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homologue-specific dna concentration-ratios bernhard mlecnik & jerome galon murine graft-versus-host disease detect neo-antigen-specific cd4+ tumor-specific immunological recognition single-cell sequencing-based technologies tumour antigens recognized t-cell compartment includes article download pdf automatized http-mediated download myeloid-derived suppressor cells human leukocyte antigen log-transformed odds ratios dna/rna-based vaccines promotes t-cell activation tumor-infiltrating lymphocyte subpopulations t-cell metagene predicts t-cell responses directed neo-antigen space suggests high-performance computing infrastructure cancer-germline antigen-specific central memory cd4+ t-cell epitope prediction high-throughput expression studies adoptively transferred tumor-reactive histopathologic-based prognostic factors largest neo-antigen frequencies syngenic c57bl/6 wild-type elicit t-cell responses induce t-cell responses 10-fold cross-validation procedure cell type-specific expression explore genomic data neo-antigen frequencies decreased anti-cancer immune response highest neo-antigen frequencies activate anti-tumor immunity patient-derived xenograft models raw rna-seq data raw exome-sequencing data parent-specific copy number linear regression modeling colorectal cancer neo-antigens decreasing neo-antigen frequencies cancer genome atlas cancer-germline antigen expression mhc/tap binding peptides her2-positive breast cancers anti-pd-l1 antibody multi-epitope vaccine regimen

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• The CpG island methylator phenotype: what's in a name?

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         headline:Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy
         description:While large-scale cancer genomic projects are comprehensively characterizing the mutational spectrum of various cancers, so far little attention has been devoted to either define the antigenicity of these mutations or to characterize the immune responses they elicit. Here we present a strategy to characterize the immunophenotypes and the antigen-ome of human colorectal cancer. We apply our strategy to a large colorectal cancer cohort (n = 598) and show that subpopulations of tumor-infiltrating lymphocytes are associated with distinct molecular phenotypes. The characterization of the antigenome shows that a large number of cancer-germline antigens are expressed in all patients. In contrast, neo-antigens are rarely shared between patients, indicating that cancer vaccination requires individualized strategy. Analysis of the genetic basis of the tumors reveals distinct tumor escape mechanisms for the patient subgroups. Hypermutated tumors are depleted of immunosuppressive cells and show upregulation of immunoinhibitory molecules. Non-hypermutated tumors are enriched with immunosuppressive cells, and the expression of immunoinhibitors and MHC molecules is downregulated. Reconstruction of the interaction network of tumor-infiltrating lymphocytes and immunomodulatory molecules followed by a validation with 11 independent cohorts (n = 1,945) identifies BCMA as a novel druggable target. Finally, linear regression modeling identifies major determinants of tumor immunogenicity, which include well-characterized modulators as well as a novel candidate, CCR8, which is then tested in an orthologous immunodeficient mouse model. The immunophenotypes of the tumors and the cancer antigenome remain widely unexplored, and our findings represent a step toward the development of personalized cancer immunotherapies.
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         Immune Cell Type
         Immunosuppressive Cell
         Cancer Vaccination
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         Plant Genetics and Genomics
         Microbial Genetics and Genomics
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         Evolutionary Biology
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               type:PostalAddress
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      name:Zlatko Trajanoski
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            name:Medical University of Innsbruck
            address:
               name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
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      name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
      name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
      name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
      name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
      name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria
      name:Department of Medicine 1, University of Erlangen-Nuremberg, Erlangen, Germany
      name:INSERM U872, Integrative Cancer Immunology Laboratory, Paris, France
      name:Cordeliers Research Centre, Université Pierre et Marie Curie Paris 6, Paris, France
      name:INSERM U872, Integrative Cancer Immunology Laboratory, Paris, France
      name:Cordeliers Research Centre, Université Pierre et Marie Curie Paris 6, Paris, France
      name:INSERM U872, Integrative Cancer Immunology Laboratory, Paris, France
      name:Cordeliers Research Centre, Université Pierre et Marie Curie Paris 6, Paris, France
      name:Biocenter, Division of Bioinformatics, Medical University of Innsbruck, Innsbruck, Austria

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