Identification of potential biomarkers for nonsurvivor sepsis patients via microarray technology: A study based on GEO datasets

被引:0
|
作者
Ma, Yan [1 ]
Shan, Shichao [1 ]
Luo, Cheng [1 ]
Mo, Jianlan [1 ]
Hu, Zhaokun [2 ,3 ,4 ]
Jing, Ren [2 ,3 ,4 ]
机构
[1] Maternal & Child Hlth Hosp Guangxi Zhuang Autonomo, Dept Anesthesiol, Nanning, Peoples R China
[2] Guangxi Clin Res Ctr Anesthesiol, Nanning, Peoples R China
[3] Guangxi Med Univ, Dept Anesthesiol, Canc Hosp, He Di Rd 71, Nanning 530021, Peoples R China
[4] Guangxi Engn Res Ctr Tissue & Organ Injury & Repai, Nanning, Peoples R China
关键词
sepsis; nonsurvivor; biomarkers; hub genes; lipopolysaccharide-induced lung injury; EARLY-DIAGNOSIS; GENE; CONSTRUCTION; INFLAMMATION; CLASSIFIER; MEDIATORS; PROGNOSIS; MONOCYTES; AUTOPHAGY; PATHWAYS;
D O I
10.1177/1721727X231202661
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: The mechanism of sepsis especially non-survivors has not yet been identified. Objective: To identify the key genes concerned with non-survivor sepsis (NSS) and analyze its molecular mechanism. Methods: The original data were obtained from the GEO database to screen deferentially expressed genes (DEGs). GO and KEGG analysis were performed to analyze the functional annotation of DEGs. The protein-protein interaction (PPI) network and related analysis of hub genes were carried out. Further, hub genes were confirmed in the lipopolysaccharide (LPS)-induced septic mice by western blotting and immunohistochemistry. Results: We obtained 188 DEGs and 32 hub genes between NSS patients and healthy volunteers. Among of them, the top 10 hub genes including STAT1, ISG15, HERC1, EIF2AK2, RPL27, LY6E, IFI44L, XAF1, RSAD2 and HERC6 were studied, which predict sepsis based on receiver operator characteristic curve analysis. These hub genes were enriched in positive regulation of biomedical process including translation, response to virus and suppression of mitochondrial depolarization, etc.; cell component including mitochondrial inner membrane; molecular function containing ligase activity, etc. These hub genes are also enriched in influenza A infection and leukocyte trans-endothelial migration. The expression of these hub genes is better involved in a diagnosis of NSS, such as HERC6 (AUC = 0.9753, p = .0007), RPL27 (AUC = 0.9691, p = .0008), ISG15 (AUC = 0.9630, p = .0009), STAT1 (AUC = 0.9383, p = .0017), HERC1 (AUC = 0.9259, p = .0023), and XAF1 (AUC = 0.9259, p = .0023). Furthermore, 20 mg/kg of LPS injection up-regulated the expression of ISG15, RPL27, LY6E and HERC6 in the lung tissues compared with control mice. Conclusion: These identified 188 DEGs and 10 hub genes were associated with NSS, especially ISG15, RPL27, LY6E and HERC6 genes expressed in the lung as the most vulnerable organ.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Identification of potential biomarkers of leprosy: A study based on GEO datasets
    Zhou, Qun
    Shi, Ping
    Shi, Wei dong
    Gao, Jun
    Wu, Yi chen
    Wan, Jing
    Yan, Li li
    Zheng, Yi
    PLOS ONE, 2024, 19 (05):
  • [2] Identification of Potential Biomarkers for Thyroid Cancer Using Bioinformatics Strategy: A Study Based on GEO Datasets
    Shen, Yujie
    Dong, Shikun
    Liu, Jinhui
    Zhang, Liqing
    Zhang, Jiacheng
    Zhou, Han
    Dong, Weida
    BIOMED RESEARCH INTERNATIONAL, 2020, 2020
  • [3] The identification of new biomarkers for bladder cancer: A study based on TCGA and GEO datasets
    Hu, Junyi
    Zhou, Lijie
    Song, Zhengshuai
    Xiong, Ming
    Zhang, Youpeng
    Yang, Yu
    Chen, Ke
    Chen, Zhaohui
    JOURNAL OF CELLULAR PHYSIOLOGY, 2019, 234 (09) : 15607 - 15618
  • [4] Identification of potential biomarkers and immune infiltration in pediatric sepsis via multiple-microarray analysis
    Yao, Yinhui
    Zhao, Jingyi
    Hu, Junhui
    Song, Hong
    Wang, Sizhu
    Ying, Wang
    EUROPEAN JOURNAL OF INFLAMMATION, 2022, 20
  • [5] Identification of potential biomarkers for melanoma cancer (black tumor) using bioinformatics strategy: a study based on GEO and SRA datasets
    Tahani Ahmad ALMatrafi
    Zuhair M. Mohammedsaleh
    Mamdoh S. Moawadh
    Zaid Bassfar
    Mohammed M. Jalal
    Fatima Ahmed Badahdah
    Youssef S. Alghamdi
    Hassan Hussain Almasoudi
    Mohammed Ageeli Hakami
    Abdulkarim S. Binshaya
    Hailah M. Almohaimeed
    Mona H. Soliman
    Journal of Applied Genetics, 2024, 65 : 83 - 93
  • [6] Identification of potential biomarkers for melanoma cancer (black tumor) using bioinformatics strategy: a study based on GEO and SRA datasets
    Almatrafi, Tahani Ahmad
    Mohammedsaleh, Zuhair M.
    Moawadh, Mamdoh S.
    Bassfar, Zaid
    Jalal, Mohammed M.
    Badahdah, Fatima Ahmed
    Alghamdi, Youssef S.
    Almasoudi, Hassan Hussain
    Hakami, Mohammed Ageeli
    Binshaya, Abdulkarim S.
    Almohaimeed, Hailah M.
    Soliman, Mona H.
    JOURNAL OF APPLIED GENETICS, 2024, 65 (01) : 83 - 93
  • [7] Screening and identification of biomarkers for systemic sclerosis via microarray technology
    Xu, Chen
    Meng, Ling-Bing
    Duan, Yu-Chen
    Cheng, Yong-Jing
    Zhang, Chun-Mei
    Zhou, Xing
    Huang, Ci-Bo
    INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE, 2019, 44 (05) : 1753 - 1770
  • [8] Identification of Potential Biomarkers and Survival Analysis for Head and Neck Squamous Cell Carcinoma Using Bioinformatics Strategy: A Study Based on TCGA and GEO Datasets
    Shen, Yujie
    Liu, Jinhui
    Zhang, Liqing
    Dong, Shikun
    Zhang, Jiacheng
    Liu, Yaqin
    Zhou, Han
    Dong, Weida
    BIOMED RESEARCH INTERNATIONAL, 2019, 2019
  • [9] Identification of gastric cancer biomarkers through in-silico analysis of microarray based datasets
    Akhtar, Arbaz
    Hameed, Yasir
    Ejaz, Samina
    Abdullah, Iqra
    BIOCHEMISTRY AND BIOPHYSICS REPORTS, 2024, 40
  • [10] Identification of potential genes and miRNAs associated with sepsis based on microarray analysis
    Li, Yin
    Zhang, Fengxia
    Cong, Yan
    Zhao, Yun
    MOLECULAR MEDICINE REPORTS, 2018, 17 (05) : 6227 - 6234