Integration of Gene Mapping and Expression Arrays Identifies Mechanisms by Which Genes Are Dysregulated as a Result of Copy Number Loss and Gain Associated with IgH Translocations in Multiple Myeloma.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 395-395 ◽  
Author(s):  
Matthew W. Jenner ◽  
Gonzalez David ◽  
Paola E. Leone ◽  
Brian A. Walker ◽  
David C. Johnson ◽  
...  

Abstract We have previously shown that integration of gene expression and SNP based mapping arrays can identify genes dysregulated as a result of copy number loss and gain in multiple myeloma. Using FISH, it has been possible to identify that gain and loss frequently occurs in association with primary IgH translocations, such as loss of FGFR3 and gain of CCND1 in a proportion of t(4;14) and t(11;14) cases. The aim of this study was to determine the frequency and size of such copy number change associated with IgH translocations and to identify the genes dysregulated as a consequence of these. FISH was performed on CD138 selected plasma cells from 80 newly diagnosed myeloma cases to identify cases with primary IgH translocations. Affymetrix 500K mapping arrays were used to determine copy number change using paired tumor and constitutional DNA and Affymetrix U133 plus 2.0 expression arrays were used to determine global gene expression. Samples were analyzed in dChip and CNAG. Thirty eight of 80 cases (47.5%) had primary IgH translocations: 7 t(4;14), 1 t(6;14), 16 t(11;14), 3 t(14;16), 2 t(14;20) and 9 with an unknown translocation partner. Of 29 cases with a known translocation partner, 11 had gain or loss of all or part of the derivative chromosome. Three of 7 t(4;14) cases had loss of FGFR3 by FISH, confirmed by mapping array as being due to deletion of the derivative 14, with loss of 4p16.3-pter and the remainder of chromosome 14 excluding IgH. The region on 4p commenced at FGFR3 and extended to the telomere. Gene expression analysis showed that there was underexpression of FGFR3 and 4 other genes in the deleted region in the 4p16 deleted cases. In 6 of 16 t(11;14) cases, the translocation was associated with an additional copy of CCND1 by FISH. Mapping arrays revealed in all cases the gain commenced at the presumed translocation breakpoint: in 4 cases there was gain of 11q13.3-qter and in 2 there was gain of a small region of 11q13 only. In most cases there was isolated gain of a variable sized region of 14q32 suggesting a sequence whereby translocation was followed by gain then by deletion of a portion of the derivative chromosome. Gene expression analysis identified 4 genes overexpressed on 11q in t(11;14) cases with 11q gain. In a single t(6;14) case there was a complex rearrangement involving gain of 6p21.1-pter and IgH with loss of the derivative 6, again suggesting translocation followed by gain then loss. In one t(14;16) case there was UPD of 16q except for 16q23-qter with associated gain of IgH alone. This complex pattern suggests a sequence whereby deletion is followed by IgH translocation then by duplication of the untranslocated 16q. This study has shown that loss and gain of translocated regions is a frequent occurrence, present in 11/29 cases with known IgH translocations. Using mapping arrays it is possible to demonstrate that in the majority of cases, the translocation is the initial event, followed by subsequent gain or loss as a later event. We have shown the variable size of these regions and have identified genes dysregulated as a result of the deletions of 4p in t(4;14) cases and gains of 11q in t(11;14) cases. These findings provide evidence of collaborating mechanisms that may be responsible for disease progression in these cases.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2493-2493
Author(s):  
Gareth J. Morgan ◽  
Matthew W. Jenner ◽  
Brian A. Walker ◽  
David C. Johnson ◽  
Paola A. Leone ◽  
...  

Abstract Whilst gene expression signatures have been defined that correspond to poor overall survival, the mechanism for deregulation of such genes is often elusive. We and others have described acquired copy number change as one potential mechanism of gene deregulation in myeloma. Other potential mechanisms exist that may influence the expression of myeloma-associated genes such as inherited SNPs and copy number variation (CNV). We have therefore embarked upon an integrated pharmacogenomic strategy to determine the importance of acquired and inherited genetic changes in determining response to therapy. We have carried out gene expression analysis on CD 138 selected bone marrow plasma cells from 231 newly diagnosed myeloma cases using Affymetrix U133 Plus 2.0 expression arrays and copy number analysis using 500K Gene Mapping arrays on a subset of 90 cases. Peripheral blood DNA has been genotyped using Affymetrix 500K Gene Mapping arrays and the BOAC chips. Cytogenetics was available in the majority of cases. Younger, fitter patients received either cyclophosphamide, thalidomide and dexamethasone (CTD) or cyclohosphamide-VAD (C-VAD), followed by high dose melphalan (HDM). Older, less fit patients received attenuated dose CTD or MP. Response was assessed before and after HDM in the intensive group and on completion of therapy in the non-intensive group using EBMT criteria plus the category of VGPR. We used a supervised approach to define a gene expression signature corresponding to high level response (CR, VGPR or PR) against poor response (NC, PD or MR) overall and for each of the three induction strategies, CTD/CTDA, CVAD and MP. We have combined the data from expression arrays together with mapping data from tumor DNA and 2 different SNP arrays performed on germline DNA. We defined a poor response expression signature initially and then identified the genomic loci of these genes and how they were affected by acquired copy number change. For each candidate gene we also examined the constitutional DNA to see if each fell within a region of inherited CNV and how this could be affected by acquired copy number change. In a similar fashion, we used the BOAC chip to define genes and SNPs associated with response. This is different as it utilized mostly functional cSNPs in candidate genes. We then looked at how CNV affected these genes. Although not all genes in which functional cSNPs are present would necessarily be expected to be expressed in plasma cells, this approach is a vital step in identifying the clinical relevance of such cSNPs in myeloma. We also took the alternate approach and designed an algorithm able to correlate acquired copy number change with paraprotein response. We then identified differentially expressed genes in these loci and their impact on response, narrowing the candidate genes down to define a signature which could be validated. Using this approach has allowed us to identify genes important in determining response and their relation to tumor-associated copy number change and inherited CNV. Overall, this methodology provides significant insight in to the factors that predict response to different chemotherapy regimens. Preliminary data will be presented.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3360-3360
Author(s):  
Erik Wendlandt ◽  
Guido J. Tricot ◽  
Benjamin Darbro ◽  
Fenghuang Zhan

