Virus-Based Immuno-Oncology Models.
Virus-Based Immuno-Oncology Models.
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DOI:
10.3390/biomedicines10061441
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发表时间:
2022-06-18
期刊:
影响因子:
4.7
通讯作者:
中科院分区:
文献类型:
--
作者:
Immunotherapy has been extensively explored in recent years with encouraging results in selected types of cancer. Such success aroused interest in the expansion of such indications, requiring a deep understanding of the complex role of the immune system in carcinogenesis. The definition of hot vs. cold tumors and the role of the tumor microenvironment enlightened the once obscure understanding of low response rates of solid tumors to immune check point inhibitors. Although the major scope found in the literature focuses on the T cell modulation, the innate immune system is also a promising oncolytic tool. The unveiling of the tumor immunosuppressive pathways, lead to the development of combined targeted therapies in an attempt to increase immune infiltration capability. Oncolytic viruses have been explored in different scenarios, in combination with various chemotherapeutic drugs and, more recently, with immune check point inhibitors. Moreover, oncolytic viruses may be engineered to express tumor specific pro-inflammatory cytokines, antibodies, and antigens to enhance immunologic response or block immunosuppressive mechanisms. Development of preclinical models capable to replicate the human immunologic response is one of the major challenges faced by these studies. A thorough understanding of immunotherapy and oncolytic viruses’ mechanics is paramount to develop reliable preclinical models with higher chances of successful clinical therapy application. Thus, in this article, we review current concepts in cancer immunotherapy including the inherent and synthetic mechanisms of immunologic enhancement utilizing oncolytic viruses, immune targeting, and available preclinical animal models, their advantages, and limitations.
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影响因子:
3.6
作者:
Bandola-Simon J;Roche PA
通讯作者:
Roche PA
影响因子:
4.8
作者:
Dillman RO
通讯作者:
Dillman RO
影响因子:
4.7
作者:
Denton NL;Chen CY;Scott TR;Cripe TP
通讯作者:
Cripe TP
DOI:
10.1126/science.1252510
发表时间:
2014-05-23
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Franklin RA;Liao W;Sarkar A;Kim MV;Bivona MR;Liu K;Pamer EG;Li MO
通讯作者:
Li MO
影响因子:
7.4
作者:
De Carlo, Flavia;Thomas, Litty;Howard, Candace M.
通讯作者:
Howard, Candace M.