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Comprehensive analysis of ubiquitin-specific protease 1 reveals its importance in hepatocellular carcinoma.

ABSTRACT: OBJECTIVES:In this study, we comprehensively analysed the role of ubiquitin-specific protease 1(USP1) in hepatocellular carcinoma (HCC) using data from a set of public databases. MATERIALS AND METHODS:We analysed the mRNA expression of USP1 in HCC and subgroups of HCC using Oncomine and UALCAN. Survival analysis of USP1 in HCC was conducted with the Kaplan-Meier Plotter database. The mutations of USP1 in HCC were analysed using cBioPortal and the Catalogue of Somatic Mutations in Cancer database. Differential genes correlated with USP1 and WD repeat domain 48 (WDR48) were obtained using LinkedOmics. USP1 was knocked down with small interfering RNA (siRNA) or pharmacologically inhibited by ML-323 in MHCC97H or SK-Hep-1 cell lines for function analysis. RESULTS:High USP1 expression predicted unfavourable overall survival in HCC patients. USP1 showed positive correlations with the abundances of macrophages and neutrophils. We identified 98 differential genes that were positively correlated with both USP1 and WDR48. These genes were mainly involved in the cell cycle, aldosterone synthesis and secretion and oestrogen signalling pathways. Interactions between USP1 and WDR 48 were confirmed using co-immunoprecipitation. USP1 knockdown or ML-323 treatment reduced the expression of proliferating cell nuclear antigen (PCNA), cyclin D1 and cyclin E1. CONCLUSIONS:Overall, USP1 is a promising target for HCC treatment with good prognostic value. USP1 and WDR48 function together in regulating cancer cell proliferation via the cell cycle.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC7574869 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Comprehensive analysis of ubiquitin-specific protease 1 reveals its importance in hepatocellular carcinoma.

Zhao Yalei Y Xue Chen C Xie Zhongyang Z Ouyang Xiaoxi X Li Lanjuan L

Cell proliferation 20200919 10

<h4>Objectives</h4>In this study, we comprehensively analysed the role of ubiquitin-specific protease 1(USP1) in hepatocellular carcinoma (HCC) using data from a set of public databases.<h4>Materials and methods</h4>We analysed the mRNA expression of USP1 in HCC and subgroups of HCC using Oncomine and UALCAN. Survival analysis of USP1 in HCC was conducted with the Kaplan-Meier Plotter database. The mutations of USP1 in HCC were analysed using cBioPortal and the Catalogue of Somatic Mutations in ...[more]

PMID: 32951278

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Project description:BackgroundDue to the complicated molecular and cellular heterogeneity in hepatocellular carcinoma (HCC), the morbidity and mortality still remains high level in the world. However, the number of novel metabolic biomarkers and prognostic models could be applied to predict the survival of HCC patients is still small. In this study, we constructed a metabolic gene signature by systematically analyzing the data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC).MethodsDifferentially expressed genes (DEGs) between tumors and paired non-tumor samples of 50 patients from TCGA dataset were calculated for subsequent analysis. Univariate cox proportional hazard regression and LASSO analysis were performed to construct a gene signature. The Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC), Univariate and Multivariate Cox regression analysis, stratification analysis were used to assess the prognostic value of the gene signature. Furthermore, the reliability and validity were validated in four types of testing cohorts. Moreover, the diagnostic capability of the gene signature was investigated to further explore the clinical significance. Finally, Go enrichment analysis and Gene Set Enrichment Analysis (GSEA) have been performed to reveal the different biological processes and signaling pathways which were active in high risk or low risk group.ResultsTen prognostic genes were identified and a gene signature were constructed to predict overall survival (OS). The gene signature has demonstrated an excellent ability for predicting survival prognosis. Univariate and Multivariate analysis revealed the gene signature was an independent prognostic factor. Furthermore, stratification analysis indicated the model was a clinically and statistically significant for all subgroups. Moreover, the gene signature demonstrated a high diagnostic capability in differentiating normal tissue and HCC. Finally, several significant biological processes and pathways have been identified to provide new insights into the development of HCC.ConclusionThe study have identified ten metabolic prognostic genes and developed a prognostic gene signature to provide more powerful prognostic information and improve the survival prediction for HCC.

Project description:BACKGROUND:Hepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC. METHODS:Deep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed. RESULTS:Expression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis. CONCLUSIONS:Transcriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.

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Comprehensive analysis of ubiquitin-specific protease 1 reveals its importance in hepatocellular carcinoma.

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Comprehensive analysis of ubiquitin-specific protease 1 reveals its importance in hepatocellular carcinoma.

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