Exploring EZH2-Linked lncRNAs in Gastric Cancer: Insights from Sequencing Data and Gene Modulation.

IF 1.6 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Ali Masoudi Kazemabad, Reza Safaralizadeh, Mehdi Haghi, Mohammad Mahdi Forghanifard
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引用次数: 0

Abstract

Gastric cancer (GC) is one of the leading causes of cancer-related deaths globally. Enhancer of zeste homolog 2 (EZH2), a methyl-transferase and master transcriptional regulator frequently overexpresses in a variety of malignancies. Long non-coding RNAs (lncRNAs) play a significant role in regulating gene expression and are intricately involved in the EZH2 oncogenic regulatory network. We aimed in this study to investigate the expression of EZH2-associated lncRNAs and their probable regulatory role in GC progression. RNA-seq and miRNA-seq data from 375 tumor and 32 normal samples were retrieved from the TCGA database. Differential expression and correlation analyses were performed to identify EZH2-associated lncRNAs. A competing endogenous RNA (ceRNA) network comprising lncRNAs, miRNAs, and mRNAs was constructed and visualized. Functional genomics analysis including EZH2 knockdown and induced overexpression experiments were carried out in AGS and MKN-45 GC cell lines to validate the expression of selected lncRNAs using RT-qPCR. EZH2-correlated analysis revealed 16 upregulated and 8 downregulated lncRNAs with significant associations. EZH2 expression modulation studies confirmed that expression levels of lncRNAs including PVT1, MNX1-AS1, AC103702.2, PCAT7, LINC01235, LINC02086, MIR99AHG, and MAGI2-AS3 were regulated by EZH2 in GC cells. EZH2 modulates the expression of several key lncRNAs associated with gastric cancer progression, suggesting that the EZH2/lncRNA axis could serve as a potential therapeutic target. Targeting this axis may open new avenues for influencing critical molecular pathways involved in GC development.

探索胃癌中ezh2相关lncrna:来自测序数据和基因调控的见解。
胃癌(GC)是全球癌症相关死亡的主要原因之一。zeste同源物2增强子(EZH2)是一种甲基转移酶和主转录调节因子,在多种恶性肿瘤中经常过表达。长链非编码rna (lncRNAs)在调控基因表达中发挥着重要作用,并复杂地参与了EZH2致癌调控网络。我们在这项研究中旨在研究ezh2相关lncrna的表达及其在GC进展中的可能调节作用。从TCGA数据库中检索375例肿瘤和32例正常样本的RNA-seq和miRNA-seq数据。进行差异表达和相关性分析以鉴定ezh2相关的lncrna。构建并可视化了一个由lncRNAs、miRNAs和mrna组成的竞争性内源性RNA (ceRNA)网络。在AGS和MKN-45 GC细胞系中进行功能基因组学分析,包括EZH2敲低和诱导过表达实验,利用RT-qPCR验证所选lncrna的表达。ezh2相关分析显示,16个上调的lncrna和8个下调的lncrna具有显著相关性。EZH2表达调节研究证实PVT1、MNX1-AS1、AC103702.2、PCAT7、LINC01235、LINC02086、MIR99AHG、MAGI2-AS3等lncrna在GC细胞中的表达水平受EZH2调控。EZH2调节与胃癌进展相关的几个关键lncRNA的表达,表明EZH2/lncRNA轴可以作为潜在的治疗靶点。靶向这一轴可能为影响GC发展的关键分子途径开辟新的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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