Reverse immunology

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Reverse Immunology ( engl. Reverse immunology ) is a method for predicting and identifying antigens . It is particularly used in vaccine design and in tumor immunology to identify tumor antigens .

description

The “classic” methods of identifying tumor antigens, such as cDNA expression cloning , start with T lymphocytes and antibodies and determine which antigens they recognize. In reverse immunology, the starting point - as the name suggests - is reversed, and identification is started from the antigen.

Reverse immunology begins with the theoretical prediction of MHC class I and II ligands from protein sequences and subsequent testing of the recognition of these epitopes by T lymphocytes in the course of epitope mapping . The process can be largely automated and works as a high-throughput screening .

The prediction of the antigen epitopes takes place with the support of computers ( in silico ), for example by means of NetMHCpan. There are a number of epitope prediction programs available. The epitopes are mostly tested in vitro , but can also be done in vivo in model organisms . The prediction is then checked using ELISPOT or, in the case of cytotoxic T cells , using a cytotoxicity release assay . The antigen candidates can either come from amino acid sequences of natural ligands or from peptide libraries of synthetic peptides. The epitopes consist of about 8-11 (for MHC I) or about 15-20 (for MHC II) amino acids. Synthetic epitopes can be produced, for example, by solid phase synthesis .

Potential

With reverse immunology, completely new disease-associated antigens can be identified. In principle, the method has the potential to specifically identify tumor antigens for each individual patient. In the future, individual cancer vaccination with several tumor antigens could become possible.

See also

Individual evidence

  1. ↑ V. Lennerz: Identification and characterization of T-cell-recognized tumor antigens in the MZ7 melanoma model. Dissertation, Johannes Gutenberg University Mainz, 2002
  2. ↑ a b M. Schirle et al .: Identification of tumor-associated MHC class I ligands by a novel T cell-independent approach. In: Eur J Immunol 30, 2000, pp. 2216-2225. PMID 10940913
  3. ↑ S. Viatte include: reverse immunology approach for the identification of CD8 T-cell-defined antigens: Advantages and hurdles. In: Immunology and Cell Biology 84, 2006, pp. 318-330. PMID 16681829 doi : 10.1111 / j.1440-1711.2006.01447.x (Review)
  4. ↑ NetMHCpan, a method for quantitative predictions of peptide binding to any HLA-A and -B locus protein of known sequence. Nielsen M, Lundegaard C, Blicher T, Lamberth K, Harndahl M, Justesen S, Roeder G, Peters B, Sette A, Lund O, Buus S. PMID 17726526
  5. ↑ K. Falk et al.: Allelespecific motifs revealed by sequencing of self-peptides eluted from MHC molecules. In: Nature 351, 1991, pp. 290-296. PMID 1709722
  6. ↑ KC Parker et al: Scheme for ranking potential HLA-A2 binding peptides based on independent binding of individual peptide side chains. J Immunol 152, 1994, pp. 163-175. PMID 8254189
  7. ↑ J. Hammer et al .: Precise prediction of major histocompatibility complex class II-peptide interaction based on peptide side chain scanning. In: J Exp Med 180, 1994, pp. 2353-2358. PMID 7964508
  8. ^ HG Rsamee et al .: Towards patient-specific tumor antigen selection for vaccination. In: Immunol Rev 188, 2002, pp. 164-176. PMID 12445290
  9. ↑ M. Schwarz: Identification of potentially immunogenic peptides on cells of chronic myeloid leukemia. Dissertation, FU Berlin, 2004

literature

Reference books

  • C. Huber (editor) among others: Cancer immunotherapies. Deutscher Ärzteverlag, 2007, ISBN 3-769-11212-1 , p. 17.
  • ML Disis: Immunotherapy of Cancer. Humana Press, 2006, ISBN 1-588-29564-8 (English) pp. 23f.

Review article

  • JH Kessler and CJ Melief: Identification of T-cell epitopes for cancer immunotherapy. In: Leukemia 21, 2007, pp. 1859-1874. PMID 17611570
  • KS Anderson and J. LaBaer: The sentinel within: Exploiting the immune system for cancer biomarkers. In: J. Proteome Res. 4, 2005, pp. 1123-1133. PMID 16083262
  • S. Stevanovic: Antigen processing is predictable: From genes to T cell epitopes. In: Transpl Immunol 14, 2005, pp. 171-174. PMID 15982559
  • A. Paschen et al .: Identification of tumor antigens and T-cell epitopes, and its clinical application. In: Cancer Immunol Immunother 53, 2004, pp. 196-203. PMID 14689239
  • B. Maecker et al: Linking genomics to immunotherapy by reverse immunology - 'immunomics' in the new millennium. In: Curr Mol Med 1, 2001, pp. 609-619. PMID 11899235