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Blood, 15 March 2007, Vol. 109, No. 6, pp. 2276-2284.
Prepublished online as a Blood First Edition Paper on November 14, 2006; DOI 10.1182/blood-2006-07-038430.


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PLENARY PAPER

A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1

John D. Shaughnessy, Jr1, Fenghuang Zhan1, Bart E. Burington2, Yongsheng Huang1, Simona Colla1, Ichiro Hanamura1, James P. Stewart1, Bob Kordsmeier1, Christopher Randolph1, David R. Williams1, Yan Xiao1, Hongwei Xu1, Joshua Epstein1, Elias Anaissie1, Somashekar G. Krishna1, Michele Cottler-Fox1, Klaus Hollmig1, Abid Mohiuddin1, Mauricio Pineda-Roman1, Guido Tricot1, Frits van Rhee1, Jeffrey Sawyer1, Yazan Alsayed1, Ronald Walker1, Maurizio Zangari1, John Crowley2, and Bart Barlogie1

1 Donna D. and Donald M. Lambert Laboratory of Myeloma Genetics at the Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock; 2 Cancer Research and Biostatistics, Seattle, WA

To molecularly define high-risk disease, we performed microarray analysis on tumor cells from 532 newly diagnosed patients with multiple myeloma (MM) treated on 2 separate protocols. Using log-rank tests of expression quartiles, 70 genes, 30% mapping to chromosome 1 (P < .001), were linked to early disease-related death. Importantly, most up-regulated genes mapped to chromosome 1q, and down-regulated genes mapped to chromosome 1p. The ratio of mean expression levels of up-regulated to down-regulated genes defined a high-risk score present in 13% of patients with shorter durations of complete remission, event-free survival, and overall survival (training set: hazard ratio [HR], 5.16; P < .001; test cohort: HR, 4.75; P < .001). The high-risk score also was an independent predictor of outcome endpoints in multivariate analysis (P < .001) that included the International Staging System and high-risk translocations. In a comparison of paired baseline and relapse samples, the high-risk score frequency rose to 76% at relapse and predicted short postrelapse survival (P < .05). Multivariate discriminant analysis revealed that a 17-gene subset could predict outcome as well as the 70-gene model. Our data suggest that altered transcriptional regulation of genes mapping to chromosome 1 may contribute to disease progression, and that expression profiling can be used to identify high-risk disease and guide therapeutic interventions.


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