Identification of T-cell epitopes for cancer immunotherapy. Export

@article{citeulike:1440291, abstract = {The effectiveness of T-cell-mediated immunotherapy of cancer depends on both an optimal immunostimulatory context of the therapy and the proper selection with respect to quality and quantity of the targeted tumor-associated antigens (TAA), and, more precisely, the T-cell epitopes contained in these tumor proteins. Our progressing insight in human leukocyte antigen (HLA) class I and class II antigen processing and presentation mechanisms has improved the prediction by reverse immunology of novel cytotoxic T lymphocyte and T-helper cell epitopes within known antigens. Computer algorithms that in silico predict HLA class I and class II binding, proteasome cleavage patterns and transporter associated with antigen processing translocation are now available to expedite epitope identification. The advent of genomics allows a high-throughput screening for tumor-specific transcripts and mutations, with that identifying novel shared and unique TAA. The increasing power of mass spectrometry and proteomics will lead to the direct identification from the tumor cell surface of numerous novel tumor-specific HLA class I and class II presented ligands. Together, the expanded repertoire of tumor-specific T-cell epitopes will enable more precise immunomonitoring and the development of effective epitope-defined adoptive T-cell transfer and multi-epitope-based vaccination strategies targeting epitopes derived from a wider diversity of TAA presented in a broader array of HLA molecules.}, author = {Kessler, J. H. and Melief, C. J.}, citeulike-article-id = {1440291}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/sj.leu.2404787}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/17611570}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=17611570}, doi = {10.1038/sj.leu.2404787}, issn = {0887-6924}, journal = {Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, U.K}, keywords = {algorithm, cancer-antigen, epitope, prediction, review}, month = {September}, number = {9}, pages = {1859--1874}, posted-at = {2008-07-15 16:25:18}, priority = {2}, publisher = {Nature Publishing Group}, title = {Identification of T-cell epitopes for cancer immunotherapy.}, url = {http://dx.doi.org/10.1038/sj.leu.2404787}, volume = {21}, year = {2007} }

TY - JOUR ID - citeulike:1440291 L3 - citeulike-article-id:1440291 N2 - The effectiveness of T-cell-mediated immunotherapy of cancer depends on both an optimal immunostimulatory context of the therapy and the proper selection with respect to quality and quantity of the targeted tumor-associated antigens (TAA), and, more precisely, the T-cell epitopes contained in these tumor proteins. Our progressing insight in human leukocyte antigen (HLA) class I and class II antigen processing and presentation mechanisms has improved the prediction by reverse immunology of novel cytotoxic T lymphocyte and T-helper cell epitopes within known antigens. Computer algorithms that in silico predict HLA class I and class II binding, proteasome cleavage patterns and transporter associated with antigen processing translocation are now available to expedite epitope identification. The advent of genomics allows a high-throughput screening for tumor-specific transcripts and mutations, with that identifying novel shared and unique TAA. The increasing power of mass spectrometry and proteomics will lead to the direct identification from the tumor cell surface of numerous novel tumor-specific HLA class I and class II presented ligands. Together, the expanded repertoire of tumor-specific T-cell epitopes will enable more precise immunomonitoring and the development of effective epitope-defined adoptive T-cell transfer and multi-epitope-based vaccination strategies targeting epitopes derived from a wider diversity of TAA presented in a broader array of HLA molecules. IS - 9 JF - Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, U.K SN - 0887-6924 EP - 1874 TI - Identification of T-cell epitopes for cancer immunotherapy. PB - Nature Publishing Group VL - 21 SP - 1859 KW - algorithm KW - cancer-antigen KW - epitope KW - prediction KW - review AU - Kessler, JH AU - Melief, CJ PY - 2007/09// UR - http://dx.doi.org/10.1038/sj.leu.2404787 ER -