Affiliation:
1. College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081,
China
Abstract
Abstract:
Background: Long noncoding RNAs (LncRNAs) represent a large category of functional RNA molecules that play a significant role in human cancers. lncRNAs can be genes modulators to affect the biological process of multiple cancers.
Methods:
Here, we developed a computational framework that uses lncRNA-mRNA network and mutations in individual genes of 9 cancers from TCGA to prioritize cancer lncRNA modulators. Our method screened risky cancer lncRNA regulators based on integrated multiple lncRNA functional networks and 3 calculation methods in network.
Results:
Validation analyses revealed that our method was more effective than prioritization based on a single lncRNA network. This method showed high predictive performance and the highest ROC score was 0.836 in breast cancer. It’s worth noting that we found that 5 lncRNAs scores were abnormally high and these lncRNAs appeared in 9 cancers. By consulting the literatures, these 5 lncRNAs were experimentally supported lncRNAs. Analyses of prioritizing lncRNAs reveal that these lncRNAs are enriched in various cancer-related biological processes and pathways.
Conclusions:
Together, these results demonstrated the ability of this method identifying candidate lncRNA molecules and improved insights into the pathogenesis of cancer.
Funder
National Natural Science Foundation of China
Publisher
Bentham Science Publishers Ltd.
Subject
Computational Mathematics,Genetics,Molecular Biology,Biochemistry
Cited by
3 articles.
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