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.

A Comparison of Clinical FISH and Sequencing Based FISH Estimates in Multiple Myeloma: An Mmrf Commpass Analysis

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 374-374 ◽  
Author(s):  
Chase Miller ◽  
Jennifer Yesil ◽  
Mary Derome ◽  
Andrea Donnelly ◽  
Jean Marrian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Rna Sequencing ◽  
Plasma Cell ◽  
Copy Number ◽  
Target Gene ◽  
False Negative ◽  
Single Individual ◽  
Sequencing Data ◽  
Target Gene Expression

Abstract Fluorescent in situ hybridization (FISH) is commonly used in the multiple myeloma field to subtype and risk-stratify patients. There are many benefits to FISH based assays, which are widely used around the world and represent true single cell assays. However, there are significant discrepancies in the specific assays, utilization of reflex testing strategies, and enumeration requirements between clinical centers. By comparison next-generation sequencing tests can be designed to simultaneously detect the copy number abnormalities and translocations detected by clinical FISH along with gene mutations that cannot be detected by FISH. As part of the MMRF CoMMpass Study we have compared the results attained using clinical FISH assays compared to sequencing based FISH (Seq-FISH) results. Clinical FISH reports from a random subset of 339 CoMMpass patients were extraction by a single individual based on the ISCN result lines of each report. To validate the accuracy of the central data extraction, two independent cross validations of 10% of the cohort were performed, after which our data entry error rate is expected to be less than 0.348%. The Seq-FISH results were extracted from the whole genome sequencing data available from each patient using a rapid and fully automated informatics process and the results were cross-validated using the matching exome sequencing data for copy number abnormalities and by RNA sequencing data for dysregulated immunoglobulin translocation target genes. There were 230 patients with clinical FISH and Seq-FISH results. In this cohort, 151 translocations were identified by Seq-FISH. This includes translocations to MYC, CCND2, MAFA, and those involving IgK and IgL, which are not tested by clinical FISH. After filtering non-tested translocations there are 118 translocations identified by Seq-FISH. Only 97 of these translocations had a clinical FISH assay performed with 89 (91.75%) of these being detected by clinical FISH, yet spiked target gene expression was observed in all 89 cases by RNA sequencing. Conversely, 93 translocations were called by clinical FISH, of these 89 were called by Seq-FISH(95.7%). Of the 4 translocations only called by clinical FISH, 3 were t(4;14) and 1 was a t(11;14). In two of these t(4;14) cases we did observe spiked target gene expression by RNA sequencing, suggesting these are false negatives by Seq-FISH. However, the remaining two events appear to be false positive clinical FISH results. The t(4;14) event was only observed in 1/200 cells and a co-occuring t(11;14) was also called, which was confirmed by Seq-FISH and spiked gene expression. Similarly, the one t(11;14) was observed in 3/56 cells but a del13q14 was seen in 47/50 cells, unfortunately RNA sequencing data is not available to cross-validate in this case. Plasma cell enrichment or identification is commonly used to prepare myeloma samples for FISH because even in myeloma, the total plasma cell percentage can be low (median 8.3% in the MMRF CoMMpass Baseline Cohort). Therefore, performing FISH on a sample without performing purification or plasma cell identification will indiscriminately assay non-plasma cells and limit the efficacy of the assay. We looked at the two most common translocations in myeloma, t(4;14) and t(11;14), to test the effect of enrichment on sensitivity. Sensitivity was higher for both sets of translocations in the enriched cohort. There was 1 false negative in the enriched population, yielding sensitivities of 100% (32/32) and 95%(19/20) for CCND1 and WHSC1 respectively. For those reports that did not indicate enrichment was performed the observed sensitivities were 86.36% (19/22) and 92.86% (13/14). Seq-FISH identified almost all of the translocations called by clinical FISH and simultaneously; it identified 30 translocations missed by clinical FISH. The translocations that were not reported by clinical FISH can be attributed to a mixture of the correct assay not being performed and the translocation being missed even though the assay was performed. We believe that Seq-FISH is a viable alternative to clinical FISH, with similar specificity and greater sensitivity. It is important to note that a single Seq-FISH assay is sufficient to investigate all translocations, while each translocation must be investigated separately with clinical FISH. As such, Seq-FISH obviates the concern that a translocation would be missed because the correct assay was not performed. Disclosures McBride: Instat: Employment.

scholarly journals Stratification of knee osteoarthritis: two major patient subgroups identified by genome-wide expression analysis of articular cartilage

2017 ◽  
Vol 77 (3) ◽  
pp. 423-423 ◽  
Author(s):  
Jamie Soul ◽  
Sara L Dunn ◽  
Sanjay Anand ◽  
Ferdinand Serracino-Inglott ◽  
Jean-Marc Schwartz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Disease ◽  
Calcium Signalling ◽  
Rna Seq ◽  
Knee Cartilage ◽  
Knee Oa ◽  
Genome Wide ◽  
Group A ◽  
Group B ◽  
Patient Subgroups

