Journal of Radiation Research and Radiation Processing ›› 2020, Vol. 38 ›› Issue (1): 32-41.doi: 10.11889/j.1000-3436.2020.rrj.38.010302

• RADIOBIOLOGY AND RADIOMEDICINE • Previous Articles     Next Articles

Bioinformatic analysis of differentially expressed genes in tumor-associated fibroblasts after ionizing radiation

YANG Yuhong1,LI Na2,3()   

  1. 1. Department of Basic Medicine, Yongzhou Vocational Technical College, Yongzhou 425100, China
    2. Department of Pathology, the First Affiliated Hospital of Hunan University of Medicine, Huaihua 418000, China
    3. Hunan Provincial Key Laboratory of Dong Medicine, Hunan University of Medicine, Huaihua 418000, China
  • Received:2019-07-06 Revised:2019-09-09 Accepted:2019-09-09 Online:2020-02-20 Published:2020-02-25
  • Contact: LI Na E-mail:magic5909@163.com
  • About author:YANG Yuhong (female) was born in October 1984, and obtained her master’s degree from University of South China in 2015, lecturer
  • Supported by:
    Natural Science Foundation of Hunan Province(2019JJ50425);Project of Hunan Provincial Science and Technology Department(2018SK4006);General Project of Hunan Provincial Education Department(18C1129)

Abstract:

Tumor-associated fibroblast gene expression microarray data were obtained from the GEO database (GSE37318). Data were screened for differentially expressed genes using GEO2R software. GO and KEGG pathways were analyzed using the DAVID tool. A protein-protein interaction network was then constructed, and hub genes were identified using Cytoscape software. Prognostic value analysis of hub genes was performed using GEPIA. A total of 144 up-regulated genes and 54 down-regulated genes were identified from the dataset GSE37318. These were mainly expressed during cell stress, DNA damage, cell cycle, senescence, apoptosis, oxidative stress, and in the p53 signaling pathway. A protein-protein interaction network consisting of 103 nodes and 376 edges was constructed, and the top 20 hub genes were identified. Of the top 10 hub genes, low expression levels of eight genes including MCM10, DLGAP5, FANCI, CENPA, CDC6, FBXO5, NCAPG, and DTL were related to poor overall survival (OS) in lung cancer patients (p<0.05). However, high levels of PCNA expression were also associated with poor OS in lung cancer patients (p<0.05). Ionizing radiation may induce both up- and down-regulation of genes in tumor-associated fibroblasts. These differentially expressed genes provide potential molecular markers for evaluating the efficacy of tumor radiotherapy, patient prognosis, risk of recurrence, and metastasis.

Key words: Ionizing radiation, Tumor, Fibroblast, Differential expression, Gene, Bioinformatics

CLC Number: 

  • R818