Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Liu, Guang-Weia | Qin, Zhao-Minb | Shen, Qin-Haic; *
Affiliations: [a] Department of Gastroenterology, The First Affiliated Hospital, Henan University of Traditional Chinese Medicine, Zhengzhou, Henan, China | [b] Department of Nursing, Shandong Medical College, Jinan, Shandong, China | [c] Department of Medicine, Shandong Medical College, Jinan, Shandong, China
Correspondence: [*] Corresponding author: Qin-Hai Shen, Department of Medicine, Shandong Medical College, No. 5460 of South Erhuan Road, Jinan 250002, Shandong, China Tel.: +86 0531 86305265; Fax: +86 0531 86305265; E-mail: [email protected].
Abstract: OBJECTIVE: It is crucially important to discover the relationships between genes and microRNAs (miRNAs) in cancer. Thus, we proposed a combined bioinformatics method integrating Pearson’s correlation coefficient (PCC), Lasso, and causal inference method (IDA) to identify the potential miRNA targets for stomach adenocarcinoma (STAD) using Borda count election. MATERIALS AND METHODS:Firstly, the ensemble method integrating PCC, IDA, and Lasso was used to predict miRNA targets. Subsequently, to validate the performance ability of this ensemble method, comparisons between verified database and predicted miRNA targets were implemented. Pathway analysis for target genes in the top 1000 miRNA-mRNA interactions was implemented to discover significant pathways. Finally, the top 10 target genes were identified based on predicted times > 3. RESULTS:The ensemble approach was confirmed to be a feasible method to predict miRNA targets The 527 target genes of the top 1000 miRNA-mRNA interactions were enriched in 21 pathways. Of note, cell adhesion molecules (CAMs) was the most significant one. The top 10 target genes were identified based on predicted times > 3, such as GABRA3, CSAG1 and PTPN7. These targets were all predicted by 4 times. Moreover, GABRA3 and CSAG1 were simultaneously targeted by miRNA-105-1, miRNA-105-2, and miRNA-767. Significantly, among these top 10 targets, PTPN7 and GABRA3-miRNA interactions owned the highest correlation with 691. CONCLUSION:The combined bioinformatics method integrating PCC, IDA, and Lasso might be a valuable method for miRNA target prediction, and dys-regulated expression of miRNAs and their potential targets might be prominently involved in the pathogenesis of STAD.
Keywords: Stomach adenocarcinoma, ensemble method, miRNA targets
DOI: 10.3233/CBM-170595
Journal: Cancer Biomarkers, vol. 20, no. 4, pp. 617-625, 2017
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]