| Title |
Induction of Polyclonal Prostate Cancer-Specific CTL Using Dendritic Cells Transfected with Amplified Tumor RNA
|
|---|---|
| Published in |
The Journal of Immunology, March 2001
|
| DOI | 10.4049/jimmunol.166.5.2953 |
| Pubmed ID | |
| Authors |
Axel Heiser, Margaret A. Maurice, Donna R. Yancey, Ning Z. Wu, Philipp Dahm, Scott K. Pruitt, David Boczkowski, Smita K. Nair, Michael S. Ballo, Eli Gilboa, Johannes Vieweg |
| Abstract |
Polyvalent cancer vaccines targeting the entire antigenic spectrum on tumor cells may represent a superior therapeutic strategy for cancer patients than vaccines solely directed against single Ags. In this study, we show that autologous dendritic cells (DC) transfected with RNA amplified from microdissected tumor cells are capable of stimulating CTL against a broad set of unidentified and critical prostate-specific Ags. Although the polyclonal CTL responses generated with amplified tumor RNA-transfected DC encompassed as a subcomponent a response against prostate-specific Ag (PSA) as well as against telomerase reverse transcriptase, the tumor-specific CTL were consistently more effective than PSA or telomerase reverse transcriptase CTL to lyse tumor targets, suggesting the superiority of the polyclonal response. Although tumor RNA-transfected DC stimulated CTL, which recognized not only tumor but also self-Ags expressed by benign prostate tissue, these cross-reactive CTL were exclusively specific for the PSA, indicating an immunodominant role of PSA in the prostate cancer-specific immune response. Our data suggest that tumor RNA-transfected DC may represent a broadly applicable, potentially clinically effective vaccine strategy for prostate cancer patients, which is not limited by tumor tissue availability for Ag preparation and may minimize the risk of clonal tumor escape. |
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Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 3% |
| Unknown | 35 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 22% |
| Researcher | 5 | 14% |
| Student > Bachelor | 4 | 11% |
| Other | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 6 | 17% |
| Unknown | 7 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 31% |
| Medicine and Dentistry | 7 | 19% |
| Biochemistry, Genetics and Molecular Biology | 6 | 17% |
| Immunology and Microbiology | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 0 | 0% |
| Unknown | 8 | 22% |