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Computational and Mathematical Methods in Medicine
Volume 2016 (2016), Article ID 3186051, 8 pages
http://dx.doi.org/10.1155/2016/3186051
Research Article

Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer

1The 2nd Department of Gynecology, The Affiliated Tumor Hospital of Xinjiang Medical University, Urumqi, Xinjiang 830000, China
2Department of Gynecology, Ninth Hospital of Xi’an, Xi’an, Shaanxi 715100, China

Received 7 December 2015; Revised 25 January 2016; Accepted 7 February 2016

Academic Editor: Emil Alexov

Copyright © 2016 Yun-Xia Zhang and Yan-Li Zhao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose. The objective of our study was to predicate candidate genes in cervical cancer (CC) using a network-based strategy and to understand the pathogenic process of CC. Methods. A pathogenic network of CC was extracted based on known pathogenic genes (seed genes) and differentially expressed genes (DEGs) between CC and normal controls. Subsequently, cluster analysis was performed to identify the subnetworks in the pathogenic network using ClusterONE. Each gene in the pathogenic network was assigned a weight value, and then candidate genes were obtained based on the weight distribution. Eventually, pathway enrichment analysis for candidate genes was performed. Results. In this work, a total of 330 DEGs were identified between CC and normal controls. From the pathogenic network, 2 intensely connected clusters were extracted, and a total of 52 candidate genes were detected under the weight values greater than 0.10. Among these candidate genes, VIM had the highest weight value. Moreover, candidate genes MMP1, CDC45, and CAT were, respectively, enriched in pathway in cancer, cell cycle, and methane metabolism. Conclusion. Candidate pathogenic genes including MMP1, CDC45, CAT, and VIM might be involved in the pathogenesis of CC. We believe that our results can provide theoretical guidelines for future clinical application.