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      Immunogenic neoantigens derived from gene fusions stimulate T cell responses

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          Abstract

          Anti-tumor immunity is driven by self vs. non-self discrimination. Many immunotherapeutic approaches to cancer have taken advantage of tumor neoantigens derived from somatic mutations. Here, we demonstrate that gene fusions are a source of immunogenic neoantigens that can mediate responses to immunotherapy. We identified an exceptional responder with metastatic head and neck cancer who experienced a complete response to immune checkpoint inhibitor therapy, despite a low mutational load and minimal pre-treatment immune infiltration in the tumor. Using whole genome sequencing (WGS) and RNA sequencing (RNA-seq), we identified a novel gene fusion, and demonstrated that it produces a neoantigen that can specifically elicit a host cytotoxic T cell response. In a cohort of head and neck tumors with low mutation burden, minimal immune infiltration, and prevalent gene fusions, we also identified gene fusion-derived neoantigens that generate cytotoxic T cell responses. Finally, analyzing additional datasets of fusion-positive cancers, including checkpoint inhibitor-treated tumors, we found evidence of immune surveillance resulting in negative selective pressure against gene fusion-derived neoantigens. These findings highlight an important class of tumor-specific antigens, and have implications for targeting gene fusion events in cancers that would otherwise be less poised for response to immunotherapy, including cancers with low mutational load and minimal immune infiltration.

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          Most cited references16

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          Identifying specificity groups in the T cell receptor repertoire

          T cell receptor (TCR) sequences are very diverse, with many more possible sequence combinations than T cells in any one individual. Here we define the minimal requirements for TCR antigen specificity, through an analysis of TCR sequences using a panel of peptide and major histocompatibility complex (pMHC)-tetramer-sorted cells and structural data. From this analysis we developed an algorithm that we term GLIPH (grouping of lymphocyte interactions by paratope hotspots) to cluster TCRs with a high probability of sharing specificity owing to both conserved motifs and global similarity of complementarity-determining region 3 (CDR3) sequences. We show that GLIPH can reliably group TCRs of common specificity from different donors, and that conserved CDR3 motifs help to define the TCR clusters that are often contact points with the antigenic peptides. As an independent validation, we analysed 5,711 TCRβ chain sequences from reactive CD4 T cells from 22 individuals with latent Mycobacterium tuberculosis infection. We found 141 TCR specificity groups, including 16 distinct groups containing TCRs from multiple individuals. These TCR groups typically shared HLA alleles, allowing prediction of the likely HLA restriction, and a large number of M. tuberculosis T cell epitopes enabled us to identify pMHC ligands for all five of the groups tested. Mutagenesis and de novo TCR design confirmed that the GLIPH-identified motifs were critical and sufficient for shared-antigen recognition. Thus the GLIPH algorithm can analyse large numbers of TCR sequences and define TCR specificity groups shared by TCRs and individuals, which should greatly accelerate the analysis of T cell responses and expedite the identification of specific ligands.
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            Immunogenicity of somatic mutations in human gastrointestinal cancers.

            It is unknown whether the human immune system frequently mounts a T cell response against mutations expressed by common epithelial cancers. Using a next-generation sequencing approach combined with high-throughput immunologic screening, we demonstrated that tumor-infiltrating lymphocytes (TILs) from 9 out of 10 patients with metastatic gastrointestinal cancers contained CD4(+) and/or CD8(+) T cells that recognized one to three neo-epitopes derived from somatic mutations expressed by the patient's own tumor. There were no immunogenic epitopes shared between these patients. However, we identified in one patient a human leukocyte antigen-C*08:02-restricted T cell receptor from CD8(+) TILs that targeted the KRAS(G12D) hotspot driver mutation found in many human cancers. Thus, a high frequency of patients with common gastrointestinal cancers harbor immunogenic mutations that can potentially be exploited for the development of highly personalized immunotherapies.
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              The head and neck cancer immune landscape and its immunotherapeutic implications.

