Synchronous profiling of mRNA N6-methyladenosine modifications and mRNA expression in high-grade serous ovarian cancer: a pilot study

高级别浆液性卵巢癌中 mRNA N6-甲基腺苷修饰和 mRNA 表达的同步分析:一项初步研究

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作者:Li Yang #, Jingfang Liu #, Yanlu Jin, Jie Xing, Jiejie Zhang, Xin Chen, Aijun Yu

Abstract

This study aimed to synchronously determine epitranscriptome-wide RNA N6-methyladenosine (m6A) modifications and mRNA expression profile in high grade serous ovarian cancer (HGSOC). The methylated RNA immunoprecipitation sequencing (MeRIP-seq) was used to comprehensively examine the m6A modification profile and the RNA-sequencing (RNA-seq) was performed to analyze the mRNA expression profile in HGSOC and normal fallopian tube (FT) tissues. Go and KEGG analyses were carried out in the enrichment of those differentially methylated and expressed genes. MeRIP-seq data showed 53,794 m6A methylated peaks related to 19,938 genes in the HGSOC group and 51,818 m6A peaks representing 19,681 genes in the FT group. RNA-seq results revealed 2321 upregulated and 2486 downregulated genes in HGSOC. Conjoint analysis of MeRIP-seq and RNA-seq data identified differentially expressed genes in which 659 were hypermethylated (330 up- and 329 down-regulated) and 897 were hypomethylated (475 up- and 422 down-regulated). Functional enrichment analysis indicated that these differentially modulated genes are involved in pathways related to cancer development. Among methylation regulators, the m6A eraser (FTO) expression was significantly lower, but the m6A readers (IGF2BP2 and IGF2BP3) were higher in HGSOC, which was validated by the subsequent real-time PCR assay. Exploration through public databases further corroborated their possible clinical application of certain methylation regulators and differentially expressed genes. For the first time, our study screens the epitranscriptome-wide m6A modification and expression profiles of their modulated genes and signaling pathways in HGSOC. Our findings provide an alternative direction in exploring the molecular mechanisms of ovarian pathogenesis and potential biomarkers in the diagnosis and predicting the prognosis of the disease.

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