title: A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide gene dosage effect.
abstract: Multiple myeloma (MM) is characterized by marked genomic heterogeneity. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To elucidate better the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. We firstly generated genome-wide profiles of 41 MMs and four plasma cell leukemias, using a self-developed procedure to infer exact local copy numbers (CNs) for each sample. Our analysis allowed the identification of a significant fraction of patients showing near-tetraploidy. Furthermore, a conventional hierarchical clustering analysis showed that near-tetraploidy, 1q gain, hyperdiploidy, and recursive deletions at 1p and chromosomes 13, 14, and 22 were the main aberrations driving samples grouping. Moreover, mapping information was integrated with gene expression profiles of the tumor samples. A multiclass analysis of transcriptional profiles characterizing the different clusters showed marked gene-dosage effects, particularly concerning 1q transcripts; this finding was also confirmed by a nonparametric analysis between normalized gene expression levels and local CN variations (1027 highly-significant correlated genes). Finally, we identified several loci in which gene expression correlated with the occurrence of loss of heterozygosity. Our results provide insights into the composite network linking genome structure and transcriptional features in MM.
authors.affiliation: Department of Medical Sciences, University of Milano and Hematology 1-CTMO, Fondazione IRCCS Ospedale Maggiore Policlinico Mangiagalli Regina Elena, Milano, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Agnelli
authors.forename: Laura
authors.initials: L
authors.lastname: Mosca
authors.forename: Sonia
authors.initials: S
authors.lastname: Fabris
authors.forename: Marta
authors.initials: M
authors.lastname: Lionetti
authors.forename: Adrian
authors.initials: A
authors.lastname: Andronache
authors.forename: Ivo
authors.initials: I
authors.lastname: Kwee
authors.forename: Katia
authors.initials: K
authors.lastname: Todoerti
authors.forename: Donata
authors.initials: D
authors.lastname: Verdelli
authors.forename: Cristina
authors.initials: C
authors.lastname: Battaglia
authors.forename: Francesco
authors.initials: F
authors.lastname: Bertoni
authors.forename: Giorgio Lambertenghi
authors.initials: GL
authors.lastname: Deliliers
authors.forename: Antonino
authors.initials: A
authors.lastname: Neri
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D022981:Allelic Imbalance; D002869:Chromosome Aberrations; D002874:Chromosome Mapping; D016000:Cluster Analysis; D005260:Female; D018628:Gene Dosage; D020869:Gene Expression Profiling; D015894:Genome, Human; D006801:Humans; D017404:In Situ Hybridization, Fluorescence / Q000379:methods*; D019656:Loss of Heterozygosity; D008297:Male; D008875:Middle Aged; D009101:Multiple Myeloma / Q000235:genetics* / Q000378:metabolism; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010088:Oxidoreductases / Q000235:genetics / Q000378:metabolism; D020641:Polymorphism, Single Nucleotide; D016160:Retinoblastoma Protein / Q000235:genetics / Q000378:metabolism; D025521:Tumor Suppressor Proteins / Q000235:genetics / Q000378:metabolism; D000074584:WW Domain-Containing Oxidoreductase
chemical_list: D016160:Retinoblastoma Protein; D025521:Tumor Suppressor Proteins; D010088:Oxidoreductases; D000074584:WW Domain-Containing Oxidoreductase; C486071:WWOX protein, human