发现增强子rna在肾透明细胞癌中的相互作用、功能和临床相关性。

IF 2.1 4区 医学 Q3 GENETICS & HEREDITY
Zhaohui Sun, Haojie Du, Xudong Zheng, Hepeng Zhang, Huajie Hu
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引用次数: 0

摘要

增强子RNA (Enhancer RNA, eRNA)在癌症生物学中扮演着重要角色,影响着肿瘤发生和发展的各个方面。在这项研究中,我们研究了erna在肾透明细胞癌(KIRC)中的作用,肾透明细胞癌是肾细胞癌最常见的亚型。利用高通量测序数据和生物信息学分析,我们确定了KIRC中差异表达的erna,并构建了以erna为中心的调控网络。我们的研究结果表明,KIRC中erna的上调可能调节免疫反应和缺氧途径,而erna的下调可能影响离子转运、细胞周期和代谢。此外,我们建立了一个基于eRNA表达谱的诊断预测模型,证明了其在KIRC诊断中的有效性。最后,我们通过生物信息学分析和体外验证实验,阐明了eRNA (ENSR00000305834)对KIRC潜在预后生物标志物SLC15A2表达的调控机制。总之,我们的研究强调了erna在KIRC中的临床意义,并强调了它们作为治疗靶点的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discovering the interactome, functions, and clinical relevance of enhancer RNAs in kidney renal clear cell carcinoma.

Enhancer RNA (eRNA) has emerged as a key player in cancer biology, influencing various aspects of tumor development and progression. In this study, we investigated the role of eRNAs in kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma. Leveraging high-throughput sequencing data and bioinformatics analysis, we identified differentially expressed eRNAs in KIRC and constructed eRNA-centric regulatory networks. Our findings revealed that up-regulated eRNAs in KIRC potentially regulate immune response and hypoxia pathways, while down-regulated eRNAs may impact ion transport, cell cycle, and metabolism. Furthermore, we developed a diagnostic prediction model based on eRNA expression profiles, demonstrating its effectiveness in KIRC diagnosis. Finally, we elucidated the regulatory mechanism of an eRNA (ENSR00000305834) on the expression of SLC15A2, a potential prognostic biomarker in KIRC, through bioinformatics analysis and in vitro validation experiments. In summary, Our study highlights the clinical significance of eRNAs in KIRC and underscores their potential as therapeutic targets.

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来源期刊
BMC Medical Genomics
BMC Medical Genomics 医学-遗传学
CiteScore
3.90
自引率
0.00%
发文量
243
审稿时长
3.5 months
期刊介绍: BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.
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