title: A molecular score by quantitative PCR as a new prognostic tool at diagnosis for chronic lymphocytic leukemia patients.
abstract: BACKGROUND
  Several markers have been proposed to predict the outcome of chronic lymphocytic leukemia (CLL) patients. However, discordances exist between the current prognostic factors, indicating that none of these factors are totally perfect.
  
  
  RESULTS
  Here, we compared the prognostic power of new RNA-based markers in order to construct a quantitative PCR (qPCR) score composed of the most powerful factors. ZAP70, LPL, CLLU1, microRNA-29c and microRNA-223 were measured by real time PCR in a cohort of 170 patients with a median follow-up of 64 months (range3-330). For each patient, cells were obtained at diagnosis and RNA was extracted from purified CD19 cells. The best markers were included in a qPCR score, which was thereafter compared to each individual factor. Statistical analysis showed that all five RNA-based markers can predict treatment-free survival (TFS), but only ZAP70, LPL and microRNA-29c could significantly predict overall survival (OS). These three markers were thus included in a simple qPCR score that was able to significantly predict TFS and OS by dividing patients into three groups (0/3, 1-2/3 and 3/3). Median TFS were >210, 61 and 24 months (P<0.0001) and median OS were >330, 242 and 137 months (P<0.0001), respectively. Interestingly, TFS results were also confirmed in Binet stage A patients (P<0.0001). When compared to other classical factors, this score displays the highest univariate Cox hazard ratio (TFS: HR=9.45 and OS: HR=13.88) but also provides additional prognostic information.
  
  
  CONCLUSIONS
  In our hands, this score is the most powerful tool for CLL risk stratification at the time of diagnosis.
authors.affiliation: Laboratory of Experimental Hematology, Faculty of Medicine, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium. bstamato@ulb.ac.be
authors.forename: Basile
authors.initials: B
authors.lastname: Stamatopoulos
authors.forename: Nathalie
authors.initials: N
authors.lastname: Meuleman
authors.forename: Cécile
authors.initials: C
authors.lastname: De Bruyn
authors.forename: Karlien
authors.initials: K
authors.lastname: Pieters
authors.forename: Géraldine
authors.initials: G
authors.lastname: Anthoine
authors.forename: Philippe
authors.initials: P
authors.lastname: Mineur
authors.forename: Dominique
authors.initials: D
authors.lastname: Bron
authors.forename: Laurence
authors.initials: L
authors.lastname: Lagneaux
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000235:genetics*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000175:diagnosis* / Q000235:genetics*; D008297:Male; D008875:Middle Aged; D016133:Polymerase Chain Reaction / Q000379:methods*; D011379:Prognosis
chemical_list: D014408:Biomarkers, Tumor