DNA Copy Number Changes Have Gene Dosage Effects with Consequent Impact On Disease Biology and Prognosis in Multiple Myeloma

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3984-3984
Author(s):  
Mehmet Kemal Samur ◽  
Parantu K Shah ◽  
Xujun Wang ◽  
Norman Huang ◽  
Stephane Minvielle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Copy Number ◽  
Dosage Effect ◽  
Chromosome 9 ◽  
Copy Number Alterations ◽  
Dna Copy Number ◽  
A Genome ◽  
The Impact ◽  
Affect Gene Expression

Abstract Abstract 3984 Copy number alterations, deletions and amplifications, are very frequent in multiple myeloma (MM), however, it is less clear how these alterations affect gene expression. We performed a genome-wide analysis of 170 newly-diagnosed uniformly treated MM patients using high-density SNP arrays and Exon ST 1.0 gene expression arrays, and evaluated how copy number alterations affect gene expression in MM. Using SNP array data just over 40% patients had hyperdiploid MM (HMM) while the rest had non-hyperdiploid MM (N-HMM). We used two-step procedure to identify dosage effect scores of genes. At first, for each gene, percentage of copy number altered samples was calculated. Then for each gene percentage of samples that had dosage effect was calculated. Finally dosage effect score for each gene was calculated as a ratio of dosage effect samples percentage to copy number alteration sample percentage. We show that dosage effect in MM is wide-spread and some chromosomal locations are affected by dosage effect more compared to other locations. The dosage effect tracks can be observed at trisomy chromosomes and chromosome 1q, but most explicitly at chromosome 9, 11, 15 and 19. Also for deleted genes, dosage effect can be mostly observed at chromosome 13 and 16q. Separate analysis of HMM and N-HMM patients also showed that HMM patients have higher dosage effect especially in chromosome 15 compared to the others. In addition, relation between dosage effect and gene expression analysis show that the highly expressed genes have significantly higher dosage effect compared to the lowly expressed genes. Also function enrichment analysis showed that genes involved with crucial biological processes including translation, RNA processing and transcription factor genes are enriched in genes with higher dosage effect. Interstingly, dosage resistant genes are enriched in cell death and GTPase processes. These results help us understand the impact of aneuploidy in MM on global gene expression changes. In conclusion, our analysis identifies concordant and discordant gene expression changes associated with DNA copy number alterations, identifying genes and pathways that may play an important role in myeloma disease behavior as well as prognosis. Disclosures: No relevant conflicts of interest to declare.

DNA copy number alterations, gene expression changes and disease-free survival in patients with colorectal cancer: a 10 year follow-up

2016 ◽  
Vol 39 (6) ◽  
pp. 545-558 ◽  
Author(s):  
Elisabetta Bigagli ◽  
Carlotta De Filippo ◽  
Cinzia Castagnini ◽  
Simona Toti ◽  
Francesco Acquadro ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Copy Number ◽  
Disease Free Survival ◽  
Copy Number Alterations ◽  
Dna Copy Number ◽  
Free Survival ◽  
Dna Copy Number Alterations ◽  
Disease Free

Correlation of DNA Copy Number, Gene Expression, Protein Expression and Clinical Outcome in a Group of Patients with Diffuse Large B Cell Lymphoma (DLBCL) Treated with CHOP Plus Rituximab (CHOP-R).

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2027-2027
Author(s):  
N.A. Johnson ◽  
T. Relander ◽  
P. Farinha ◽  
T. Nayar ◽  
D.E. Horsman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Outcome ◽  
Protein Expression ◽  
B Cell ◽  
Human Genome ◽  
Copy Number ◽  
B Cell Lymphoma ◽  
Dna Copy Number ◽  
The Impact ◽  
Successes And Failures

