Title |
Workshop on challenges, insights, and future directions for mouse and humanized models in cancer immunology and immunotherapy: a report from the associated programs of the 2016 annual meeting for the Society for Immunotherapy of cancer
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Published in |
Journal for Immunotherapy of Cancer, September 2017
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DOI | 10.1186/s40425-017-0278-6 |
Pubmed ID | |
Authors |
Andrew Zloza, A. Karolina Palucka, Lisa M. Coussens, Philip J. Gotwals, Mark B. Headley, Elizabeth M. Jaffee, Amanda W. Lund, Arlene H. Sharpe, Mario Sznol, Derek A. Wainwright, Kwok-Kin Wong, Marcus W. Bosenberg |
Abstract |
Understanding how murine models can elucidate the mechanisms underlying antitumor immune responses and advance immune-based drug development is essential to advancing the field of cancer immunotherapy. The Society for Immunotherapy of Cancer (SITC) convened a workshop titled, "Challenges, Insights, and Future Directions for Mouse and Humanized Models in Cancer Immunology and Immunotherapy" as part of the SITC 31st Annual Meeting and Associated Programs on November 10, 2016 in National Harbor, MD. The workshop focused on key issues in optimizing models for cancer immunotherapy research, with discussions on the strengths and weaknesses of current models, approaches to improve the predictive value of mouse models, and advances in cancer modeling that are anticipated in the near future. This full-day program provided an introduction to the most common immunocompetent and humanized models used in cancer immunology and immunotherapy research, and addressed the use of models to evaluate immune-targeting therapies. Here, we summarize the workshop presentations and subsequent panel discussion. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 63% |
Sweden | 1 | 13% |
France | 1 | 13% |
Unknown | 1 | 13% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 63% |
Practitioners (doctors, other healthcare professionals) | 2 | 25% |
Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 30 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 8 | 27% |
Professor | 4 | 13% |
Student > Ph. D. Student | 4 | 13% |
Other | 2 | 7% |
Student > Bachelor | 1 | 3% |
Other | 2 | 7% |
Unknown | 9 | 30% |
Readers by discipline | Count | As % |
---|---|---|
Immunology and Microbiology | 7 | 23% |
Medicine and Dentistry | 6 | 20% |
Agricultural and Biological Sciences | 3 | 10% |
Biochemistry, Genetics and Molecular Biology | 2 | 7% |
Veterinary Science and Veterinary Medicine | 1 | 3% |
Other | 0 | 0% |
Unknown | 11 | 37% |