Construction of a lncRNA-mediated feed-forward loop network reveals global topological features and prognostic motifs in human cancers
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Shangwei Ning1,*, Yue Gao1,*, Peng Wang1,*, Xiang Li2, Hui Zhi1, Yan Zhang1, Yue Liu1, Jizhou Zhang1, Maoni Guo1, Dong Han2, Xia Li1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China
2National Center for Nanoscience and Technology, Beijing, 100190, China
*These authors have contributed equally to this work
Xia Li, email: email@example.com
Dong Han, email: firstname.lastname@example.org
Keywords: long non-coding RNA, feed-forward loop, network motif, topological feature, prognostic biomarker
Received: February 25, 2016 Accepted: May 29, 2016 Published: June 14, 2016
Long non-coding RNAs (lncRNAs), transcription factors and microRNAs can form lncRNA-mediated feed-forward loops (L-FFLs), which are functional network motifs that regulate a wide range of biological processes, such as development and carcinogenesis. However, L-FFL network motifs have not been systematically identified, and their roles in human cancers are largely unknown. In this study, we computationally integrated data from multiple sources to construct a global L-FFL network for six types of human cancer and characterized the topological features of the network. Our approach revealed several dysregulated L-FFL motifs common across different cancers or specific to particular cancers. We also found that L-FFL motifs can take part in other types of regulatory networks, such as mRNA-mediated FFLs and ceRNA networks, and form the more complex networks in human cancers. In addition, survival analyses further indicated that L-FFL motifs could potentially serve as prognostic biomarkers. Collectively, this study elucidated the roles of L-FFL motifs in human cancers, which could be beneficial for understanding cancer pathogenesis and treatment.
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