IntroductionOsteoarthritis (OA) is a heterogeneous and complex disease. We have used a network biology approach based on genome-wide analysis of gene expression in OA knee cartilage to seek evidence for pathogenic mechanisms that may distinguish different patient subgroups.MethodsResults from RNA-Sequencing (RNA-Seq) were collected from intact knee cartilage at total knee replacement from 44 patients with OA, from 16 additional patients with OA and 10 control patients with non-OA. Results were analysed to identify patient subsets and compare major active pathways.ResultsThe RNA-Seq results showed 2692 differentially expressed genes between OA and non-OA. Analysis by unsupervised clustering identified two distinct OA groups: Group A with 24 patients (55%) and Group B with 18 patients (41%). A 10 gene subgroup classifier was validated by RT-qPCR in 16 further patients with OA. Pathway analysis showed increased protein expression in both groups. PhenomeExpress analysis revealed group differences in complement activation, innate immune responses and altered Wnt and TGFβ signalling, but no activation of inflammatory cytokine expression. Both groups showed suppressed circadian regulators and whereas matrix changes in Group A were chondrogenic, in Group B they were non-chondrogenic with changes in mechanoreceptors, calcium signalling, ion channels and in cytoskeletal organisers. The gene expression changes predicted 478 potential biomarkers for detection in synovial fluid to distinguish patients from the two groups.ConclusionsTwo subgroups of knee OA were identified by network analysis of RNA-Seq data with evidence for the presence of two major pathogenic pathways. This has potential importance as a new basis for the stratification of patients with OA for drug trials and for the development of new targeted treatments.

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

Coordinate Interstitial Deletion of Retinoblastoma (RB1) and Neurobeachin (NBEA) Is a Recurring Event in Multiple Myeloma.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 2480-2480
Author(s):  
Julie O’Neal ◽  
AnnaLynn Molitoris ◽  
Feng Gao ◽  
Anjum Hassan ◽  
Ryan Monahan ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cell Lines ◽  
Copy Number ◽  
Plasma Cells ◽  
Interstitial Deletion ◽  
Oligonucleotide Array ◽  
Comparative Genomic ◽  
Copy Number Loss ◽  
Dna Copy Number ◽  
Chromosome 13

Abstract Monoallelic chromosome 13 deletion detected by cytogenetics predicts poor patient survival in multiple myeloma (MM), but the genes responsible have not been conclusively identified. To this end, we performed array comparative genomic hybridization (aCGH) using a novel, human chromosome 13 oligonucleotide array (Nimblegen) with 385,272 probes and median probe spacing of 60 base pairs. The dense coverage, and the use of germline DNA collected from each patient as internal controls for DNA copy number polymorphisms, enabled unprecedented map resolution of somatic DNA gains and losses on chromosome 13. Array CGH was performed on genomic DNA isolated from CD138+ bone marrow plasma cells purified from 20 patients with MM, monoclonal gammopathy of undetermined significance (MGUS), or amyloidosis. Visual analysis of the aCGH data identified 4 patients with chromosome 13 interstitial deletions that were confirmed using a circular binary segment algorithm (Nimblegen). Monosomy chromosome 13 was detected in 5 patients by cytogenetics, and as expected, appeared normal by aCGH due to data normalization. We also performed an unsupervised analysis of the data, which identified 49 genes with DNA copy number decreases. Both methods identified copy number decreases at 13q14 commonly affected in MM and MGUS patients and thought to harbor a relevant tumor suppressor. Three of the 4 patients with interstitial deletions at 13q14 had striking regions of DNA copy loss whose minimally deleted region was defined by a patient with a small deletion spanning exon 20 of RB1, encoding part of the functionally important ‘pocket domain’ responsible for binding E2F transcription factors. We found RB1 protein levels in MM cell lines correlated with RB1 genomic copy number, and therefore considered the model that RB1 haploinsufficiency contributes to MM. However, we found Rb1 heterozygous (HET) and wild type (WT) mice had indistinguishable steady-state B, T and myeloid compartments in addition to plasma cell induction in response to sheep red blood cell stimulation. Disease burden was similar in HET vs. WT Rb1 mice in a model of NRAS induced tumorigenesis. These results suggest other genomic events cooperate with RB1 copy number loss in MM. Unexpectedly, we found the 3 patients that had an interstitial deletion of RB1 at 13q14 concomitantly harbored a separate interstitial loss at 13q13. Every patient with DNA copy number loss of RB1 also had DNA copy loss within 13q13 (5 patients who lost the entire chromosome and 3 patients with interstitial deletions). The minimally deleted region at 13q13 mapped to the 5′ end of Neurobeachin (NBEA), which encodes a Protein Kinase A (PKA) anchoring protein. We detected NBEA transcripts at low levels in normal human plasma cells. NBEA transcripts and protein were robustly expressed in 3/5 MM cell lines. This is the first report of coordinate copy number loss of RB1 and NBEA on chromosome 13 in MM. Taken together, our data suggest that chromosome 13 deletions in MM may target protein dose level of RB1 and at least one other gene, likely NBEA. Our data provide a novel rationale for future studies to examine the biological consequences of coordinate loss of NBEA and RB1.