Abstract Background: DLBCL is the most common subtype of Non-Hodgkin lymphoma and has a mortality rate of 40%. It is characterized by marked clinical and biological heterogeneity. Tumors with similar histology have different genetic abnormalities. The influence of many of these genetic changes on clinical outcome is unknown. Furthermore, treatment itself can influence the prognostic significance of certain biomarkers. Exploring the impact of genetic aberrations on gene expression, protein expression and clinical outcome is the focus of this investigation. Understanding the biology of DLBCL from patients treated with CHOP-R may lead to the discovery of novel biomarkers that are relevant in the CHOP-R era. Methods: RNA and DNA were extracted from frozen de novo DLBCL biopsies taken at the time of diagnosis from April 2001 to April 2005. Cases were selected based on their clinical outcome (11 patients with a >2 year remission with CHOP-R and 10 patients who progressed or relapsed after CHOP-R). We studied DNA amplifications and deletions using array comparative genomic hybridization (aCGH) comprising of >26,000 overlapping bacterial artificial chromosomes. This provides a >95% coverage of the human genome and the capability to reproducibly detect amplifications and deletions as small as 120 kb. We performed gene expression profiling (GEP) using the Affymetrix Human Genome U133 Plus 2 array. A tissue microarray was constructed to assess protein expression using paraffin active antibodies. BCL2, BCL6, P53 and MUM1 genes were assessed using all three platforms and results were correlated with clinical outcome. Results: DNA gains and losses were identified in all patients with an average of 19 alterations per tumor with amplifications being more frequent than deletions. GEP revealed a predominance (57%) of Activated B Cell (ABC) type. A supervised analysis identified a list of 471 genes that were differentially expressed (p<0.01) between treatment failures and successes, many of which are implicated in nucleic acid binding and cell cycle regulation. The correlation between DNA copy number and gene expression was poor especially in areas of DNA gain. The correlation between gene expression and copy number was greater for BCL2 and P53 than for BCL6 and MUM1 (r= 0.67 and 0.80 versus −0.02 and −0.08). The correlation between protein expression and gene expression were r = 0.22, 0.65, 0.66 and 0.53 for BCL2, P53, BCL6 and MUM1, respectively. In this small group of patients treated with CHOP-R, the international prognostic index (IPI) was higher in the patients “failing” CHOP-R (mean IPI 3.2 vs. 1.7). Deletions of 17p13.1 (P53) and high P53 protein expression were predominantly seen in the failures (7 vs 1). High BCL2 protein, low BCL6 protein and ABC signature were randomly distributed in both CHOP-R successes and failures. Conclusion: In this limited group of patients with DLBCL treated with CHOP-R, IPI had the strongest prognostic value. Candidate genes that could predict CHOP-R successes and failures will be validated by RT-PCR and TMA on a larger cohort of patients. The unpredictable correlation between gene expression and DNA copy number suggests that alternate mechanisms of gene regulation are involved in the pathogenesis of DLBCL.

scholarly journals Integrative analysis of DNA copy number, DNA methylation and gene expression in multiple myeloma reveals alterations related to relapse

Oncotarget ◽  
2016 ◽  
Vol 7 (49) ◽  
pp. 80664-80679 ◽  
Author(s):  
Patryk Krzeminski ◽  
Luis A. Corchete ◽  
Juan L. García ◽  
Lucía López-Corral ◽  
Encarna Fermiñán ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Multiple Myeloma ◽  
Copy Number ◽  
Integrative Analysis ◽  
Dna Copy Number

Genome-Wide Analysis of DNA Copy Number in Multiple Myeloma Using High-Density SNP Arrays Reveals Clustering Patterns with Distinct Transcriptional Profiles.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2482-2482
Author(s):  
Laura Mosca ◽  
Luca Agnelli ◽  
Ivo Kwee ◽  
Sonia Fabris ◽  
Domenica Ronchetti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Plasma Cell ◽  
Copy Number ◽  
Dna Copy Number ◽  
Snp Arrays ◽  
Chromosome 13 ◽  
Genome Wide ◽  
Group A ◽  
Group B

Abstract Multiple myeloma (MM) is characterized by a high genomic instability that involves both ploidy and structural rearrangements. Nearly half of MM tumors are non-hyperdiploid and are frequently associated with 13q deletion and chromosomal translocations involving the immunoglobulin heavy chain (IGH) locus on chromosome 14q32. The remaining tumors are hyperdiploid, showing low prevalence of both IGH translocations and chromosome 13 deletions. Our study was aimed at providing insights into the genomic heterogeneity associated with plasma cell neoplasms by defining the genome-wide pattern of genetic lesions in a representative and stratified panel of MM patients. To this end, genome-wide profiling data of 45 plasma cell dyscrasia patients (41 MM and 4 plasma cell leukemia) were generated on GeneChip® Human Mapping 50K Xba SNP arrays, and the local DNA copy number variations were calculated using the DNAcopy Bioconductor package. The patients were clustered using the non-negative matrix factorization (NMF) algorithm to identify, within the natural grouping of profiles, the strongest clusters on the basis of their genomic characteristics. We identified three consistent clusters, characterized byrecurrent gains of odd-chromosomes, suggestive of the hyperdiploid status (Group A),high frequency of chromosome 13 deletion and 1q gains (Group B), orhigh frequency of chromosomes 13, 14, 16 and 22 deletions and losses of 1p and 4p regions, together with some cases showing 1q gains (Group C). To determine whether peculiar transcription fingerprints characterized these groups, gene expression profiles of 40 out of 45 corresponding samples generated on GeneChip® HG-U133A arrays were analyzed using the Prediction Analysis of Microarray (PAM) software. The multi-class analysis identified 229 transcripts (corresponding to 195 genes), which specifically marked the three groups. In particular, Group A was characterized by the overexpression of genes involved in the translational machinery or thought to be involved in MM pathogenesis such as the HGF, the tumor necrosis factor ligand TRAIL, DKK1, and c-KIT. Upregulation of the CKS1B gene was present in Group B and C, most likely reflecting the high frequencies of 1q gains in tumors within group B and C and its consequent deregulation. Group C was marked by the specific downregulation of genes mainly mapped to 1p arm: AMPD1, CSDE1, AKR1A1 and the PRKACB kinase, suggesting a relationship with the recurrent 1p loss within the group. Our data further supported the notion that structural abnormalities in multiple myeloma are associated with gene expression imbalances, and provide novel analytical approaches for the identification of genetic lesions and molecular patterns of the disease.

