Literature DB >> 26448606

A cross-cancer differential co-expression network reveals microRNA-regulated oncogenic functional modules.

Chen-Ching Lin1, Ramkrishna Mitra2, Feixiong Cheng2, Zhongming Zhao3.   

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that can regulate their target gene expressions at the post-transcriptional level. Moreover, they have been reported as either oncomirs or tumor suppressors and possess therapeutic potential in cancer. In this study, we investigated differential co-expression of miRNAs across four cancer types. We observed that the loss of positive co-expressions among miRNAs frequently occurs in the studied cancer types. This observation suggests that the disruption of positive co-expressions among miRNAs may be prevalent during tumorigenesis. By systematically collecting these lost positive co-expressions among miRNAs in cancer, we constructed a cross-cancer miRNA differential co-expression network. We observed that the influential miRNAs in the proposed network, i.e., hubs or in larger cliques, tended to be involved in more cancer types than other miRNAs. Moreover, we found that miRNAs which lose their positive co-expressions in cancers might co-contribute to cancer development, and even could be used to predict the cancer types in which miRNAs were involved. Finally, we identified two potential miRNA-regulated onco-modules, mitosis and DNA replication, that are associated with poor survival outcomes in patients across multiple cancers. Collectively, our study suggested that the disruption of miRNA positive co-expression in cancer might contribute to cancer development. Our findings also form an important basis for identifying miRNAs with potential co-contribution to carcinogenesis.

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Year:  2015        PMID: 26448606      PMCID: PMC4643368          DOI: 10.1039/c5mb00443h

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  44 in total

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2.  Prediction of conditional gene essentiality through graph theoretical analysis of genome-wide functional linkages.

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Review 3.  miR-106b-25/miR-17-92 clusters: polycistrons with oncogenic roles in hepatocellular carcinoma.

Authors:  Weiqi Tan; Yang Li; Seng-Gee Lim; Theresa M C Tan
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Review 4.  miR-92a family and their target genes in tumorigenesis and metastasis.

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Journal:  Exp Cell Res       Date:  2014-01-04       Impact factor: 3.905

5.  Differential expression of microRNA species in human gastric cancer versus non-tumorous tissues.

Authors:  Junming Guo; Ying Miao; Bingxiu Xiao; Rong Huan; Zhen Jiang; Dan Meng; Yanjun Wang
Journal:  J Gastroenterol Hepatol       Date:  2008-11-03       Impact factor: 4.029

6.  Mammalian microRNAs predominantly act to decrease target mRNA levels.

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Journal:  Nature       Date:  2010-08-12       Impact factor: 49.962

7.  MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features.

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Journal:  Nucleic Acids Res       Date:  2010-10-06       Impact factor: 16.971

8.  Global and local architecture of the mammalian microRNA-transcription factor regulatory network.

Authors:  Reut Shalgi; Daniel Lieber; Moshe Oren; Yitzhak Pilpel
Journal:  PLoS Comput Biol       Date:  2007-07       Impact factor: 4.475

9.  Long noncoding RNA associated-competing endogenous RNAs in gastric cancer.

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Journal:  Sci Rep       Date:  2014-08-15       Impact factor: 4.379

10.  Regulation rewiring analysis reveals mutual regulation between STAT1 and miR-155-5p in tumor immunosurveillance in seven major cancers.

Authors:  Chen-Ching Lin; Wei Jiang; Ramkrishna Mitra; Feixiong Cheng; Hui Yu; Zhongming Zhao
Journal:  Sci Rep       Date:  2015-07-09       Impact factor: 4.379

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  5 in total

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Review 2.  Differential Regulatory Analysis Based on Coexpression Network in Cancer Research.

Authors:  Junyi Li; Yi-Xue Li; Yuan-Yuan Li
Journal:  Biomed Res Int       Date:  2016-08-11       Impact factor: 3.411

Review 3.  Discovering MicroRNA-Regulatory Modules in Multi-Dimensional Cancer Genomic Data: A Survey of Computational Methods.

Authors:  Christopher J Walsh; Pingzhao Hu; Jane Batt; Claudia C Dos Santos
Journal:  Cancer Inform       Date:  2016-10-03

Review 4.  Anakoinosis: Correcting Aberrant Homeostasis of Cancer Tissue-Going Beyond Apoptosis Induction.

Authors:  Daniel Heudobler; Florian Lüke; Martin Vogelhuber; Sebastian Klobuch; Tobias Pukrop; Wolfgang Herr; Christopher Gerner; Pan Pantziarka; Lina Ghibelli; Albrecht Reichle
Journal:  Front Oncol       Date:  2019-12-20       Impact factor: 6.244

Review 5.  Differential Co-Expression Analyses Allow the Identification of Critical Signalling Pathways Altered during Tumour Transformation and Progression.

Authors:  Aurora Savino; Paolo Provero; Valeria Poli
Journal:  Int J Mol Sci       Date:  2020-12-12       Impact factor: 5.923

  5 in total

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