Guo Houtian, Lu Fei, Lu Rongqi, Huang Meiqi, Li Xuejing, Yuan Jianhui, Wang Feng
First Clinical College of Guangxi Medical University, Nanning, China.
Department of Physiology, School of Basic Medical Sciences, Guangxi Medical University, Nanning, China.
Heliyon. 2023 Jun 7;9(6):e17054. doi: 10.1016/j.heliyon.2023.e17054. eCollection 2023 Jun.
Hepatocellular carcinoma (HCC), the main type of liver cancer, is the second most lethal tumor worldwide, with a 5-year survival rate of only 18%. Driver genes facilitate cancer cell growth and spread in the tumor microenvironment. Here, a comprehensive driver gene signature for the prognosis of HCC was developed.
HCC driver genes were analyzed comprehensively to develop a better prognostic signature. The dataset of HCC patients included mRNA sequencing data and clinical information from the TCGA, the ICGC, and the Guangxi Medical University Cancer Hospital cohorts. First, LASSO was performed to develop a prognostic signature for differentially expressed driver genes in the TCGA cohort. Then, the robustness of the signature was assessed using survival and time-dependent ROC curves. Furthermore, independent predictors were determined using univariate and multivariate Cox regression analyses. Stepwise multi-Cox regression analysis was employed to identify significant variables for the construction of a nomogram that predicts survival rates. Functional analysis by Spearman correlation analysis, enrichment analysis (GO, KEGG, and GSEA), and immunoassay (ssGSEA and xCell) were performed.
A 4-driver gene signature (CLTC, DNMT3A, GMPS, and NRAS) was successfully constructed and showed excellent predictive efficiency in three cohorts. The nomogram indicated high predictive accuracy for the 1-, 3-, and 5-year prognoses of HCC patients, which included clinical information and risk score. Enrichment analysis revealed that driver genes were involved in regulating oncogenic processes, including the cell cycle and metabolic pathways, which were associated with the progression of HCC. ssGSEA and xCell showed differences in immune infiltration and the immune microenvironment between the two risk groups.
The 4-driver gene signature is closely associated with the survival prediction of HCC and is expected to provide new insights into targeted therapy for HCC patients.
肝细胞癌（HCC）是肝癌的主要类型，是全球第二大致命肿瘤，5年生存率仅为18%。驱动基因促进癌细胞在肿瘤微环境中的生长和扩散。在此，开发了一种用于HCC预后的综合驱动基因特征。
全面分析HCC驱动基因以开发更好的预后特征。HCC患者数据集包括来自TCGA、ICGC和广西医科大学附属肿瘤医院队列的mRNA测序数据和临床信息。首先，进行LASSO分析以开发TCGA队列中差异表达驱动基因的预后特征。然后，使用生存曲线和时间依赖的ROC曲线评估该特征的稳健性。此外，通过单变量和多变量Cox回归分析确定独立预测因子。采用逐步多Cox回归分析来识别构建预测生存率列线图的显著变量。通过Spearman相关分析、富集分析（GO、KEGG和GSEA）和免疫分析（ssGSEA和xCell）进行功能分析。
成功构建了一个由4个驱动基因组成的特征（CLTC、DNMT3A、GMPS和NRAS），并在三个队列中显示出优异的预测效率。列线图显示对HCC患者1年、3年和5年预后具有较高的预测准确性，其中包括临床信息和风险评分。富集分析表明，驱动基因参与调控致癌过程，包括细胞周期和代谢途径，这些过程与HCC的进展相关。ssGSEA和xCell显示两个风险组之间在免疫浸润和免疫微环境方面存在差异。
4个驱动基因组成的特征与HCC的生存预测密切相关，有望为HCC患者的靶向治疗提供新的见解。
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