Identification of Glycolysis-Related Gene Signature and Prediction on Prognosis of Colon Cancer

被引:0
|
作者
Ran, Qingsen [1 ,2 ]
Li, Manjing [3 ]
Han, Jiayin [3 ]
Wang, Lifang [3 ]
Wang, Han [3 ,4 ]
Liu, Shaobo [5 ]
Wang, Yanping [1 ]
机构
[1] China Acad Chinese Med Sci, Inst Basic Res Clin Med, Beijing 100700, Peoples R China
[2] China Acad Chinese Med Sci, Postdoctoral Res Stn, Beijing 100700, Peoples R China
[3] China Acad Chinese Med Sci, Inst Chinese Mat Med, Beijing 100700, Peoples R China
[4] Changchun Univ Chinese Med, Affiliated Hosp, Changchun 130021, Peoples R China
[5] Guizhou Med Univ, Sch Pharmaceut Sci, Key Lab Optimal Utilizat Nat Med Resources, Guiyang 550025, Peoples R China
关键词
Colon cancer; Glycolysis; Biomarkers; Metabolic signature; Prognosis Judgment; Risk score model; EXOSOMAL GLYPICAN-1; METABOLISM; STANNIOCALCIN-1; PROGRESSION; PKM2;
D O I
10.17582/journal.pjz/20211124031155
中图分类号
Q95 [动物学];
学科分类号
071002 ;
摘要
Identification of core biomarkers for cancer prevention and treatment is crucial. Tumor glycolysis is an important metabolic phenotype and many natural compounds from medicinal plants exhibit antiglycation effects. Therefore, it is of potential significant to find biomarkers based on glycolysis-related genes in predicting the prognosis of colon cancer (CC), a common invasive gastrointestinal tumor. In this study, clinical and gene data were collected to identify glycolytic genes that significantly associated with overall survival (OS) rate of CC patients through gene set enrichment analysis (GSEA) and Cox regression models. The K -M method was used to determine the difference of OS rate with high and low risk scores. The accuracy of risk scores were determined based on receiver operating characteristic (ROC) curve. Hierarchical analysis and Cox regression were performed to assess the correlation between CC risk score and clinical symptoms. Moreover, qPCR was used to verify the expression level of prognostic genes in human colorectal cancer cell line (HCT116) and human colorectal epithelial cells (FHC cells). The results showed 202 glycolytic genes were found with statistical differences, and 4 glycolytic genes were identified, including Enolase 3 (ENO3), glypican-1 (GPC1), Nucleolar Protein 3 (NOL3) and Stanniocalcin 2 (STC2). A prognostic risk score model was established, and the OS rate of high -risk patients was found significantly reduced (p <0.001) compared to low-risk patients. The 5 -year OS ROC area under curve (AUC) of the model was 0.75. qPCR results confirmed that glycolysis-related genes ENO3, GPC1, NOL3 and STC2 were significantly upregulated in HCT116 cells compared to FHC cells. In conclusion, our study identified four glycolytic genes that significant impact prognosis of CC, and established a prognostic risk prediction model, which can provide reference for prognosis assessment and efficient treatment in CC.
引用
收藏
页码:263 / 272
页数:10
相关论文
共 50 条
  • [31] Identification and Validation of the Glycolysis and Immune- related Gene Signature for Prognosis in Colorectal Cancer
    Jiang, Min
    Liu, Yong
    Xu, Jianzhong
    Xu, Zhen
    Ye, Tao
    Li, Shiyang
    Jiang, Chunying
    ANTICANCER RESEARCH, 2024, 44 (01) : 117 - 131
  • [32] A Novel Ferroptosis Related Gene Signature for Prognosis Prediction in Patients With Colon Cancer
    Nie, Jianhua
    Shan, Dan
    Li, Shun
    Zhang, Shuyuan
    Zi, Xiaolin
    Xing, Fan
    Shi, Jiaqi
    Liu, Caiqi
    Wang, Tianjiao
    Sun, Xiaoyuan
    Zhang, Qian
    Zhou, Meng
    Luo, Shengnan
    Meng, Hongxue
    Zhang, Yanqiao
    Zheng, Tongsen
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [33] Identification of glycolysis-related gene signatures for prognosis and therapeutic targeting in idiopathic pulmonary fibrosis
    Gao, Han
    Sun, Zhongyi
    Hu, Xingxing
    Song, Weiwei
    Liu, Yuan
    Zou, Menglin
    Zhu, Minghui
    Cheng, Zhenshun
    FRONTIERS IN PHARMACOLOGY, 2025, 16
  • [34] Identification of a Novel Glycolysis-Related Gene Signature Correlates With the Prognosis and Therapeutic Responses in Patients With Clear Cell Renal Cell Carcinoma
    Lv, Zhengtong
    Qi, Lin
    Hu, Xiheng
    Mo, Miao
    Jiang, Huichuan
    Li, Yuan
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [35] The effect of a novel glycolysis-related gene signature on progression, prognosis and immune microenvironment of renal cell carcinoma
    Fangshi Xu
    Yibing Guan
    Li Xue
    Shanlong Huang
    Ke Gao
    Zhen Yang
    Tie Chong
    BMC Cancer, 20
  • [36] Comprehensive Analysis of the Glycolysis-Related Gene Prognostic Signature and Immune Infiltration in Endometrial Cancer
    Yang, Xiao
    Li, Xingchen
    Cheng, Yuan
    Zhou, Jingyi
    Shen, Boqiang
    Zhao, Lijun
    Wang, Jianliu
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2022, 9
  • [37] Identification of a novel glycolysis-related gene signature that can predict the survival of patients with lung adenocarcinoma
    Liu, Chang
    Li, Yinyan
    Wei, Minjie
    Zhao, Lin
    Yu, Yangyang
    Li, Guang
    CELL CYCLE, 2019, 18 (05) : 568 - 579
  • [38] A Novel Glycolysis-Related Signature for Predicting the Prognosis and Immune Infiltration of Uveal Melanoma
    Guo, Xiaoyu
    Yu, Xin
    Zhang, Yuying
    Luo, Huijuan
    Huang, Rong
    Zeng, Yuyang
    Duan, Chaoye
    Chen, Changzheng
    OPHTHALMIC RESEARCH, 2023, 66 (01) : 692 - 705
  • [39] Identification of a novel glycolysis-related gene signature for predicting metastasis and survival in patients with lung adenocarcinoma
    Zhang, Lei
    Zhang, Zhe
    Yu, Zhenglun
    JOURNAL OF TRANSLATIONAL MEDICINE, 2019, 17 (01)
  • [40] Identification of a novel glycolysis-related gene signature for predicting metastasis and survival in patients with lung adenocarcinoma
    Lei Zhang
    Zhe Zhang
    Zhenglun Yu
    Journal of Translational Medicine, 17