Identifikation und immunologische Charakterisierung von MHC ...

Abstract:
CD4+ T cells play important roles in antitumor responses through several
different mechanisms. Ultimately, they provide crucial help in the induction
and maintenance of CTL responses. Experiments in animal models have
demonstrated the importance of antigen-specific CD4+ T cells in the
elimination of tumors. Peptide vaccination to elicit antitumor immunity
remains an attractive way to treat cancer patients. Because the main effort has
been to induce CTL responses, a logical way to enhance the potency of these
tumor vaccines is to include CD4+ T cell epitopes for the same tumor antigen.
The central goal of the work was to identify MHC class II peptide epitopes in
such proteins, which exhibit a tumor-associated expression and which were
already well-known target antigens of cytotoxic T-cell reactions. In this work,
proteinase 3 (PR3) and survivin (SVN) were selected as candidate antigens
associated with leukemia and lymphoma. MHC class II candidate epitopes
from these proteins were computer-assisted predicted and used as synthetic
peptides for in vitro stimulation by human CD4+ T-cells. Peptide specific CD4+
T-cells were examined regarding their immune reactivity with the
corresponding tumor protein. Several class-II epitope candidates in SVN and
PR3 were identified by examining human T-cell responses to synthetic
peptides. Then, epitope candidates were characterized by establishing and
analyzing peptide-specific T-cell clones. It was demonstrated that CD4+ T cells
specific for the SVN10 epitope respond to naturally processed SVN proteins.
This epitope was presented by several HLA-DR alleles, including DR3, DR4,
DR7, and DR11. Furthermore, the SVN10-specific T cells recognized SVN
antigen from various tumor cell lines. Moreover, the T-cell clones were
examined for MHC restriction patterns, immunophenotypes and epitope-
MHC avidity. It was further found that SVN10 was promiscuous and capable
of inducing CD4+ T cell responses in cancer patients. Thus, the identification
of the naturally processed SVN epitope, together with the previous finding of
class I-restricted SVN epitopes, provide a basis for the combined application of