CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Dynamic changes in immune cells in humanized liver metastasis and subcutaneous xenograft mouse models.
Dynamic changes in immune cells in humanized liver metastasis and subcutaneous xenograft mouse models.
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临床前药物疗效和肿瘤微环境(TME)研究通常使用人源化异种移植小鼠模型,但这些模型通常难以复制复杂的TME。我们通过移植人外周血单个核细胞(PBMCs)开发了一种人源化肝转移(LM)模型,并将其与常规皮下(SC)异种移植模型进行对比评估,重点关注移植后免疫细胞动态和免疫治疗反应。将PBMCs接种至NOD-scid IL2Rgamma null(NSG)小鼠以建立人源化模型。
我们使用HCT116细胞诱导SC和LM模型,分别研究和比较免疫细胞亚群的分布和转化。两种模型均接受抗PD-L1治疗,随后进行TME分析。与SC模型的外周模式相比,LM模型表现出增强的中央肿瘤浸润性淋巴细胞(TILs)浸润。LM模型中的TIL亚群呈进行性增加,而SC模型则表现为先升高后下降。抗PD-L1治疗后,LM模型显示中央记忆T细胞和效应记忆T细胞显著增加,而SC模型无此反应。
我们的研究揭示了SC和LM模型之间的差异性TME反应,并介绍了一种稳健的人源化LM模型,该模型能快速指示免疫治疗的潜在疗效。这些发现可简化靶向TME的免疫治疗药物的临床前评估。
Preclinical drug efficacy and tumor microenvironment (TME) investigations often utilize humanized xenograft mouse models, yet these models typically fall short in replicating the intricate TME.
We developed a humanized liver metastasis (LM) model by transplanting human peripheral blood mononuclear cells (PBMCs) and assessed it against the conventional subcutaneous (SC) xenograft model, focusing on immune cell dynamics post-transplantation and immunotherapy response. NOD-scid IL2Rgamma null (NSG) were inoculated with PBMCs to create humanized models.
We induced SC and LM models using HCT116 cells, to investigate and compare the distributions and transformations of immune cell subsets, respectively. Both models were subjected to anti-PD-L1 therapy, followed by an analysis the TME analysis. The LM model demonstrated enhanced central tumor infiltration by tumor-infiltrating lymphocytes (TILs) compared to the peripheral pattern of SC model.
TIL subpopulations in the LM model showed a progressive increase, contrasting with an initial rise and subsequent decline in the SC model. Post-anti-PD-L1 therapy, the LM model exhibited a significant rise in central and effector memory T cells, a response absents in the SC model.
Our study highlights differential TME responses between SC and LM models and introduces a robust humanized LM model that swiftly indicates the potential efficacy of immunotherapies. These insights could streamline the preclinical evaluation of TME-targeting immunotherapeutic agents.
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