Prediction of Cytogenetic Abnormalities in Multiple Myeloma Based on Gene Expression Profiles

Abstract 629 Background: Cytogenetic abnormalities (CA) are a hallmark of multiple myeloma (MM) and other cancers and are commonly used as clinical parameters for determining disease stage and guiding therapy decisions. Traditional techniques, including fluorescence in situ hybridization (FISH) and karyotyping, and the recently developed array-based comparative genomic hybridization are expensive and time consuming. As gene expression profiling (GEP) is becoming more integrated in the diagnostic workup of MM and is increasingly being used for risk stratification as well as tailoring therapy, we are presented with vast amounts of data that should reflect disease associated alterations of the genome. We therefore sought to develop a GEP based vitual CA (vCA) model to predict CA in MM. Methods/Results: We determined genome-wide gene expression profiles and DNA copy numbers (CNs) in purified plasma cell samples obtained from 92 newly diagnosed MM patients, using the Affymetrix GeneChip and the Agilent aCGH platforms, respectively. We identified 1,114 CN-sensitive genes by Pearson9s correlation coefficient (PCC) of gene expression levels and the copy numbers of the corresponding DNA loci, keeping the false discovery rate to Conclusion: Our results provide a proof of concept that GEP data alone can reveal all the information provided by conventional cytogenetic techniques. We show that re-purposing gene expression data using our model is a fast and economical way to obtain cytogenetic information that is accurate and can be used for diagnosis and observation in MM and potentially other malignancies. GEP can serve as a one-stop genomic data source for information from the level of specific genes to whole chromosomes. Disclosures: Barlogie: Celgene: Consultancy, Honoraria, Research Funding; IMF: Consultancy, Honoraria; MMRF: Consultancy; Millennium: Consultancy, Honoraria, Research Funding; Genzyme: Consultancy; Novartis: Research Funding; NCI: Research Funding; Johnson & Johnson: Research Funding; Centocor: Research Funding; Onyx: Research Funding; Icon: Research Funding. Shaughnessy: Myeloma Health, Celgene, Genzyme, Novartis: Consultancy, Employment, Equity Ownership, Honoraria, Patents & Royalties.