BACKGROUND: Traditional cancer vaccines that utilize peptides or proteins often exhibit limited efficacy as a result of mutations in cancer antigenic epitopes, also known as antigenic drift, which reduce the ability of traditional vaccines to target tumor antigens and elicit robust immune response. METHODS: To address these challenges, we propose an innovative and universal strategy for dendritic cell (DC)-targeted neoepitope delivery via proximity-induced conjugation (PIC). This approach enables the site-specific crosslink of a broad spectrum of neoepitopes tailored to diverse cancer types, thereby increasing both vaccine flexibility and applicability. The PIC method involves the use of recombinant Fc-affinity peptides that are modified with two distinct unnatural amino acids: the photoreactive amino acid p-benzoyl-L-phenylalanine (pBPA) and the bioorthogonal reactive amino acid 4-fluorophenyl carbamate lysine (FPheK). These modified peptides allow for the precise conjugation of neoepitopes through ultraviolet (UV) irradiation or mild incubation, thereby achieving controlled antigen coupling. RESULTS: Through optimization of this strategy, we observed a substantial increase in DCs mediated antigen uptake and processing, leading to enhanced T cell activation, a robust cytotoxic immune response, and significant improvements in antitumor efficacy. Moreover, the DC-targeted vaccine exhibited promising synergistic effects with an immune checkpoint inhibitor (ICI), resulting in a marked reduction in tumor growth and prolonged survival in preclinical models. CONCLUSION: These findings underscore the potential of the PIC-based DC-targeted vaccine system to augment the immunogenicity, versatility, and therapeutic efficacy of cancer vaccines. This strategy offers a compelling solution to the challenges posed by antigenic drift and mutation, thereby improving clinical outcomes across a broad range of cancers.
Development of a dendritic cell-targeted vaccine strategy using proximity-induced conjugation.
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作者:Wang Zhidong, Yang Xiaolin, Li Jianjiang, Chen Guang, Ma Haodi, Xu Zhengshuang, Cao Yu J
| 期刊: | Theranostics | 影响因子: | 13.300 |
| 时间: | 2026 | 起止号: | 2026 Feb 11; 16(9):4641-4656 |
| doi: | 10.7150/thno.122332 | ||
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