Genomic Complexity and Recurrent Aberration in Multiple Myeloma: Analysis of a Compendium of aCGH and Gene Expression Profiles.

Abstract

Multiple Myeloma (MM) is the second most prevalent haematological disorder in the US with great recent progress propelled by various technological and therapeutic advances. Nevertheless, the complexity of MM genomes remains inadequately characterized. We have combined high-resolution (44K Agilent) array comparative genomic hybridization (aCGH) and gene expression data with clinical outcomes in an initial attempt at indexing genomic complexity in MM and its clinical implication in 100 MM patients. We enumerated the Number of Aberrations per Tumor (NAPT) as defined by the ADM-1 algorithm available within CGH Analytics. There appear to be no difference in degree of genetic complexity between hyperdiploid and non-hyperdiploid myeloma. Generally, t(11;14) have low NAPT whereas D2 tumors have high NAPT. Amongst the high-risk genetic subtypes, tumors with maf translocations have relatively low NAPT whereas t(4;14) have high NAPT. Whilst a Multivariate Cox Proportional Hazards regression of survival outcome showed little statistical support for popular indicators such as ploidy and TC classification, results for NAPT were considerably more encouraging (p~ 0.07, median survival of 40 months in low complexity vs 18 months in high). Log-rank tests further supported prognosis based on NAPT independent of clinical status and ploidy. To characterize complexity, we clustered aCGH profiles by clinical status, ploidy and TC classification. Clear patterns of aggregation and recurrent aberration were observed suggesting that they were possibly instrument to aberrant gene expression. Indeed, expression of a large proportion of genes approximately 2Mb of the recurrent breakpoints varied significantly between patients carrying aberrations vis-a-viz others that did not. Comparison against known gene sets showed an enrichment for cell-cycle and apoptosis genes. We are presently characterizing several such breakpoint-associated genes for their functional significance.