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Mendeley readers
| Title |
Chitosan gel vaccine protects against tumour growth in an intracaecal mouse model of cancer by modulating systemic immune responses
|
|---|---|
| Published in |
BMC Immunology, October 2016
|
| DOI | 10.1186/s12865-016-0178-4 |
| Pubmed ID | |
| Authors |
Andrew J. Highton, Adam Girardin, Georgia M. Bell, Sarah M. Hook, Roslyn A. Kemp |
| Abstract |
Vaccination generating a robust memory population of CD8(+) T cells may provide protection against cancer. However, immune therapies for cancer are influenced by the local tumour immune microenvironment. An infiltrate of T cells into tumours of people with colorectal cancer has proven to be a significant indicator of good prognosis. We used an intracaecal mouse model of cancer to determine whether a protective immune response against a mucosal gut tumour could be generated using a systemic intervention. We investigated the generation of murine memory CD8(+) T cells using a sustained antigen release vaccine vehicle (chitosan gel; Gel + OVA) containing the model antigen ovalbumin, chitosan gel alone (Gel) or conventional dendritic cell vaccination (DC + OVA) using the same protein antigen. Following vaccination with Gel + OVA, CD8(+) T cell memory populations specific for ovalbumin protein were detected. Only vaccination with Gel + OVA gave decreased tumour burden compared to unvaccinated or DC + OVA-vaccinated mice in the intracaecal cancer challenge model. These results indicate that subcutaneous vaccination with Gel + OVA generates a population of functional CD8(+) memory T cells in lymphoid tissue able to protect against intracaecal tumour challenge. Vaccination with chitosan gel may be valuable in anti-cancer treatment at both peripheral and mucosal sites. |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Unknown | 29 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 30% |
| Student > Bachelor | 5 | 17% |
| Student > Doctoral Student | 4 | 13% |
| Researcher | 3 | 10% |
| Student > Master | 3 | 10% |
| Other | 2 | 7% |
| Unknown | 4 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 27% |
| Agricultural and Biological Sciences | 6 | 20% |
| Psychology | 2 | 7% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Other | 6 | 20% |
| Unknown | 5 | 17% |