title: Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer.
abstract: In this work an integrated approach was used to identify functional miRNAs regulating gene pathway cross-talk in breast cancer (BC). We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes. For each pair of pathways, a score was derived from the distribution of gene expression levels by quantifying their pathway cross-talk. Random forest classification allowed the identification of pairs of pathways with high cross-talk. We assessed miRNAs regulating the identified gene pathways by a mutual information analysis. A Fisher test was applied to demonstrate their significance in the regulated pathways. Our results suggest interesting networks of pathways that could be key regulatory of target genes in BC, including stem cell pluripotency, coagulation, and hypoxia pathways and miRNAs that control these networks could be potential biomarkers for diagnostic, prognostic, and therapeutic development in BC. This work shows that standard methods of predicting normal and tumor classes such as differentially expressed miRNAs or transcription factors could lose intrinsic features; instead our approach revealed the responsible molecules of the disease.
authors.affiliation: Interuniversity Institute of Bioinformatics in Brussels (IB) , 1050 Brussels, Belgium ; Machine Learning Group, ULB, 1050 Brussels, Belgium.
authors.forename: Antonio
authors.initials: A
authors.lastname: Colaprico
authors.affiliation: IBFM-CNR, Segrate, 20090 Milan, Italy.
authors.forename: Claudia
authors.initials: C
authors.lastname: Cava
authors.affiliation: IBFM-CNR, Segrate, 20090 Milan, Italy.
authors.forename: Gloria
authors.initials: G
authors.lastname: Bertoli
authors.affiliation: Interuniversity Institute of Bioinformatics in Brussels (IB) , 1050 Brussels, Belgium ; Machine Learning Group, ULB, 1050 Brussels, Belgium.
authors.forename: Gianluca
authors.initials: G
authors.lastname: Bontempi
authors.affiliation: IBFM-CNR, Segrate, 20090 Milan, Italy.
authors.forename: Isabella
authors.initials: I
authors.lastname: Castiglioni
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics; D001943:Breast Neoplasms / Q000235:genetics* / Q000473:pathology; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics*; D052138:Genes, Neoplasm / Q000235:genetics; D005819:Genetic Markers / Q000235:genetics; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D009361:Neoplasm Invasiveness; D020239:Receptor Cross-Talk; D015398:Signal Transduction / Q000235:genetics*; D018511:Systems Integration
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers; D035683:MicroRNAs