Title |
Designer vaccine nanodiscs for personalized cancer immunotherapy
|
---|---|
Published in |
Nature Materials, December 2016
|
DOI | 10.1038/nmat4822 |
Pubmed ID | |
Authors |
Rui Kuai, Lukasz J. Ochyl, Keith S. Bahjat, Anna Schwendeman, James J. Moon |
Abstract |
Despite the tremendous potential of peptide-based cancer vaccines, their efficacy has been limited in humans. Recent innovations in tumour exome sequencing have signalled the new era of personalized immunotherapy with patient-specific neoantigens, but a general methodology for stimulating strong CD8α(+) cytotoxic T-lymphocyte (CTL) responses remains lacking. Here we demonstrate that high-density lipoprotein-mimicking nanodiscs coupled with antigen (Ag) peptides and adjuvants can markedly improve Ag/adjuvant co-delivery to lymphoid organs and sustain Ag presentation on dendritic cells. Strikingly, nanodiscs elicited up to 47-fold greater frequencies of neoantigen-specific CTLs than soluble vaccines and even 31-fold greater than perhaps the strongest adjuvant in clinical trials (that is, CpG in Montanide). Moreover, multi-epitope vaccination generated broad-spectrum T-cell responses that potently inhibited tumour growth. Nanodiscs eliminated established MC-38 and B16F10 tumours when combined with anti-PD-1 and anti-CTLA-4 therapy. These findings represent a new powerful approach for cancer immunotherapy and suggest a general strategy for personalized nanomedicine. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 25 | 27% |
Spain | 6 | 6% |
France | 4 | 4% |
United Kingdom | 3 | 3% |
Netherlands | 2 | 2% |
Mexico | 2 | 2% |
Italy | 2 | 2% |
Japan | 2 | 2% |
Germany | 1 | 1% |
Other | 12 | 13% |
Unknown | 34 | 37% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 61 | 66% |
Scientists | 22 | 24% |
Practitioners (doctors, other healthcare professionals) | 9 | 10% |
Science communicators (journalists, bloggers, editors) | 1 | 1% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
South Africa | 1 | <1% |
Australia | 1 | <1% |
Unknown | 629 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 142 | 23% |
Researcher | 83 | 13% |
Student > Bachelor | 64 | 10% |
Student > Master | 61 | 10% |
Student > Doctoral Student | 38 | 6% |
Other | 76 | 12% |
Unknown | 167 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 101 | 16% |
Agricultural and Biological Sciences | 64 | 10% |
Engineering | 52 | 8% |
Immunology and Microbiology | 45 | 7% |
Chemistry | 39 | 6% |
Other | 135 | 21% |
Unknown | 195 | 31% |