BackgroundT-cell based immunotherapy for lung cancer (LC) could be a promising and novel therapeutic approach. Six-transmembrane epithelial antigen of the prostate (STEAP) and the polycomb group protein enhancer of zeste homolog 2 (EZH2) are highly expressed in LC and since the expression of molecules in normal tissue is significantly lower as compared to tumor cells, these proteins are considered as potential tumor-associated antigens (TAAs) for developing T-cell based immunotherapy.MethodsWe assessed the capacity of predicted CD4 T-cell epitopes from STEAP and EZH2 to induce anti-tumor immune responses to LC cell lines.ResultsOut of several predicted epitopes, two synthetic peptides, STEAP281-296 and EZH295-109, were effective in inducing CD4 T-cell responses that were restricted by HLA-DR1, DR15, or DR53 molecules, indicating that the peptides function as promiscuous T-cell epitopes. Moreover, STEAP281-296 and EZH295-109-reactive T-cells could directly recognize STEAP or EZH2 expressing LC cells in an HLA-DR restricted manner. In addition, some STEAP-reactive T-cells responded to STEAP+ tumor cell lysates presented by autologous dendric cells. Most significantly, both of these peptides were capable of stimulating in vitro T-cell responses in patients with LC.ConclusionsPeptides STEAP281-296 and EZH295-109 function as strong CD4 T-cell epitopes that can elicit effective anti-tumor T-cell responses against STEAP or EZH2 expressing LC. These observations may facilitate the translation of T-cell based immunotherapy into the clinic for the treatment of LC.
Six-transmembrane epithelial antigen of the prostate and enhancer of zeste homolog 2 as immunotherapeutic targets for lung cancer
S. Hayashi,T. Kumai,Yoshiya Matsuda,N. Aoki,Keisuke Sato,S. Kimura,M. Kitada,M. Tateno,E. Celis,Hiroya Kobayashi
Published 2011 in Journal of Translational Medicine
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- Publication year
2011
- Venue
Journal of Translational Medicine
- Publication date
2011-11-05
- Fields of study
Biology, Medicine
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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