journal article·2013-07

Particle-size-dependent toxicity and immunogenic activity of mesoporous silica-based adjuvants for tumor immunotherapy

Xiupeng Wang, Xia Li, Atsuo Ito, Yu Sogo, Tadao Ohno

Acta Biomaterialia· Volume 9· Issue 7
Publisher page

Abstract

Conventionally used adjuvants alone are insufficient for triggering cell-mediated immunity, although they have been successfully developed to elicit protective antibody responses in some vaccines. Here, with the aim of eliciting cell-mediated immunity, pathogen-associated molecular patterns (PAMPs) were immobilized with apatite within the pores and on the surface of mesoporous silica (MS) with particle sizes from 30 to 200nm to prepare novel MS-Ap-PAMP adjuvants, which showed cell-mediated anti-tumor immunity that was markedly improved compared to commercial alum adjuvant in vitro and in vivo. The toxicity and antitumor immunity of the MS-Ap-PAMP adjuvants were evaluated in vitro and in vivo. MS with a particle size of 200nm showed minimum in vitro cytotoxicity to NIH3T3 cells, particularly at concentrations no higher than 100μgml(-1). In particular, apatite precipitation within the pores and on the surface of MS decreased the in vitro cytotoxicity of MS particles. The MS-Ap-PAMP adjuvants showed the maximum in vitro immunogenic activity among original culture medium, PAMP and alum-PAMP. Moreover, injection of the MS-Ap-PAMP adjuvant in combination with liquid-nitrogen-treated tumor tissue (derived from Lewis lung carcinoma cells) into C57BL/6 mice markedly inhibited in vivo tumor recurrence and the development of rechallenged tumor compared to those with commercial alum adjuvant. The MS-Ap-PAMP adjuvant contributed to the elicitation of a potent systemic antitumor immunity without obvious toxicity in vivo.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Nanoparticle-Based Drug Delivery · Nanoplatforms for cancer theranostics · Graphene and Nanomaterials Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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