Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database

被引:11
|
作者
Wang, Guanglin [1 ]
Wang, Feifei [1 ]
Meng, Zesong [1 ]
Wang, Na [2 ]
Zhou, Chaoxi [1 ]
Zhang, Juan [1 ]
Zhao, Lianmei [3 ]
Wang, Guiying [1 ,4 ]
Shan, Baoen [3 ]
机构
[1] Hebei Med Univ, Hosp 4, Dept Surg 2, Shijiazhuang, Hebei, Peoples R China
[2] Hebei Med Univ, Hosp 4, Inst Tumor, Shijiazhuang, Hebei, Peoples R China
[3] Hebei Med Univ, Hosp 4, Sci Res Ctr, 12 Jiankang Rd, Shijiazhuang 050010, Hebei, Peoples R China
[4] Hebei Med Univ, Hosp 3, Dept Gen Surg, Shijiazhuang, Hebei, Peoples R China
关键词
Colorectal cancer; Differentially expressed genes; Differentially methylated genes; Diagnosis; Prognosis; CELLULAR-TRANSFORMATION; UP-REGULATION; COLON-CANCER; TUMOR; CLAUDIN-1; PROLIFERATION; IDENTIFICATION; METASTASIS; MIGRATION; PATHWAYS;
D O I
10.1186/s12885-022-09185-0
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background Colorectal cancer (CRC) is major cancer-related death. The aim of this study was to identify differentially expressed and differentially methylated genes, contributing to explore the molecular mechanism of CRC. Methods Firstly, the data of gene transcriptome and genome-wide DNA methylation expression were downloaded from the Gene Expression Omnibus database. Secondly, functional analysis of differentially expressed and differentially methylated genes was performed, followed by protein-protein interaction (PPI) analysis. Thirdly, the Cancer Genome Atlas (TCGA) dataset and in vitro experiment was used to validate the expression of selected differentially expressed and differentially methylated genes. Finally, diagnosis and prognosis analysis of selected differentially expressed and differentially methylated genes was performed. Results Up to 1958 differentially expressed (1025 up-regulated and 993 down-regulated) genes and 858 differentially methylated (800 hypermethylated and 58 hypomethylated) genes were identified. Interestingly, some genes, such as GFRA2 and MDFI, were differentially expressed-methylated genes. Purine metabolism (involved IMPDH1), cell adhesion molecules and PI3K-Akt signaling pathway were significantly enriched signaling pathways. GFRA2, FOXQ1, CDH3, CLDN1, SCGN, BEST4, CXCL12, CA7, SHMT2, TRIP13, MDFI and IMPDH1 had a diagnostic value for CRC. In addition, BEST4, SHMT2 and TRIP13 were significantly associated with patients' survival. Conclusions The identified altered genes may be involved in tumorigenesis of CRC. In addition, BEST4, SHMT2 and TRIP13 may be considered as diagnosis and prognostic biomarkers for CRC patients.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database
    Guanglin Wang
    Feifei Wang
    Zesong Meng
    Na Wang
    Chaoxi Zhou
    Juan Zhang
    Lianmei Zhao
    Guiying Wang
    Baoen Shan
    [J]. BMC Cancer, 22
  • [2] Uncovering the Potential Differentially Expressed miRNAs and mRNAs in Ischemic Stroke Based on Integrated Analysis in the Gene Expression Omnibus Database
    Zhu, Xiaotun
    Liu, Xiao
    Liu, Ying
    Chang, Wansheng
    Song, Yanfeng
    Zhu, Shulai
    [J]. EUROPEAN NEUROLOGY, 2020, 83 (04) : 404 - 414
  • [3] Discovery of Key Genes in Dermatomyositis Based on the Gene Expression Omnibus Database
    Xie, Shuoshan
    Luo, Hui
    Zhang, Huali
    Zhu, Honglin
    Zuo, Xiaoxia
    Liu, Sijia
    [J]. DNA AND CELL BIOLOGY, 2018, 37 (12) : 982 - 992
  • [4] Identification of pathogenic genes of pterygium based on the Gene Expression Omnibus database
    Xiao-Li Yue
    Zi-Qing Gao
    [J]. International Journal of Ophthalmology, 2019, (04) : 529 - 535
  • [5] Identification of potential key genes linked to gender differences in bladder cancer based on gene expression omnibus (GEO) database
    Rasti, Azam
    Abazari, Omid
    Dayati, Parisa
    Kardan, Zahra
    Salari, Ali
    Khalili, Masoud
    Motlagh, Fatemeh
    Modarressi, Mohammad
    [J]. ADVANCED BIOMEDICAL RESEARCH, 2023, 12 (01): : 157
  • [6] Identification of pathogenic genes of pterygium based on the Gene Expression Omnibus database
    Yue, Xiao-Li
    Gao, Zi-Qing
    [J]. INTERNATIONAL JOURNAL OF OPHTHALMOLOGY, 2019, 12 (04) : 529 - 535
  • [7] Integrated Analysis of Hub Genes and Pathways In Esophageal Carcinoma Based on NCBI's Gene Expression Omnibus (GEO) Database: A Bioinformatics Analysis
    Tan Yu-jing
    Tang Wen-jing
    Tang Biao
    [J]. MEDICAL SCIENCE MONITOR, 2020, 26
  • [8] Seeking for potential pathogenic genes of major depressive disorder in the Gene Expression Omnibus database
    Feng, Jianfei
    Zhou, Qing
    Gao, Wenquan
    Wu, Yanying
    Mu, Ruibin
    [J]. ASIA-PACIFIC PSYCHIATRY, 2020, 12 (01)
  • [9] Identification of key pathogenic genes of sepsis based on the Gene Expression Omnibus database
    Lu, Xinxing
    Xue, Lu
    Sun, Wenbin
    Ye, Jilu
    Zhu, Zhiyun
    Mei, Haifeng
    [J]. MOLECULAR MEDICINE REPORTS, 2018, 17 (02) : 3042 - 3054
  • [10] Integrated analysis of gene expression and DNA methylation profiles in ovarian cancer
    Gong, Guanghui
    Lin, Ting
    Yuan, Yishu
    [J]. JOURNAL OF OVARIAN RESEARCH, 2020, 13 (01)