Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis
- Chang Yu
- Fuqiang Chen
- Jianjun Jiang
- Hong Zhang
- Meijuan Zhou
Affiliations: Department of Radiation Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China, Department of Thoracic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P.R. China, The First Affiliated Hospital, University of Science and Technology of China, Hefei, Anhui 230026, P.R. China
- Published online on: June 4, 2019 https://doi.org/10.3892/mmr.2019.10336
Copyright: © Yu
et al. This is an open access article distributed under the
terms of Creative
Commons Attribution License.
Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )
This article is mentioned in:
The aim of the present study was to identify potential key genes associated with the progression and prognosis of colorectal cancer (CRC). Differentially expressed genes (DEGs) between CRC and normal samples were screened by integrated analysis of gene expression profile datasets, including the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to identify the biological role of DEGs. In addition, a protein‑protein interaction network and survival analysis were used to identify the key genes. The profiles of GSE9348, GSE22598 and GSE113513 were downloaded from the GEO database. A total of 405 common DEGs were identified, including 236 down‑ and 169 upregulated. GO analysis revealed that the downregulated DEGs were mainly enriched in ‘detoxification of copper ion’ [biological process, (BP)], ‘oxidoreductase activity, acting on CH‑OH group of donors, NAD or NADP as acceptor’ [molecular function, (MF)] and ‘brush border’ [cellular component, (CC)]. Upregulated DEGs were mainly involved in ‘nuclear division’ (BP), ‘snoRNA binding’ (MF) and ‘nucleolar part’ (CC). KEGG pathway analysis revealed that DEGs were mainly involved in ‘mineral absorption’, ‘nitrogen metabolism’, ‘cell cycle’ and ‘caffeine metabolism’. A PPI network was constructed with 268 nodes and 1,027 edges. The top one module was selected, and it was revealed that module‑related genes were mainly enriched in the GO terms ‘sister chromatid segregation’ (BP), ‘chemokine activity’ (MF), and ‘condensed chromosome (CC)’. The KEGG pathway was mainly enriched in ‘cell cycle’, ‘progesterone‑mediated oocyte maturation’, ‘chemokine signaling pathway’, ‘IL‑17 signaling pathway’, ‘legionellosis’, and ‘rheumatoid arthritis’. DNA topoisomerase II‑α (TOP2A), mitotic arrest deficient 2 like 1 (MAD2L1), cyclin B1 (CCNB1), checkpoint kinase 1 (CHEK1), cell division cycle 6 (CDC6) and ubiquitin conjugating enzyme E2 C (UBE2C) were indicated as hub genes. Furthermore, survival analysis revealed that TOP2A, MAD2L1, CDC6 and CHEK1 may serve as prognostic biomarkers in CRC. The present study provided insights into the molecular mechanism of CRC that may be useful in further investigations.