Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 45937-45947 |
| Number of pages | 11 |
| Journal | Oncotarget |
| Volume | 7 |
| Issue number | 29 |
| DOIs | |
| State | Published - 2016 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Feed-forward loop
- Long non-coding RNA
- Network motif
- Prognostic biomarker
- Topological feature
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