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      Persistent antigen at vaccination sites induces tumor-specific CD8+ T cell sequestration, dysfunction and deletion

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          Abstract

          To understand why cancer vaccine-induced T cells often fail to eradicate tumors, we studied immune responses in mice vaccinated with gp100 melanoma peptide in incomplete Freund’s adjuvant (IFA), commonly used in clinical cancer vaccine trials. Peptide/IFA vaccination primed tumor-specific CD8 + T cells, which accumulated not in tumors but at the persisting, antigen-rich vaccination site. Once there, primed T cells became dysfunctional and underwent antigen-driven, Interferon-γ (IFN-γ) and Fas ligand (FasL)-mediated apoptosis, resulting in hyporesponsiveness to subsequent vaccination. Provision of anti-CD40 antibody, Toll-like receptor 7 (TLR7) agonist and interleukin-2 (IL-2) reduced T cell apoptosis but did not prevent vaccination site sequestration. A non-persisting vaccine formulation shifted T cell localization towards tumors, inducing superior anti-tumor activity while reducing systemic T cell dysfunction and promoting memory formation. Persisting peptide/IFA vaccine depots can induce specific T cell sequestration, dysfunction and deletion at vaccination sites; short-lived formulations may overcome these limitations and result in greater therapeutic efficacy of peptide-based cancer vaccines.

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          Most cited references 69

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          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

            Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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              Cancer immunotherapy: moving beyond current vaccines.

              Great progress has been made in the field of tumor immunology in the past decade, but optimism about the clinical application of currently available cancer vaccine approaches is based more on surrogate endpoints than on clinical tumor regression. In our cancer vaccine trials of 440 patients, the objective response rate was low (2.6%), and comparable to the results obtained by others. We consider here results in cancer vaccine trials and highlight alternate strategies that mediate cancer regression in preclinical and clinical models.
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                Author and article information

                Journal
                9502015
                8791
                Nat Med
                Nat. Med.
                Nature medicine
                1078-8956
                1546-170X
                8 February 2013
                03 March 2013
                April 2013
                01 October 2013
                : 19
                : 4
                : 465-472
                Affiliations
                [1 ]Department of Melanoma Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX
                [2 ]Department of Lymphoma/Myeloma, The University of Texas M.D. Anderson Cancer Center, Houston, TX
                [3 ]Department of Immunology, The University of Texas M.D. Anderson Cancer Center, Houston, TX
                Article
                NIHMS439415
                10.1038/nm.3105
                3618499
                23455713

                Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

                Funding
                Funded by: National Cancer Institute : NCI
                Award ID: P01 CA128913 || CA
                Categories
                Article

                Medicine

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