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Next Generation Sequencing Facilitates Quantitative Analysis of METTL3 overexpression in THP-1 cells [m6A-Seq]

ABSTRACT: Next Generation Sequencing Facilitates Quantitative Analysis of METTL3 overexpression in THP-1 cells [m6A-Seq]

PROVIDER: PRJNA874055 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR21225623_1.fastq.gz	Fastqsanger.gz
	SRR21225623_2.fastq.gz	Fastqsanger.gz
	SRR21225624_1.fastq.gz	Fastqsanger.gz
	SRR21225624_2.fastq.gz	Fastqsanger.gz
	SRR21225625_1.fastq.gz	Fastqsanger.gz

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Project description:METTL3-mediated RNA N6-methyladenosine (m6A) is the most prevalent modification participates in tumor initiation and progression via regulating expression of their target genes in cancers. However, its role in tumor cell metabolism remains poorly appreciated. In this study, we conducted a multi-omics analysis including m6A microarray and quantitative proteomics to explore the potential effect and mechanism of METTL3 on the metabolism in gastric cancer cells. Our results found that significant alterations in the protein and m6A modification profile which induced by METTL3 overexpression in GC cells. Gene Ontology (GO) enrichment results showed that down-regulated proteins were significantly enriched in intracellular mitochondrial oxidative phosphorylation (OXPHOS), and the Protein-Protein Interaction (PPI) network analysis found that these differentially expressed proteins were significantly associated with OXPHOS. Subsequently, a prognostic model constructed based on the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the high-risk group showed a worse prognosis in GC patients. Meanwhile, the Gene Set Enrichment Analysis (GSEA) showed a significant enrichment in the energy metabolism signaling pathway. Then, combined with the results of the m6A microarray analysis, the intersection molecules of DEPs and differential methylation genes (DMGs) were significantly correlated with the genes involved in OXPHOS. Besides, there were also significant differences in prognosis and GSEA enrichment between the two clusters of GC patients classified according to consensus clustering algorithm. Finally, we focused on highly expressed, highly methylated molecules regulated by METTL3 and identified three (AVEN, DAZAP2, DNAJB1) genes that were significantly associated with poor prognosis in patients with GC. These results indicated that METTL3-regulated DEPs in GC cells were significantly associated with OXPHOS. After combined with m6A microarray analysis, the results suggested that these proteins might be involved in cell energy metabolism through m6A modifications thus influencing the prognosis of GC patients. Overall, our study revealed that METTL3 involved in cell metabolism through an m6A-dependent mechanism in GC cells, and indicated a potential biomarker for prognostic prediction in GC.

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Next Generation Sequencing Facilitates Quantitative Analysis of METTL3 overexpression in THP-1 cells [m6A-Seq]

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