Abstract Neoantigens arise from tumor-specific, somatic mutations and have the potential to be recognized by T cells that are associated with anti-tumor immune responses. Since they are non-self, they are hypothesized to provide an attractive therapeutic modality because T cells that can respond to those sequences have not undergone thymic selection. The ATLASTM platform enables identification of biologically relevant CD4+ and CD8+ T cell neoantigens in any subject in an unbiased manner, overcoming the limitations of conventional in silico predictive approaches. The ATLAS platform utilizes matched patient tumor biopsy and blood samples to identify recall T cell responses to tumor specific mutations. From patient peripheral blood, CD14+ monocytes were isolated and differentiated into dendritic cells (MDDCs), and T cells were sorted into CD4+ and CD8+ populations and non-specifically expanded. Tumor-specific changes (single nucleotide variants and insertion/deletions) were identified through whole exome sequencing and cloned into E. coli expression vectors with and without co-expressed listeriolysin O to enable presentation via MHC class I or class II, respectively. For each patient, their unique clones were co-cultured with autologous MDDCs in an ordered array, then their CD4+ or CD8+ T cells were added and incubated overnight. T cell activation was determined by measurement of TNF-α and IFN-γ levels in the supernatants by a Meso-Scale Discovery assay. Neoantigens were defined as clones that elicited cytokine responses >2 median absolute deviations from the median of negative control clones. Historically, ATLAS has identified CD4+ and CD8+ T cells responses to up to 15% of mutant polypeptide sequences. Here we will present ATLAS profiling of T cell responses to >2,500 potential neoantigens, across a broad cohort of patients with different tumor types, including tumors with a wide range of mutational burden. T cell responses detected by ATLAS challenge assumptions in the field, with the majority of empirically identified neoantigens not predicted by algorithms, and many predicted neoantigens demonstrating “inhibitory” activity. When exploring neoantigens selected by ATLAS by tumor type, no patterns in overall mutational burden, RNA expression level, or DNA mutant allele frequency have yet been identified. We will also present broader functional analysis, including pathway analysis of proteins containing neoantigens, review of the immunogenicity of known oncogenes and features of immunogenic peptide sequences. The ATLAS platform empirically defines which potential neoantigens created by somatic mutations elicit immune responses in individual patients independently of a patient's HLA type and T cell receptor repertoire. This approach provides the opportunity to identify better targets to include in a personalized vaccine formulation. Citation Format: Jason Dobson, Huilei Xu, Johanna Kaufmann, James Foti, Jin Yuan, Michael O''Keeffe, Crystal Cabral, James Loizeaux, Christopher Warren, Ning Wu, Erick Donis, Kyle Ferber, Pamela Carroll, Jessica B. Flechtner, Wendy Broom. Neoantigen identification using the ATLAS T cell profiling platform highlights the need to empirically define neoantigens [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 730.
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Oct 24, 2018
Christina Kyung Eun Baek + 1
Open Access