Zhu Jun, Zhou Yifan, Wang Liang, Hao Jun, Chen Rui, Liu Lei, Li Jipeng
State Key Laboratory of Cancer Biology, Institute of Digestive Diseases, Xijing Hospital, The Fourth Military Medical University, Xi'an, China.
Department of Basic Medicine, The Fourth Military Medical University, Xi'an, China.
J Gastrointest Oncol. 2020 Dec;11(6):1364-1380. doi: 10.21037/jgo-20-556.
Immune checkpoint blockers (ICBs) are increasingly applied to treat patients with advanced HCC. However, the overall survival (OS) of HCC patients is still unsatisfactory, and there is no confirmed immune-related and prognostic gene to identify patients who could clinically benefit from this treatment. The tumor microenvironment (TME) is known to be closely related to immunotherapy and plays a pivotal role in the recurrence and progression of HCC. Our aim is to explore TME-related genes and identify the prognostic value in HCC patients.
ESTIMATE, immune, and stromal scores were calculated for HCC patients based on RNA expression data from The Cancer Genome Atlas database. Differential expression analysis was performed to screen the differentially expressed genes (DEGs). A protein-protein interaction (PPI) network was constructed to identify the key DEGs. Univariate and multivariate Cox analyses were adopted to validate hub DEGs associated with clinical prognosis, and a single-sample gene set enrichment analysis (ssGSEA) algorithm was used to dissect the landscape of tumor-infiltrating cells (TIC) in HCC. Finally, the relationship between hub immune-related genes and TIC was explored through difference and correlation analyses.
ESTIMATE, immune and stromal scores were all found to be associated with the OS of patients (P<0.05). A total of 1,112 DEGs were identified by comparing low and high score groups of immune and stromal scores. Most of DEGs were enriched in immune-related gene sets by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Additionally, the top 34 genes were included in the protein-protein interaction (PPI) network, and univariate Cox analysis focus on a novel prognosis-related gene cluster CXCL5/CXCL8 (P<0.001). Regarding the immune landscape of HCC, univariable Cox regression analysis showed six immune cells to be associated with OS. Finally, 21 immune cells were commonly determined between high and low expression of CXCL5/CXCL8, suggesting there is a close relationship between expression of CXCL5 and CXCL8 .
Our study has revealed that the immune-related gene cluster of CXCL5 /CXCL8 could be a promising prognostic indicator for HCC and a potential novel biomarker to guide the selection of HCC patients for ICB immunotherapy.
免疫检查点阻断剂（ICB）越来越多地应用于治疗晚期肝癌患者。然而，肝癌患者的总生存期（OS）仍不尽人意，且尚无经证实的免疫相关预后基因来识别可从该治疗中临床获益的患者。已知肿瘤微环境（TME）与免疫治疗密切相关，且在肝癌的复发和进展中起关键作用。我们的目的是探索与TME相关的基因，并确定其在肝癌患者中的预后价值。
基于来自癌症基因组图谱数据库的RNA表达数据，计算肝癌患者的ESTIMATE、免疫和基质评分。进行差异表达分析以筛选差异表达基因（DEG）。构建蛋白质-蛋白质相互作用（PPI）网络以识别关键DEG。采用单因素和多因素Cox分析来验证与临床预后相关的核心DEG，并使用单样本基因集富集分析（ssGSEA）算法剖析肝癌中肿瘤浸润细胞（TIC）的格局。最后，通过差异和相关性分析探索核心免疫相关基因与TIC之间的关系。
发现ESTIMATE、免疫和基质评分均与患者的OS相关（P<0.05）。通过比较免疫和基质评分的低分和高分群体，共鉴定出1112个DEG。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析，大多数DEG富集于免疫相关基因集。此外，34个顶级基因被纳入蛋白质-蛋白质相互作用（PPI）网络，单因素Cox分析聚焦于一个新的预后相关基因簇CXCL5/CXCL8（P<0.001）。关于肝癌的免疫格局，单因素Cox回归分析显示六种免疫细胞与OS相关。最后，在CXCL5/CXCL8的高表达和低表达之间共同确定了21种免疫细胞，表明CXCL5和CXCL8的表达之间存在密切关系。
我们的研究表明，CXCL5/CXCL8免疫相关基因簇可能是肝癌一个有前景的预后指标，也是指导肝癌患者选择ICB免疫治疗的潜在新型生物标志物。
