Combined nano cancer immunotherapy based on immune status in a tumor microenvironment

免疫系统 佐剂 肿瘤微环境 免疫疗法 癌症研究 癌症免疫疗法 癌症 免疫增强剂 医学 免疫学 辅助治疗 遗传增强 生物 基因 内科学 生物化学
作者
Takashi Nakamura,Kimihiro Kawakami,Momoka Nomura,Yusuke Sato,Mamoru Hyodo,Hiroto Hatakeyama,Yoshihiro Hayakawa,Hideyoshi Harashima
出处
期刊:Journal of Controlled Release [Elsevier]
卷期号:345: 200-213 被引量:14
标识
DOI:10.1016/j.jconrel.2022.03.026
摘要

Since the effect of cancer immunotherapy is largely dependent on the status of the immune system in the tumor microenvironment (TME), choice of therapy and the development of new therapies based on the immune status in the TME would be predicted to be effective. Unfortunately, the development of delivery systems for such therapy has been slow. Here, we defined a parameter of immune status in TME showing antitumor effects and demonstrated the cancer immunotherapy with an adjuvant loaded lipid nanoparticle (LNP), which was taken advantage the parameter. An analysis was carried out to determine the relationship between antitumor effects and gene expression (22 target genes) in tumors (MC38 and E.G7-OVA) that respond to the programmed cell death 1 (PD-1) antibody and non-responding tumors (B16-F10 and 4T1). The immune status showing an effective antitumor effect, which consisted of 10 genes, was then extracted. Treatment with the adjuvant loaded LNP caused a significant antitumor effect against an E.G7-OVA tumor, and the gene expression in the E.G7-OVA tumor was completely within the range of gene expression for showing an effective antitumor effect, as defined by the identified immune status panel (IS-panel-10). Although the treatment with the adjuvant loaded LNP failed to induce a sufficient antitumor effect against the 4T1 tumor, we succeeded in enhancing the antitumor effect by using a combination therapy that was adopted based on the analysis by the IS-panel-10 in the TME. The 10 genes were found to affect the prognosis in a variety of human cancers. Collectively, the findings reported herein demonstrate the potential of immune status analysis in the TME for developing cancer immunotherapies using a delivery system.
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