Pidgeon, Tyler S.

Abstract Chromosome 13 (Δ13) abnormalities are found in greater than 50% of patients with Multiple Myeloma (MM). MM is most commonly defined by chromosome 13 monosomy or 13q loss (85%). Interstitial deletions comprise the remaining 15%. Many studies have revealed that Δ13 in MM are associated with poor survival and reduced response to therapy. Genes mapping to chromosome 13 may be involved in pathogenesis and/or progression of the disease due to loss of function from gene mutation or from epigenetic effects such as haploinsufficiency. In this study, array-based comparative genomic hybridization coupled with microarray technology (aCGH) is used to detect gene copy number loss on chromosome 13 from nine MM patient samples. Whole genome long-oligo microarrays constructed by Agilent Technologies were used which contain 40,000 genes that span the human genome with an average spatial resolution of ~75 kb. Using genomic DNA isolated from MM patients with interstitial deletions on chromosome 13, DNA was amplified, labeled and hybridized with a differentially labeled normal DNA reference to determine gene/genomic copy number changes. Arrays were analyzed to search for the minimum region of loss based upon single copy loss for a series of nearby mapping transcripts. A common region of loss of 2.2 Mb, at 13q14.2 was detected. Additionally, we investigated the correlation between genomic copy number change and the expression level for MM patients in the13q region. From an independent gene expression data set whose expression measurements were conducted with Affymetrix HG-U133A v2 microarrays, data was selected that corresponded to the samples used for current aCGH. Expression values from MM samples were divided by the mean expression values from 12 normal bone marrow samples for each gene and the resulting values were treated as surrogate ratios between MM and normal samples. Probes from both microarrays were then aligned according to their chromosomal positions and merged if their chromosomal positions overlapped. Composite chromosomal maps were generated that displayed the expression levels and copy number changes. The maps were used to differentiate chromosomal regions in 13q where copy number changes and expression levels show high correlation and regions where such correlation was not observed. Although the number of probes sampled in the expression microarray was much smaller than those in aCGH microarray, a chromosomal region of great interest, that encompasses 13q14.2, arose naturally from this analysis. Although the mechanism by which loss of 13q effects tumorigenesis in MM could be a haploinsufficiency model, we are not ruling out the presence of a tumor suppressor gene in this region. We are evaluating candidate tumor suppressor genes in the region for loss of function by mutational analysis and hypermethylation studies.

Abstract Chromosome 13 abnormalities (Δ13), monosomy or deletion, are seen in greater than 50% in patients with Multiple Myeloma (MM) and are associated with poor survival and reduced response to therapy. Δ13 is suggestive of a tumor suppressor model. In this study, we use a comprehensive, high-throughput approach involving array-based technologies to identify genes on chromosome 13 that are important in the pathogenesis and/or progression of MM. Array-based Comparative Genomic Hybridization (aCGH) is being conducted to identify a minimum region of 13q loss in a series of MM cell lines and patient samples. DNA is isolated, labeled and hybridized with a differentially labeled normal DNA reference to determine gene/genomic copy number changes. Arrays are analyzed to search for the minimum region of loss based upon single copy loss for a series of nearby mapping transcripts in each cell line. Data will be cross-referenced to determine the true minimum region of 13q loss in MM. Also, to discover genes harboring potential inactivating mutations, we are using inhibition of nonsense-mediated RNA decay (NMD) coupled with cDNA microarray. This modification of the Gene Identification by NMD Inhibition (GINI) method, first introduced by Noensie and Dietz (2001), is used to identify genes on chromosome 13 that may be inactivated due to premature truncating codons (PTCs). This method is based upon a cell’s natural ability to survey for and degrade RNA species that contain PTCs by activation of the nonsense mediated RNA decay (NMD) pathway. Treating cells with the drug Emetine can inhibit NMD and increase the expression of genes likely harboring truncating mutations. Preliminary data have revealed several candidate genes, with increased ratios after Emetine treatment, which map to chromosome 13. Upon defining a minimum region of loss based upon aCGH data, we will prioritize genes from our NMD study for mutational analysis. It our hope to also perform an array-based CpG island screen to simultaneously analyze all CpG islands on chromosome 13 to detect genes possibly inactivated by hypermethylation. This comprehensive, organized approach incorporating high-throughput techniques for the detection of genomic loss, mutation, and methylation is the first of its kind to our knowledge and may maximize the potential for the identification of a 13q tumor suppressor in MM.