Identification of key pathways and hub genes in basal-like breast cancer using bioinformatics analysis

被引:43
|
作者
Yang, Kaidi [1 ,2 ]
Gao, Jian [3 ]
Luo, Mao [1 ,4 ,5 ]
机构
[1] Southwest Med Univ, Collaborat Innovat Ctr Prevent & Treatment Cardio, Key Lab Med Electrophysiol, Minist Educ, Luzhou, Peoples R China
[2] Army Med Univ, Affiliated Hosp 1, Key Lab Tumor Immunol, Chongqing, Peoples R China
[3] Yangtze Normal Univ, Dept Life Sci & Technol, Chongqing, Peoples R China
[4] Southwest Med Univ, Drug Discovery Res Ctr, Luzhou, Sichuan, Peoples R China
[5] Southwest Med Univ, Sch Pharm, Dept Pharmacol, Lab Cardiovasc Pharmacol, Luzhou, Sichuan, Peoples R China
来源
ONCOTARGETS AND THERAPY | 2019年 / 12卷
基金
中国国家自然科学基金;
关键词
basal-like breast cancer; bioinformatics; differentially expressed genes; hub genes; molecular mechanism; CHECKPOINT GENES; EXPRESSION; CARCINOMA; CELLS; SUBTYPES; REVEALS; BUB1;
D O I
10.2147/OTT.S158619
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Basal-like breast cancer (BLBC) is the most aggressive subtype of breast cancer (BC) and links to poor outcomes. As the molecular mechanism of BLBC has not yet been completely discovered, identification of key pathways and hub genes of this disease is an important way for providing new insights into exploring the mechanisms of BLBC initiation and progression. Objective: The aim of this study was to identify potential gene signatures of the development and progression of the BLBC via bioinformatics analysis. Methods and results: The differential expressed genes (DEGs) including 40 up-regulated and 21 down-regulated DEGs were identified between GSE25066 and GSE21422 microarrays, and these DEGs were significantly enriched in the terms related to oncogenic or suppressive roles in BLBC progression. In addition, KEGG pathway and GSEA (Gene Set Enrichment Analysis) enrichment analyses were performed for DEGs between the basal type and non-basal-type breast cancer from GSE25066 microarray. These DEGs were enriched in pathways such as cell cycle, cytokine-cytokine receptor interaction, chemokine signaling pathway, central carbon metabolism signaling and TNF signaling pathway. Moreover, the protein-protein interaction (PPI) network was constructed with those 61 DEGs using the Cytoscape software, and the biological significance o f putative modules was established using MCODE. The module 1 was found to be closely related with a term of mitosis regulation and enriched in cell cycle pathway, and thus confirmed the pathological characteristic of BLBC with a high mitotic index. Furthermore, prediction values of the top 10 hub genes such as CCNB2, BUB1, NDC80, CENPE, KIF2C, TOP2A, MELK, TPX2, CKS2 and KIF20A were validated using Oncomine and Kaplan-Meier plotter. Conclusion: Our results suggest the intriguing possibility that the hub genes and modules in the PPI network contributed to in-depth knowledge about the molecular mechanism of BLBC, paving a way for more accurate discovery of potential treatment targets for BLBC patients.
引用
收藏
页码:1319 / 1331
页数:13
相关论文
共 50 条
  • [1] Identification of hub genes and pathways in bladder cancer using bioinformatics analysis
    Li, Danhui
    Zhen, Fan
    Le, Jianwei
    Chen, Guodong
    Zhu, Jianhua
    AMERICAN JOURNAL OF CLINICAL AND EXPERIMENTAL UROLOGY, 2022, 10 (01): : 13 - 24
  • [2] Hub genes identification and association of key pathways with hypoxia in cancer cells: A bioinformatics analysis
    Aziz, Faiza
    Shoaib, Naila
    Rehman, Abdul
    SAUDI JOURNAL OF BIOLOGICAL SCIENCES, 2023, 30 (09)
  • [3] Identification of key genes unique to the luminal a and basal-like breast cancer subtypes via bioinformatic analysis
    Rong Jia
    Zhongxian Li
    Wei Liang
    Yucheng Ji
    Yujie Weng
    Ying Liang
    Pengfei Ning
    World Journal of Surgical Oncology, 18
  • [4] Identification of key genes unique to the luminal a and basal-like breast cancer subtypes via bioinformatic analysis
    Jia, Rong
    Li, Zhongxian
    Liang, Wei
    Ji, Yucheng
    Weng, Yujie
    Liang, Ying
    Ning, Pengfei
    WORLD JOURNAL OF SURGICAL ONCOLOGY, 2020, 18 (01)
  • [5] IDENTIFICATION OF HUB GENES AND KEY PATHWAYS IN SARCOPENIA THROUGH BIOINFORMATICS ANALYSIS
    Gui, W. W.
    Zhou, C. P.
    Lin, X. H.
    AGING CLINICAL AND EXPERIMENTAL RESEARCH, 2024, 36 : S602 - S604
  • [6] Identification of key pathways and genes in colorectal cancer using bioinformatics analysis
    Bin Liang
    Chunning Li
    Jianying Zhao
    Medical Oncology, 2016, 33
  • [7] Identification of key pathways and genes in colorectal cancer using bioinformatics analysis
    Liang, Bin
    Li, Chunning
    Zhao, Jianying
    MEDICAL ONCOLOGY, 2016, 33 (10)
  • [8] Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
    Oumeddour, Abdelkader
    MEDICINE, 2023, 102 (11) : E33291
  • [9] Identification of key pathways and genes in the progression of cervical cancer using bioinformatics analysis
    Wu, Kejia
    Yi, Yuexiong
    Liu, Fulin
    Wu, Wanrong
    Chen, Yurou
    Zhang, Wei
    ONCOLOGY LETTERS, 2018, 16 (01) : 1003 - 1009
  • [10] Identification of Core Genes and Key Pathways in Gastric Cancer using Bioinformatics Analysis
    Z. Li
    Y. Zhou
    G. Tian
    M. Song
    Russian Journal of Genetics, 2021, 57 : 963 - 971