Title |
Dendritic Cell-Based Vaccine Efficacy: Aiming for Hot Spots
|
---|---|
Published in |
Frontiers in immunology, March 2015
|
DOI | 10.3389/fimmu.2015.00091 |
Pubmed ID | |
Authors |
Gabriela Andrea Pizzurro, María Marcela Barrio |
Abstract |
Many approaches for cancer immunotherapy have targeted dendritic cells (DCs), directly or indirectly, for the induction of antitumor immune responses. DC-based vaccines have been developed using a wide variety of ex vivo DC culture conditions, antigen (Ag) source and loading strategies, maturation agents, and routes of vaccination. Adjuvants are used to activate innate immune cells at the vaccine injection site, to promote Ag transport to the draining lymph nodes (LNs) and to model adaptive immune responses. Despite years of effort, the effective induction of strong and durable antitumor T-cell responses in vaccinated patients remains a challenge. The study of vaccine interactions with other immune cells in the LNs and, more recently, in the injection site has opened new doors for understanding antitumor effector T-cell licensing and function. In this review, we will briefly discuss the relevant sites and up-to-date facts regarding possible targets for antitumor vaccine refinement. We will focus on the processes taking place at the injection site, adjuvant combinations and their role in DC-based vaccines, LN homing, and modeling vaccine-induced immune responses capable of controlling tumor growth and generating immune memory. |
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Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 50% |
Switzerland | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Science communicators (journalists, bloggers, editors) | 1 | 50% |
Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 1% |
Denmark | 1 | 1% |
Unknown | 85 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 19 | 22% |
Researcher | 17 | 20% |
Student > Master | 15 | 17% |
Student > Bachelor | 14 | 16% |
Student > Postgraduate | 4 | 5% |
Other | 12 | 14% |
Unknown | 6 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 25 | 29% |
Medicine and Dentistry | 22 | 25% |
Biochemistry, Genetics and Molecular Biology | 12 | 14% |
Immunology and Microbiology | 7 | 8% |
Engineering | 5 | 6% |
Other | 9 | 10% |
Unknown | 7 | 8% |