Cross-sectional study of gene expression analysis identifies critical biological pathways and key genes implicated in non-small cell lung cancer
Joint Authors
Hu, Jing
Zhao, Hongbo
Wang, Tonglian
Xu, Lutong
Li, Yuanyue
Shou, Tao
Xia, Xueshan
Chen, Qiang
Source
Iranian Red Crescent Medical Journal
Issue
Vol. 20, Issue 3 (31 Mar. 2018), pp.1-12, 12 p.
Publisher
Publication Date
2018-03-31
Country of Publication
United Arab Emirates
No. of Pages
12
Main Subjects
Abstract EN
Background: Non-small cell lung cancer (NSCLC) is the most common type of lung Neoplasms, which accounts for about 85% of all lung cancer types.
However, critical biological pathways and key genes implicated in NSCLC remain ambiguous.
Objectives: The present study aimed at identifying the critical biological pathways and key genes implicated in NSCLC, and providing insight into the molecular mechanism underlying NSCLC.
Methods: In this case-control bioinformatics study, the researchers used four microarray data of NSCLC from public gene expression omnibus (GEO) database at the national center for biotechnology information (NCBI) website.
The microarray data came from studies of American, Spanish, and Taiwanese NSCLC patients, and in total contained 190 NSCLC tissue and 180 normal lung tissue.
A standardized- microarray preprocessing and gene set enrichment analysis (GSEA) were used to analyze each microarray data and obtained significantly regulated pathways.
Venn analysis was used to identify the common significantly regulated biological pathways.
Protein and protein interaction (PPI) network analysis was used to identify the key genes within common significantly regulated pathways.
The PPI information was retrieved from the STRING database, and Cytoscape software was used to construct and visualize the PPI network.
Results: Through integrating GSEA results of four microarray data, finally, the researchers identified 22 common up-regulated and 85 common down-regulated pathways.
Many genes within 107 common significantly regulated pathways were significantly enriched within cell cycle pathway (P value of 2.58e-79) and focal adhesion pathway (P value of 2.44e-81).
The PPI network showed that up-regulated CDK1 (P value = 1.33e-18 and logFC = 1.41) and down-regulated PIK3R1 (P value = 5.09e-22 and logFC = -1.13) genes shared the most abundant edges, and were associated with NSCLC.
Conclusions: This cross-sectional study showed increased concordance between gene expression profiling data.
These identified pathways and genes provide some insight into the molecular mechanisms of NSCLC, and the genes may serve as candidate diagnostic and therapeutic targets of NSCLC.
American Psychological Association (APA)
Wang, Tonglian& Hu, Jing& Xu, Lutong& Zhao, Hongbo& Li, Yuanyue& Shou, Tao…[et al.]. 2018. Cross-sectional study of gene expression analysis identifies critical biological pathways and key genes implicated in non-small cell lung cancer. Iranian Red Crescent Medical Journal،Vol. 20, no. 3, pp.1-12.
https://search.emarefa.net/detail/BIM-840481
Modern Language Association (MLA)
Wang, Tonglian…[et al.]. Cross-sectional study of gene expression analysis identifies critical biological pathways and key genes implicated in non-small cell lung cancer. Iranian Red Crescent Medical Journal Vol. 20, no. 3 (Mar. 2018), pp.1-12.
https://search.emarefa.net/detail/BIM-840481
American Medical Association (AMA)
Wang, Tonglian& Hu, Jing& Xu, Lutong& Zhao, Hongbo& Li, Yuanyue& Shou, Tao…[et al.]. Cross-sectional study of gene expression analysis identifies critical biological pathways and key genes implicated in non-small cell lung cancer. Iranian Red Crescent Medical Journal. 2018. Vol. 20, no. 3, pp.1-12.
https://search.emarefa.net/detail/BIM-840481
Data Type
Journal Articles
Language
English
Notes
Includes appendices : p. 9-12
Record ID
BIM-840481