Identification of biomarkers for the diagnosis and treatment of primary colorectal cancer based on microarray technology

Zhi Gang Zheng; Bao Qing Ma; Yu Xiao; Tian Xi Wang; Tian Yu; Yu Hu Huo; Qing Qing Wang; Meng Jie Shan; Ling Bing Meng; Jing Han

doi:10.21037/tcr-19-2290

Identification of biomarkers for the diagnosis and treatment of primary colorectal cancer based on microarray technology

Transl Cancer Res. 2020 May;9(5):3453-3467. doi: 10.21037/tcr-19-2290.

Authors

Zhi Gang Zheng¹, Bao Qing Ma², Yu Xiao³, Tian Xi Wang⁴, Tian Yu⁵, Yu Hu Huo⁶, Qing Qing Wang⁷, Meng Jie Shan⁸, Ling Bing Meng⁹, Jing Han¹⁰

Affiliations

¹ The First Ward of the General Surgery Department, The First Hospital of Shijiazhuang, Shijiazhuang 050011, China.
² Department of Gastrointestinal Surgery, Dezhou People's Hospital, Dezhou 253000, China.
³ School of Basic Medicine, Peking University, Beijing 100191, China.
⁴ School of Artificial Intelligence, Hebei University of Technology, Tianjin 300401, China.
⁵ Department of Surgery, Beijing Hospital, National Center of Gerontology, Beijing 100730, China.
⁶ Department of Breast and Thyroid Surgery, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.
⁷ Department of Biotherapy, Tianjin Medical University Cancer Institute, and Hospital, Tianjin 300060, China.
⁸ Graduate School, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
⁹ Neurology Department, Beijing Hospital, National Center of Gerontology, Beijing 100730, China.
¹⁰ Department of Medical Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang 050000, China.

Abstract

Background: Primary colorectal cancer (PCRC) is one of the most common malignant tumors in clinic, and is characterized by high heterogeneity occurring between tumors and intracellularly. Therefore, this study aimed to explore potential gene targets for the diagnosis and treatment of PCRC via bioinformatic technology.

Methods: Gene Expression Omnibus (GEO) was used to download the data used in this study. Differently expressed genes (DEGs) were identified with GEO2R, and the gene set enrichment analysis (GSEA) was implemented for enrichment analysis. Then, the researchers constructed a protein-protein interaction (PPI) network, a significant module, and a hub genes network.

Results: The GSE81558 dataset was downloaded, and a total of 97 DEGs were found. There were 23 up-regulated DEGs and 74 down-regulated DEGs in the PCRC samples, compared with the control group. The PPI network included a total of 42 nodes and 63 edges. One module network consisted of 11 nodes and 25 edges. Another module network consisted of 4 nodes and 6 edges. The hub genes network was created by cytoHubba using GCG, GUCA2B, CLCA4, ZG16, TMIGD1, GUCA2A, CHGA, PYY, SST, and MS4A12.

Conclusions: Ten hub genes were found from the genomic samples of patients with PCRC and normal controls by bioinformatics analysis. The hub genes might provide novel ideas and evidence for the diagnosis and targeted therapy of PCRC.

Keywords: Primary colorectal cancer (PCRC); differentially expressed genes; gene set enrichment analysis (GSEA); hub genes.