Identification of MicroRNA Clusters Cooperatively Acting on Epithelial to Mesenchymal Transition in Triple Negative Breast Cancer

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2019 Jan 19

PMID 30657980

Citations 43

Authors

Laura Cantini

Gloria Bertoli

Claudia Cava

Thierry Dubois

Andrei Zinovyev

Michele Caselle

Isabella Castiglioni

Emmanuel Barillot

Loredana Martignetti

Affiliations

Soon will be listed here.

Abstract

MicroRNAs play important roles in many biological processes. Their aberrant expression can have oncogenic or tumor suppressor function directly participating to carcinogenesis, malignant transformation, invasiveness and metastasis. Indeed, miRNA profiles can distinguish not only between normal and cancerous tissue but they can also successfully classify different subtypes of a particular cancer. Here, we focus on a particular class of transcripts encoding polycistronic miRNA genes that yields multiple miRNA components. We describe 'clustered MiRNA Master Regulator Analysis (ClustMMRA)', a fully redesigned release of the MMRA computational pipeline (MiRNA Master Regulator Analysis), developed to search for clustered miRNAs potentially driving cancer molecular subtyping. Genomically clustered miRNAs are frequently co-expressed to target different components of pro-tumorigenic signaling pathways. By applying ClustMMRA to breast cancer patient data, we identified key miRNA clusters driving the phenotype of different tumor subgroups. The pipeline was applied to two independent breast cancer datasets, providing statistically concordant results between the two analyses. We validated in cell lines the miR-199/miR-214 as a novel cluster of miRNAs promoting the triple negative breast cancer (TNBC) phenotype through its control of proliferation and EMT.

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References

Ozsolak F, Poling L, Wang Z, Liu H, Liu X, Roeder R . Chromatin structure analyses identify miRNA promoters. Genes Dev. 2008; 22(22):3172-83. PMC: 2593607. DOI: 10.1101/gad.1706508. View

Liu B, Zhang X, Song F, Zheng H, Zhao Y, Li H . MiR-502/SET8 regulatory circuit in pathobiology of breast cancer. Cancer Lett. 2016; 376(2):259-67. DOI: 10.1016/j.canlet.2016.04.008. View

Altuvia Y, Landgraf P, Lithwick G, Elefant N, Pfeffer S, Aravin A . Clustering and conservation patterns of human microRNAs. Nucleic Acids Res. 2005; 33(8):2697-706. PMC: 1110742. DOI: 10.1093/nar/gki567. View

Farazi T, Ten Hoeve J, Brown M, Mihailovic A, Horlings H, van de Vijver M . Identification of distinct miRNA target regulation between breast cancer molecular subtypes using AGO2-PAR-CLIP and patient datasets. Genome Biol. 2014; 15(1):R9. PMC: 4053773. DOI: 10.1186/gb-2014-15-1-r9. View

Burgess A, Vigneron S, Brioudes E, Labbe J, Lorca T, Castro A . Loss of human Greatwall results in G2 arrest and multiple mitotic defects due to deregulation of the cyclin B-Cdc2/PP2A balance. Proc Natl Acad Sci U S A. 2010; 107(28):12564-9. PMC: 2906566. DOI: 10.1073/pnas.0914191107. View

Rooj A, Ricklefs F, Mineo M, Nakano I, Chiocca E, Bronisz A . MicroRNA-Mediated Dynamic Bidirectional Shift between the Subclasses of Glioblastoma Stem-like Cells. Cell Rep. 2017; 19(10):2026-2032. PMC: 5514838. DOI: 10.1016/j.celrep.2017.05.040. View

Wang J, Haubrock M, Cao K, Hua X, Zhang C, Wingender E . Regulatory coordination of clustered microRNAs based on microRNA-transcription factor regulatory network. BMC Syst Biol. 2011; 5:199. PMC: 3262773. DOI: 10.1186/1752-0509-5-199. View

Song R, Catchpoole D, Kennedy P, Li J . Identification of lung cancer miRNA-miRNA co-regulation networks through a progressive data refining approach. J Theor Biol. 2015; 380:271-9. DOI: 10.1016/j.jtbi.2015.05.025. View

Ma L, Teruya-Feldstein J, Weinberg R . Tumour invasion and metastasis initiated by microRNA-10b in breast cancer. Nature. 2007; 449(7163):682-8. DOI: 10.1038/nature06174. View

10.

Hoshida Y . Nearest template prediction: a single-sample-based flexible class prediction with confidence assessment. PLoS One. 2010; 5(11):e15543. PMC: 2990751. DOI: 10.1371/journal.pone.0015543. View

11.

Cursons J, Pillman K, Scheer K, Gregory P, Foroutan M, Hediyeh-Zadeh S . Combinatorial Targeting by MicroRNAs Co-ordinates Post-transcriptional Control of EMT. Cell Syst. 2018; 7(1):77-91.e7. DOI: 10.1016/j.cels.2018.05.019. View

12.

Dentelli P, Traversa M, Rosso A, Togliatto G, Olgasi C, Marchio C . miR-221/222 control luminal breast cancer tumor progression by regulating different targets. Cell Cycle. 2014; 13(11):1811-26. PMC: 4111727. DOI: 10.4161/cc.28758. View

13.

Cimmino A, Calin G, Fabbri M, Iorio M, Ferracin M, Shimizu M . miR-15 and miR-16 induce apoptosis by targeting BCL2. Proc Natl Acad Sci U S A. 2005; 102(39):13944-9. PMC: 1236577. DOI: 10.1073/pnas.0506654102. View

14.

Chang Y, Kuo W, Hung J, Lee C, Lee Y, Chang Y . Deregulated microRNAs in triple-negative breast cancer revealed by deep sequencing. Mol Cancer. 2015; 14:36. PMC: 4351690. DOI: 10.1186/s12943-015-0301-9. View

15.

Yang D, Sun Y, Hu L, Zheng H, Ji P, Pecot C . Integrated analyses identify a master microRNA regulatory network for the mesenchymal subtype in serous ovarian cancer. Cancer Cell. 2013; 23(2):186-99. PMC: 3603369. DOI: 10.1016/j.ccr.2012.12.020. View

16.

Liang H, Li W . MicroRNA regulation of human protein protein interaction network. RNA. 2007; 13(9):1402-8. PMC: 1950750. DOI: 10.1261/rna.634607. View

17.

Marisa L, De Reynies A, Duval A, Selves J, Gaub M, Vescovo L . Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS Med. 2013; 10(5):e1001453. PMC: 3660251. DOI: 10.1371/journal.pmed.1001453. View

18.

Friedman R, Farh K, Burge C, Bartel D . Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2008; 19(1):92-105. PMC: 2612969. DOI: 10.1101/gr.082701.108. View

19.

He J, Zhou Z, Reed M, Califano A . Accelerated parallel algorithm for gene network reverse engineering. BMC Syst Biol. 2017; 11(Suppl 4):83. PMC: 5615246. DOI: 10.1186/s12918-017-0458-5. View

20.

Martignetti L, Tesson B, Almeida A, Zinovyev A, Tucker G, Dubois T . Detection of miRNA regulatory effect on triple negative breast cancer transcriptome. BMC Genomics. 2015; 16:S4. PMC: 4460783. DOI: 10.1186/1471-2164-16-S6-S4. View