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

Author:

Shaughnessy John D.1,Zhan Fenghuang1,Burington Bart E.2,Huang Yongsheng1,Colla Simona1,Hanamura Ichiro1,Stewart James P.1,Kordsmeier Bob1,Randolph Christopher1,Williams David R.1,Xiao Yan1,Xu Hongwei1,Epstein Joshua1,Anaissie Elias1,Krishna Somashekar G.1,Cottler-Fox Michele1,Hollmig Klaus1,Mohiuddin Abid1,Pineda-Roman Mauricio1,Tricot Guido1,van Rhee Frits1,Sawyer Jeffrey1,Alsayed Yazan1,Walker Ronald1,Zangari Maurizio1,Crowley John2,Barlogie Bart1

Affiliation:

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

Abstract

Abstract 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.

Publisher

American Society of Hematology

Subject

Cell Biology,Hematology,Immunology,Biochemistry

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