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Poster sessions. Identification of collaborating oncogeneic events leading to disease progression in myeloma cases with a t(4;14) and t(11;14) using SNP and gene expression arrays

Poster sessions. Identification of collaborating oncogeneic events leading to disease progression in myeloma cases with a t(4;14) and t(11;14) using SNP and gene expression arrays
Poster sessions. Identification of collaborating oncogeneic events leading to disease progression in myeloma cases with a t(4;14) and t(11;14) using SNP and gene expression arrays
Immunoglobulin heavy chain translocations are an initiating genetic event in the pathogenesis of 50% of multiple myeloma cases. The t(4;14) and t(11;14) translocations each occur in approximately 15% of cases but have distinct clinical outcomes with t(4;14) being associated with a poor prognosis. This may reflect the patterns of genes deregulated by the translocation but also by additional genetic events acquired later in the disease natural history collaborating with the initial translocation. Previous analysis has shown that the t(4;14) results in overexpression of both FGFR3 and MMSET, whereas the t(11;14) results in dysregulation of cyclin D1. In order to identify collaborating genes important in disease progression, we have used the Affyemtrix 50K SNP mapping array to determine chromosomal copy number and loss of heterozygosity (LOH), and the Affymetrix U133 plus 2 array to determine gene expression levels, in t(4;14) and t(11;14) cases. CD138 plasma cells were selected from 22 newly diagnosed myeloma cases, and the presence of the translocation and hyperdiploid status were determined by FISH (9 t(4;14) cases, 13 t(11;14) cases, all cases non-hyperdiploid using the FISH ploidy index). In keeping with our previous studies both t(4;14) and t(11;14) had distinct gene expression profiles characterized by overexpression of FGFR3, MMSET, cyclin D1 and cyclin D2 using hierarchical clustering programmes. A significant percentage of cases lacking a t(4;14) also appeared to have dysregulation of MMSET and its splice variants, as using the array specific hybridization patterns and RT-PCR there was overexpression of the C terminal exons of MMSET but a lack of IgH-MMSET fusions. There was a good correlation between the hyperdiploid status of the cells using FISH and SNP arrays, although some chromosomes that were not tested by FISH showed the presence of chromosomal trisomies in the SNP array. All of the t(4;14) cases had numerous large regions of chromosomal amplification and deletion, some of which were associated with LOH whereas a number of the t(11;14) cases showed diploid SNP calls with no regions of LOH, suggesting greater genomic instability in t(4;14). There was 90% correlation between the presence of a t(4;14) and deletion of chromosome 13q. Chromosome 1 has been suggested to be the site of important collaborating genes previously and in keeping with this we identified 1p amplifications in 12/22 cases, 1q amplifications in 7/22 cases and 1p deletions in 2/22 cases. These abnormalities were equally distributed across both translocation groups suggesting that they are common events in myeloma which are not associated with any particular translocation. In contrast, deletion of regions 16q appear to be specific to a subgroup of t(11;14) cases, with loss in 5 of 13 t(11;14) cases and none being seen in the t(4;14) cases. Current studies comparing the abnormalities detected with high resolution SNP array to gene expression profiles will help to determine how the expression of genes within these key regions of gain and loss are altered and how they may contribute to myeloma pathogenesis.
hematology, gene, expression, time, disease progression, gene expression, london, england, disease
0006-4971
442A-443A
Jenner, Matthew W.
af4d9ce0-1282-4eb3-8440-98b16ee7cc85
Walker, Brian A.
7e45e107-ca85-4368-8673-7177f2328405
Leone, Paola E. Leone
8f06065e-b199-4e9e-a330-f5df9e18528e
Gonzalez, David
23765c4d-1658-40fd-a487-bc11bad2aea3
Ross, Fiona M.
08e9ce4d-608a-413f-b9bf-95cdfa24186e
Li, Cheng
b18a76fb-45ed-4894-9ace-c4897be16c18
Davies, Faith E.
9ea9e143-ac51-431b-8cb5-57b8dc0a38af
Morgan, Gareth J.
d285dcf8-ac2c-4fe0-acf9-4787eb025939
Jenner, Matthew W.
af4d9ce0-1282-4eb3-8440-98b16ee7cc85
Walker, Brian A.
7e45e107-ca85-4368-8673-7177f2328405
Leone, Paola E. Leone
8f06065e-b199-4e9e-a330-f5df9e18528e
Gonzalez, David
23765c4d-1658-40fd-a487-bc11bad2aea3
Ross, Fiona M.
08e9ce4d-608a-413f-b9bf-95cdfa24186e
Li, Cheng
b18a76fb-45ed-4894-9ace-c4897be16c18
Davies, Faith E.
9ea9e143-ac51-431b-8cb5-57b8dc0a38af
Morgan, Gareth J.
d285dcf8-ac2c-4fe0-acf9-4787eb025939

