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Construction of a lncRNA-mediated feed-forward loop network reveals global topological features and prognostic motifs in human cancers.
Ning, Shangwei; Gao, Yue; Wang, Peng; Li, Xiang; Zhi, Hui; Zhang, Yan; Liu, Yue; Zhang, Jizhou; Guo, Maoni; Han, Dong; Li, Xia.
Afiliação
  • Ning S; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Gao Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Wang P; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Li X; National Center for Nanoscience and Technology, Beijing, 100190, China.
  • Zhi H; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Zhang Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Liu Y; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Zhang J; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Guo M; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
  • Han D; National Center for Nanoscience and Technology, Beijing, 100190, China.
  • Li X; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Oncotarget ; 7(29): 45937-45947, 2016 Jul 19.
Article em En | MEDLINE | ID: mdl-27322142
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Biomarcadores Tumorais / MicroRNAs / Transcriptoma / RNA Longo não Codificante / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fatores de Transcrição / Biomarcadores Tumorais / MicroRNAs / Transcriptoma / RNA Longo não Codificante / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article