Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, China.
South Sichuan Institute of Translational Medicine, Luzhou, China.
Front Immunol. 2021 Apr 7;12:653836. doi: 10.3389/fimmu.2021.653836. eCollection 2021.
Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis. ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER). Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine-cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration. This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.
肝细胞癌（HCC）是世界上最常见的恶性肿瘤之一。免疫疗法的疗效通常取决于肿瘤微环境（TME）中的免疫调节相互作用。本研究旨在通过生物信息学分析探讨基于基质-免疫评分的与 HCC 免疫治疗相关的潜在预后基因。使用癌症基因组图谱（TCGA）转录组数据，ESTIMATE 算法计算 HCC 的免疫/基质/Estimate 评分和肿瘤纯度。差异表达基因（DEGs）的功能富集分析通过数据库 for Annotation, Visualization, and Integrated Discovery 数据库（DAVID）进行分析。单因素和多因素 Cox 回归分析以及最小绝对值收缩和选择算子（LASSO）回归分析用于预后基因筛选。这些基因的表达和预后价值通过 KM-plotter 数据库和人类蛋白质图谱（HPA）数据库进一步验证。通过单样本基因集富集分析（ssGSEA）算法和肿瘤免疫估计资源（TIMER）分析选择基因与免疫细胞浸润的相关性。数据分析显示，7 年内 HCC 中较高的免疫/基质/Estimate 评分与生存获益显著相关，而肿瘤纯度呈相反趋势。基于免疫和基质评分的 DEGs 主要影响细胞因子-细胞因子受体相互作用信号通路。在 DEGs 中，有三个基因（CASKIN1、EMR3 和 GBP5）与生存最显著相关。此外，CASKIN1、EMR3 和 GBP5 基因的表达水平与免疫/基质/Estimate 评分或肿瘤纯度和多种免疫细胞浸润显著相关。其中，GBP5 基因与免疫浸润高度相关。本研究确定了三个与 TME 相关且与 HCC 预后相关的关键基因，它们可能是预测免疫治疗效果的有前途的标志物。
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