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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.
 Previous Article | Next Article 
Submitted July 31, 2006
Accepted October 27, 2006
A validated gene expression model of high-risk multiple myeloma is defined by deregulated expression of genes mapping to chromosome 1
John D Shaughnessy, Jr*, Fenghuang Zhan, Bart E Burington, Yongsheng Huang, Simona Colla, Ichiro Hanamura, James P Stewart, Bob Kordsmeier, Christopher Randolph, David R Williams, Yan Xiao, Hongwei Xu, Joshua Epstein, Elias Anaissie, Somashekar G Krishna, Michele Cottler-Fox, Klaus Hollmig, Abid Mohiuddin, Mauricio Pineda-Roman, Guido Tricot, Frits van Rhee, Jeffrey Sawyer, Yazan Alsayed, Ronald Walker, Maurizio Zangari, John Crowley, and Bart Barlogie
University of Arkansas for Medical Sciences, Little Rock, AR
Cancer Research and Biostatistics, Seattle, WA
* Corresponding author; email: shaughnessyjohn{at}uams.edu.
To molecularly define high-risk disease, we performed microarray analysis on tumor cells from 532 newly diagnosed patients with multiple myeloma (MM) treated on two 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, the majority of up-regulated genes mapped to chromosome 1q and of down-regulated genes mapped to chromosome 1p. The ratio of mean expression levels of up- to down-regulated genes defined a high-risk score present in 13% of patients with shorter durations of complete remission, event-free and overall survival (training set: HR 5.16, P < .0001; test cohort: HR 4.75, P < .0001). The high-risk score also was an independent predictor of outcome endpoints in multivariate analysis (P < .0001) 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 post-relapse survival (P < .05). Multivariate discriminant analysis revealed that a 17-gene subset could predict outcome a 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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