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J Clin Oncol. 2008 Oct 10;26(29):4798-805. doi: 10.1200/JCO.2007.13.8545. Epub 2008 Jun 30.

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.

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  • 1L'Institut National de la Santé et de la Recherche Médicale, U892, University of Nantes, University, Hospital, Hematology Laboratory, Nantes, France.

Abstract

PURPOSE:

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.

PATIENTS AND 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.

CONCLUSION:

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.

PMID:
18591550
[PubMed - indexed for MEDLINE]
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