Identification and verification of key cancer genes associated with prognosis of colorectal cancer based on bioinformatics analysis.
10.11817/j.issn.1672-7347.2021.200952
- Author:
Yi QIN
1
;
Lu CHEN
2
;
Lizhang CHEN
3
Author Information
1. Xiangya School of Public Health, Central South University, Changsha 410078. 112813128@qq.com.
2. Department of Gastrointestinal Surgery, Xiangya Hospital, Central South University, Changsha 410008, China.
3. Xiangya School of Public Health, Central South University, Changsha 410078. chenliz@csu.edu.cn.
- Publication Type:Journal Article
- Keywords:
RNA sequencing;
bioinformatics analysis;
colorectal cancer;
different expressed genes
- MeSH:
Biomarkers, Tumor/metabolism*;
Colorectal Neoplasms/genetics*;
Computational Biology;
Formins;
Gene Expression Profiling;
Gene Expression Regulation, Neoplastic;
Glycoproteins;
Humans;
Intercellular Signaling Peptides and Proteins;
Oncogenes;
Prognosis;
Protein Interaction Maps
- From:
Journal of Central South University(Medical Sciences)
2021;46(10):1063-1070
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:The biomarkers targeting colorectal cancer (CRC) prognosis are short of high accuracy and sensitivity in clinic. Through bioinformatics analysis, we aim to identify and confirm a series of key genes referred to the diagnosis and prognosis of CRC.
METHODS:GSE31905, GSE35279, and GSE41657 were selected as complete RNA sequencing data sets of CRC and colorectal mucosa (CRM) tissues from the NCBI-GEO database, and the differentially expressed genes (DEGs) were analyzed. The common DEGs in these 3 data sets were obtained by Venn map, and enriched by STRING network system and Cytoscape software. The Kaplan-Meier plotter website was used to verify the correlation between the enriched genes and the prognosis of CRC.
RESULTS:For the whole RNA sequencing data sets of CRC and normal intestinal mucosa samples, the DEGs of CRC and CRM in the 3 data sets (|log
CONCLUSIONS:The above 11 genes verified by bioinformatics retrieval and analysis can predict the poor prognosis of CRC to a certain extent, and they provide a possible target for the diagnosis and treatment of CRC.
