MiRNA target enrichment analysis of co-expression network modules reveals important miRNAs and their roles in breast cancer progression.

IF 1.5 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Journal of Integrative Bioinformatics Pub Date : 2024-12-25 eCollection Date: 2024-12-01 DOI:10.1515/jib-2022-0036
Mohammad Javad Bazyari, Seyed Hamid Aghaee-Bakhtiari
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引用次数: 0

Abstract

Breast cancer has the highest incidence and is the fifth cause of death in cancers. Progression is one of the important features of breast cancer which makes it a life-threatening cancer. MicroRNAs are small RNA molecules that have pivotal roles in the regulation of gene expression and they control different properties in breast cancer such as progression. Recently, systems biology offers novel approaches to study complicated biological systems like miRNAs to find their regulatory roles. One of these approaches is analysis of weighted co-expression network in which genes with similar expression patterns are considered as a single module. Because the genes in one module have similar expression, it is rational to think the same regulatory elements such as miRNAs control their expression. Herein, we use WGCNA to find important modules related to breast cancer progression and use hypergeometric test to perform miRNA target enrichment analysis and find important miRNAs. Also, we use negative correlation between miRNA expression and modules as the second filter to ensure choosing the right candidate miRNAs regarding to important modules. We found hsa-mir-23b, hsa-let-7b and hsa-mir-30a are important miRNAs in breast cancer and also investigated their roles in breast cancer progression.

共表达网络模块的MiRNA靶富集分析揭示了重要的MiRNA及其在乳腺癌进展中的作用。
乳腺癌发病率最高,是癌症的第五大死因。进展是乳腺癌的重要特征之一,使其成为一种危及生命的癌症。microrna是一种小的RNA分子,在调节基因表达方面起着关键作用,它们控制着乳腺癌的不同特性,比如进展。近年来,系统生物学提供了新的方法来研究复杂的生物系统,如mirna,以发现它们的调控作用。其中一种方法是分析加权共表达网络,其中具有相似表达模式的基因被视为单个模块。由于一个模块中的基因具有相似的表达,因此认为相同的调控元件(如miRNAs)控制它们的表达是合理的。本文利用WGCNA寻找与乳腺癌进展相关的重要模块,并利用hypergeometric test进行miRNA靶富集分析,发现重要的miRNA。此外,我们使用miRNA表达与模块之间的负相关作为第二过滤器,以确保选择正确的重要模块候选miRNA。我们发现hsa-mir-23b、hsa-let-7b和hsa-mir-30a是乳腺癌中重要的mirna,并研究了它们在乳腺癌进展中的作用。
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
Journal of Integrative Bioinformatics
Journal of Integrative Bioinformatics Medicine-Medicine (all)
CiteScore
3.10
自引率
5.30%
发文量
27
审稿时长
12 weeks
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