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Bioinformatic Analysis of mRNA and miRNA Expression Patterns In p53 Knock-out C666-1 cells [miRNA-Seq]

ABSTRACT: Unlike other EBV-associated human tumors, nearly 100% wild-type p53 gene is found in NPC, p53 protein is also frequently found to accumulate in NPC biopsies. However, the role of p53 in EBV-positive nasopharyngeal carcinoma is unclear. The expression profiles of mRNAs and miRNAs of EBV-positive NPC cells are unknown. To elucidate the function of p53 in EBV-positive NPC, we used the CRISPR-Cas9 gene editing system to p53 knockout C666-1 cells with Epstein-Barr virus and performed mRNA and miRNA sequencing in p53 KO C666-1 and their control cells. Gene Ontology (GO), KEGG and STRING analyses were implemented to identify significant functions, pathways of differentially expressed mRNAs. Through comparative analysis of p53-regulated genes from EBV-positive C666-1 cells and EBV-negative HONE2 cells with p53 target genes from 16 high throughput data sets, we found that the number of target genes and KEGG pathways downregulated by p53 in EBV-positive C666-1 cells were much less than in EBV-negative HONE2 cells, but “p53 signaling pathway” and related cell cycle arrest and apoptosis genes were significantly downregulated after knockout of p53 gene in C666-1 cells. To explore the effect of p53 on cell cycle and apoptosis, we established stable p53 C666-1-KO cell lines with stable expression of exogenous p53-WT and their control cell lines. Using the established cell lines, we observed that stable expression of p53 repressed cell proliferation, increased cell apoptosis and blocked G1/S phase progression. In conclusion, our results show that the accumulated p53 protein in EBV-positive C666-1 cells still has some tumour suppressor functions such as blocking cell-cycle progression and promoting apoptosis, but the ability of p53 to downregulate gene expression is inhibited.

ORGANISM(S): Homo sapiens

PROVIDER: GSE138257 | GEO | 2021/03/01

REPOSITORIES: GEO

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Project description:Comprehensive Profiling of Epstein-Barr Virus-Encoded miRNAome Associated with Specific Latent Type in Tumor Cells Epstein-Barr virus (EBV) is an etiological cause of many human lymphocytic and epithelial malignancies. EBV expressed different genes associated with three latent types. So far as many as 44 EBV-encoded miRNA species have been found but their comprehensive and comparative profiling is not well documented in three latent infection states linked to various tumor cells. In this study, we utilized the polyA-tailed quantitative real time RT-PCR procedure to measure the relative abundance of viral miRNA species that linked to individual viral genome locations in combination with microarray evaluation in a subset of representative lymphoid and epithelial tumor cells undergoing various types of EBV latent infection. The results showed that miR-BHRF1 family and miR-BART family are expressed differentially in a tissue-dependent and latency-dependent manner. In particular, in NPC tissue and the only EBV consistently harboring cell line C666-1 with latency type II, there were highly abundant miR-BART family but not miR-BHRF1 family members that accounted for more than 10% of the whole known human miRNA library, implicating their important roles in maintaining EBV latent infection and driving NPC tumorigenesis. In addition, EBV miRNAome-based clustering analysis could classify three distinct EBV latency types, meanwhile, for the first time, we found and subsequently evaluated a novel secret latent switch in BL cell line Daudi from type I to III, which was unable to be identified by traditional latent biomarkers. Together, our data provided an in-depth and comparative profiling of EBV miRNA transcriptome in correspondence with three EBV latent infections, suggesting that different viral miRNA species were involved in divergent host cell carcinogenesis. Finally, EBV miRNAome, as a cluster of novel latency biomarkers expressed variedly in tumor cells, greatly complements and improves the classical typing criteria in conjunction with other latently expressed marker genes. 2 NPC tissue samples and 2 NPC cell lines and 5 lymphocytic cell lines

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Bioinformatic Analysis of mRNA and miRNA Expression Patterns In p53 Knock-out C666-1 cells [miRNA-Seq]

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