Lin Zhuo, Xu Qian, Miao Dan, Yu Fujun
Department of Hepatology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Department of Accurate Diagnosis and Treatment of Chronic Liver Diseases, Key Laboratory of Zhejiang Province, Wenzhou, China.
Front Oncol. 2021 Mar 22;11:644416. doi: 10.3389/fonc.2021.644416. eCollection 2021.
Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, which makes the prognostic prediction challenging. As part of the active cross-talk between the tumor and the host, inflammatory response in the tumor or its microenvironment could affect prognosis. However, the prognostic value of inflammatory response-related genes in HCC remains to be further elucidated.
In this study, the mRNA expression profiles and corresponding clinical data of HCC patients were downloaded from the public database. The least absolute shrinkage and selection operator Cox analysis was utilized to construct a multigene prognostic signature in the TCGA cohort. HCC patients from the ICGC cohort were used for validation. Kaplan Meier analysis was used to compare the overall survival (OS) between high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS. Single-sample gene set enrichment analysis was utilized to calculate the immune cell infiltration score and immune related pathway activity. Gene set enrichment analysis was implemented to conduct GO terms and KEGG pathways. The qRT-PCR and immunohistochemistry were utilized to perform the mRNA and protein expression of prognostic genes between HCC tissues and normal liver tissues respectively.
An inflammatory response-related gene signature model was constructed by LASSO Cox regression analysis. Compared with the low-risk group, patients in the high-risk group showed significantly reduced OS. Receiver operating characteristic curve analysis confirmed the predictive capacity of the prognostic gene signature. Multivariate Cox analysis revealed that the risk score was an independent predictor for OS. Functional analysis indicated that immune status was definitely different between two risk groups, and cancer-related pathways were enriched in high-risk group. The risk score was significantly correlated with tumor grade, tumor stage and immune infiltrate types. The expression levels of prognostic genes were significantly correlated with sensitivity of cancer cells to anti-tumor drugs. Furthermore, the expression of prognostic genes showed significant difference between HCC tissues and adjacent non-tumorous tissues in the separate sample cohort.
A novel signature constructed with eight inflammatory response-related genes can be used for prognostic prediction and impact the immune status in HCC. Moreover, inhibition of these genes may be a therapeutic alternative.
肝细胞癌（HCC）是一种高度异质性疾病，这使得预后预测具有挑战性。作为肿瘤与宿主之间活跃的相互作用的一部分，肿瘤或其微环境中的炎症反应可能影响预后。然而，HCC中炎症反应相关基因的预后价值仍有待进一步阐明。
在本研究中，从公共数据库下载了HCC患者的mRNA表达谱和相应的临床数据。利用最小绝对收缩和选择算子Cox分析在TCGA队列中构建多基因预后特征。来自ICGC队列的HCC患者用于验证。采用Kaplan Meier分析比较高风险组和低风险组的总生存期（OS）。应用单因素和多因素Cox分析确定OS的独立预测因子。利用单样本基因集富集分析计算免疫细胞浸润评分和免疫相关通路活性。实施基因集富集分析以进行GO术语和KEGG通路分析。分别利用qRT-PCR和免疫组化检测HCC组织和正常肝组织中预后基因的mRNA和蛋白表达。
通过LASSO Cox回归分析构建了炎症反应相关基因特征模型。与低风险组相比，高风险组患者的OS显著降低。受试者工作特征曲线分析证实了预后基因特征的预测能力。多因素Cox分析显示风险评分是OS的独立预测因子。功能分析表明，两个风险组的免疫状态明显不同，癌症相关通路在高风险组中富集。风险评分与肿瘤分级、肿瘤分期和免疫浸润类型显著相关。预后基因的表达水平与癌细胞对抗肿瘤药物的敏感性显著相关。此外，在独立样本队列中，HCC组织和相邻非肿瘤组织中预后基因的表达存在显著差异。
由八个炎症反应相关基因构建的新型特征可用于预后预测并影响HCC的免疫状态。此外，抑制这些基因可能是一种治疗选择。
