Literature DB >> 30652311

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis.

Guangwei Sun1, Yalun Li1, Yangjie Peng1, Dapeng Lu1, Fuqiang Zhang1, Xueyang Cui1, Qingyue Zhang1, Zhuang Li1.   

Abstract

Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer-related functions and pathways. Then, the STRING database was used to construct the protein-protein interaction network. The module analysis was performed by the MCODE plug-in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug-in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  GEO; bioinformatics; colorectal cancer; differentially expressed genes; robust rank aggregation

Year:  2019        PMID: 30652311     DOI: 10.1002/jcp.28163

Source DB:  PubMed          Journal:  J Cell Physiol        ISSN: 0021-9541            Impact factor:   6.384


  21 in total

1.  Identification and Validation of a Six Immune-Related Genes Signature for Predicting Prognosis in Patients With Stage II Colorectal Cancer.

Authors:  Xianzhe Li; Minghao Xie; Shi Yin; Zhizhong Xiong; Chaobin Mao; Fengxiang Zhang; Huaxian Chen; Longyang Jin; Ping Lan; Lei Lian
Journal:  Front Genet       Date:  2021-05-04       Impact factor: 4.599

2.  A novel prognostic signature of immune-related genes for patients with colorectal cancer.

Authors:  Jun Wang; Shaojun Yu; Guofeng Chen; Muxing Kang; Xiaoli Jin; Yi Huang; Lele Lin; Dan Wu; Lie Wang; Jian Chen
Journal:  J Cell Mol Med       Date:  2020-06-21       Impact factor: 5.310

3.  The promising novel biomarkers and candidate small molecule drugs in kidney renal clear cell carcinoma: Evidence from bioinformatics analysis of high-throughput data.

Authors:  Bo Zhang; Qiong Wu; Ziheng Wang; Ran Xu; Xinyi Hu; Yidan Sun; Qiuhong Wang; Fei Ju; Shiqi Ren; Chenlin Zhang; Lin Qin; Qianqian Ma; You Lang Zhou
Journal:  Mol Genet Genomic Med       Date:  2019-02-21       Impact factor: 2.183

4.  Identification of Differentially Expressed Genes and Signaling Pathways in Acute Myocardial Infarction Based on Integrated Bioinformatics Analysis.

Authors:  Da-Qiu Chen; Xiang-Sheng Kong; Xue-Bin Shen; Mao-Zhi Huang; Jian-Ping Zheng; Jing Sun; Shang-Hua Xu
Journal:  Cardiovasc Ther       Date:  2019-08-01       Impact factor: 3.023

5.  SLC1A1, SLC16A9, and CNTN3 Are Potential Biomarkers for the Occurrence of Colorectal Cancer.

Authors:  Jie Zhou; Zhiman Xie; Ping Cui; Qisi Su; Yu Zhang; Lijia Luo; Zhuoxin Li; Li Ye; Hao Liang; Jiegang Huang
Journal:  Biomed Res Int       Date:  2020-05-23       Impact factor: 3.411

6.  Immune System Effects of Insulin-Like Peptide 5 in a Mouse Model.

Authors:  Brett Vahkal; Sergey Yegorov; Chukwunonso Onyilagha; Jacqueline Donner; Dean Reddick; Anuraag Shrivastav; Jude Uzonna; Sara V Good
Journal:  Front Endocrinol (Lausanne)       Date:  2021-01-14       Impact factor: 5.555

7.  Single-Cell Sequencing Reveals the Transcriptome and TCR Characteristics of pTregs and in vitro Expanded iTregs.

Authors:  Zhenzhen Hui; Jiali Zhang; Yu Zheng; Lili Yang; Wenwen Yu; Yang An; Feng Wei; Xiubao Ren
Journal:  Front Immunol       Date:  2021-03-31       Impact factor: 7.561

8.  Development and Validation of a Prognostic Gene Signature in Clear Cell Renal Cell Carcinoma.

Authors:  Chuanchuan Zhan; Zichu Wang; Chao Xu; Xiao Huang; Junzhou Su; Bisheng Chen; Mingshan Wang; Zhihong Qi; Peiming Bai
Journal:  Front Mol Biosci       Date:  2021-04-08

9.  Underlying Mechanism of Insulin Resistance: A Bioinformatics Analysis Based on Validated Related-Genes from Public Disease Databases.

Authors:  Peng Gao; Yan Hu; Junyan Wang; Yinghua Ni; Zhengyi Zhu; Huijuan Wang; Jufei Yang; Lingfei Huang; Luo Fang
Journal:  Med Sci Monit       Date:  2020-07-11

10.  Identification of key genes involved in the development and progression of early-onset colorectal cancer by co-expression network analysis.

Authors:  Xiaoqiong Mo; Zexin Su; Bingsheng Yang; Zhirui Zeng; Shan Lei; Hui Qiao
Journal:  Oncol Lett       Date:  2019-11-08       Impact factor: 2.967

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