title: Regulatory network reconstruction reveals genes with prognostic value for chronic lymphocytic leukemia.
abstract: BACKGROUND
  The clinical course of chronic lymphocytic leukemia (CLL) is highly variable; some patients follow an indolent course, but others progress to a more advanced stage. The mutational status of rearranged immunoglobulin heavy chain variable (IGVH) genes in CLL is a feature that is widely recognized for dividing patients into groups that are related to their prognoses. However, the regulatory programs associated with the IGVH statuses are poorly understood, and markers that can precisely predict survival outcomes have yet to be identified.
  
  
  METHODS
  In this study, (i) we reconstructed gene regulatory networks in CLL by applying an information-theoretic approach to the expression profiles of 5 cohorts. (ii) We applied master regulator analysis (MRA) to these networks to identify transcription factors (TFs) that regulate an IGVH mutational status signature. The IGVH mutational status signature was developed by searching for differentially expressed genes between the IGVH mutational statuses in numerous CLL cohorts. (iii) To evaluate the biological implication of the inferred regulators, prognostic values were determined using time to treatment (TTT) and overall survival (OS) in two different cohorts.
  
  
  RESULTS
  A robust IGVH expression signature was obtained, and various TFs emerged as regulators of the signature in most of the reconstructed networks. The TF targets expression profiles exhibited significant differences with respect to survival, which allowed the definition of a reduced profile with a high value for OS. TCF7 and its targets stood out for their roles in progression.
  
  
  CONCLUSIONS
  TFs and their targets, which were obtained merely from inferred regulatory associations, have prognostic implications and reflect a regulatory context for prognosis.
authors.affiliation: Facultad de Ciencias, Departamento de Ciencias Biológicas, Universidad de los Andes, Bogotá D.C., Colombia. sl.yepes233@uniandes.edu.co.
authors.forename: Sally
authors.initials: S
authors.lastname: Yepes
authors.affiliation: Facultad de Ciencias, Departamento de Ciencias Biológicas, Universidad de los Andes, Bogotá D.C., Colombia. maritorr@uniandes.edu.co.
authors.forename: Maria Mercedes
authors.initials: MM
authors.lastname: Torres
authors.affiliation: Departamento de Estadística, Universidad Nacional de Colombia, Bogotá D.C., Colombia. llopezk@unal.edu.co.
authors.forename: Liliana
authors.initials: L
authors.lastname: López-Kleine
mesh_terms: D014408:Biomarkers, Tumor; D019295:Computational Biology / Q000379:methods; D030561:Databases, Nucleic Acid; D005260:Female; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D053263:Gene Regulatory Networks; D006801:Humans; D007143:Immunoglobulin Heavy Chains / Q000235:genetics; D007135:Immunoglobulin Variable Region / Q000235:genetics; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000235:genetics* / Q000378:metabolism / Q000401:mortality*; D008297:Male; D015201:Meta-Analysis as Topic; D009154:Mutation; D011379:Prognosis; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D014408:Biomarkers, Tumor; D007143:Immunoglobulin Heavy Chains; D007135:Immunoglobulin Variable Region; D014157:Transcription Factors