肝细胞癌患者自噬相关基因的预后作用

构建由自噬相关基因组成的预后模型,预测肝细胞癌(HCC)患者的生存预后情况,为其个性化诊疗和临床研究提供依据.利用TCGA数据库中HCC的测序信息与人类自噬数据库联合,筛选差异表达的自噬相关基因,对其进行GO富集与KEGG通路分析;通过单因素与多因素Cox分析筛选与患者生存预后明显相关的风险基因,构建预后风险评分模型;...

Prognostic roles of autophagy-associated genes in patients withhepatocellular carcinoma

A prognostic model composed of autophagy-related genes was constructed to predict the survival and prognosis of patients with hepatocellular carcinoma (HCC) and provide basis for individualized diagnosis and clinical research. The sequencing information of HCC in TCGA database and human autophagy database was utilized to screen differentially expressed autophagy-related genes for GO enrichment and KEGG pathway analysis. The risk genes significantly related to survival prognosis were screened through univariate and multivariate Cox analyses to construct prognostic risk score model. The patient risk values were calculated, and the models were verified. GEPIA2.0 web tools and HPA database were emplayed to verify the expression of risk genes in the HCC and the relationship with survival prognosis. Results show that compared with normal tissues, a total of 61 differentially expressed autophagy-related genes (57 up-regulated and 4 down-regulated) were screened from HCC tumor tissues. GO enrichment and KEGG pathway analysis results showed that these genes were autophayg-associated. A total of 12 genes related to survival and prognosis of patients were selected by univariate Cox analysis. After multivariate Cox analysis, four genes (SQSTM1, HDAC1, RHEB. and ATIC) were included in the prognostic risk scoring model. The formula was as follows: risk score=SQSTM1 expression levels×0.185+HDAC1 expression levels×0.382+RHEB expression levels×0.423+ATIC expression levels×0.438. K-M survival curves showed that the survival rate in high risk group was lower than that in low risk group, risk curves suggested that four genes were closely related to poor prognosis, and ROC curves proved that the model had predictive significance. Results obtained from GEPIA2.0 web tool and HPA database showed that the high expression of four genes resulted in reduced survival. The constructed prognostic risk score model can effectively predict the survival and prognosis of patients and provide personalized diagnosis and treatment strategies.