Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan.
Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan.
J Control Release. 2022 May;345:200-213. doi: 10.1016/j.jconrel.2022.03.026. Epub 2022 Mar 18.
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.
由于癌症免疫疗法的效果在很大程度上取决于肿瘤微环境 (TME) 中免疫系统的状态,因此基于 TME 中的免疫状态选择治疗方法和开发新疗法预计将是有效的。不幸的是,这种治疗方法的递送系统的发展一直很缓慢。在这里,我们定义了一个在 TME 中显示抗肿瘤作用的免疫状态参数,并展示了一种用负载佐剂的脂质纳米颗粒 (LNP) 进行的癌症免疫疗法,该方法利用了该参数。进行了一项分析,以确定对程序性细胞死亡 1 (PD-1) 抗体有反应和无反应的肿瘤 (MC38 和 E.G7-OVA) 中抗肿瘤作用与基因表达 (22 个靶基因) 之间的关系。然后提取出显示有效抗肿瘤作用的免疫状态,该免疫状态由 10 个基因组成。用负载佐剂的 LNP 治疗对 E.G7-OVA 肿瘤产生了显著的抗肿瘤作用,并且 E.G7-OVA 肿瘤中的基因表达完全在由确定的免疫状态面板 (IS-panel-10) 定义的显示有效抗肿瘤作用的基因表达范围内。尽管用负载佐剂的 LNP 治疗未能对 4T1 肿瘤产生足够的抗肿瘤作用,但我们成功地通过采用基于 TME 中 IS-panel-10 的分析的联合治疗增强了抗肿瘤作用。这 10 个基因被发现影响各种人类癌症的预后。总的来说,本研究结果表明,在 TME 中进行免疫状态分析具有利用递送系统开发癌症免疫疗法的潜力。