Chen Wenbiao, Zhang Xujun, Bi Kefan, Zhou Hetong, Xu Jia, Dai Yong, Diao Hongyan
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Disease, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, School of Medicine, The First Affiliated Hospital, Zhejiang University, Hangzhou, China.
Department of Clinical Medical Research Center, The Second Clinical Medical College of Jinan University, The First Affiliated Hospital Southern University of Science and Technology, Shenzhen People's Hospital, Shenzhen, China.
Front Oncol. 2020 Sep 24;10:554165. doi: 10.3389/fonc.2020.554165. eCollection 2020.
The tumor immune microenvironment (TIME) is an external immune system that regulates tumorigenesis. However, cellular interactions involving the TIME in hepatocellular carcinoma (HCC) are poorly characterized. In this study, we used multidimensional bioinformatic methods to comprehensively analyze cellular TIME characteristics in 735 HCC patients. Additionally, we explored associations involving TIME molecular subtypes and gene types and clinicopathological features to construct a prognostic signature. Based on their characteristics, we classified TIME and gene signatures into three phenotypes (TIME T1-3) and two gene clusters (Gene G1-2), respectively. Further analysis revealed that Gene G1 was associated with immune activation and surveillance and included CD8 T cells, natural killer cell activation, and activated CD4 memory T cells. In contrast, Gene G2 was characterized by increased M0 macrophage and regulatory T cell levels. After calculation of principal component algorithms, a TIME score (TS) model, including 78 differentially expressed genes, was constructed based on TIME phenotypes and gene clusters. Furthermore, we observed that the Gene G2 cluster was characterized by high TS, and Gene G1 was characterized by low TS, which correlated with poor and favorable prognosis of HCC, respectively. Correlation analysis showed that TS had a positive association with several clinicopathologic signatures such as grade, stage, tumor (T), and node (N)] and known somatic gene mutations (such as and ). The prognostic value of the TS model was verified using external data sets. We constructed a TS model based on differentially expressed genes and involving immune phenotypes and demonstrated that the TS model is an effective prognostic biomarker and predictor for HCC patients.
肿瘤免疫微环境（TIME）是一种调节肿瘤发生的外部免疫系统。然而，肝细胞癌（HCC）中涉及TIME的细胞相互作用的特征尚不明确。在本研究中，我们使用多维生物信息学方法全面分析了735例HCC患者的细胞TIME特征。此外，我们探讨了TIME分子亚型、基因类型与临床病理特征之间的关联，以构建一个预后特征。根据其特征，我们将TIME和基因特征分别分为三种表型（TIME T1 - 3）和两个基因簇（基因G1 - 2）。进一步分析表明，基因G1与免疫激活和监测相关，包括CD8 T细胞、自然杀伤细胞激活和活化的CD4记忆T细胞。相反，基因G2的特征是M0巨噬细胞和调节性T细胞水平升高。在计算主成分算法后，基于TIME表型和基因簇构建了一个包含78个差异表达基因的TIME评分（TS）模型。此外，我们观察到基因G2簇的特征是高TS，而基因G1的特征是低TS，这分别与HCC的不良和良好预后相关。相关性分析表明，TS与几个临床病理特征如分级、分期、肿瘤（T）和淋巴结（N）以及已知的体细胞基因突变（如 和 ）呈正相关。使用外部数据集验证了TS模型的预后价值。我们基于差异表达基因构建了一个涉及免疫表型的TS模型，并证明该TS模型是HCC患者有效的预后生物标志物和预测指标。
