System biology analysis of miRNA-gene interaction network reveals novel drug targets in breast cancer.

IF 1.1 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Nucleosides, Nucleotides & Nucleic Acids Pub Date : 2024-12-04 DOI:10.1080/15257770.2024.2436421
Jing Huang, Yichun Gao, Jipan Liu, Zhiyuan Yang, Xiaoli Zhang
{"title":"System biology analysis of miRNA-gene interaction network reveals novel drug targets in breast cancer.","authors":"Jing Huang, Yichun Gao, Jipan Liu, Zhiyuan Yang, Xiaoli Zhang","doi":"10.1080/15257770.2024.2436421","DOIUrl":null,"url":null,"abstract":"<p><p>Breast cancer is a heterogeneous disease that is ranked as one of the most common cancers worldwide. Currently, although there are existing molecules such as progesterone receptor and estrogen receptor for breast cancer treatment, discovering more effective drug targets is still in urgent need. In this study, we have obtained six sequencing datasets of breast cancer from GEO database and identified a set of differentially expressed molecules, including 67 miRNAs and 133 genes. Function enrichment analysis by miRPathDB database indicated that targets of 11 miRNAs could be enriched in breast cancer pathway with a <i>p</i>-value ≤ .05. A special miRNA-gene interaction network was constructed for analysis of the progression of breast cancer. We then ranked the importance of each molecule (i.e. miRNA and gene) by their node centrality indexes in the network and selected the top 10% of molecules. The statistical analysis of these molecules showed three miRNAs (hsa-miR-1275, hsa-miR-2392, hsa-miR-3141) have significant effects on the prognosis and survival of patients. By searching for potential drugs in Drugbank database, we have identified four candidates (phenethyl isothiocyanate, amuvatinib, theophylline, trifluridine) for targeting these genes. In conclusion, we believe that these drugs and their analogs could be used in the targeted therapy of breast cancer in the future.</p>","PeriodicalId":19343,"journal":{"name":"Nucleosides, Nucleotides & Nucleic Acids","volume":" ","pages":"1-16"},"PeriodicalIF":1.1000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nucleosides, Nucleotides & Nucleic Acids","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1080/15257770.2024.2436421","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Breast cancer is a heterogeneous disease that is ranked as one of the most common cancers worldwide. Currently, although there are existing molecules such as progesterone receptor and estrogen receptor for breast cancer treatment, discovering more effective drug targets is still in urgent need. In this study, we have obtained six sequencing datasets of breast cancer from GEO database and identified a set of differentially expressed molecules, including 67 miRNAs and 133 genes. Function enrichment analysis by miRPathDB database indicated that targets of 11 miRNAs could be enriched in breast cancer pathway with a p-value ≤ .05. A special miRNA-gene interaction network was constructed for analysis of the progression of breast cancer. We then ranked the importance of each molecule (i.e. miRNA and gene) by their node centrality indexes in the network and selected the top 10% of molecules. The statistical analysis of these molecules showed three miRNAs (hsa-miR-1275, hsa-miR-2392, hsa-miR-3141) have significant effects on the prognosis and survival of patients. By searching for potential drugs in Drugbank database, we have identified four candidates (phenethyl isothiocyanate, amuvatinib, theophylline, trifluridine) for targeting these genes. In conclusion, we believe that these drugs and their analogs could be used in the targeted therapy of breast cancer in the future.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
mirna -基因相互作用网络的系统生物学分析揭示了乳腺癌的新药物靶点。
乳腺癌是一种异质性疾病,是世界上最常见的癌症之一。目前,虽然已有孕激素受体、雌激素受体等分子用于治疗乳腺癌,但仍急需发现更有效的药物靶点。在本研究中,我们从GEO数据库中获得了6个乳腺癌测序数据集,鉴定出一组差异表达分子,包括67个mirna和133个基因。miRPathDB数据库功能富集分析显示,11个miRNAs靶点在乳腺癌通路中可富集,p值≤0.05。构建了一个特殊的mirna -基因相互作用网络,用于分析乳腺癌的进展。然后,我们根据每个分子(即miRNA和基因)在网络中的节点中心性指数对其重要性进行排序,并选择前10%的分子。对这些分子的统计分析显示,hsa-miR-1275、hsa-miR-2392、hsa-miR-3141三种mirna对患者的预后和生存有显著影响。通过在Drugbank数据库中搜索潜在药物,我们确定了四种候选药物(异硫氰酸苯乙酯、阿莫替尼、茶碱、三氟啶)靶向这些基因。总之,我们相信这些药物及其类似物可以在未来用于乳腺癌的靶向治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Nucleosides, Nucleotides & Nucleic Acids
Nucleosides, Nucleotides & Nucleic Acids 生物-生化与分子生物学
CiteScore
2.60
自引率
7.70%
发文量
91
审稿时长
6 months
期刊介绍: Nucleosides, Nucleotides & Nucleic Acids publishes research articles, short notices, and concise, critical reviews of related topics that focus on the chemistry and biology of nucleosides, nucleotides, and nucleic acids. Complete with experimental details, this all-inclusive journal emphasizes the synthesis, biological activities, new and improved synthetic methods, and significant observations related to new compounds.
期刊最新文献
Pharmacological interventions that activate mitochondrial biogenesis stimulate nucleotide generation in isoproterenol-stressed rat cardiomyocytes. Clinical diagnostic value and potential regulatory mechanisms of lncRNA NOP14-AS1 in chronic kidney disease. Sustainable synthesis of benzimidazole-based Schiff base using reusable CaAl2O4 nanophosphors catalyst: Insights into metal(II) complexes and DNA interactions. Evaluation of ACE I/D and ATIR A1166C variants in patients with diabetes mellitus with and without peripheral neuropathy in Turkish patients. Innovations in RNA therapeutics: a review of recent advances and emerging technologies.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1