The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Mouse Models for Cancer Immunotherapy Research
Open accessAbstract
Immunotherapy has revolutionized cancer therapy, largely attributed to the success of immune-checkpoint blockade. However, there are subsets of patients across multiple cancers who have not shown robust responses to these agents. A major impediment to progress in the field is the availability of faithful mouse models that recapitulate the complexity of human malignancy and immune contexture within the tumor microenvironment. These models are urgently needed across all malignancies to interrogate and predict antitumor immune responses and therapeutic efficacy in clinical trials. Herein, we seek to review pros and cons of different cancer mouse models, and how they can be used as platforms to predict efficacy and resistance to cancer immunotherapies. Significance: Although immunotherapy has shown substantial benefit in the treatment of a variety of malignancies, a key hurdle toward the advancement of these therapies is the availability of immunocompetent preclinical mouse models that recapitulate human disease. Here, we review the evolution of preclinical mouse models and their utility as coclinical platforms for mechanistic interrogation of cancer immunotherapies. Cancer Discov; 8(11); 1358–65. ©2018 AACR.
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Cited by
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Microbial metabolite enhances immunotherapy efficacy by modulating T cell stemness in pan-cancer
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Metallodrugs in cancer nanomedicine
Peña, Q., Wang, A., Zaremba, O., Shi, Y., Scheeren, H. W., Metselaar, J. M., Kiessling, F., Pallares, R. M., Wuttke, S., & Lammers, T. (2022) · Chemical Society Reviews · doi:10.1039/d1cs00468a · Cited by 259
Metadata
- Authors
- Olson, B., Li, Y., Lin, Y., Liu, E. T., & Patnaik, A.
- Venue
- Cancer Discovery
- Published
- 2018-11-01
- Volume
- 8
- Issue
- 11
- Pages
- 1358-1365
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- OpenAlex
- W2897100571
- Cited by
- 435
- References
- 46
- FWCI
- 11.12
- Type
- journal article
- Language
- en
- Open access
- green
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