Size Tuning of Mesoporous Silica Adjuvant for One-Shot Vaccination with Long-Term Anti-Tumor Effect.
Xiupeng WangYu SogoXia LiPublished in: Pharmaceutics (2024)
Despite recent clinical successes in cancer immunotherapy, it remains difficult to initiate a long-term anti-tumor effect. Therefore, repeated administrations of immune-activating agents are generally required in most cases. Herein, we propose an adjuvant particle size tuning strategy to initiate a long-term anti-tumor effect by one-shot vaccination. This strategy is based on the size-dependent immunostimulation mechanism of mesoporous silica particles. Hollow mesoporous silica (HMS) nanoparticles enhance the antigen uptake with dendritic cells around the immunization site in vivo. In contrast, hierarchically porous silica (HPS) microparticles prolong cancer antigen retention and release in vivo. The size tuning of the mesoporous silica adjuvant prepared by combining both nanoparticles and microparticles demonstrates the immunological properties of both components and has a long-term anti-tumor effect after one-shot vaccination. One-shot vaccination with HMS-HPS-ovalbumin (OVA)-Poly IC (PIC, a TLR3 agonist) increases CD4 + T cell, CD8 + T cell, and CD86 + cell populations in draining lymph nodes even 4 months after vaccination, as well as effector memory CD8 + T cell and tumor-specific tetramer + CD8 + T cell populations in splenocytes. The increases in the numbers of effector memory CD8 + T cells and tumor-specific tetramer + CD8 + T cells indicate that the one-shot vaccination with HMS-HPS-OVA-PIC achieved the longest survival time after a challenge with E.G7-OVA cells among all groups. The size tuning of the mesoporous silica adjuvant shows promise for one-shot vaccination that mimics multiple clinical vaccinations in future cancer immunoadjuvant development. This study may have important implications in the long-term vaccine design of one-shot vaccinations.
Keyphrases
- dendritic cells
- early stage
- lymph node
- immune response
- magnetic resonance
- regulatory t cells
- computed tomography
- machine learning
- squamous cell carcinoma
- working memory
- oxidative stress
- induced apoptosis
- bone marrow
- mass spectrometry
- deep learning
- neoadjuvant chemotherapy
- cell proliferation
- big data
- childhood cancer
- lymph node metastasis