Screening of the shared pathogenic genes of ulcerative colitis and colorectal cancer by integrated bioinformatics analysis

Xu Shi; Jun Yu; Chen Lu; Qian Luo; Caihong Xu; Jie Li; Wei Wang

doi:10.1111/jcmm.17878

Screening of the shared pathogenic genes of ulcerative colitis and colorectal cancer by integrated bioinformatics analysis

J Cell Mol Med. 2023 Jul 26;28(5):e17878. doi: 10.1111/jcmm.17878. Online ahead of print.

Authors

Xu Shi¹, Jun Yu², Chen Lu³, Qian Luo³, Caihong Xu⁴, Jie Li³, Wei Wang⁵

Affiliations

¹ Department of Orthopaedics, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
² Department of Paediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Taicang Hospital of Traditional Chinese Medicine, Taicang, China.
³ Department of General Surgery, Siyang Hospital, Suqian, China.
⁴ Department of Obstetrics and Gynaecology, Nanjing Tongren Hospital, School of Medicine, Southeast University, Nanjing, China.
⁵ Department of Clinical Laboratory, Lianshui County People's Hospital, Huai'an, China.

Abstract

Ulcerative colitis (UC) is one of the high-risk pathogenic factors for colorectal cancer (CRC). However, the shared gene and signalling mechanisms between UC and CRC remain unclear. The goal of this study was to delve more into the probable causal relationship between UC and CRC. CRC and UC datasets were downloaded from the Gene Expression Omnibus database. Using R software and Perl, differentially expressed genes (DEGs) in both UC and CRC tissues were re-annotated and screened. The biological activities and signalling pathways involved in DEGs were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. The STRING database and Cytoscape software were used to construct the gene interaction network. A total of 384 DEGs were selected for further investigation, and functional analysis revealed that inflammatory and immunological responses were crucial in the development of the two diseases. Moreover, the top 15 key genes involved in the UC and CRC were screened using cytoHubba, including IL1B, CXCL10, CCL20, MMP9, ICAM1, CCL4, CXCR1, MMP3, TLR2, PTGS2, IL1RN, IL6, COL1A2, TIMP1 and CXCL1. The identification of these genes in the present study may provide a novel perspective for the prediction, prevention and personalized medicine of UC and CRC patients.

Keywords: colorectal cancer; immune-related genes; integrated bioinformatics analysis; machine learning; the shared pathogenic genes; ulcerative colitis.