Jenner, Matthew W., Walker, Brian A., Leone, Paola E. Leone, Gonzalez, David, Ross, Fiona M., Li, Cheng, Davies, Faith E. and Morgan, Gareth J. (2005) Poster sessions. Identification of collaborating oncogeneic events leading to disease progression in myeloma cases with a t(4;14) and t(11;14) using SNP and gene expression arrays. Blood, 106 (11), 442A-443A.

Record type: Article

Abstract

Immunoglobulin heavy chain translocations are an initiating genetic event in the pathogenesis of 50% of multiple myeloma cases. The t(4;14) and t(11;14) translocations each occur in approximately 15% of cases but have distinct clinical outcomes with t(4;14) being associated with a poor prognosis. This may reflect the patterns of genes deregulated by the translocation but also by additional genetic events acquired later in the disease natural history collaborating with the initial translocation. Previous analysis has shown that the t(4;14) results in overexpression of both FGFR3 and MMSET, whereas the t(11;14) results in dysregulation of cyclin D1. In order to identify collaborating genes important in disease progression, we have used the Affyemtrix 50K SNP mapping array to determine chromosomal copy number and loss of heterozygosity (LOH), and the Affymetrix U133 plus 2 array to determine gene expression levels, in t(4;14) and t(11;14) cases. CD138 plasma cells were selected from 22 newly diagnosed myeloma cases, and the presence of the translocation and hyperdiploid status were determined by FISH (9 t(4;14) cases, 13 t(11;14) cases, all cases non-hyperdiploid using the FISH ploidy index). In keeping with our previous studies both t(4;14) and t(11;14) had distinct gene expression profiles characterized by overexpression of FGFR3, MMSET, cyclin D1 and cyclin D2 using hierarchical clustering programmes. A significant percentage of cases lacking a t(4;14) also appeared to have dysregulation of MMSET and its splice variants, as using the array specific hybridization patterns and RT-PCR there was overexpression of the C terminal exons of MMSET but a lack of IgH-MMSET fusions. There was a good correlation between the hyperdiploid status of the cells using FISH and SNP arrays, although some chromosomes that were not tested by FISH showed the presence of chromosomal trisomies in the SNP array. All of the t(4;14) cases had numerous large regions of chromosomal amplification and deletion, some of which were associated with LOH whereas a number of the t(11;14) cases showed diploid SNP calls with no regions of LOH, suggesting greater genomic instability in t(4;14). There was 90% correlation between the presence of a t(4;14) and deletion of chromosome 13q. Chromosome 1 has been suggested to be the site of important collaborating genes previously and in keeping with this we identified 1p amplifications in 12/22 cases, 1q amplifications in 7/22 cases and 1p deletions in 2/22 cases. These abnormalities were equally distributed across both translocation groups suggesting that they are common events in myeloma which are not associated with any particular translocation. In contrast, deletion of regions 16q appear to be specific to a subgroup of t(11;14) cases, with loss in 5 of 13 t(11;14) cases and none being seen in the t(4;14) cases. Current studies comparing the abnormalities detected with high resolution SNP array to gene expression profiles will help to determine how the expression of genes within these key regions of gain and loss are altered and how they may contribute to myeloma pathogenesis.

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More information

Published date: 2005
Additional Information: ASH Annual Meeting Abstracts: abstract 1542
Keywords: hematology, gene, expression, time, disease progression, gene expression, london, england, disease

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Local EPrints ID: 59875
URI: http://eprints.soton.ac.uk/id/eprint/59875
ISSN: 0006-4971
PURE UUID: 02ab953b-a969-4f3f-88a8-0525ffa9d32d

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Date deposited: 07 Nov 2008
Last modified: 22 Jul 2022 21:11

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Contributors

Author: Matthew W. Jenner
Author: Brian A. Walker
Author: Paola E. Leone Leone
Author: David Gonzalez
Author: Fiona M. Ross
Author: Cheng Li
Author: Faith E. Davies
Author: Gareth J. Morgan

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