoma
Authors: Hanna Starobinets, Catarina Nogueira, Kyle Ferber, Huilei Xu, Abha Dhaneshwar, Jason R. Dobson, James Loizeaux, James Foti, Michael O'Keefe, Erick Donis, Wendy Broom, Pamela Carroll, Paul Kirschmeier, Jessica B. Flechtner, Hubert Lam
Journal: Cancer Research (2018)

Abstract Neoantigens are emerging as attractive vaccine targets for personalized cancer immunotherapy. As opposed to tumor-associated antigens, neoantigens contain non-synonymous mutations that enable their identification as foreign targets not subject to central tolerance in the thymus. Personalized cancer vaccines leverage neoantigens to specifically direct the immune system to recognize cancer cells for the coordinated attack and destruction of tumors. While in silico methods are commonly used to predict immunogenic neoantigens primarily via putative binding to major histocompatibility complexes (MHC), the positive predictive value of these approaches is low as they cannot account for the complexity of antigen processing, the diversity of MHC class I and class II alleles, and the additional steps of T cell activation. Ex vivo technologies have the potential to overcome the limitations of neoantigen identification by utilizing biologically-relevant testing. ATLAS™ is an unbiased immune response profiling platform that enables comprehensive screening of a tumor mutanome by using a patient's own autologous immune cells, specifically monocyte-derived dendritic cells (MDDC) as antigen presenting cells (APCs) and sorted CD8+ and CD4+ T cells. By utilizing autologous APCs and T cells, ATLAS is agnostic to MHC diversity and assesses preexisting T cell responses to any given mutation. Patient MDDC are pulsed with an ordered array of Escherichia coli expressing patient-specific mutations as short polypeptides. CD8+ and CD4+ T cell response screening is performed using APCs and E. coli with and without pore-forming lysteriolysin O (cLLO) facilitating MHC class I or class II presentation, respectively. Thus, preexisting patient T cell responses to cancer antigens can be characterized by inflammatory cytokine secretion. We utilized a mouse melanoma model to demonstrate the capability of the ATLAS platform for identification of vaccine neoantigens. Whole exome sequencing was performed on B16F10 melanomas resected from C57BL/6 mice, identifying &amp;gt;1600 non-somatic, non-silent mutations. E. coli libraries individually expressing all mutations were constructed and used to screen APCs and T cells from the spleens of B16F10 tumor-bearing mice. Biologically relevant neoantigens were identified by their ability to modulate the secretion of inflammatory cytokines by CD4+ and CD8+ T cells. The significance of the identified neoantigens in comparison to predicted and previously reported B16F10 antigens is described. Top neoantigen candidates were selected and manufactured as synthetic long peptides. Therapeutic vaccination with ATLAS-identified neoantigens in tumor challenge studies is planned and progress will be reported. These studies demonstrate a biologically-relevant approach to improve neoantigen selection for personalized cancer vaccine design enabling improved therapeutic efficacy. Citation Format: Hanna Starobinets, Catarina Nogueira, Kyle Ferber, Huilei Xu, Abha Dhaneshwar, Jason R. Dobson, James Loizeaux, James Foti, Michael O'Keefe, Erick Donis, Wendy Broom, Pamela Carroll, Paul Kirschmeier, Jessica B. Flechtner, Hubert Lam. Ex vivo ATLAS-identification of neoantigens for personalized cancer immunotherapy in mouse melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5718.