| Objective:The pseudouridine synthase(PUS)family is a group of proteins responsible for the formation of an RNA modification called pseudouridylation.And the potential role of these proteins and their encoding genes in human cancers has been initially explored.Previous studies have identified pseudouridine synthases to be closely associated with many human cancer types,but their role in the most common primary malignancy of the liver,hepatocellular carcinoma(HCC),remains poorly studied.To fill this scientific gap,the present study integrates transcriptomic,genomic and proteomic data,mainly using bioinformatics and statistical methods,to comprehensively assess the potential of PUS family proteins and encoding genes as novel biomarkers for hepatocellular carcinoma from diagnostic,prognostic and molecular functional perspectives.In addition,the potential value of PUS in the treatment of HCC was also evaluated in this study.Methods:The transcriptome data included in the present study involved two RNA sequencing datasets and one gene microarray dataset.Among them,two RNA sequencing datasets(TCGA-LIHC cohort and LIRI-JP cohort)were downloaded from The Cancer Genome Atlas(TCGA)data portal and the International Cancer Genome Consortium(ICGC)data portal,respectively.The gene expression microarray dataset was obtained from the Gene Expression Omnibus(GEO)database with the cohort number GSE36376.In the proteomics analysis,an hepatitis B virus(HBV)-associated hepatocellular carcinoma cohort was included this study.The raw proteomic data were obtained from the Clinical Proteomic Tumor Analysis Consortium(CPTAC)data portal.In addition,gene mutation analysis and gene copy number variation(CNV)analysis were also involved in this study.Mutation data were downloaded in the same way as the two RNA sequencing data,and samples in the mutation data corresponded to those in the RNA sequencing cohort.CNV-related analyses were performed through the Gene Set Cancer Analysis(GSCA)online database,and the patients included in the analysis were derived from the TCGA-LIHC cohort.In this study,Receiver Operating Characteristic(ROC)curve was used to evaluate the diagnostic efficacy of PUSs,and Kaplan-Meier survival curve,Cox proportional hazards model,and time-dependent ROC curve were used to assess the prognostic value of PUSs.For bioinformatics analysis,this study used Gene Set Enrichment Analysis(GSEA),Gene Set Variation Analysis(GSVA)and cluster Profiler R package for functional enrichment analysis,and used single sample Gene Set Enrichment Analysis(ss GSEA)and ESTIMATE algorithm for tumor microenvironment(TME)related analysis.Results:Through differential gene expression analysis,seven PUS genes(DKC1,PUS1,PUS7,PUSL1,RPUSD1,RPUSD2 and RPUSD3)with significant differences in expression between HCC and normal tissues were identified,and all these genes were significantly upregulated in HCC.Meanwhile,five of them(DKC1,PUS1,PUS7,PUSL1 and RPUSD3)were independent of patient’s gender,age,tumor stage and tumor grade,could be used as independent risk factors for overall survival(OS).And the clinical nomogram constructed based on prognosis-related PUS genes can effectively predict the prognosis of HCC patients.In proteomic analysis,this study found that the protein expression of DKC1,PUS1 and PUS7 was also significantly upregulated in HCC and was associated with poor prognosis.Futhermore,the expression levels of all these PUS genes or proteins mentioned above can effectively distinguish between HCC tissue and normal tissue.The study also analyzed CNV data for the PUS genes in HCC and found that CNV for the PUS1,PUS7,PUS7 L and RPUSD2 genes were also associated with patients prognosis.Finally,functional analysis suggested that PUS may be involved in HCC mainly through genetic information processing,substance metabolism,cell cycle regulation and immune regulation.Conclusion:The PUS family may play important roles in HCC and could serve as potential biomarkers for patient diagnosis and prognosis. |
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