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An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia

Leukemia volume 25, pages 1639–1645 (2011)Cite this article

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The clinical course of chronic lymphocytic leukemia (CLL) is highly variable, ranging from slow progression and survival for several decades to rapidly progressive and chemotherapy-resistant disease with death within 1 year of diagnosis. The hierarchical model of common genomic aberrations determined by interphase fluorescence in situ hybridization (FISH) and the analysis of the mutational status of the immunoglobulin heavy-chain variable region genes (IGVH status) are broadly used molecular markers to predict the prognosis of CLL patients. Despite the high prognostic value of IGVH status and FISH analysis, the clinical course of some patients defies the predictions.1 Until now the presence of del(17p) or a TP53 mutation are the only established predictive markers for therapy response.2 However, they are infrequent in newly diagnosed patients (del(17p): 4%; additional TP53 mutation: 1.1%),3, 4 and sometimes misleading (overall survival (OS) rate 65% at 3 years in treatment-naïve patients).1 Thus, a more accurate easy assessable risk classifier for CLL patients is desirable.

To improve our ability to predict the prognosis of CLL patients, gene expression profiling (GEP) and microRNA expression levels were used to develop prognostic scores.5, 6 Calin et al.6 reported a molecular signature of 13 microRNAs associated with the expression of ZAP70, the mutational status of IGVH, and the time between diagnosis and initial treatment. Rodriguez et al.5 used a small custom oligonucleotide microarray to generate a prognostic model based on the expression of seven genes (including genes involved in Wnt and NF-κB signaling) for time to treatment (TTT) and validated this model in an independent CLL series. Although these studies provided new insights into the biology of CLL, all these signatures fell short of surpassing the traditional genetic markers in prognostic power; they were generated on small micro array platforms or were not validated using routine diagnostic techniques like real-time PCR (RT-PCR) or—most importantly—they were not shown to predict overall survival.

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Acknowledgements

We would like to thank the MCR, MCC and IBE for cooperation. Further we would like to thank the Laboratory for Leukemia Diagnostics for providing the microarray data and patient samples and, especially, Claudia and Torsten Haferlach, Frank Dicker, Alexander Kohlmann and Susanne Schnittger. Furthermore, we would like to thank Natalia Kerber and Evelyn Zellmeier for assistance in sample processing. T Herold was supported by the KL Weigand'schen Stiftung, the Curt-Bohnewands- Fonds and the Georg und Traud Gravenhorst–Stiftung and by the Deutsche Forschungsgemeinschaft, collaborative research center SFB 684 ‘Molecular mechanisms of normal and malignant hematopoiesis’. This work was in part supported by grants from the German Ministry of Research and Education (BMBF; 01GS0876) and the Deutsche Forschungsgemeinschaft (SFB 684) to C. Buske and SK Bohlander. V Jurinovic was supported by the German José Carreras Leukaemia Foundation (DJCLS H06/04V) and the BMBF medical systems biology project HaematoSYS (BMBF-FKZ 03415452I).

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  1. C Buske and S K Bohlander: Joint senior authors.

Authors and Affiliations

  1. Department of Internal Medicine III, University Hospital Grosshadern, Ludwig-Maximilians-University (LMU), Munich, Germany

    T Herold, K H Metzeler, M Bergmann, T Seiler, A Dufour, Z Pasalic, S Schneider, P M Kakadia, J Braess, K Spiekermann, W Hiddemann & S K Bohlander

  2. Institute for Medical Informatics, Biometry and Epidemiology (IBE), Ludwig-Maximilians-University (LMU), Munich, Germany

    V Jurinovic, A-L Boulesteix, M Schmidberger & U Mansmann

  3. Clinical Cooperative Group Acute Leukemia, Helmholtz Center Munich for Environmental Health, Munich, Germany

    M Mulaw, S Thoene, P M Kakadia, K Spiekermann, W Hiddemann & S K Bohlander

  4. Munich Cancer Registry (MCR) of the Munich Cancer Center (MCC) at the Institute for Medical Informatics, Biometry and Epidemiology (IBE), Ludwig-Maximilians-University (LMU), Munich, Germany

    M Schmidt

  5. Department of Internal Medicine III, University Hospital Ulm, Ulm, Germany

    M Bergmann & M Feuring-Buske

  6. Institute of Experimental Cancer Research, Comprehensive Cancer Center Ulm, University of Ulm, Ulm, Germany

    M Feuring-Buske & C Buske

Authors
  1. T Herold
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  2. V Jurinovic
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  18. U Mansmann
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  20. C Buske
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Corresponding authors

Correspondence to C Buske or S K Bohlander.

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The authors declare no conflict of interest.

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Herold, T., Jurinovic, V., Metzeler, K. et al. An eight-gene expression signature for the prediction of survival and time to treatment in chronic lymphocytic leukemia. Leukemia 25, 1639–1645 (2011). https://doi.org/10.1038/leu.2011.125

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