Oncotarget

Research Papers:

Integrating gene and lncRNA expression to infer subpathway activity for tumor analyses

Chunlong Zhang, Yanjun Xu, Haixiu Yang, Yingqi Xu, Qun Dong, Siyao Liu, Tan Wu and Yunpeng Zhang _

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Oncotarget. 2017; 8:111433-111443. https://doi.org/10.18632/oncotarget.22811

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Abstract

Chunlong Zhang1,*, Yanjun Xu1,*, Haixiu Yang1, Yingqi Xu1, Qun Dong1, Siyao Liu1, Tan Wu1 and Yunpeng Zhang1

1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China

*These authors have contributed equally to this work

Correspondence to:

Yunpeng Zhang, email: zhangyp@hrbmu.edu.cn

Keywords: subpathway; lncRNA

Received: September 14, 2017     Accepted: November 16, 2017     Published: November 30, 2017

ABSTRACT

LncRNAs acting as miRNA sponges to indirectly regulate mRNAs is a novel layer of gene regulation, therefore, it is necessary to integrate lncRNA and gene levels for interpreting tumor biological mechanism. In this study, we developed a lncRNA-gene integrated strategy to infer functional activities for tumor analyses at the subpathway level. In this strategy, we reconstructed subpathway graphs by embedding lncRNA components and considered the expression levels of both genes and lncRNAs to infer subpathway activities for each tumor sample. And the activities were applied to three aspects of tumor analyses; First, the subpathway activities across tumor samples of five tumor types were analyzed, and it was observed that the samples with consistent subpathway activities were derived from the same or similar tumor types. Also, the subpathway activities could stratify samples into several subtypes which has different clinical characterization, e.g. survival status. Second, the subpathway activities between tumor and normal samples were analyzed, and the comparative results showed that subpathway activities displayed more specificities than entire pathway activities. Finally, based on the subpathway activities, we identified prognostic subpathways for lung cancer. Our subpathway-based signatures shared significant overlap with enrichment analysis results and displayed predictive power in the independent testing sets. In conclusion, our integrated strategy provided a framework to infer subpathway activities for tumor analyses and identify subpathway signatures for clinical use.


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