Stimulation of natural killer cells with rhCD137 ligand enhances tumor-targeting antibody efficacy in gastric cancer
Although many anticancer agents for gastric cancer have been developed, the prognosis for many patients remains poor. Recently, costimulatory immune molecules that reactivate antitumor immune responses by utilizing the host immune system have attracted attention as new therapeutic strategies. CD137 is a costimulatory molecule that reportedly potentiates the antitumor activity of tumor-targeting monoclonal antibodies (mAbs) by enhancing antibody-dependent cellular cytotoxicity. However, it remains unclear whether CD137 stimulates tumor-regulatory activity in gastric cancer. In this study, we investigated the antitumor effects of CD137 stimulation on gastric cancer cells administered tumor-targeting mAbs. Our results showed that human natural killer (NK) cells were activated by expressing CD137 after encountering trastuzumab-coated gastric cancer cells, and that stimulation of activated NK cells in the presence of trastuzumab and recombinant human CD137 ligand (rhCD137L) enhanced cytotoxicity and release of cytokines (IFN-γ, TNF, granzyme A, or granzyme B) as compared with activated NK cells with trastuzumab alone (p < 0.05). By combination treatment with rhCD137L, similar effects were obtained regarding cancer cell cytotoxicity in the presence of cetuximab (p < 0.01). Moreover, we revealed that CD137 expression was dependent upon the affinity between the Fc portion of the antibodies and FcγRIIIa of NK cells based on results indicating that human IgG1 and IgG3 subclasses enhanced CD137 expression (p < 0.001). These results confirmed that FcγRIIIA polymorphisms (158 V/V) enhanced CD137 expression to a greater degree than 158 F polymorphisms (p = 0.014). Our results suggested that CD137 stimulation could promote the effects of tumor-targeting mAbs in gastric cancer, and that further investigation of antibody binding affinity and in vivo activities might improve therapeutic strategies related to the treatment of gastric cancer patients.
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组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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