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

被引:0
|
作者
Huang, Jing [1 ]
Gao, Yichun [1 ]
Liu, Jipan [1 ]
Yang, Zhiyuan [1 ,2 ]
Zhang, Xiaoli [1 ]
机构
[1] Hangzhou Dianzi Univ, Sch Artificial Intelligence, Hangzhou 310018, Peoples R China
[2] Chinese Univ Hong Kong, Sch Biomed Sci, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Breast cancer; miRNA-gene interaction analysis; drug target analysis; systems biology; RESOURCE;
D O I
10.1080/15257770.2024.2436421
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页数:16
相关论文
共 50 条
  • [21] Identification of Drug Targets in Breast Cancer Metabolic Network
    Kanhaiya, Krishna
    Tiwari, Dwitiya
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2020, 27 (06) : 975 - 986
  • [22] Comprehensive Analysis of MicroRNA (miRNA) Targets in Breast Cancer Cells
    Fan, Meiyun
    Krutilina, Raisa
    Sun, Jing
    Sethuraman, Aarti
    Yang, Chuan He
    Wu, Zhao-hui
    Yue, Junming
    Pfeffer, Lawrence M.
    JOURNAL OF BIOLOGICAL CHEMISTRY, 2013, 288 (38) : 27480 - 27493
  • [23] Gene and lncRNA co-expression network analysis reveals novel ceRNA network for triple-negative breast cancer
    Le, Kehao
    Guo, Hui
    Zhang, Qiulei
    Huang, Xiaojuan
    Xu, Ming
    Huang, Ziwei
    Yi, Pengfei
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [24] Gene and lncRNA co-expression network analysis reveals novel ceRNA network for triple-negative breast cancer
    Kehao Le
    Hui Guo
    Qiulei Zhang
    Xiaojuan Huang
    Ming Xu
    Ziwei Huang
    Pengfei Yi
    Scientific Reports, 9
  • [25] Dynamic network curvature analysis of gene expression reveals novel potential therapeutic targets in sarcoma
    Elkin, Rena
    Oh, Jung Hun
    Cruz, Filemon Dela
    Norton, Larry
    Deasy, Joseph O.
    Kung, Andrew L.
    Tannenbaum, Allen R.
    SCIENTIFIC REPORTS, 2024, 14 (01)
  • [26] Dynamic network curvature analysis of gene expression reveals novel potential therapeutic targets in sarcoma
    Rena Elkin
    Jung Hun Oh
    Filemon Dela Cruz
    Larry Norton
    Joseph O. Deasy
    Andrew L. Kung
    Allen R. Tannenbaum
    Scientific Reports, 14
  • [27] Integrative analysis of miRNA and gene expression reveals regulatory networks in tamoxifen-resistant breast cancer
    Joshi, Tejal
    Elias, Daniel
    Stenvang, Jan
    Alves, Carla L.
    Teng, Fei
    Lyng, Maria B.
    Lykkesfeldt, Anne E.
    Brunner, Nils
    Wang, Jun
    Gupta, Ramneek
    Workman, Christopher T.
    Ditzel, Henrik J.
    ONCOTARGET, 2016, 7 (35) : 57239 - 57253
  • [28] Novel therapeutic targets identification in breast cancer by systems biology approach
    Mohammed, M. Peer
    ANNALS OF ONCOLOGY, 2017, 28 : 21 - 21
  • [29] Mapping of natural antimutagenic chemotherapeutic ding targets on breast cancer network using System biology approach
    Singh, Abhilasha
    Kumar, Amrendar
    Bhattacharjee, Biplab
    BIOLOGY, ENVIRONMENT AND CHEMISTRY, 2011, : 269 - 272
  • [30] Potential Therapeutic Targets in Triple-Negative Breast Cancer Based on Gene Regulatory Network Analysis: A Comprehensive Systems Biology Approach
    Ahmadi, Maryam
    Barkhoda, Neda
    Alizamir, Aida
    Taherkhani, Amir
    INTERNATIONAL JOURNAL OF BREAST CANCER, 2024, 2024