The First Hospital of Lanzhou University, Lanzhou.
Xifeng District People's Hospital of Qingyang City.
Medicine (Baltimore). 2021 Apr 16;100(15):e25374. doi: 10.1097/MD.0000000000025374.
The pathogenesis of hepatocellular carcinoma (HCC) can be divided into viral infection (VIR) and nonviral (NVIR) infection. Two types of HCC performed different tumor immune microenvironment (TIME) which directly affected prognosis of HCC. This study aimed to identify an effective 2 types of HCC prognostic gene signature that related to immune TIME.The differential expression genes (DEGs) were analyzed by Limma R package from the Cancer Genome Atlas. Immune related genes getting from IMMport database were matched to DEGs for testing prognosis. Prognostic index (PI) consisted of prognostic immune related genes was calculated in different types of HCC by COX regression and the correlation with the abundance of immune infiltrates, including 6 type cells, via gene modules. Tumor immune estimation resource database was applied to analyze TIME. Finally, the correlations between PI of DEGs and TIICs were analyzed by the Spearman method.Results showed that PI consisted of 11 messenger RNAs in VIR and 12 messenger RNAs in NVIR groups. The PI related to HCC prognosis has different correlations with immune infiltrating cells in VIR and NVIR groups. The PI value of DEGs has significant correlations with neutrophils (R = 0.22, P-value = .029) and dendritic (R = 0.21, P-value = .036) infiltration levels in VIR group. However, in NVIR group, the result showed there were no significant correlations between PI and other 5 type cell infiltration levels (P-value > .05).The 11-gene signature in VIR and 12-gene signature in NVIR group selected based on data from the Cancer Genome Atlas database had a different correlation with immune infiltrating cells of HCC patients.
肝细胞癌（HCC）的发病机制可分为病毒感染（VIR）和非病毒（NVIR）感染。两种类型的 HCC 表现出不同的肿瘤免疫微环境（TIME），这直接影响 HCC 的预后。本研究旨在确定与免疫 TIME 相关的有效 2 种 HCC 预后基因特征。通过 Limma R 包从癌症基因组图谱中分析差异表达基因（DEGs）。从 IMMport 数据库中获取的免疫相关基因与 DEGs 匹配以测试预后。通过 COX 回归计算不同类型 HCC 中由预后免疫相关基因组成的预后指数（PI），并通过基因模块与免疫浸润细胞的丰度进行相关性分析，包括 6 种细胞。肿瘤免疫评估资源数据库用于分析 TIME。最后，通过 Spearman 方法分析 DEGs 的 PI 与 TIICs 的相关性。结果表明，VIR 组有 11 个信使 RNA 和 NVIR 组有 12 个信使 RNA 组成的 PI。与 HCC 预后相关的 PI 在 VIR 和 NVIR 组中与免疫浸润细胞的相关性不同。DEGs 的 PI 值与 VIR 组中性粒细胞（R=0.22，P 值=0.029）和树突状细胞（R=0.21，P 值=0.036）浸润水平有显著相关性。然而，在 NVIR 组中，结果显示 PI 与其他 5 种细胞浸润水平之间没有显著相关性（P 值>.05）。基于癌症基因组图谱数据库的数据，VIR 组的 11 基因特征和 NVIR 组的 12 基因特征与 HCC 患者的免疫浸润细胞具有不同的相关性。
