LncmiRSRN: identification and analysis of long non-coding RNA related miRNA sponge regulatory network in human cancer

MicroRNAs (miRNAs) are small non-coding RNAs with the length of ∼22 nucleotides. miRNAs are involved in many biological processes including cancers. Recent studies show that long non-coding RNAs (lncRNAs) are emerging as miRNA sponges, playing important roles in cancer physiology and development. Despite accumulating appreciation of the importance of lncRNAs, the study of their complex functions is still in its preliminary stage. Based on the hypothesis of competing endogenous RNAs (ceRNAs), several computational methods have been proposed for investigating the competitive relationships between lncRNAs and miRNA target messenger RNAs (mRNAs). However, when the mRNAs are released from the control of miRNAs, it remains largely unknown as to how the sponge lncRNAs influence the expression levels of the endogenous miRNA targets.

We propose a novel method to construct lncRNA related miRNA sponge regulatory networks (LncmiRSRNs) by integrating matched lncRNA and mRNA expression profiles with clinical information and putative miRNA-target interactions. Using the method, we have constructed the LncmiRSRNs for four human cancers (glioblastoma multiforme, lung cancer, ovarian cancer and prostate cancer). Based on the networks, we discover that after being released from miRNA control, the target mRNAs are normally up-regulated by the sponge lncRNAs, and only a fraction of sponge lncRNA-mRNA regulatory relationships and hub lncRNAs are shared by the four cancers. Moreover, most sponge lncRNA-mRNA regulatory relationships show a rewired mode between different cancers, and a minority of sponge lncRNA-mRNA regulatory relationships conserved (appearing) in different cancers may act as a common pivot across cancers. Besides, differential and conserved hub lncRNAs may act as potential cancer drivers to influence the cancerous state in cancers. Functional enrichment and survival analysis indicate that the identified differential and conserved LncmiRSRN network modules work as functional units in biological processes, and can distinguish metastasis risks of cancers. Our analysis demonstrates the potential of integrating expression profiles, clinical information and miRNA-target interactions for investigating lncRNA regulatory mechanism.

LncmiRSRN is freely available (https://github.com/zhangjunpeng411/LncmiRSRN).

Supplementary data are available at Bioinformatics online.