Chapter title |
Mouse Models of Tumor Immunotherapy
|
---|---|
Book title |
Tumor Immunology
|
Published in |
Advances in Immunology, January 2016
|
DOI | 10.1016/bs.ai.2015.12.004 |
Pubmed ID | |
Book ISBNs |
978-0-12-805156-6
|
Authors |
Shin Foong Ngiow, Sherene Loi, David Thomas, Mark J. Smyth, Ngiow, Shin Foong, Loi, Sherene, Thomas, David, Smyth, Mark J, Smyth, Mark J. |
Abstract |
Immunotherapy is now evolving into a major therapeutic option for cancer patients. Such clinical advances also promote massive interest in the search for novel immunotherapy targets, and to understand the mechanism of action of current drugs. It is projected that a series of novel immunotherapy agents will be developed and assessed for their therapeutic activity. In light of this, in vivo experimental mouse models that recapitulate human malignancies serve as valuable tools to validate the efficacy and safety profile of immunotherapy agents, before their transition into clinical trials. In this review, we will discuss the major classes of experimental mouse models of cancer commonly used for immunotherapy assessment and provide examples to guide the selection of appropriate models. We present some new data concerning the utility of a carcinogen-induced tumor model for comparing immunotherapies and combining immunotherapy with chemotherapy. We will also highlight some recent advances in experimental modeling of human malignancies in mice that are leading towards personalized therapy in patients. |
X Demographics
Geographical breakdown
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 151 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 40 | 26% |
Student > Ph. D. Student | 34 | 23% |
Student > Master | 17 | 11% |
Student > Bachelor | 16 | 11% |
Student > Postgraduate | 8 | 5% |
Other | 14 | 9% |
Unknown | 22 | 15% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 34 | 23% |
Agricultural and Biological Sciences | 24 | 16% |
Medicine and Dentistry | 18 | 12% |
Immunology and Microbiology | 16 | 11% |
Pharmacology, Toxicology and Pharmaceutical Science | 11 | 7% |
Other | 17 | 11% |
Unknown | 31 | 21% |