Abstract
BackgroundColorectal cancer (CRC) is one of the most common malignant tumors. In the present study, the expression profile of human multistage colorectal mucosa tissues, including healthy, adenoma, and adenocarcinoma samples was downloaded to identify critical genes and potential drugs in CRC.MethodsExpression profiles, GSE33113 and GSE44076, were integrated using bioinformatics methods. Differentially expressed genes (DEGs) were analyzed by R language. Functional enrichment analyses of the DEGs were performed using the Database for Annotation, visualization, and integrated discovery (DAVID) database. Then, the search tool for the retrieval of interacting genes (STRING) database and Cytoscape were used to construct a protein–protein interaction (PPI) network and identify hub genes. Subsequently, survival analysis was performed among the key genes using Gene Expression Profiling Interactive Analysis (GEPIA). Connectivity Map (CMap) was used to query potential drugs for CRC.ResultsA total of 428 upregulated genes and 751 downregulated genes in CRC were identified. The functional changes of these DEGs were mainly associated with cell cycle, oocyte meiosis, DNA replication, p53 signaling pathway, and progesterone‐mediated oocyte maturation. A PPI network was identified by STRING with 482 nodes and 2,368 edges. Survival analysis revealed that high mRNA expression of AURKA, CCNB1, CCNF, and EXO1 was significantly associated with longer overall survival. Moreover, CMap predicted a panel of small molecules as possible adjuvant drugs to treat CRC.ConclusionOur study found key dysregulated genes involved in CRC and potential drugs to combat it, which may provide novel insights and potential biomarkers for prognosis, as well as providing new CRC treatments.
Highlights
Colorectal cancer (CRC) is one of the most common cancers with high morbidity worldwide
It is similar to the Saccharomyces cerevisiae protein Exo1 which interacts with Msh2 and which is involved in mismatch repair and recombination
AURKA, CCNB1, CCNF, and EXO1 were significantly upregulated in CRC compared with normal samples, and in CRC patients, the survival rate was positively correlated with the high expression of these genes
Summary
Colorectal cancer (CRC) is one of the most common cancers with high morbidity worldwide. Several studies have used gene expression profiling to identify key genes between CRC samples and normal samples. Yang, and Huang (2018) identified hundreds of CRC associated differentially expressed genes (DEGs) based on the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. We selected the following microarray datasets GSE33113 (de Sousa et al, 2011; Kemper et al.., 2012) and GSE44076 (Closa et al, 2014; Cordero et al, 2014; Sanz‐Pamplona et al, 2014; Solé et al, 2014) from the GEO database to identify DEGs. Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) pathway analysis were used to investigate DEGs. we identified hub genes from the common DEGs by constructing protein–protein interaction (PPI) network. Candidate small molecules were identified for their potential use in the treatment of CRC
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