The gene expression level and prognosis analysis of membrane protein AP2M1 based on the protein spectrum of exosomes in hepatocellular carcinoma cells

Objective:Adopting mass spectrometry to analyze the protein spectrum of the exosomes in human hepatocellular carcinoma cells and screening the target membrane protein in order to analyze the relationship between its gene expression level and prognosis.Methods:The exosomes of hepatocellular carcinoma cells HepG2 and 7721 were isolated by ultracentrifugation,and the extracted exosomes were verified by transmission electron microscope, western blotting,and nanosight.The relative quantitative proteomics analysis was used to analyze the protein spectrum of HepG2 and 7721 cells in exosomes.The bioinformatics was used to collect the signal pathway,and the target protein AP2M1 was verified by qRTPCR.Gene Expression Profiling Interactive Analysis(GEPIA),OncoLnc,and The Cancer Genome Atlas(TCGA)database were used to analyze the expression level of AP2M1 and the survival rate of patients with liver cancer.Results:The extracellular exosomes of HepG2 and 7721 cells were isolated by ultracentrifugation.High-purity exosomes were obtained and verified by transmission electron microscopy,western blotting,and nanosight.There were 836 proteins co-expressed by the exosomes of HepG2 and 7721.By the analysis of Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway,a total of 34 pathways that were related to liver cancer were collected,and the target membrane protein AP2M1 was screened.AP2M1 highly expressed in HepG2 cells,HepG2 and Huh7 cells' exosomes were detected by qRT-PCR(P<0.05).The data of GEPIA showed that comparing to the adjacent tissues,gene AP2M1 was highly expressed in hepatocarcinoma tissues.Kaplan-Meier survival curve analysis was performed by OncoLnc.It was found that the survival rate of patients with liver cancer and high expression of AP2M1 was significantly lower than patients with liver cancer and low expression of AP2M1(P<0.01).Conclusion:The high expression of membrane protein AP2M1 in the exosomes of hepatoma cells and the high expression of its gene in liver cancer tissues predicted the low survival rate.

Bioinformatics analysis of exosome proteome derived from hepatic carcinoma HepG2 cells

Objective:The aim of this study was to analyze the exosome proteome derived from hepatic carcinoma HepG2 cells and normal hepatocytes HL-7702,and look for the key factors in carcinogenesis of hepatocellular carcinoma(HCC).Methods:HepG2 and HL-7702 cells were cultured,and exosome samples were obtained from the culture supernatant and verified.LTQ-Orbitrap Elite mass spectrometry was applied to analyze and identify the exosome proteome derived from the hepatic carcinoma cells and normal liver cells,which was for seeking hepatic carcinoma cells specifically expressed proteins.Furthermore,gene ontology(GO),protein-protein interaction(PPI)network,and pathway enrichment were constructed to analyze hepatic carcinoma cells specifically expressed proteins.Results:The exosomes of HL-7702 expressed 3,366proteins,and the exosomes of HepG2 expressed 2,874proteins,of which 1,224were expressed specifically in HepG2 exosomes.102 target proteins were selected and going on bioinformatics analysis under the condition that the unique peptide was≥1and PSMs≥10.GO analysis results showed that the target expression protein of HepG2 was concentrated on metabolism,proliferation,and localization adhesion function.76target proteins were chosen and formed a PPI network;combining with pathway analysis,ACTN1,FN1,RAC1and GSN were found to be involved in important signaling pathways of HCC.The 26target proteins which not in PPI network were analyzed pathway involved in,respectively.AKR1C2 and C5 were found to be involved in differently important signaling pathways of HCC.Conclusion:Exosomes proteomics provides the sources of specific protein derived from hepatic carcinoma cell;when it combines with bioinformatics analysis,they are able to reveal the important molecules that are related to carcinogenesis of HCC and provide new ideas for investigation of HCC biomarkers.