| Background and Objective:Hepatocellular carcinoma(HCC,hereinafter referred to as liver cancer)is one of the most common malignant tumors in China.Although the level of diagnosis and treatment of liver cancer in China has significantly improved compared to the previous period,and the prognosis of patients has also improved significantly,the overall survival rate of patients with liver cancer is still not optimistic due to the onset and rapid progress of liver cancer,and the recurrence and metastasis of liver cancer are the prognosis Poor key factor.Therefore,exploring the potential prognostic indicators of liver cancer has important clinical significance for improving the prognosis of patients with liver cancer.And ubiquitination is one of the important ways to regulate post-translational modification of proteins in vivo,which is closely related to various biological processes.E3 ubiquitin ligase,as one of the three key enzymes for ubiquitination modification,determines the specificity of ubiquitination modification.Their abnormal activity has also been confirmed to be closely related to the occurrence and development of various tumors.However,due to the large number of E3 ubiquitin ligases,which key E3 ubiquitin ligases are closely related to the development of liver cancer? Little is known about it,so it is of great significance to screen for key E3 ubiquitin ligase molecules that are closely related to the malignant behavior of liver cancer.In recent years,with the rapid development of bioinformatics research,the use of high-throughput data analysis to mine disease-related biomarkers has become an efficient research method.This study builds on this foundation,and aims to integrate the liver cancer data in the TCGA database with the E3 ubiquitin ligase gene library and perform screening and verification through corresponding technical means.It is expected to obtain from the E3 ubiquitin ligase gene library.Key molecular markers that are closely related to the occurrence and development of liver cancer and have great value in predicting the prognosis of liver cancer.Methods:Download the TCGA-LIHC transcriptome Manifest and Metadata data through the TCGA database website,and then use the GDC-client download tool to download the HTSeq-fpkm data in the cmd environment.The Perl language script was used to extract the expression matrix of the original data.The Homo_sapiens.GRCh38.95.chr.gtf.gz file was downloaded through the Ensembl website,and the gene expression matrix based on the gene symbol was obtained after comparison.Then we have collected a total of 718 E3 ubiquitin ligase-related genes(through the biosignal pathways involved in E3 ubiquitin ligase in KEGG,this step was assisted by Jiangsu Suzhou Hongxun Biological Technology Co.,Ltd.)and KEGG Established in 1995 by the Kanehisa laboratory of the Center for Bioinformatics at Kyoto University.A bioinformatics analysis tool that can use R to achieve signal pathway enrichment analysis.)Find the expression level one by one from the gene expression matrix obtained from the TCGA database.To establish an E3 ubiquitin ligase gene library.The data was imported into the Gene Spring 11.5 software to screen differential expression genes(DGEs)and set thresholds(| log2 FC |> 2.0 and adj.P.val<0.05).The protein protein interaction network(PPI)of DGEs was constructed using the STRING10.5 database.At the same time,a text file was downloaded,and the file was imported into Cytoscape software to calculate the centrality and degree of the degree of each DGEs in the PPI network.The higher the centrality value,the more the DGEs are at the center of the PPI network.The top 10 DGEs with the highest screening value are used as the central gene.The biological function of the E3 ubiquitin ligase gene library was analyzed using DAVID.The highest concentration of biological functions(ie,the process of apoptosis),the genes enriched in apoptosis as candidate genes for further research.The clinical data of 436 liver cancer samples were downloaded from the TCGA database,and the data included detailed clinical data of patients.The relationship between candidate genes and the survival prognosis and clinical TNM staging of liver cancer samples in the database were verified respectively,and genes closely related to the liver cancer prognosis and clinical TNM staging were screened(P<0.05),and these screened genes were further correlated with 10 central genes.Cross-alignment yields key genes.Finally,immunohistochemical staining was used to detect and verify the expression of cancer and its adjacent tumors in clinical samples of liver cancer collected by our center,and analyze the relationship between its expression and clinical pathological parameters and survival time of patients.Results:Through differential gene screening,a total of 23 DGEs were obtained,a PPI network of 23 DGEs was constructed,and the top 10 with the highest degree of centrality were selected as central genes.The biological function of the E3 ubiquitin ligase gene library was analyzed,and 37 genes with the highest enrichment in biological functions were selected as candidate genes for further research.Eleven of the 37 candidate genes were found to be significantly correlated with the prognosis of liver cancer and have statistical significance(P<0.05).Twelve were found to be significantly related to clinical TNM staging and have statistical significance(P<0.05).Cross-matching candidate genes related to liver cancer prognosis and clinical TNM staging with central genes in the PPI protein network to obtain the key genes of TRAIP,the expression of which is significantly higher in liver cancer tissues than in adjacent tissues.The protein interaction network is also at the center,and the high expression of TRAIP and the poor prognosis of patients with liver cancer and clinical TNM staging are statistically significant(P<0.05).For further verification,the clinical samples collected by our center were used to detect the expression of TRAIP in cancer and adjacent tissues by immunohistochemical staining.It was found that the expression of TRAIP was mainly expressed in cytoplasm,and the expression in cancer was significantly higher than that in adjacent tissues.The relationship between its expression and the clinicopathological parameters and survival time of the patients was found to be statistically significant(P<0.05)and the TNM stage and tumor differentiation of patients with liver cancer were significantly lower,and the survival rate of patients was significantly reduced when TRAIP was positively expressed.(P<0.05).Conclusion:(1)Through data mining and single-center clinical sample testing and verification,it was found that the expression of TRAIP in liver cancer tissues was significantly up-regulated,and its expression level was closely related to the clinical TNM stage and survival status of liver cancer patients.(2)The high expression of TRAIP is a significant risk factor for poor prognosis of liver cancer patients,and a new target for prognosis of liver cancer patients.(3)TRAIP may affect the occurrence and development of liver cancer by mediating the apoptosis process,but its specific molecular mechanism has yet to be further clarified,and it is expected to make it a potential new target for the treatment of liver cancer. |
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