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Letter to the Editor: The Hepa 1–6 may not be suitable for use in hepatocellular carcinoma models to explore responses to drug therapy

肝细胞癌 赫帕 药品 医学 肿瘤科 内科学 重症监护医学 药理学 计算机科学 计算机视觉 滤波器(信号处理)
作者
Taicheng Lu,Jingzhi Zhang,Haiming Li,Guangda Li,Xiaohui Yin,Jingwen Yu,Yingying Zheng,Zishen Liu,Yue Wang,Dong Chen,Yuancan Pan,Tongjing Ding,Yutong Zhang,Zhengzheng Yang,Zichun Yuan,Gan‐Lin Zhang,Qingsheng Fan,Xiaomin Wang
出处
期刊:Hepatology [Lippincott Williams & Wilkins]
卷期号:79 (4): E123-E124 被引量:2
标识
DOI:10.1097/hep.0000000000000733
摘要

To the editor, We read with interest the study by Zabransky et al, who analyzed the immune microenvironment in a homozygous mouse model of HCC with Hep53.4, Hepa1–6, RIL-175, and TIBx.1 The authors concluded that the Hepa 1–6 model does not encapsulate the tumor immune microenvironment of the vast majority of human HCC. Among them, the authors considered that Hepa 1–6 triggered a strong immune response and that this portended potentially misleading preclinical results. However, we would like to further broaden the conclusions. Hepa 1–6 may not be suitable for use in HCC models to explore responses to drug therapy. Firstly, the SD of the subcutaneous tumor model of the Hepa1–6 model in the article was very large in the control group, which to some extent, indicates the instability of this model. Furthermore, there was no difference in survival between the control and treatment groups in the Hepa 1–6 model, potentially suggesting that the Hepa 1–6 tumors had dissipated during development. The hematoxylin-eosin staining results in the article, as well as the immunohistochemistry results for CD8 and B220, show that Hepa 1–6 tumors are characterized by many inflammatory cells surrounding the tumor tissue, as if an army were stationed around the tumor. This is despite the relevant publications reporting solutions for this possible situation. Yang et al used younger weekly mice (4 weeks old) for Hepa 1–6 modeling.2 Some of the researchers eliminated the effect of too large SD in the control group by increasing the sample size or using tumor response rate.3,4 Even though this approach may be able to reflect differences in response to drug therapy, it is more important to use a more stable HCC model to explore responses to drug therapy.
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