Literature DB >> 29955818

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

Junpeng Zhang1, Lin Liu2, Jiuyong Li2, Thuc Duy Le2.   

Abstract

Motivation: 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.
Results: 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. Availability and implementation: LncmiRSRN is freely available (https://github.com/zhangjunpeng411/LncmiRSRN). Supplementary information: Supplementary data are available at Bioinformatics online.

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Year:  2018        PMID: 29955818     DOI: 10.1093/bioinformatics/bty525

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  29 in total

1.  NEAT1 polyA-modulating antisense oligonucleotides reveal opposing functions for both long non-coding RNA isoforms in neuroblastoma.

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Review 2.  Non-Coding RNAs as Regulators and Markers for Targeting of Breast Cancer and Cancer Stem Cells.

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Journal:  Cancers (Basel)       Date:  2020-02-04       Impact factor: 6.639

Review 3.  Long non-coding RNAs and their potential impact on diagnosis, prognosis, and therapy in prostate cancer: racial, ethnic, and geographical considerations.

Authors:  Rebecca Morgan; Willian Abraham da Silveira; Ryan Christopher Kelly; Ian Overton; Emma H Allott; Gary Hardiman
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6.  Comprehensive analysis of lncRNA biomarkers in kidney renal clear cell carcinoma by lncRNA-mediated ceRNA network.

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7.  The circular RNA PVT1/miR-203/HOXD3 pathway promotes the progression of human hepatocellular carcinoma.

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8.  Prediction of competing endogenous RNA coexpression network as prognostic markers in AML.

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Journal:  Aging (Albany NY)       Date:  2019-05-31       Impact factor: 5.682

9.  Variation of Long Non-Coding RNA And mRNA Profiles in Breast Cancer Cells With Influences of Adipocytes.

Authors:  Xin-Hui Cao; Kai Yang; Ming-Xing Liang; Pei Ma; Di Xu; Yin-Jiao Fei; Wei Zhang; Xiu Chen; Jin-Hai Tang
Journal:  Front Oncol       Date:  2021-05-21       Impact factor: 6.244

10.  Dissecting immune cell stat regulation network reveals biomarkers to predict ICB therapy responders in melanoma.

Authors:  Jingwen Wang; Feng Li; Yanjun Xu; Xuan Zheng; Chunlong Zhang; Congxue Hu; Yingqi Xu; Wanqi Mi; Xia Li; Yunpeng Zhang
Journal:  J Transl Med       Date:  2021-07-08       Impact factor: 5.531

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