Research Paper Volume 16, Issue 8 pp 7022—7042
Mining and exploration of rehabilitation nursing targets for colorectal cancer
- 1 Gastrointestinal Rehabilitation Center, Beijing Rehabilitation Hospital Affiliated to Capital Medical University, Shijingshan 100144, Beijing, China
- 2 Department of Colorectal Surgery, China Aerospace Science and Industry Corporation 731 Hospital, Fengtai, Beijing, China
Received: September 28, 2023 Accepted: November 20, 2023 Published: April 16, 2024
https://doi.org/10.18632/aging.205739How to Cite
Copyright: © 2024 He et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: There are often subtle early symptoms of colorectal cancer, a common malignancy of the intestinal tract. However, it is not yet clear how MYC and NCAPG2 are involved in colorectal cancer.
Method: We obtained colorectal cancer datasets GSE32323 and GSE113513 from the Gene Expression Omnibus (GEO). After downloading, we identified differentially expressed genes (DEGs) and performed Weighted Gene Co-expression Network Analysis (WGCNA). We then undertook functional enrichment assay, gene set enrichment assay (GSEA) and immune infiltration assay. Protein-protein interaction (PPI) network construction and analysis were undertaken. Survival analysis and Comparative Toxicogenomics Database (CTD) analysis were conducted. A gene expression heat map was generated. We used TargetScan to identify miRNAs that are regulators of DEGs.
Results: 1117 DEGs were identified. Their predominant enrichment in activities like the cellular phase of the cell cycle, in cell proliferation, in nuclear and cytoplasmic localisation and in binding to protein-containing complexes was revealed by Gene Ontology (GO). When the enrichment data from GSE32323 and GSE113513 colon cancer datasets were merged, the primary enriched DEGs were linked to the cell cycle, protein complex, cell cycle control, calcium signalling and P53 signalling pathways. In particular, MYC, MAD2L1, CENPF, UBE2C, NUF2 and NCAPG2 were identified as highly expressed in colorectal cancer samples. Comparative Toxicogenomics Database (CTD) demonstrated that the core genes were implicated in the following processes: colorectal neoplasia, tumour cell transformation, inflammation and necrosis.
Conclusions: High MYC and NCAPG2 expression has been observed in colorectal cancer, and increased MYC and NCAPG2 expression correlates with worse prognosis.
Abbreviations
CRC: Colorectal cancer; GEO: Gene Expression Omnibus; DEGs: differentially expressed genes; WGCNA: weighted gene co-expression network analysis; GSEA: gene set enrichment analysis; PPI: protein-protein interactions; CTD: Comparative Toxicogenomics Database; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; FC: Fold change; FDR: false discovery rate; MAD: Median Absolute Deviation; STRING: Search Tool for the Retrieval of Interacting Genes; TCGA: The Cancer Genome Atlas; ROC: receiver operating characteristic; AUC: area under the curve; NCAPG2: Non-SMC Condensin II Complex Subunit G2.