title: A supervised network analysis on gene expression profiles of breast tumors predicts a 41-gene prognostic signature of the transcription factor MYB across molecular subtypes.
abstract: BACKGROUND
  MYB is predicted to be a favorable prognostic predictor in a breast cancer population. We proposed to find the inferred mechanism(s) relevant to the prognostic features of MYB via a supervised network analysis.
  
  
  METHODS
  Both coefficient of intrinsic dependence (CID) and Galton Pierson's correlation coefficient (GPCC) were combined and designated as CIDUGPCC. It is for the univariate network analysis. Multivariate CID is for the multivariate network analysis. Other analyses using bioinformatic tools and statistical methods are included.
  
  
  RESULTS
  ARNT2 is predicted to be the essential gene partner of MYB. We classified four prognostic relevant gene subpools in three breast cancer cohorts as feature types I-IV. Only the probes in feature type II are the potential prognostic feature of MYB. Moreover, we further validated 41 prognosis relevant probes to be the favorable prognostic signature. Surprisingly, two additional family members of MYB are elevated to promote poor prognosis when both levels of MYB and ARNT2 decline. Both MYBL1 and MYBL2 may partially decrease the tumor suppressive activities that are predicted to be up-regulated by MYB and ARNT2.
  
  
  CONCLUSIONS
  The major prognostic feature of MYB is predicted to be determined by the MYB subnetwork (41 probes) that is relevant across subtypes.
authors.affiliation: Biometry Division, Department of Agronomy, National Taiwan University, Taipei 106, Taiwan.
authors.forename: Li-Yu D
authors.initials: LY
authors.lastname: Liu
authors.affiliation: Department of Obstetrics and Gynecology, College of Medicine, National Taiwan University, Taipei 100, Taiwan.
authors.forename: Li-Yun
authors.initials: LY
authors.lastname: Chang
authors.affiliation: Department of Surgery, College of Medicine, National Taiwan University, Taipei 100, Taiwan.
authors.forename: Wen-Hung
authors.initials: WH
authors.lastname: Kuo
authors.affiliation: Department of Obstetrics and Gynecology, College of Medicine, National Taiwan University, Taipei 100, Taiwan.
authors.forename: Hsiao-Lin
authors.initials: HL
authors.lastname: Hwa
authors.affiliation: Department of Surgery, College of Medicine, National Taiwan University, Taipei 100, Taiwan ; Cheng Ching General Hospital, Taichung 400, Taiwan.
authors.forename: King-Jen
authors.initials: KJ
authors.lastname: Chang
authors.affiliation: Department of Obstetrics and Gynecology, College of Medicine, National Taiwan University, Taipei 100, Taiwan ; Research Center for Developmental Biology and Regenerative Medicine, National Taiwan University, Taipei 100, Taiwan.
authors.forename: Fon-Jou
authors.initials: FJ
authors.lastname: Hsieh
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000378:metabolism; D001943:Breast Neoplasms / Q000473:pathology*; D015331:Cohort Studies; D019295:Computational Biology / Q000379:methods; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007150:Immunohistochemistry; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D020598:Proto-Oncogene Proteins c-myb / Q000378:metabolism*; D015398:Signal Transduction; D014158:Transcription, Genetic
chemical_list: D014408:Biomarkers, Tumor; D020598:Proto-Oncogene Proteins c-myb