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Critical Reviews™ in Immunology

Publication de 6  numéros par an

ISSN Imprimer: 1040-8401

ISSN En ligne: 2162-6472

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.3 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 2.6 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00079 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.24 SJR: 0.429 SNIP: 0.287 CiteScore™:: 2.7 H-Index: 81

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Transcriptional Analysis of Tumor-Specific T-Cell Responses in Cancer Patients

Volume 22, Numéro 5-6, 2002, 14 pages
DOI: 10.1615/CritRevImmunol.v22.i5-6.60
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RÉSUMÉ

Over the last decade, tumor immunology in general and tumor immunotherapy in particular have made important progress. Thanks to the discovery of tumor-associated antigens (TAA), and the consequent development of active-specific immunization protocols, TAA-specific T-cell responses can now be induced reproducibly in cancer patients. However, clinical responses directly ascribable to TAA-specific T cells occur only occasionally. It is not clear why TAA-specific T cells do not eliminate tumor cells in vivo. This paradoxical coexistence of antigen-bearing tumor cells and antigen-specific T cells constitutes a critical point of current investigation. In recent years, protein–ligand interaction–based methods aimed at the identification and characterization of T cells using antibodies (cell surface phenotyping, intracellular and secreted cytokine detection), or HLA-peptide multimers, have significantly improved the analysis of TAA-specific T cells. These methods, however, seem to have reached the limit of their usefulness. Transcriptional analysis may add sensitivity and resolution and may provide global pictures of the multifactorial requirements for an efficient immune response against tumors. In this review, we describe the use of molecular genetic methods, such as real time qRT-PCR, cDNA microarrays, and TCR repertoire analysis. In addition, we describe techniques for high-fidelity messenger RNA amplification that allow high-throughput analysis of samples obtained from minimal sources, such as HLA/peptide tetramer sorted antigen-specific T cells, laser capture dissection, or fine needle aspirates. Recent work discussed in this review summarizes the complementarity of transcriptional analysis as an essential tool that, in addition to conventional methods, may deepen and broaden the characterization of tumor-specific T cells.

CITÉ PAR
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  6. Ochsenreither Sebastian, Fusi Alberto, Wojtke Susanne, Busse Antonia, Nüssler Natascha C, Thiel Eckhard, Keilholz Ulrich, Nagorsen Dirk, Comparison of T-cell receptor repertoire restriction in blood and tumor tissue of colorectal cancer patients, Journal of Translational Medicine, 8, 1, 2010. Crossref

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