Modeling the response to interleukin-21 to inform natural killer cell immunotherapy

模拟白细胞介素-21的反应以指导自然杀伤细胞免疫疗法

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Abstract

Natural killer (NK) cells are emerging agents for cancer therapy. Several different cytokines are used to generate NK cells for adoptive immunotherapy including interleukin (IL)-2, IL-12, IL-15 and IL-18 in solution, and membrane-bound IL-21. These cytokines drive NK cell activation through the integration of signal transducers and activators of transcription (STAT) and nuclear factor-kappa B (NF-κB) pathways, which overlap and synergize, making it challenging to predict optimal cytokine combinations for both proliferation and cytotoxicity. We integrated functional assays for NK cells cultured in a variety of cytokine combinations with mathematical modeling using feature selection and mechanistic regression models. Our regression model successfully predicts NK cell proliferation for different cytokine combinations and indicates synergy of activated STATs and NF-κB transcription factors between priming and post-priming phases. The use of IL-21 in solution in the priming of NK cell culture resulted in an improved NK cell proliferation, without compromising cytotoxicity potential or interferon gamma secretion against hepatocellular carcinoma cell lines. Our work provides an integrative framework for interrogating NK cell proliferation and activation for cancer immunotherapy.

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