Identification of Survival Critical Genomic Gains or Losses in Myeloma (MM) Using Array-Comparative Genomic Hybridization (aCGH).

Genetic abnormalities are important in the pathobiology of myeloma and established prognostic factors. High-density aCGH allow global unbiased detection of genomic gains and losses. In this study, we attempt to identify survival critical genomic aberrations by correlating aCGH-defined abnormalities with survival in 2 different cohorts of patients. aCGH was performed in 64 MM patients treated with high dose therapy from the Mayo Clinic using Agilent’s 44k DNA microarray genechip. In addition, a publicly available aCGH dataset performed in 67 MM patients treated with total therapy from the University of Arkansas Medical School using the lower density Agilent 22k chip (Human 1A v2) was also analyzed. Base 2 logarithms of the ratios between red and green intensities (log-ratios) were treated as a primary measure of copy number ratio between tumor and normal samples. To detect the regions of genomic aberration, values of a sliding window of 15 consecutive log-ratios were compared with those of an artificial ‘reference’ chromosome using the Wilcoxon rank sum test. The reference chromosome, constructed for each sample, was assembled by collecting log-ratio values close to zero. For this, 15 randomly sampled log-ratios from autosomal regions whose p-value of Wilcoxon signed rank test against 0 was larger than 0.05 were recursively accepted until the number of log-ratios in the assembled reference chromosome reached 1000. The p-values and their corresponding false discovery rates (q-values) for the copy number gain or loss were calculated independently for each sliding window and assigned to the center position of corresponding sliding window. The survival difference was examined between samples that had gained or lost a chromosomal region (sliding window) and samples that had not using the method of Kaplan-Meier and the statistical significance was assessed by the log-rank test. The sliding window was identified as gained or lost if P-value < 10 ⁻⁴ and Q-value < 10[suo]-3. Sliding windows whose gains or losses led to poor survival with log-rank test p-value < 0.5, corresponding q-value < 0.5, and happened to ≥ 10% of all samples were retained. Several regions of genomic gains and losses were significantly associated with poorer survival with 5 deletion hotspots common between the 2 datasets (Table). We validated the prognostic significance of these survival critical loci using FISH in an independent dataset of 169 patients treated with high dose therapy. Clustering of these survival critical loci revealed clusters of MM characterized by low, intermediate or high number of these abnormalities, which are independent of ploidy and translocations subtypes. These subgroups have significantly different survival. In addition, the clustering analysis suggests the chromosome 13 loss is an early event whereas chromosome 1 abnormalities are late events. Our strategy therefore identified novel regions of genomic aberration that are important prognostically. However, it is likely that these regions are manifestation of genomically unstable tumors with complex abnormalities that have poorer prognosis.