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Integrated miRNA-risk gene-pathway pair network analysis provides prognostic biomarkers for gastric cancer

Authors Cai H, Xu J, Han Y, Lu Z, Han T, Ding Y, Ma L

Received 26 August 2015

Accepted for publication 4 March 2016

Published 19 May 2016 Volume 2016:9 Pages 2975—2986

DOI https://doi.org/10.2147/OTT.S95129

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Manfred Beleut

Peer reviewer comments 2

Editor who approved publication: Dr William Cho


Hui Cai,1 Jiping Xu,2 Yifang Han,3 Zhengmao Lu,1 Ting Han,1 Yibo Ding,4 Liye Ma1

1Department of General Surgery, Changhai Hospital, Second Military Medical University, Shanghai, 2Department of Medical Administration, Changhai Hospital, Second Military Medical University, Shanghai, 3Department of Epidemiology, Research Institute for Medicine of Nanjing Command, Nanjing, 4Department of Epidemiology, Changhai Hospital, Second Military Medical University, Shanghai, People’s Republic of China

Purpose: This study aimed to identify molecular prognostic biomarkers for gastric cancer.
Methods: mRNA and miRNA expression profiles of eligible gastric cancer and control samples were downloaded from Gene Expression Omnibus to screen the differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs), using MetaDE and limma packages, respectively. Target genes of the DEmiRs were also collected from both predictive and experimentally validated target databases of miRNAs. The overlapping genes between selected targets and DEGs were identified as risk genes, followed by functional enrichment analysis. Human pathways and their corresponding genes were downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for the expression analysis of each pathway in gastric cancer samples. Next, co-pathway pairs were selected according to the Pearson correlation coefficients. Finally, the co-pathway pairs, miRNA–target pairs, and risk gene–pathway pairs were merged into a complex interaction network, the most important nodes (miRNAs/target genes/co-pathway pairs) of which were selected by calculating their degrees.
Results: Totally, 1,260 DEGs and 144 DEmiRs were identified. There were 336 risk genes found in the 9,572 miRNA–target pairs. Judging from the pathway expression files, 45 co-pathway pairs were screened out. There were 1,389 interactive pairs and 480 nodes in the integrated network. Among all nodes in the network, focal adhesion/extracellular matrix–receptor interaction pathways, CALM2, miR-19b, and miR-181b were the hub nodes with higher degrees.
Conclusion: CALM2, hsa-miR-19b, and hsa-miR-181b might be used as potential prognostic targets for gastric cancer.

Keywords: gastric cancer, dysfunction, co-pathway pairs, integrated network, miRNA targets
 

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