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Background: Hepatitis E virus (HEV) infection is a common cause of acute hepatitis worldwide and causes approximately 30% case fatality rate among pregnant women. Pregnancy serum (PS), which contains a high concentration of estradiol, facilitates HEV replication in vitro through the suppression of the PI3K–AKT–mTOR and cAMPK–PKA–CREB signaling pathways. However, the proteomics of the complex host responses to HEV infection, especially how PS facilitates viral replication, remains unclear. Methods: In this study, the differences in the proteomics of HEV-infected HepG2 cells supplemented with fetal bovine serum (FBS) from those of HEV-infected HepG2 cells supplemented with serum from women in their third trimester of pregnancy were quantified by using isobaric tags for relative and absolute quantification technology. Results: A total of 1511 proteins were identified, among which 548 were defined as differentially expressed proteins (DEPs). HEV-infected cells supplemented with PS exhibited the most significant changes at the protein level. A total of 328 DEPs, including 66 up-regulated and 262 down-regulated proteins, were identified in HEV-infected cells supplemented with FBS, whereas 264 DEPs, including 201 up-regulated and 63 down-regulated proteins, were found in HEV-infected cells supplemented with PS. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that in HEV-infected cells, PS supplementation adjusted more host genes and signaling pathways than FBS supplementation. The DEPs involved in virus–host interaction participated in complex interactions, especially a large number of immune-related protein emerged in HEV-infected cells supplemented with PS. Three significant or interesting proteins, including filamin-A, thioredoxin, and cytochrome c, in HEV-infected cells were functionally verified. Conclusions: The results of this study provide new and comprehensive insight for exploring virus–host interactions and will benefit future studies on the pathogenesis of HEV in pregnant women. [ABSTRACT FROM AUTHOR]

Background: Gamma delta (γδ) T cells play dual roles in human tumors, with both antitumor and tumor-promoting functions. However, the role of γδT cells in HPV-infected cervical cancer is still undetermined. Therefore, we aimed to identify γδT cell-related prognostic signatures in the cervical tumor microenvironment., Methods: Single-cell RNA-sequencing (scRNA-seq) data, bulk RNA-seq data, and corresponding clinical information of cervical cancer patients were obtained from the TCGA and GEO databases. The Seurat R package was used for single-cell analysis, and machine learning algorithms were used to screen and construct a γδT cell-related prognostic signature. Real-time quantitative PCR (RT-qPCR) was performed to detect the expression of prognostic signature genes., Results: Single-cell analysis indicated distinct populations of γδT cells between HPV-positive (HPV+) and HPV-negative (HPV-) cervical cancers. A trajectory analysis indicated γδT cells clustered into differential clusters with the pseudotime. High-dimensional Weighted Gene Co-expression Network Analysis (hdWGCNA) identified the key γδT cell-related gene modules. Bulk RNA-seq analysis also demonstrated the heterogeneity of immune cells, and the γδT-score was positively associated with inflammatory response and negatively associated with MYC stemness. Eight γδT cell-related hub genes (GTRGs), including ITGAE, IKZF3, LSP1, NEDD9, CLEC2D, RBPJ, TRBC2, and OXNAD1, were selected and validated as a prognostic signature for cervical cancer., Conclusion: We identified γδT cell-related prognostic signatures that can be considered independent factors for survival prediction in cervical cancer., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.