Original Research ARTICLE
The identification and analysis of mRNA-lncRNA-miRNA cliques from the integrative network of ovarian cancer
- 1First people's Hospital of Changzhou, China
- 2Shanghai Institutes for Biological Sciences (CAS), China
Ovarian cancer is one of the leading causes of cancer mortality in women. Since little clinical symptoms were shown in the early period of ovarian cancer, most patients were found in phase III-IV or with abdominal metastasis when diagnosed. The lack of effective early diagnosis biomarkers makes ovarian cancer difficult to screening. But in essence, the fundamental problem is we know very little about the regulatory mechanisms during tumorigenesis of ovarian cancer. There are emerging regulatory factors, such as long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), which have played important roles in cancers. Therefore, we analyzed the RNA-seq profiles of 407 ovarian cancer patients. An integrative network of 20,424 coding RNAs (mRNAs), 10,412 lncRNAs and 742 miRNAs were construed with variance inflation factor (VIF) regression method. The mRNA-lncRNA-miRNA cliques were identified from the network and analyzed. Such promising cliques showed significant correlations with survival and stage of ovarian cancer, and characterized the complex sponge regulatory mechanism, suggesting their contributions to tumorigenicity. Our results provided novel insights of the regulatory mechanisms among mRNAs, lncRNAs and miRNAs and highlighted several promising regulators for ovarian cancer detection and treatment.
Keywords: variance inflation factor regression, mRNA-lncRNA-miRNA cliques, regulatory network construction, ovarian cancer, functional regulator
Received: 30 Jan 2019;
Accepted: 17 Jul 2019.
Edited by:Marco Pellegrini, Institute of Computer Science and Telematics, Italian National Research Council, Italy
Reviewed by:Qi Zhao, Shenyang Aerospace University, China
Suman Ghosal, National Institutes of Health (NIH), United States
Copyright: © 2019 Zhou, Zheng, Xu, Hu, Huang and Jiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Dr. Tao Huang, Shanghai Institutes for Biological Sciences (CAS), Shanghai, 200031, Shanghai Municipality, China, firstname.lastname@example.org
Prof. Jingting Jiang, First people's Hospital of Changzhou, Changzhou, China, email@example.com