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

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.

Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells.

Bone marrow plasma cells (PCs) from 74 patients with newly diagnosed multiple myeloma (MM), 5 with monoclonal gammopathy of undetermined significance (MGUS), and 31 healthy volunteers (normal PCs) were purified by CD138(+) selection. Gene expression of purified PCs and 7 MM cell lines were profiled using high-density oligonucleotide microarrays interrogating about 6800 genes. On hierarchical clustering analysis, normal and MM PCs were differentiated and 4 distinct subgroups of MM (MM1, MM2, MM3, and MM4) were identified. The expression pattern of MM1 was similar to normal PCs and MGUS, whereas MM4 was similar to MM cell lines. Clinical parameters linked to poor prognosis, abnormal karyotype (P =.002) and high serum beta(2)-microglobulin levels (P =.0005), were most prevalent in MM4. Also, genes involved in DNA metabolism and cell cycle control were overexpressed in a comparison of MM1 and MM4. In addition, using chi(2) and Wilcoxon rank sum tests, 120 novel candidate disease genes were identified that discriminate normal and malignant PCs (P <.0001); many are involved in adhesion, apoptosis, cell cycle, drug resistance, growth arrest, oncogenesis, signaling, and transcription. A total of 156 genes, including FGFR3 and CCND1, exhibited highly elevated ("spiked") expression in at least 4 of the 74 MM cases (range, 4-25 spikes). Elevated expression of these 2 genes was caused by the translocation t(4;14)(p16;q32) or t(11;14)(q13;q32). Thus, novel candidate MM disease genes have been identified using gene expression profiling and this profiling has led to the development of a gene-based classification system for MM.