Construction And Validation Exosome-related MRNA Prognostic Models For Hepatocellular Carcinoma Via Integrated Bioinformatics

Objective: Hepatocellular carcinoma(HCC)is the sixth most common cancer and the fourth leading cause of cancer-related deaths.Exosomes are nanoscale vesicles with lipid bilayers secreted by cells and have a remarkable impact on liver cancer occurrence and progression.Some studies have shown that exosomes are involved in inducing angiogenesis,tumor invasion,and metastasis.The components of exosomes,including proteins,DNA,m RNA,mi RNA,lnc RNA,circ RNA,etc.,are increasingly considered potential biomarkers for tumor diagnoses and prognosis.Various proteins encoded by m RNA are involved in cell regulation.The abnormal changes in m RNA reflect the occurrence and development of cancer.At present,the main areas of m RNA in antibody therapy are antitoxins,infectious diseases,and oncology.m RNA has bright prospects for disease treatment.Therefore,this study adopted bioinformatics methods and databases to construct prognostic models of hepatocellular carcinoma patients based on exosome-related m RNAs.Measured the performance of the models and analyzed the m RNAs obtained from screening,aiming to evaluate the prognosis of hepatocellular carcinoma patients through the model and provide target genes for m RNA therapy of hepatocellular carcinoma patients.Methods: Obtained the information of exosome-related m RNAs from exo RBase,downloaded clinical and transcriptome data on HCC patients from the TCGA database.Seven m RNA with expression and survival differences were screened to construct prognostic models of HCC.The models can successfully distinguish patients as high-risk or low-risk,and m RNAs can provide a new reference for the drug treatment of HCC.Then,verified models from several aspects with the data downloaded from the ICGC database.Finally,the models’ functions were analyzed,including independent prognostic analysis,GO analysis,KEGG analysis,and GSEA analysis.Results: 1.Twenty-four exosome-related m RNAs were acquired through differential analysis,and twenty-two exosome-related m RNAs were achieved through univariate Cox analysis,the intersection of the two retrieved eight intersection m RNAs.2.The model was constructed based on the seven m RNAs screened by lasso regression(risk score=∑(Expi×βi)).3.Deviation map,survival curves,ROC curves,risk curves,and survival state diagrams were constructed to assess the model.It could sensitively divide HCC patients into high/low-risk groups.4.PCA and t-SNE analysis found that the model can distinguish the most part of HCC patients.5.According to independent prognostic analysis,stage and risk score could serve as independent prognostic factors.And m RNAs NOX1 and CFHR4 had a significant impact on the HCC patients’ stage.6.GO analysis showed functions: extracellular structure organization,mitotic nuclear division,condensed chromosome,centromeric region,iron ion binding,and monooxygenase activity were remarkably enriched in TCGA and ICGC.7.The risk differential genes in both TCGA and ICGC were notably enriched in three KEGG pathways: drug metabolism-cytochrome P450,metabolism of xenobiotics by cytochrome P450,and chemical carcinogenesis.8.GSEA analysis demonstrated Immune cells a DC,i DC,macrophages,NK＿cells,and Th2＿cells played a crucial role in the prognosis of HCC patients.As for immune functions,MHC＿class＿I and Type＿II＿IFN＿Reponse performed well in both TCGA and ICGC.Conclusion: 1.The low-risk genes CHFR4 and CYP3A43 were significantly transcribed in normal liver,while the high-risk genes NOX1,RBP2,CALR3,RNF148,and GABRR3 were not,this phenomenon illustrates the association between the development of HCC and model genes.2.Seven exosome-related m RNAs CFHR4,CYP3A43,NOX1,RNF148,CALR3,GABRR3,and RBP2 had constructed well-performed prognostic models for predicting HCC patients,the vast majority of patients were classified as high risk and low risk by models sensitively.The risk differences between the two groups were significant.3.Based on GO and KEGG analysis,exosome-related m RNAs noticeable exert in multiple cell metabolism functions and pathways.GSEA analysis suggesting that exosome-related genes worked in immune ways,which affected patients’ prognosis.