Title |
Mining the mutanome: developing highly personalized Immunotherapies based on mutational analysis of tumors
|
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Published in |
Journal for Immunotherapy of Cancer, July 2013
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DOI | 10.1186/2051-1426-1-11 |
Pubmed ID | |
Authors |
Willem W Overwijk, Ena Wang, Francesco M Marincola, Hans-Georg Rammensee, Nicholas P Restifo, for the Organizing Committee of the 2013 SITC Workshop on Personalized Immunotherapy |
Abstract |
T cells can mediate remarkable tumor regressions including complete cure in patients with metastatic cancer. Genetic alterations in an individual's cancer cells (the mutanome) encode unique peptides (m-peptides) that can be targets for T cells. The recent advances in next-generation sequencing and computation prediction allows, for the first time, the rapid and affordable identification of m-peptides in individual patients. Despite excitement about the extended spectrum of potential targets in personalized immunotherapy, there is no experience or consensus on the path to their successful clinical application. Major questions remain, such as whether clinical responses to cytokine therapy, T cell transfer, and checkpoint blockade are primarily mediated by m-peptide-specific reactivity, whether m-peptides can be effectively used as vaccines, and which m-peptides are most potently recognized. These and other technological, immunological and translational questions will be explored during a 1-day Workshop on Personalized Cancer Immunotherapy by the Society for Immunotherapy of Cancer, directly before the Annual Meeting, on November 7, 2013 at the National Harbor, MD near Washington, DC. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Spain | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 3% |
Korea, Republic of | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 102 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 22 | 21% |
Researcher | 20 | 19% |
Student > Master | 12 | 11% |
Other | 11 | 10% |
Student > Bachelor | 7 | 7% |
Other | 18 | 17% |
Unknown | 17 | 16% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 32 | 30% |
Medicine and Dentistry | 23 | 21% |
Biochemistry, Genetics and Molecular Biology | 18 | 17% |
Immunology and Microbiology | 5 | 5% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 3% |
Other | 4 | 4% |
Unknown | 22 | 21% |