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.
journal_name
Nucleic Acids Resjournal_title
Nucleic acids researchauthors
Cantini L,Bertoli G,Cava C,Dubois T,Zinovyev A,Caselle M,Castiglioni I,Barillot E,Martignetti Ldoi
10.1093/nar/gkz016subject
Has Abstractpub_date
2019-03-18 00:00:00pages
2205-2215issue
5eissn
0305-1048issn
1362-4962pii
5290485journal_volume
47pub_type
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