Genomic Landscape Predictive of Minimal Residual Disease (MRD) in Multiple Myeloma (MM)

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4212-4212
Author(s):  
Mehmet K Samur ◽  
Stephane Minvielle ◽  
Florence Magrangeas ◽  
Giovanni Parmigiani ◽  
Kenneth C Anderson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Board Of Directors ◽  
Copy Number ◽  
Residual Disease ◽  
Copy Number Alterations ◽  
Advisory Committees ◽  
Genomic Landscape ◽  
Equity Ownership ◽  
Minimal Residual

Abstract Progress in the treatment of multiple myeloma (MM) has increased extent and frequency of response, as well as prolonged progression-free (PFS) and overall survival (OS). Today complete remission (CR) rates up to 70% are achieved with new drug combinations. This has lead to development of sensitive next generation sequencing (NGS) -based methods to predict deeper responses that may more accurately predict survival outcomes in MM. Our large recent study has confirmed the clinical impact of achieving MRD- status in MM. Here we are evaluating the genomic alterations that may predict attainment of MRD negative status in MM. MRD status was evaluted in 279 patients from IFM/DFCI 2009 trial. We obtained gene expression by RNA-seq, and copy number profile by cytoScan HD array to evaluate genomic differences between MRD negative and MRD positive groups. We generated copy number data for 175 / 279 patients (72 MRD- and 103 MRD+) with Affymetrix Cytoscan HD array and compared genome wide copy number alterations. We observed statistically significant copy number alterations in chromosome 1p, 2, 4q, 11q, 13, 14 and 20 between MRD- and MRD+ patients. However, the extent of alterations in these regions is limited. The largest difference was on chromosome 11q arm where MRD- patients had 2.2 copies on average and MRD+ had 2.4 (p value < 0.001). Similarly, we generated gene expression profiles with RNAseq for 69 MRD- patients and 92 MRD+ patients to study gene expression alterations that may predict attainment of MRD negative status and to examine possible biological pathways. Although first two component of principle component analysis (PCA) showed that two groups have similar expression profile, we were able to identify 586 differentially expressed genes; 333 of those were up and 253 were down regulated in MRD+ compared to MRD- groups. We found that seven oncogenes (CCND1, CD79B, IDH1, PATZ1, PAX5, POU2AF1, RUNX1) were significantly high in MRD+ and two (CCND2 and MYCN) were high in MRD-. Additional genes that were high in MRD+ samples were enriched in genes regulated by NF-kB in response to TNF, P53 pathway, KRAS signaling and genes down-regulated in response to ultraviolet (UV) radiation. Genes that were high in MRD- compared to MRD+ were also enriched in genes up-regulated by STAT5 in response to IL2 stimulation, p53 pathways and networks, and genes up-regulated in response to ultraviolet (UV) radiation pathways. Finally, we have created a signature to predict MRD+ and MRD- in MM samples from differentially expressed genes. We used 40 genes that has at least 2 fold change difference between MRD+ and MRD- groups as a predictor and we randomly separated 161 RNAseq samples into train (n=99) and test group (n=62). We developed our classifiers with diagonal discriminant analysis and we achieved 0.79 classifier performance on test dataset. Then we tested our signature against 1000 random signature and it was significantly different than random signatures (Figure). In conclusion, we here report a first genomic landscape predictive of minimal residual disease (MRD) in Multiple Myeloma (MM). This analysis will help understand genomic and molecular correlates of achieving minimal residula disease and confirms feasibility of using RNAseq data from diagnosis sample to predict MRD status. The ongoing integration of other genomic correlates such as copy number status as well as alternate splicing may allow further improvement in the performance of prediction. Figure 1. Figure 1. Disclosures Anderson: Gilead: Consultancy; acetylon pharmaceuticals: Equity Ownership; Oncocorp: Equity Ownership; Celgene Corporation: Consultancy; BMS: Consultancy; Millennium: Consultancy. Attal:jansen: Honoraria; celgene: Membership on an entity's Board of Directors or advisory committees. Munshi:onyx: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; novartis: Membership on an entity's Board of Directors or advisory committees.

Genome‐wide analysis of DNA copy number alterations and gene expression in gastric cancer

2008 ◽  
Vol 216 (4) ◽  
pp. 471-482 ◽  
Author(s):  
Y Tsukamoto ◽  
T Uchida ◽  
S Karnan ◽  
T Noguchi ◽  
LT Nguyen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Copy Number ◽  
Copy Number Alterations ◽  
Dna Copy Number ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Dna Copy Number Alterations
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