Identification of significant hub genes and pathways associated with metastatic breast cancer and tolerogenic dendritic cell via bioinformatics analysis

被引:0
|
作者
Ching, Kirstie Wong Chee [1 ]
Mokhtar, Noor Fatmawati [2 ]
Tye, Gee Jun [1 ]
机构
[1] Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Health Campus, Kelantan, Kubang Kerian,16150, Malaysia
[2] Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Main Campus, Pulau Pinang, 11800, Malaysia
关键词
D O I
10.1016/j.compbiomed.2024.109396
中图分类号
学科分类号
摘要
Metastatic breast cancer (MBC) is an advanced-stage breast cancer associated with more than 90 % of cancer-related deaths. Immunosuppressive properties of tolerogenic dendritic cells (tolDCs) in tumour immune microenvironment (TIME) may be a risk factor for the rapid progression to MBC. However, the exact connections between the two are unknown. The aim of the current study is to uncover gene signatures and key pathways associated with MBC and tolDCs via an integrated bioinformatics approach. Gene expression profiles of MBC and tolDCs were retrieved from Gene Expression Omnibus (GEO) to identify common differentially expressed genes (DEGs). From DGE analysis, 529 upregulated common DEGs and 367 downregulated common DEGs had been identified. In enrichment analysis, common DEGs enriched in GO terms of defense response to virus and KEGG pathway of transcriptional misregulation in cancer were reported to be significantly associated with MBC and tolDCs. From the constructed PPI networks, 23 hub genes were identified, although only 5 genes were significant; 3 upregulated (ISG15, OAS2 and RSAD2) and 2 downregulated (eEF2 and PPARG) as they were found to be significantly correlated and had the same expression trend as predicted in validation analysis of overall survival (OS) analysis, expression levels, immune infiltration analysis and immunohistochemistry (IHC) analysis. These 5 hub genes can now be exploited in developing novel therapeutic interventions and as diagnostic biomarkers for enhancing the clinical outcomes of MBC patients. © 2024 Elsevier Ltd
引用
收藏
相关论文
共 50 条
  • [31] Identification of Multiple Hub Genes and Pathways in Hepatocellular Carcinoma: A Bioinformatics Analysis
    Liu, Junwei
    Han, Fang
    Ding, Jianyi
    Liang, Xiaodong
    Liu, Jie
    Huang, Dongsheng
    Zhang, Chengwu
    BIOMED RESEARCH INTERNATIONAL, 2021, 2021
  • [32] 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
  • [33] Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
    Liu, Xiaoqun
    Liu, Xiangdong
    Qiao, Tiankui
    Chen, Wei
    ONCOLOGY LETTERS, 2020, 19 (03) : 1881 - 1889
  • [34] Identification of hub genes associated with EMT-induced chemoresistance in breast cancer using integrated bioinformatics analysis
    Kaur, Bhavjot
    Mukhlis, Yahya
    Natesh, Jagadish
    Penta, Dhanamjai
    Meeran, Syed Musthapa
    GENE, 2022, 809
  • [35] Identification of hub genes in triple-negative breast cancer by integrated bioinformatics analysis
    Wei, Li-Min
    Li, Xin-Yang
    Wang, Zi-Ming
    Wang, Yu-Kun
    Yao, Ge
    Fan, Jia-Hao
    Wang, Xin-Shuai
    GLAND SURGERY, 2021, 10 (02) : 799 - 806
  • [36] Identification of breast cancer hub genes and analysis of prognostic values using integrated bioinformatics analysis
    Fang, Enhao
    Zhang, Xiuqing
    CANCER BIOMARKERS, 2018, 21 (02) : 373 - 381
  • [37] Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation
    Zhao, Yuzi
    Pi, Jie
    Liu, Lihua
    Yan, Wenjie
    Ma, Shufang
    Hong, Li
    CANCER MANAGEMENT AND RESEARCH, 2021, 13 : 707 - 721
  • [38] Identification of Significant Genes in Lung Cancer of Nonsmoking Women via Bioinformatics Analysis
    Wang, Yu
    Hu, Sibo
    Bai, Xianguang
    Zhang, Ke
    Yu, Ruixue
    Xia, Xichao
    Zheng, Xinhua
    BIOMED RESEARCH INTERNATIONAL, 2021, 2021
  • [39] Identification of potential hub genes and therapeutic drugs in ovarian cancer via bioinformatics analysis
    Zhou, Xinyue
    Song, Zuofei
    Chen, Jia
    Wang, Dongxue
    Sun, Jingli
    ALL LIFE, 2023, 16 (01)
  • [40] Identification of Hub Genes Associated With Clear Cell Renal Cell Carcinoma by Integrated Bioinformatics Analysis
    Huang, Hao
    Zhu, Ling
    Huang, Chao
    Dong, Yi
    Fan, Liangliang
    Tao, Lijian
    Peng, Zhangzhe
    Xiang, Rong
    FRONTIERS IN ONCOLOGY, 2021, 11