Abstract 632: Genome-scale neoantigen screening using ATLAS™ prioritizes candidate antigens for immunotherapy in a non-small cell lung cancer patient

• Published in: Cancer research (Chicago, Ill.) Vol. 77; no. 13_Supplement; p. 632
• Main Authors: Ghamsari, Lila, Flano, Emilio, Jacques, Judy, Liu, Biao, Yan, Zheng, Alami, Aula, Kelley, Christine, Zhang, Theresa, Havel, Jonathan, Makarov, Vladimir, Merghoub, Taha, Wolchok, Jedd D., Hellman, Matthew, Carroll, Pamela, Chan, Timothy, Flechtner, Jessica B.
• Format: Journal Article
• Language: English
• Published: 01.07.2017
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.AM2017-632

Abstract Despite the unprecedented efficacy of checkpoint blockade (CPB) therapy in treating some cancers, the majority of patients fail to respond. Several lines of evidence support that the combination of CPB and neoantigen vaccine prolongs survival curves in cancer patients. Capitalizing on neoantigens derived from non-synonymous somatic mutations is a good strategy for therapeutic immunization. Current approaches to neoantigen prioritization involve mutanome sequencing, in silico epitope prediction algorithms, and experimental validation of cancer neoepitopes. Even the best in class in silico epitope prediction algorithms lack the accuracy necessary for efficacious personalized cancer vaccines. We sought to circumvent some of the limitations of currently available prediction algorithms by prioritizing neoantigens empirically using ATLAS™, a technology developed to screen T cell responses from any subject against their entire complement of potential neoantigens. Exome sequences were obtained from peripheral blood mononuclear cells (PBMC) and tumor biopsies from a non-small cell lung cancer patient who had been successfully treated with pembrolizumab. The tumor exome was sequenced and somatic mutations were identified. Individual DNA sequences (399 nucleotides) spanning each mutation site were built, cloned and expressed in E. coli co-expressing listeriolysin O. Polypeptide expression was validated using a surrogate T cell assay or by Western Blotting. Frozen PBMCs, collected pre- and post-therapy, were used to derive dendritic cells (MDDC). Both CD4+ and CD8+ T cells were enriched and expanded using microbeads. The E. coli clones were pulsed onto MDDC in an ordered array, then co-cultured either with CD8+ or with CD4+ T cells overnight. T cell activation was detected by analyzing cytokines in supernatants. Antigens were identified as clones that induced a cytokine response that exceeded three standard deviations of the mean of all negative control wells, then their identities compared with T cell epitopes predicted using previously described algorithms. We found biological evidence for neoantigens that were specifically responsive to peripheral CD8+ and CD4+ T cells, derived from the patient’s tumor, pre- and post-CPB intervention. Some of these neoantigens were identified as a T cell target both pre- and post-CPB therapy. We identified neoantigens for which no epitopes were predicted by in silico methods. These data represent evidence that multiple patient-specific neoantigens can be identified through functional evidence of T cell response from peripheral blood without epitope prediction. By profiling natural and CPB-enhanced immunity to neoantigens, a broad catalog of T cell targets can be identified for development of immunotherapies that engage T cells against cancer to improve outcomes for patients for whom current therapies are ineffective. Citation Format: Lila Ghamsari, Emilio Flano, Judy Jacques, Biao Liu, Zheng Yan, Aula Alami, Christine Kelley, Theresa Zhang, Jonathan Havel, Vladimir Makarov, Taha Merghoub, Jedd D. Wolchok, Matthew Hellman, Pamela Carroll, Timothy Chan, Jessica B. Flechtner. Genome-scale neoantigen screening using ATLAS™ prioritizes candidate antigens for immunotherapy in a non-small cell lung cancer patient [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 632. doi:10.1158/1538-7445.AM2017-632