Background: Deubiquitinating enzymes specifically removes ubiquitin molecules from ubiquitin-tagged target proteins, thereby inhibiting the degradation of target proteins and playing an important role in tumor. However, the mechanism of deubiquitinating enzyme USP45 in tumors remains unclear.Methods: Based on the RNA-seq data of tissues and cell lines in The Cancer Genome Atlas (TCGA) database, GTEx and CCLE database, the pan-cancer analysis of USP45 expression and survival outcome were performed using R software and Kaplan-Meier Plotter. The structural variants, gene mutations and gene copy number alteration of USP45 were analyzed using the TCGA Pan-Cancer Atlas Studies dataset in the cBioPortal database. The relationships between USP45 and mRNA methylation, tumor heterogeneity, tumor stemness, and tumor immunity were performed by Sangerbox platform and TIMER2.0 using Pearson correlation analysis. Through the ENCORI database and string database, we constructed the ceRNA regulatory mechanism and protein-protein interaction network for USP45. Based on the RNA-seq data in TCGA and GTEx databases, we also constructed the downstream regulatory network for USP45 using the Limma and ClusterProfiler packages of R software. At last, the protein expression levels of USP45 were detected by immunohistochemistry in tumor tissue microarrays.Results: USP45 is upregulated in most types of tumors and negatively correlated with the overall survival and recurrence-free survival of patient. Furthermore, the structural variation, gene mutations and gene copy number variation of USP45 were identified in different types of tumors. The pan-cancer analysis showed that USP45 was closely related to mRNA methylation, tumor heterogeneity and tumor stemness. In most types of tumors, the expression of USP45 was positively correlated with many immune checkpoint molecules and immune regulators such as PD-L1, while negatively correlated with the infiltration levels of NK cells, Th1 cells, macrophages, and dendritic cells in the tumor microenvironment. Finally, we constructed the ceRNA regulatory network, protein-protein interaction network and downstream regulatory network for USP45 in different types of tumors.Conclusion: Our study firstly explored the putative oncogenic role of USP45 in pan-cancer, and provided insights for further investigation of USP45.

Introduction: Esophageal adenocarcinoma (EAC) is one of the histologic types of esophageal cancer with a poor prognosis. The majority of EAC originate from Barrett's esophagus (BE). There are few studies focusing on the dynamic progression of BE to EAC. Methods: R software was used to analyze differentially expressed genes (DEGs) based on RNA-seq data of 94 normal esophageal squamous epithelial (NE) tissues, 113 BE tissues and 147 EAC tissues. The overlapping genes of DEGs between BE and EAC were analyzed by Venn diagram tool. The hub genes were selected by Cytoscape software based on the protein-protein interaction network of the overlapping genes using STRING database. The functional analysis of hub genes was performed by R software and the protein expression was identified by immunohistochemistry. Results: In the present study, we found a large degree of genetic similarity between BE and EAC, and further identified seven hub genes (including COL1A1, TGFBI, MMP1, COL4A1, NID2, MMP12, CXCL1) which were all progressively upregulated in the progression of NE-BE-EAC. We have preliminarily uncovered the probable molecular mechanisms of these hub genes in disease development and constructed the ceRNA regulatory network of hub genes. More importantly, we explored the possibility of hub genes as biomarkers in the disease progression of NE-BE-EAC. For example, TGFBI can be used as biomarkers to predict the prognosis of EAC patients. COL1A1, NID2 and COL4A1 can be used as biomarkers to predict the response to immune checkpoint blockade (ICB) therapy. We also constructed a disease progression risk model for NE-BE-EAC based on CXCL1, MMP1 and TGFBI. Finally, the results of drug sensitivity analysis based on hub genes showed that drugs such as PI3K inhibitor TGX221, bleomycin, PKC inhibitor Midostaurin, Bcr-Abl inhibitor Dasatinib, HSP90 inhibitor 17-AAG, and Docetaxel may be potential candidates to inhibit the progression of BE to EAC. Conclusion:This study is based on a large number of clinical samples with high credibility, which is useful for revealing the probable carcinogenic mechanism of BE to EAC and developing new clinical treatment strategies.