Literature DB >> 33078282

Identification of candidate biomarkers and therapeutic drugs of colorectal cancer by integrated bioinformatics analysis.

Zhuoling Zheng1, Jingwen Xie1, Lixiong Xiong1, Min Gao1, Li Qin1, Chunmei Dai1, Zhikun Liang1, Yiting Wang1, Jing Xue1, Qinbo Wang1, Wenhui Wang2,3, Xiaoyan Li4.   

Abstract

Most colorectal cancer (CRC) patients are diagnosed with advanced stages and low prognosis. We aimed to identify potential diagnostic and prognostic biomarkers, as well as active small molecules of CRC. Microarray data (GSE9348, GSE35279, and GSE106582) were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified by the GEO2R platform. Common DEGs were selected for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Cytoscape software was used to construct protein-protein interaction networks and identify hub genes. Hub genes were evaluated by Kaplan-Meier survival analysis in the GEPIA database and validated in two independent microarray data (GSE74602 and GSE83889). Common DEGs were used to select active small molecules by the connectivity map database. A total of 166 DEGs were identified as common DEGs. GO analysis demonstrated that common DEGs were significantly enriched in the apoptotic process, cell proliferation, and cell adhesion. KEGG analysis indicated that the most enriched pathways were the PI3K-Akt signaling pathway and extracellular matrix-receptor interaction. COL1A2, THBS2, TIMP1, and CXCL8 significantly upregulated in colorectal tumor. High expressions of COL1A2, THBS2, and TIMP1 were associated with poor survival, while high expressions of CXCL8 were associated with better survival. We selected 11 small molecules for CRC therapy. In conclusion, we found key dysregulated genes associated with CRC and potential small molecules to reverse them. COL1A2, THBS2, TIMP1, and CXCL8 may act as diagnostic and prognostic biomarkers of CRC.

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Keywords:  Biomarker; COL1A2; CXCL8; Colorectal cancer; THBS2; TIMP1

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Year:  2020        PMID: 33078282     DOI: 10.1007/s12032-020-01425-2

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


  2 in total

1.  Integration of gene expression data identifies key genes and pathways in colorectal cancer.

Authors:  Hossein Hozhabri; Ali Lashkari; Seyed-Morteza Razavi; Ali Mohammadian
Journal:  Med Oncol       Date:  2021-01-07       Impact factor: 3.064

2.  A bioinformatics framework to identify the biomarkers and potential drugs for the treatment of colorectal cancer.

Authors:  Xiaogang Leng; Jianxiu Yang; Tie Liu; Chunbo Zhao; Zhongzheng Cao; Chengren Li; Junxi Sun; Sheng Zheng
Journal:  Front Genet       Date:  2022-09-27       Impact factor: 4.772

  2 in total

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