title: Prediction of survival in multiple myeloma based on gene expression profiles reveals cell cycle and chromosomal instability signatures in high-risk patients and hyperdiploid signatures in low-risk patients: a study of the Intergroupe Francophone du Myélome.
abstract: OBJECTIVE
  Survival of patients with multiple myeloma is highly heterogeneous, from periods of a few weeks to more than 10 years. We used gene expression profiles of myeloma cells obtained at diagnosis to identify broadly applicable prognostic markers.
  
  
  METHODS
  In a training set of 182 patients, we used supervised methods to identify individual genes associated with length of survival. A survival model was built from these genes. The validity of our model was assessed in our test set of 68 patients and in three independent cohorts comprising 853 patients with multiple myeloma.
  
  
  RESULTS
  The 15 strongest genes associated with the length of survival were used to calculate a risk score and to stratify patients into low-risk and high-risk groups. The survival-predictor score was significantly associated with survival in both the training and test sets and in the external validation cohorts. The Kaplan-Meier estimates of rates of survival at 3 years were 90.5% (95% CI, 85.6% to 95.3%) and 47.4% (95% CI, 33.5% to 60.1%), respectively, in our patients having a low risk or high risk independently of traditional prognostic factors. High-risk patients constituted a homogeneous biologic entity characterized by the overexpression of genes involved in cell cycle progression and its surveillance, whereas low-risk patients were heterogeneous and displayed hyperdiploid signatures.
  
  
  CONCLUSIONS
  Gene expression-based survival prediction and molecular features associated with high-risk patients may be useful for developing prognostic markers and may provide basis to treat these patients with new targeted antimitotics.
authors.affiliation: L'Institut National de la Santé et de la Recherche Médicale, U892, University of Nantes, University, Hospital, Hematology Laboratory, Nantes, France.
authors.forename: Olivier
authors.initials: O
authors.lastname: Decaux
authors.forename: Laurence
authors.initials: L
authors.lastname: Lodé
authors.forename: Florence
authors.initials: F
authors.lastname: Magrangeas
authors.forename: Catherine
authors.initials: C
authors.lastname: Charbonnel
authors.forename: Wilfried
authors.initials: W
authors.lastname: Gouraud
authors.forename: Pascal
authors.initials: P
authors.lastname: Jézéquel
authors.forename: Michel
authors.initials: M
authors.lastname: Attal
authors.forename: Jean-Luc
authors.initials: JL
authors.lastname: Harousseau
authors.forename: Philippe
authors.initials: P
authors.lastname: Moreau
authors.forename: Régis
authors.initials: R
authors.lastname: Bataille
authors.forename: Loïc
authors.initials: L
authors.lastname: Campion
authors.forename: Hervé
authors.initials: H
authors.lastname: Avet-Loiseau
authors.forename: Stéphane
authors.initials: S
authors.lastname: Minvielle
mesh_terms: D000465:Algorithms; D002453:Cell Cycle / Q000235:genetics*; D043171:Chromosomal Instability / Q000235:genetics*; D004171:Diploidy; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D009101:Multiple Myeloma / Q000235:genetics*; D011379:Prognosis; D016019:Survival Analysis