Project description:Primary plasma cell leukaemia (pPCL) is a rare, yet aggressive form of de novo plasma cell tumor, distinguished from secondary PCL (sPCL) which represents a leukemic transformation of pre-existing multiple myeloma (MM). Here, we performed a comprehensive molecular analysis of a prospective series of pPCLs by means of FISH, single nucleotide polymorphism (SNP) array and gene expression profiling (GEP). IGH@ translocations were identified in 87% of pPCL cases, with prevalence of t(11;14) (40%) and t(14;16) (30.5%), whereas the most frequently altered regions were located at 1p (38%), 1q (48%), 6q (29%), 8p (42%), 13q (74%), 14q (71%), 16q (53%) and 17p (35%). A relevant finding of our study was the identification of a minimal biallelical deletion (1.5 Mb) in 8p21.2 encompassing the putative tumor suppressor gene PPP2R2A that was significantly down-regulated in deleted cases. Mutations of TP53 were identified in 4 cases all but one associated with a monoallelic deletion of the gene, whereas activating mutations of BRAF occurred in one case and were absent for N- and K-RAS. To evaluate the influence of allelic imbalances in transcriptional expression we performed an integrated genomic analysis with GEP data, showing a significant dosage effect of genes involved in transcription, translation, methyltransferases activity, apoptosis as well as Wnt and NF-kB signaling pathways. Overall, we provide a compendium of genomic alterations in a prospective series of pPCLs which may contribute to our understanding of this particular form of plasma cell dyscrasia and to better elucidate the mechanisms of tumor progression in MM. This series of microarray experiments contains the genome-wide profiles of 17 primary Plasma Cell Leukemia. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 90 micrograms of fragmented biotin-labeled DNA were hybridized on GeneChip Human Mapping 250K NspI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChipÂ® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. The raw data for individual SNPs were extracted from CEL files and converted into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares using the Hidden Markov Model algorithm with a genomic smoothing window set to 0. After the pre-processing, piecewise constant estimates of the underlying local DNA copy number (CN) variation was calculated using the DNAcopy Bioconductor package, which looks for optimal breakpoints using circular binary segmentation (CBS). genotyping analysis of 17 primary Plasma Cell Leukemia

Project description:A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide dosage effect on gene and microRNA expression Multiple myeloma (MM) is characterized by marked genomic instability. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To better elucidate the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. Using a self-developed procedure to infer exact local copy numbers for each sample, we identified a significant fraction of patients showing marked aneuploidy. A conventional clustering analysis showed that aneuploidy, chromosome 1 alterations, hyperdiploidy and recursive deletions at 1p and chromosomes 13, 14 and 22 were the main aberrations driving samples grouping. Then, we integrated mapping information with gene and microRNAs expression profiles: a multiclass analysis of the identified clusters showed a marked gene-dosage effect, particularly concerning 1q transcripts, also confirmed by correlating gene expression levels and local copy number alterations. A wide dosage effect affected also microRNAs, indicating that structural abnormalities in MM closely reflect in their expression imbalances. Finally, we identified several loci in which genes and microRNAs expression correlated with loss-of-heterozygosity occurrence. Our results provide insights into the composite network linking genome structure and gene/microRNA transcriptional features in MM. Keywords: Integrated genomics approach based on SNP microarray and FISH procedures to detect allelic imbalances in multiple myeloma. Pathological bone marrow specimens from 41 MM and four plasma cell leukemia (PCL) patients at diagnosis. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 40 micrograms of fragmented biotin-labelled DNA were hybridized on GeneChip Human Mapping 50K XbaI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChip® Operating Software (GCOS version 1.4). Copy number values for individual SNPs were extracted and converted from CEL files into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares. Genomic Smoothing analysis was performed by using the smoothing window of 0 Mb, and inferred copy number states were derived from a Hidden Markov Model (HMM) based algorithm implemented in CNAT 4.0.1. Circular Binary Segmentation (Ohlsen et al., 2004) was applied using DNAcopy package for R Bioconductor on raw data. FBN procedure was finally applied to infer exact local copy number as described in the mentioned Reference.

Project description:Multiple myeloma (MM) is characterized by marked genomic instability. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To better elucidate the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. Using a self-developed procedure to infer exact local copy numbers for each sample, we identified a significant fraction of patients showing marked aneuploidy. A conventional clustering analysis showed that aneuploidy, chromosome 1 alterations, hyperdiploidy and recursive deletions at 1p and chromosomes 13, 14 and 22 were the main aberrations driving samples grouping. Then, we integrated mapping information with gene and microRNAs expression profiles: a multiclass analysis of the identified clusters showed a marked gene-dosage effect, particularly concerning 1q transcripts, also confirmed by correlating gene expression levels and local copy number alterations. A wide dosage effect affected also microRNAs, indicating that structural abnormalities in MM closely reflect in their expression imbalances. Finally, we identified several loci in which genes and microRNAs expression correlated with loss-of-heterozygosity occurrence. Our results provide insights into the composite network linking genome structure and gene/microRNA transcriptional features in MM. Experiment Overall Design: This series of microarray experiments contains the gene expression profiles of purified plasma cells (PCs) obtained from 4 normal donor (N), 11 monoclonal gammopathy of undetermined significance (MGUS), 133 multiple myeloma (MM) and 9 plasma cell leukemia (PCL) at diagnosis. PCs were purified from bone marrow specimens, after red blood cell lysis with 0.86% ammonium chloride, using CD138 immunomagnetic microbeads. The purity of the positively selected PCs was assessed by morphology and flow cytometry and was > 90% in all cases. 5 micrograms of total RNA was processed and, in accordance with the manufacturer's protocols, 15 micrograms of fragmented biotin-labelled cRNA were hybridized on GeneChip Human Genome U133A Arrays (Affymetrix Inc.). The arrays were scanned using the Agilent GeneChip Scanner G2500A. The images were acquired using Affymetrix MicroArray Suite (MAS) 5.0 software and the probe level data converted to expression values using the Bioconductor function for the Robust Multi-Array average (RMA) procedure (Irizarry et al, 2003), in which perfect match intensities are background adjusted, quantile-quantile normalised and log2 transformed.

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