EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma

被引:2
|
作者
Gao X. [1 ]
Yang C. [1 ,2 ,3 ]
Li H. [1 ,2 ,3 ,4 ]
Shao L. [1 ,2 ,4 ]
Wang M. [1 ,2 ,3 ]
Su R. [1 ]
机构
[1] The First Clinical Medical College, Gansu University of Chinese Medicine, Gansu, Lanzhou
[2] Department of Geriatrics, Affiliated Hospital of Gansu University of Chinese Medicine, Gansu, Lanzhou
[3] Key Laboratory of Traditional Chinese Herbs and Prescription Innovation and Transformation of Gansu Province and Gansu Provincial Traditional Chinese Medicine New Product Innovation Engineering Laboratory, Gansu University of Chinese Medicine, Gansu, Lanzh
[4] Key Laboratory of Dunhuang Medicine and Transformation, Ministry of Education, Gansu University of Chinese Medicine, Gansu, Lanzhou
关键词
D O I
10.1038/s41598-023-47886-z
中图分类号
学科分类号
摘要
This study was designed to evaluate the prognosis and pharmacological therapy sensitivity of epithelial mesenchymal transition-related genes (EMTRGs) that obtained from the EMTome database in hepatocellular carcinoma (HCC) using bioinformatical method. The expression status of EMTRGs were also investigated using the clinical information of HCC patients supported by TCGA database and the ICGC database to establish the TCGA cohort as the training set and the ICGC cohort as the validation set. Analyze the EMTRGs between HCC tissue and liver tissue in the TCGA cohort in the order of univariate COX regression, LASSO regression, and multivariate COX regression, and construct a risk model for EMTRGs. In addition, enrichment pathways, gene mutation status, immune infiltration, and response to drugs were also analyzed in the high-risk and low-risk groups of the TCGA cohort, and the protein expression status of EMTRGs was verified. The results showed a total of 286 differentially expressed EMTRGs in the TCGA cohort, and EZH2, S100A9, TNFRSF11B, SPINK5, and CCL21 were used for modeling. The TCGA cohort was found to have a worse outcome in the high-risk group of HCC patients, and the ICGC cohort confirmed this finding. In addition, EMTRGs risk score was shown to be an independent prognostic factor in both cohorts by univariate and multivariate COX regression. The results of GSEA analysis showed that most of the enriched pathways in the high-risk group were associated with tumor, and the pathways enriched in the low-risk group were mainly associated with metabolism. Patients in various risk groups had varying immunological conditions, and the high-risk group might benefit more from targeted treatments. To sum up, the EMTRGs risk model was developed to forecast the prognosis for HCC patients, and the model might be useful in assisting in the choice of treatment drugs for HCC patients. © 2023, The Author(s).
引用
收藏
相关论文
共 50 条
  • [31] Prediction model establishment of prognosis factors for distant metastasis of hepatocellular carcinoma based on the SEER database
    Wu, Jixuan
    Zhang, Chun
    Zhang, Youjia
    He, Rui
    Wang, Qin
    Zhang, Lei
    Hu, Jing
    Wan, Runlan
    CANCER EPIDEMIOLOGY, 2025, 94
  • [32] A Mitophagy-Related Gene Signature for Subtype Identification and Prognosis Prediction of Hepatocellular Carcinoma
    Liu, Chang
    Wu, Zhen
    Wang, Liping
    Yang, Qian
    Huang, Ji
    Huang, Jichang
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2022, 23 (20)
  • [33] A hypoxia-glycolysis-lactate-related gene signature for prognosis prediction in hepatocellular carcinoma
    Qin, Xiaodan
    Sun, Huiling
    Hu, Shangshang
    Pan, Yuqin
    Wang, Shukui
    BMC MEDICAL GENOMICS, 2024, 17 (01)
  • [34] Prediction of hepatocellular carcinoma prognosis based on expression of an immune-related gene set
    He, Yuting
    Dang, Qin
    Li, Jie
    Zhang, Qiyao
    Yu, Xiao
    Xue, Miaomiao
    Guo, Wenzhi
    AGING-US, 2020, 12 (01): : 965 - 977
  • [35] Construction of immune-related risk model for prognosis of hepatocellular carcinoma.
    Li, Yue
    Xu, Ximing
    JOURNAL OF CLINICAL ONCOLOGY, 2020, 38 (15)
  • [36] A New Inflammation-Related Risk Model for Predicting Hepatocellular Carcinoma Prognosis
    Xing, Mindan
    Li, Jia
    BIOMED RESEARCH INTERNATIONAL, 2022, 2022
  • [37] Establishment and validation of a risk prediction model in patients with hepatocellular carcinoma treated with transarterial radioembolization
    Lee, Jae Seung
    Lee, Han Ah
    Jeon, Mi Young
    Lim, Tae Seop
    Kim, Beom Kyung
    Park, Jun Yong
    Kim, Young
    Ahn, Sang Hoon
    Um, Soon Ho
    Han, Kwang-Hyub
    Seo, Yeon Seok
    Kim, Seung Up
    EUROPEAN JOURNAL OF GASTROENTEROLOGY & HEPATOLOGY, 2020, 32 (06) : 739 - 747
  • [38] An exosome mRNA-related gene risk model to evaluate the tumor microenvironment and predict prognosis in hepatocellular carcinoma
    Du, Zhonghai
    Han, Xiuchen
    Zhu, Liping
    Li, Li
    Castellano, Leandro
    Stebbing, Justin
    Peng, Ling
    Wang, Zhiqiang
    BMC MEDICAL GENOMICS, 2024, 17 (01)
  • [39] An immune-related signature for optimizing prognosis prediction and treatment decision of hepatocellular carcinoma
    Yao, Ninghua
    Jiang, Wei
    Wang, Yilang
    Song, Qianqian
    Cao, Xiaolei
    Zheng, Wenjie
    Zhang, Jie
    EUROPEAN JOURNAL OF MEDICAL RESEARCH, 2023, 28 (01)
  • [40] An immune-related signature for optimizing prognosis prediction and treatment decision of hepatocellular carcinoma
    Ninghua Yao
    Wei Jiang
    Yilang Wang
    Qianqian Song
    Xiaolei Cao
    Wenjie Zheng
    Jie Zhang
    European Journal of Medical Research, 28