Co-expression Network Analysis Identifies Fourteen Hub Genes Associated with Prognosis in Clear Cell Renal Cell Carcinoma

被引:4
|
作者
Chen, Jia-yi [1 ,2 ]
Sun, Yan [1 ,2 ]
Qiao, Nan [1 ,2 ]
Ge, Yang-yang [1 ,2 ]
Li, Jian-hua [1 ,2 ]
Lin, Yun [1 ,2 ]
Yao, Shang-long [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Anesthesiol, Wuhan 430022, Peoples R China
[2] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Inst Anesthesia & Crit Care Med, Wuhan 430022, Peoples R China
基金
中国国家自然科学基金;
关键词
bioinformatics; clear cell renal cell carcinoma; weighted gene co-expression network analysis; biomarker; CANCER; PROGRESSION; TUMOR; PROLIFERATION; SURVIVAL; TARGETS; FOXM1;
D O I
10.1007/s11596-020-2245-6
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Renal cancer is a common genitourinary malignance, of which clear cell renal cell carcinoma (ccRCC) has high aggressiveness and leads to most cancer-related deaths. Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC. Here, we identified 2397 common differentially expressed genes (DEGs) using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas (TCGA). Then, we performed weighted gene co-expression network analysis and protein-protein interaction network analysis, 17 candidate hub genes were identified. These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified. All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC. Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome. ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples, and between early stage and advanced stage ccRCC. Moreover, all the hub genes were positively associated with distant metastasis, lymph node infiltration, tumor recurrence and the expression of MKi67, suggesting these genes might promote tumor proliferation, invasion and metastasis. Furthermore, the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function. In summary, our study identified 14 potential biomarkers for predicting tumorigenesis and progression, which might contribute to early diagnosis, prognosis prediction and therapeutic intervention.
引用
收藏
页码:773 / 785
页数:13
相关论文
共 50 条
  • [31] Co-Expression Network Analysis Identified Genes Associated with Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma
    Qin, Songbing
    Long, Xiang
    Zhao, Qi
    Zhao, WeiXin
    CANCER INVESTIGATION, 2020, 38 (01) : 13 - 22
  • [32] Integration of bioinformatics analysis to identify possible hub genes and important pathways associated with clear cell renal cell carcinoma
    Kumar, Anshu
    Yadav, Ravi Prakash
    Chatterjee, Srilagna
    Das, Madhusudan
    Pal, Dilip Kumar
    UROLOGIA JOURNAL, 2024, 91 (02) : 261 - 269
  • [33] Weighted gene co-expression network analysis identified cell cycle signaling pathway associated hub genes correlated with progression and prognosis of multiple myeloma
    Adebayo, Olayinka O.
    Griffen, Tiara
    Young, Corey
    Dammer, Eric
    Lillard, James W.
    CANCER RESEARCH, 2020, 80 (16)
  • [34] Genes associated with inflammation for prognosis prediction for clear cell renal cell carcinoma: a multi-database analysis
    Xiao, Yonggui
    Jiang, Chonghao
    Li, Hubo
    Xu, Danping
    Liu, Jinzheng
    Huili, Youlong
    Nie, Shiwen
    Guan, Xiaohai
    Cao, Fenghong
    TRANSLATIONAL CANCER RESEARCH, 2023, 12 (10) : 2629 - 2645
  • [35] Using weighted gene co-expression network analysis to identify key modules and hub genes in tongue squamous cell carcinoma
    Yin, Ke
    Zhang, Ying
    Zhang, Suxin
    Bao, Yang
    Guo, Jie
    Zhang, Guanhua
    Li, Tianke
    MEDICINE, 2019, 98 (37)
  • [36] Signaling Pathways in Clear Cell Renal Cell Carcinoma and Candidate Drugs Unveiled through Transcriptomic Network Analysis of Hub Genes
    Suratos, Khyle S.
    Orda, Marco A.
    Tsai, Po-Wei
    Tayo, Lemmuel L.
    APPLIED SCIENCES-BASEL, 2024, 14 (19):
  • [37] Gene Expression Microarray Data Meta-Analysis Identifies Candidate Genes and Molecular Mechanism Associated with Clear Cell Renal Cell Carcinoma
    Wang, Ying
    Wei, Haibin
    Song, Lizhi
    Xu, Lu
    Bao, Jingyao
    Liu, Jiang
    CELL JOURNAL, 2020, 22 (03) : 386 - 393
  • [38] Identification and validation of key modules and hub genes associated with the pathological stage of oral squamous cell carcinoma by weighted gene co-expression network analysis
    Hu, Xuegang
    Sun, Guanwen
    Shi, Zhiqiang
    Ni, Hui
    Jiang, Shan
    PEERJ, 2020, 8
  • [39] Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis
    Darvish, Zeinab
    Ghanbari, Saeed
    Afshar, Saeid
    Tapak, Leili
    Amini, Payam
    CELL JOURNAL, 2023, 25 (06) : 418 - 426
  • [40] Identification of hub genes and pathways associated with retinoblastoma based on co-expression network analysis
    Wang, Q. L.
    Chen, X.
    Zhang, M. H.
    Shen, Q. H.
    Qin, Z. M.
    GENETICS AND MOLECULAR RESEARCH, 2015, 14 (04): : 16151 - 16161