A New Network-Based Strategy for Predicting the Potential miRNA-mRNA Interactions in Tumorigenesis

Xue, Jiwei; Xie, Fanfan; Xu, Junmei; Liu, Yuan; Yu, Liang; Wen, Zhining; Li, Menglong

doi:10.1155/2017/3538568

Cited by 6 publications

(6 citation statements)

References 56 publications

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“…Since a single miRNA has the potential to target multiple mRNAs, it is generally involved in regulating various biological processes and signaling cascades. 42 In addition, the aberrant expression of miRNAs is reported in many diseases. Therefore, it is essential to identify key miRNAs and their target genes in the development of miRNA-based therapeutics in MB.…”

Section: Discussionmentioning

confidence: 99%

Impact of miRNA-mRNA Profiling and Their Correlation on Medulloblastoma Tumorigenesis

Kumar

Chaudhary

et al. 2018

Molecular Therapy - Nucleic Acids

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Medulloblastoma (MB) is a clinically challenging, childhood brain tumor with a diverse genetic makeup and differential miRNA profile. Aiming to identify deregulated miRNAs in MB, the miRNA expression profile of human MB samples was compared to that of normal cerebellar tissues. As a result, 8 upregulated and 64 downregulated miRNAs were identified in MB samples. Although various algorithms have been developed to predict the interaction between miRNA-mRNA pairs, the complexity and fidelity of miRNA-mRNA remain a concern. Therefore, to identify the signatures of miRNA-mRNA interactions essential for MB pathogenesis, miRNA profiling, RNA sequencing, and ingenuity pathway analysis (IPA) were performed in the same primary human MB samples. Further, when miR-217 was inhibited, a significant upregulation of predicted target genes SIRT1, ROBO1, FOXO3, and SMAD7 in HDMB03 cells was observed, confirming the validity of our approach. Functional analysis revealed that the inhibition of miR-217 in HDMB03 cells suppresses colony formation, migration, invasion, promoted apoptosis, and arrested cell population in S phase, indicating that manipulation of miR-217 may have a therapeutic potential for MB patients. Therefore, our study provides an essential platform for future investigations of specific miRNAs responsible for MB pathogenesis.

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Section: Discussionmentioning

confidence: 99%

Impact of miRNA-mRNA Profiling and Their Correlation on Medulloblastoma Tumorigenesis

Kumar

Chaudhary

et al. 2018

Molecular Therapy - Nucleic Acids

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“…Network construction refers to obtaining a large number of relevant data sets through data mining [28] or from various databases, websites, and experimental data and carrying out attribute mapping through network visualization tools, namely comprehensive data visualization [29]. Some types of constructed networks are protein-protein interaction (PPI) networks [30], gene interaction networks [31], and miRNA-mRNA interaction networks [32]. After the network is built, the processes of the two approaches diverge.…”

Section: Network-based Methodsmentioning

confidence: 99%

“…By constructing and analyzing the gene interaction network in Cytoscape, nine hub genes were obtained as potential therapeutic targets for new drug development [31]. Xue et al [32] constructed a miRNA-mRNA interaction network using miRNA and mRNA expression data, and the clinical data of three cancer types downloaded from The cancer genome atlas (TCGA) database [143]. The top 20 miRNAs with the highest degree in each data set were annotated via miR-Cancer (a microRNA-cancer association database) [144], miR2Disease (a microRNA-disease database) [145], and the Human microRNA Disease Database (HMDD) [146].…”

Section: Network-based Methodsmentioning

confidence: 99%

“…The top 20 miRNAs with the highest degree in each data set were annotated via miR-Cancer (a microRNA-cancer association database) [144], miR2Disease (a microRNA-disease database) [145], and the Human microRNA Disease Database (HMDD) [146]. After mapping the genes predicted as the targets of more than three miRNAs in the subnetworks to the human protein atlas database (HPAD) [147], eight genes (ASPG, AQP2, CNOT8, CTPS1, IFNAR2, MOCS2, PRSS37, and VCP) were finally identified as potential therapeutic targets [32].…”

Section: Network-based Methodsmentioning

confidence: 99%

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In silico Methods for Identification of Potential Therapeutic Targets

Zhang

Yang

et al. 2021

Interdiscip Sci Comput Life Sci

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At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery. Graphical abstract

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“…MiRNAs, which are 18-22 non-coding RNAs, regulate proteins expression by post-transcriptionally and extensive molecular mechanisms in various cancer types via either oncogenic or tumor-suppressive activities [ 5 ]. Substantive reports have indicated that the levles of miRNAs during the progression of colorectal cancer (CRC) altered, which highlighted their crucial roles for disease diagnostic and prognostic of CRC [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

MiR-520f promotes cell aggressiveness by regulating fibroblast growth factor 16 in hepatocellular carcinoma

Xie

Zha

et al. 2017

Oncotarget

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Cancer metastasis is a multistep cellular process, which has be confirmed one of mainly causes of cancer associated-death in hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) participate in tumorigenesis function as either tumor suppressor genes or oncogenes. In order to elaborate the critical miRNAs and their targets in HCC, we compared the differential expression of miRNA between HCC tissues and normal tissues. Microarray analysis revealed there were several significantly up-expression miRNAs in HCC, compared to normal solid tissue. Among them, the expression of miR-520f was the most over-expression in HCC cell lines than that in human normal liver cells LO2, as well as up-regulated in HCC than that in the corresponding normal tissues. Moreover, Kaplan Meier-plotter analyses revealed that higher miR-520f levels were negatively correlated with poor overall survival. By applying bioinformatics methods to identify the targeting genes of miRNA, we demonstrated that fibroblast growth factor 16 (FGF16) was the miR-520f-targeted gene. Meanwhile, FGF16 exhibited similar expression patterns to miR-520f in HCC. Forced miR-520f expression accelerated HCC cells proliferation and aggressiveness in vitro and in vivo, whereas down-regulation of miR-520f caused an opposite outcome. Moreover, over-expression of FGF16 was closely related to the metastatic potential of HCC cells. Herein, we also confirmed that ectopic expression of FGF16 in HCC cells promoted proliferation, colony formation, and increased migration, invasion of HCC cells in vitro. Collectively, our results indicated that over-expression of miR-520f and FGF16 was positively associated with aggressive phenotypes and poor survival of patients with HCC, and miR-520f promoted HCC aggressive phenotypes by regulating the expression of FGF16. MiR-520f may be employed as a prognostic factor and therapeutic target for HCC.

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A New Network-Based Strategy for Predicting the Potential miRNA-mRNA Interactions in Tumorigenesis

Cited by 6 publications

References 56 publications

Impact of miRNA-mRNA Profiling and Their Correlation on Medulloblastoma Tumorigenesis

Impact of miRNA-mRNA Profiling and Their Correlation on Medulloblastoma Tumorigenesis

In silico Methods for Identification of Potential Therapeutic Targets

MiR-520f promotes cell aggressiveness by regulating fibroblast growth factor 16 in hepatocellular carcinoma

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