              Recent clinical trials have demonstrated a clear survival advantage in advanced head and neck squamous cell carcinoma (HNSCC) patients treated with immune checkpoint blockade. These emerging results reveal that HNSCC is one of the most promising frontiers for immunotherapy research. However, further progress in head and neck immuno-oncology will require a detailed understanding of the immune infiltrative landscape found in these tumors. We leveraged transcriptome data from 280 tumors profiled by The Cancer Genome Atlas (TCGA) to comprehensively characterize the immune landscape of HNSCC in order to develop a rationale for immunotherapeutic strategies in HNSCC and guide clinical investigation. We find that both HPV(+) and HPV(-) HNSCC tumors are among the most highly immune-infiltrated cancer types. Strikingly, HNSCC had the highest median Treg/CD8(+) T cell ratio and the highest levels of CD56(dim) NK cell infiltration, in our pan-cancer analysis of the most immune-infiltrated tumors. CD8(+) T cell infiltration and CD56(dim) NK cell infiltration each correlated with superior survival in HNSCC. Tumors harboring genetic smoking signatures had lower immune infiltration and were associated with poorer survival, suggesting these patients may benefit from immune agonist therapy. These findings illuminate the immune landscape of HPV(+) and HPV(-) HNSCC. Additionally, this landscape provides a potentially novel rationale for investigation of agents targeting modulators of Tregs (e.g., CTLA-4, GITR, ICOS, IDO, and VEGFA) and NK cells (e.g., KIR, TIGIT, and 4-1BB) as adjuncts to anti-PD-1 in the treatment of advanced HNSCC.
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                Author and article information

                Journal
                9502015
                8791
                Nat Med
                Nat. Med.
                Nature medicine
                1078-8956
                1546-170X
                24 March 2019
                22 April 2019
                May 2019
                22 October 2019
                : 25
                : 5
                : 767-775
                Affiliations
                [1 ]Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [2 ]Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [3 ]Department of Pediatrics, Institute of Clinical Sciences, University of Gothenburg, 41685 Gothenburg, Sweden.
                [4 ]Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [5 ]Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [6 ]Department of Surgery (Head and Neck Service), Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [7 ]New York Genome Center (NYGC), New York, NY 10013, USA.
                [8 ]Integrated Genomics Operation, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [9 ]Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [10 ]Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.
                [11 ]Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
                Author notes
                [†]

                These authors contributed equally to this work.

                Author contributions: W.Y., R. M.Srivastava, K.-W.L., T.A.C., L.G.T.M. contributed to the study conception and design. L.W., M.A.C., J.T., N.S., A.L.H. and L.G.T.M. contributed to clinical treatment and clinical research coordination. W.Y., R. M.Srivastava, M.G.D., Z.N., J.T., L.G.T.M. contributed to biospecimen processing. R.G. and N.K. contributed to pathologic analysis. The New York Genome Center (S.K.T., N.R., K.A., H.G., P.A.) and MSKCC IGO core facility (K.H., N.B., K.V.) contributed to DNA and RNA sequencing and analyses. V.M., F.K., C.K., D.H., D.C., J.S.S., L.G.T.M. contributed to the bioinformatics, computation, and statistical analyses. W.Y., R.M.Srivastava, K.-W.L., and L.G.T.M. contributed to the experimental design and execution. M.G.D., J.J.H., R.M., R.M.Samstein, N.R, T.A.C., I.G., A.L.H., R.J.W. and L.G.T.M. contributed to the interpretation of data. W.Y., K.-W.L., T.A.C. and L.G.T.M. wrote the manuscript.

                Author Information: Reprints and permissions information is available at www.nature.com/reprints.

                [* ]Correspondence to: morrisl@ 123456mskcc.org (L.G.T.M.); chant@ 123456mskcc.org (T.A.C.)
                Article
                NIHMS1525284
                10.1038/s41591-019-0434-2
                6558662
                31011208
                d6bd2c6e-54e8-4b5c-bfd4-ce532da2556f

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