Huang Wei, Han Ning, Du Lingyao, Cao Dan, Tang Hong
Center of Infectious Diseases, West China Hospital of Sichuan University, Chengdu 610041, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2022 Feb 25;39(1):120-127. doi: 10.7507/1001-5515.202101090.
Autophagy is a programmed cell degradation process that is involved in a variety of physiological and pathological processes including malignant tumors. Abnormal induction of autophagy plays a key role in the development of hepatocellular carcinoma (HCC). We established a prognosis prediction model for hepatocellular carcinoma based on autophagy related genes. Two hundred and four differentially expressed autophagy related genes and basic information and clinical characteristics of 377 registered hepatocellular carcinoma patients were retrieved from the cancer genome atlas database. Cox risk regression analysis was used to identify autophagy-related genes associated with survival, and a prognostic model was constructed based on this. A total of 64 differentially expressed autophagy related genes were identified in hepatocellular carcinoma patients. Five risk factors related to the prognosis of hepatocellular carcinoma patients were determined by univariate and multivariate Cox regression analysis, including TMEM74, BIRC5, SQSTM1, CAPN10 and HSPB8. Age, gender, tumor grade and stage, and risk score were included as variables in multivariate Cox regression analysis. The results showed that risk score was an independent prognostic risk factor for patients with hepatocellular carcinoma ( = 1.475, 95% CI = 1.280-1.699, < 0.001). In addition, the area under the curve of the prognostic risk model was 0.739, indicating that the model had a high accuracy in predicting the prognosis of hepatocellular carcinoma. The results suggest that the new prognostic risk model for hepatocellular carcinoma, established by combining the molecular characteristics and clinical parameters of patients, can effectively predict the prognosis of patients.
自噬是一种程序性细胞降解过程,参与包括恶性肿瘤在内的多种生理和病理过程。自噬的异常诱导在肝细胞癌(HCC)的发生发展中起关键作用。我们基于自噬相关基因建立了肝细胞癌的预后预测模型。从癌症基因组图谱数据库中检索到240个差异表达的自噬相关基因以及377例注册肝细胞癌患者的基本信息和临床特征。采用Cox风险回归分析来识别与生存相关的自噬相关基因,并据此构建预后模型。在肝细胞癌患者中总共鉴定出64个差异表达的自噬相关基因。通过单因素和多因素Cox回归分析确定了5个与肝细胞癌患者预后相关的危险因素,包括跨膜蛋白74(TMEM74)、杆状病毒IAP重复序列5(BIRC5)、聚集体蛋白1(SQSTM1)、钙蛋白酶10(CAPN10)和热休克蛋白B8(HSPB8)。年龄、性别、肿瘤分级和分期以及风险评分作为多因素Cox回归分析中的变量。结果显示,风险评分是肝细胞癌患者的独立预后危险因素( = 1.475,95%可信区间 = 1.280 - 1.699, < 0.001)。此外,预后风险模型的曲线下面积为0.739,表明该模型在预测肝细胞癌预后方面具有较高的准确性。结果表明,结合患者的分子特征和临床参数建立的肝细胞癌新预后风险模型能够有效预测患者的预后。