title: Inferred miRNA activity identifies miRNA-mediated regulatory networks underlying multiple cancers.
abstract: BACKGROUND
  MicroRNAs (miRNAs) play a key role in regulating tumor progression and metastasis. Identifying key miRNAs, defined by their functional activities, can provide a deeper understanding of biology of miRNAs in cancer. However, miRNA expression level cannot accurately reflect miRNA activity.
  
  
  RESULTS
  We developed a computational approach, ActMiR, for identifying active miRNAs and miRNA-mediated regulatory mechanisms. Applying ActMiR to four cancer datasets in The Cancer Genome Atlas (TCGA), we showed that (i) miRNA activity was tumor subtype specific; (ii) genes correlated with inferred miRNA activities were more likely to enrich for miRNA binding motifs; (iii) expression levels of these genes and inferred miRNA activities were more likely to be negatively correlated. For the four cancer types in TCGA we identified 77-229 key miRNAs for each cancer subtype and annotated their biological functions. The miRNA-target pairs, predicted by our ActMiR algorithm but not by correlation of miRNA expression levels, were experimentally validated. The functional activities of key miRNAs were further demonstrated to be associated with clinical outcomes for other cancer types using independent datasets. For ER(-)/HER2(-) breast cancers, we identified activities of key miRNAs let-7d and miR-18a as potential prognostic markers and validated them in two independent ER(-)/HER2(-) breast cancer datasets. Our work provides a novel scheme to facilitate our understanding of miRNA. In summary, inferred activity of key miRNA provided a functional link to its mediated regulatory network, and can be used to robustly predict patient's survival.
  
  
  METHODS
  the software is freely available at http://research.mssm.edu/integrative-network-biology/Software.html.
  
  
  BACKGROUND
  jun.zhu@mssm.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology.
authors.forename: Eunjee
authors.initials: E
authors.lastname: Lee
authors.affiliation: Department of Medicine, Hematology and Medical Oncology and.
authors.forename: Koichi
authors.initials: K
authors.lastname: Ito
authors.affiliation: Department of Genetics and Genomic Sciences.
authors.forename: Yong
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
authors.forename: Eric E
authors.initials: EE
authors.lastname: Schadt
authors.affiliation: Department of Medicine, Hematology and Medical Oncology and The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
authors.forename: Hanna Y
authors.initials: HY
authors.lastname: Irie
authors.affiliation: Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
authors.forename: Jun
authors.initials: J
authors.lastname: Zhu
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics; D045744:Cell Line, Tumor; D015331:Cohort Studies; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D035683:MicroRNAs / Q000235:genetics / Q000378:metabolism*; D058977:Molecular Sequence Annotation; D009369:Neoplasms / Q000235:genetics*; D011379:Prognosis; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D012984:Software; D015996:Survival Rate
chemical_list: D035683:MicroRNAs; D012333:RNA, Messenger