Abstract Background: Multiple myeloma is the second most common blood borne neoplasia, accounting for nearly 10% of all diagnosed hematologic malignancies and has a disproportionately high incidence in elderly populations. Here we explored copy number variations using the high fidelity CytoScan HD arrays to develop a detailed map of copy number variations and identify novel mediators of disease progression. The results from CytoScan HD microarrays provide a detailed view of the entire genome with a resolution up to 25kb. Furthermore, 750,000 single-nucleotide polymorphisms are included and the array provides information about loss of heterozygosity and uniparental disomy. Materials and methods: CytoScan HD arrays were performed on 97 myeloma patient samples to identify cytogenetic regions important to the development and progression of the disease. Gene expression profiles from 351 patients were analyzed to identify genes with a change in gene expression of 1.5 fold or more. Data from CytoScan and gene expression arrays was combined to perform chromosomal positional enrichment analysis to identify cytogenetic driver lesions, or lesions that provide a small, but significant growth and survival advantage to the cell. Furthermore, Kaplan-Meier, log-rank test and Hazard ratio analyses were performed to identify gene within the driver lesions that have a significant impact on survival when dysregulated. Results: The results from the CytoScan HD analysis closely mirrored what has been shown by FISH and SNP arrays, with gains to the odd numbered chromosomes, specifically 3, 5, 7, 9, 11, 15 and 17 as well as losses to chromosomes 1p and 13. Interestingly, we identified gains to a small region within chromosome 8p, contrary to published reports demonstrating a large scale loss of this region. We identified numerous genes within this region that are important for survival and their overexpression resulted in a decreased progression free survival. For example, Cathepsin B (CTSB) is encoded for in chromosome 8p22-p21 with an increased gene expression of at least 1.5 fold over normal controls, among others. Furthermore, Cathepsin B, a cysteine protease, has been linked to cancer of the ileum, suggesting that a similar role may be present within myeloma. We then integrated the 97 copy number profiles results with 351 myeloma gene expression profiles to identify cytogenetic driver lesions in myeloma important for disease development, progression and poor clinical outcome. Chromosomal positional enrichment analysis was employed to identify global myeloma cytogenetic driver aneuploidies as well as develop unique cytogenetic copy number profiles. Our results identified portions of chromosomes 1q, 3, 8p, 9, 13q and 16q, among others, as important driver lesions with changes to these regions providing growth advantages to the cell. Furthermore, our analysis identified five unique cytogenetic classifications based on common cytogenetic lesions. We continue to explore these driver regions to identify lesions important for the oncogenic properties of the larger regions. Conclusion: The data presented here represents a novel and highly sensitive approach for the identification of novel copy number variations and driver lesions. Furthermore, correlations between copy number variations and gene expression arrays identified novel targets important for disease progression and patient survival. CytoScan HD arrays in conjunction with gene expression analysis provided a high resolution image of important cytogenetic lesions in myeloma and identified potentially important therapeutic targets for drug development. Further work is needed to validate our findings and determine the therapeutic efficacy of the identified targets. Disclosures No relevant conflicts of interest to declare.


2012 ◽  
Vol 8 (4S_Part_18) ◽  
pp. P672-P672
Author(s):  
Kinga Szigeti ◽  
Yanchun Li ◽  
Chad Shaw ◽  
Irene Sheffer ◽  
Norbert Sule ◽  
...  

2007 ◽  
Vol 1 (10) ◽  
pp. 432-435 ◽  
Author(s):  
Lucía Conde ◽  
David Montaner ◽  
Jordi Burguet- Castell ◽  
Joaquín Tárraga ◽  
Fátima Al- Shahrour ◽  
...  

2017 ◽  
Vol 12 (1) ◽  
pp. S1007
Author(s):  
Takao Nakanishi ◽  
Toshi Menju ◽  
Ryo Miyata ◽  
Shigeto Nishikawa ◽  
Koji Takahashi ◽  
...  

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