Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

High-efficient screening method for identification of key genes in breast cancer through microarray and bioinformatics

Liu, Zihao, Liang, Gehao, Tan, Luyuan, Su, An, Jiang, Wen Guo and Gong, Chang 2017. High-efficient screening method for identification of key genes in breast cancer through microarray and bioinformatics. Anticancer Research 37 (8) , pp. 4329-4335. 10.21873/anticanres.11826

PDF - Published Version
Download (2MB) | Preview


Background/Aim: The aim of the present study was to identify key pathways and genes in breast cancer and develop a new method for screening key genes with abnormal expression based on bioinformatics. Materials and Methods: Three microarray datasets GSE21422, GSE42568 and GSE45827 were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were analyzed using GEO2R. The gene ontology (GO) and pathway enrichment analysis were established through DAVID database. The protein–protein interaction (PPI) network was performed through the Search Tool for the Retrieval of Interacting Genes (STRING) database and managed by Cytoscape. The overall survival (OS) analysis of the 4 genes including AURKA, CDH1, CDK1 and PPARG that had higher degrees in this network was uncovered Kaplan-Meier analysis. Results: A total of 811 DEGs were identified in breast cancer, which were enriched in biological processes, including cell cycle, mitosis, vessel development and lipid metabolic. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the up-regulated DEGs were particularly involved in cell cycle, progesterone-mediated oocyte maturation and leukocyte transendothelial migration, while the down-regulated DEGs were mainly involved in regulation of lipolysis, fatty acid degradation and glycerolipid metabolism. Through PPI network analysis, 14 hub genes were identified. Among them, the high expression of AURKA, CDH1 and CDK1 were associated with worse OS of breast cancer patients; while the high expression of PPARG was linked with better OS. Conclusion: The present study identified key pathways and genes involved in breast cancer which are potential molecular targets for breast cancer treatment and diagnosis.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Publisher: International Institute of Anticancer Research (IIAR)
ISSN: 0250-7005
Funders: National Key Research and Development Program of China (2017YFC1309100); the Natural Science Foundation of China (81472466 and 81672594); National Science Foundation of Guangdong Province (2014A03036003, 2014A030310378, 2014A020212059, 2015A030313172, 2015B050 501004, 2016A050502018 and 2016A030313237); China Scholarship Council (No. 201606385034); Cultivation for Major Projects and Emerging Interdisciplinary Funding Project of Sun Yat-sen University (17ykjc13) and Elite Young Scholars Program of Sun Yat-sen Memorial H, Cancer Research Wales and Wales National Life Science Research Network (NRN), Cardiff, Wales
Date of First Compliant Deposit: 15 January 2018
Date of Acceptance: 22 May 2017
Last Modified: 22 Jan 2018 12:18

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics