Table_1_An inflammation-related gene landscape predicts prognosis and response to immunotherapy in virus-associated hepatocellular carcinoma.xlsx

BackgroundDue to the viral infection, chronic inflammation significantly increases the likelihood of hepatocellular carcinoma (HCC) development. Nevertheless, an inflammation-based signature aimed to predict the prognosis and therapeutic effect in virus-related HCC has rarely been established.
MethodBased on the integrated analysis, inflammation-associated genes (IRGs) were systematically assessed. We comprehensively investigated the correlation between inflammation and transcriptional profiles, prognosis, and immune cell infiltration. Then, an inflammation-related risk model (IRM) to predict the overall survival (OS) and response to treatment for virus-related HCC patients was constructed and verified. Also, the potential association between IRGs and tumor microenvironment (TME) was investigated. Ultimately, hub genes were validated in plasma samples and cell lines via qRT-PCR. After transfection with shCCL20 combined with overSLC7A2, morphological change of SMMC7721 and huh7 cells was observed. Tumorigenicity model in nude mouse was established.
ResultsAn inflammatory response-related gene signature model, containing MEP1A, CCL20, ADORA2B, TNFSF9, ICAM4, and SLC7A2, was constructed by conjoint analysis of least absolute shrinkage and selection operator (LASSO) Cox regression and gaussian finite mixture model (GMM). Besides, survival analysis attested that higher IRG scores were positively relevant to worse survival outcomes in virus-related HCC patients, which was testified by external validation cohorts (the ICGC cohort and GSE84337 dataset). Univariate and multivariate Cox regression analyses commonly proved that the IRG was an independent prognostic factor for virus-related HCC patients. Thus, a nomogram with clinical factors and IRG was also constructed to superiorly predict the prognosis of patients. Featured with microsatellite instability-high, mutation burden, and immune activation, lower IRG score verified a superior OS for sufferers. Additionally, IRG score was remarkedly correlated with the cancer stem cell index and drug susceptibility. The measurement of plasma samples further validated that CCL20 upexpression and SLC7A2 downexpression were positively related with virus-related HCC patients, which was in accord with the results in cell lines. Furthermore, CCL20 knockdown combined with SLC7A2 overexpression availably weakened the tumor growth in vivo.
ConclusionsCollectively, IRG score, serving as a potential candidate, accurately and stably predicted the prognosis and response to immunotherapy in virus-related HCC patients, which could guide individualized treatment decision-making for the sufferers.

研究背景
由于病毒感染引发的慢性炎症会显著提升肝细胞癌（hepatocellular carcinoma, HCC）的发生风险。然而，目前针对病毒相关性肝细胞癌、用于预测患者预后与治疗响应的炎症相关标志物模型仍鲜有构建。
研究方法
本研究基于整合分析策略，对炎症相关基因（inflammation-associated genes, IRGs）开展系统性评估。我们全面探究了炎症与转录组谱、患者预后及免疫细胞浸润之间的关联。随后，构建并验证了一款炎症相关风险模型（inflammation-related risk model, IRM），用于预测病毒相关性肝细胞癌患者的总生存期（overall survival, OS）及治疗响应。此外，本研究还探讨了炎症相关基因与肿瘤微环境（tumor microenvironment, TME）之间的潜在关联。最终，通过实时荧光定量PCR（quantitative real-time polymerase chain reaction, qRT-PCR）对血浆样本及细胞系中的核心基因进行了验证。在通过shCCL20联合SLC7A2过表达载体转染细胞后，我们观察了SMMC7721与huh7细胞的形态学变化，并构建了裸鼠成瘤模型。
研究结果
本研究通过联合最小绝对收缩和选择算子（least absolute shrinkage and selection operator, LASSO）Cox回归与高斯有限混合模型（Gaussian finite mixture model, GMM）分析，构建了包含MEP1A、CCL20、ADORA2B、TNFSF9、ICAM4及SLC7A2的炎症反应相关基因标志物模型。生存分析证实，病毒相关性肝细胞癌患者的炎症相关基因评分越高，其生存预后越差，该结果通过外部验证队列（ICGC队列及GSE84337数据集）得到了验证。单因素及多因素Cox回归分析均证实，炎症相关基因评分是病毒相关性肝细胞癌患者的独立预后因素。据此，我们进一步构建了整合临床因素与炎症相关基因评分的列线图（nomogram），以更精准地预测患者预后。评分较低的患者具有更高的微卫星高度不稳定（microsatellite instability-high）水平、更高的肿瘤突变负荷及更强的免疫激活状态，且总生存期更优。此外，炎症相关基因评分与肿瘤干细胞指数及药物敏感性显著相关。血浆样本检测进一步验证，CCL20高表达与SLC7A2低表达与病毒相关性肝细胞癌患者的病情显著相关，该结果与细胞系中的检测结果一致。进一步研究发现，敲低CCL20联合过表达SLC7A2可有效在体内抑制肿瘤生长。
研究结论
综上，炎症相关基因评分可作为一款潜在的候选标志物，精准且稳定地预测病毒相关性肝细胞癌患者的预后及免疫治疗响应，可为患者的个体化治疗决策提供指导。