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Blood, 15 April 2007, Vol. 109, No. 8, pp. 3177-3188.
Prepublished online as a Blood First Edition Paper on December 21, 2006; DOI 10.1182/blood-2006-09-044974.
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CLINICAL TRIALS AND OBSERVATIONS
Gene expression profiling and correlation with outcome in clinical trials of the proteasome inhibitor bortezomib
George Mulligan1,
Constantine Mitsiades2,
Barb Bryant1,
Fenghuang Zhan3,
Wee J. Chng4,
Steven Roels1,
Erik Koenig1,
Andrew Fergus1,
Yongsheng Huang3,
Paul Richardson2,
William L. Trepicchio1,
Annemiek Broyl5,
Pieter Sonneveld5,
John D. Shaughnessy, Jr3,
P. Leif Bergsagel4,
David Schenkein1,
Dixie-Lee Esseltine1,
Anthony Boral1, and
Kenneth C. Anderson2
1 Millennium Pharmaceuticals, Cambridge, MA;
2 Dana-Farber Cancer Institute, Boston, MA;
3 Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock;
4 Mayo Clinic, Scottsdale, AZ;
5 Department of Hematology, Erasmus Medical Centre, Rotterdam, The Netherlands
The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents.

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