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.

scholarly journals Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Christina A. Castellani ◽  
Ryan J. Longchamps ◽  
Jason A. Sumpter ◽  
Charles E. Newcomb ◽  
John A. Lane ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cardiovascular Disease ◽  
Mitochondrial Dna ◽  
Copy Number ◽  
Nuclear Dna ◽  
Dna Copy Number ◽  
Mitochondrial Dna Copy Number ◽  
Genome Wide ◽  
Genome Wide Significance ◽  
Experimental Modification

Abstract Background Mitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation. Methods To investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings, we assayed an additional 2528 participants from the Cardiovascular Health Study (CHS) (N = 533) and Framingham Heart Study (FHS) (N = 1995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9. Results Thirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P < 5 × 10− 8). Meta-analysis across all cohorts identified six mtDNA-CN-associated CpGs at genome-wide significance (P < 5 × 10− 8). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN results in changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the “neuroactive ligand receptor interaction” KEGG pathway was found to be highly overrepresented in the ARIC cohort (P = 5.24 × 10− 12), as well as the TFAM knockout methylation (P = 4.41 × 10− 4) and expression (P = 4.30 × 10− 4) studies. Conclusions These results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling.

A Comparative Analysis of Chromosome 13 Gene Expression and Copy Number Changes in Multiple Myeloma Using Array-Based Methods.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 1557-1557
Author(s):  
Angela S. Baker ◽  
Tae-Hoon Chung ◽  
Tyler S. Pidgeon ◽  
Catherine Mancini ◽  
Tammy Price-Troska ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Tumor Suppressor ◽  
Copy Number ◽  
Loss Of Function ◽  
Chromosome 13 ◽  
Expression Levels ◽  
Genomic Copy Number ◽  
Genomic Copy ◽  
Copy Number Changes

Abstract Chromosome 13 (Δ13) abnormalities are found in greater than 50% of patients with Multiple Myeloma (MM). MM is most commonly defined by chromosome 13 monosomy or 13q loss (85%). Interstitial deletions comprise the remaining 15%. Many studies have revealed that Δ13 in MM are associated with poor survival and reduced response to therapy. Genes mapping to chromosome 13 may be involved in pathogenesis and/or progression of the disease due to loss of function from gene mutation or from epigenetic effects such as haploinsufficiency. In this study, array-based comparative genomic hybridization coupled with microarray technology (aCGH) is used to detect gene copy number loss on chromosome 13 from nine MM patient samples. Whole genome long-oligo microarrays constructed by Agilent Technologies were used which contain 40,000 genes that span the human genome with an average spatial resolution of ~75 kb. Using genomic DNA isolated from MM patients with interstitial deletions on chromosome 13, DNA was amplified, labeled and hybridized with a differentially labeled normal DNA reference to determine gene/genomic copy number changes. Arrays were analyzed to search for the minimum region of loss based upon single copy loss for a series of nearby mapping transcripts. A common region of loss of 2.2 Mb, at 13q14.2 was detected. Additionally, we investigated the correlation between genomic copy number change and the expression level for MM patients in the13q region. From an independent gene expression data set whose expression measurements were conducted with Affymetrix HG-U133A v2 microarrays, data was selected that corresponded to the samples used for current aCGH. Expression values from MM samples were divided by the mean expression values from 12 normal bone marrow samples for each gene and the resulting values were treated as surrogate ratios between MM and normal samples. Probes from both microarrays were then aligned according to their chromosomal positions and merged if their chromosomal positions overlapped. Composite chromosomal maps were generated that displayed the expression levels and copy number changes. The maps were used to differentiate chromosomal regions in 13q where copy number changes and expression levels show high correlation and regions where such correlation was not observed. Although the number of probes sampled in the expression microarray was much smaller than those in aCGH microarray, a chromosomal region of great interest, that encompasses 13q14.2, arose naturally from this analysis. Although the mechanism by which loss of 13q effects tumorigenesis in MM could be a haploinsufficiency model, we are not ruling out the presence of a tumor suppressor gene in this region. We are evaluating candidate tumor suppressor genes in the region for loss of function by mutational analysis and hypermethylation studies.

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

Relapse Pattern After Bortezomib Based Salvage Therapy in Patients with Multiple Myeloma

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1869-1869
Author(s):  
Jae-Sook Ahn ◽  
Deok-Hwan Yang ◽  
Sung-Hoon Jung ◽  
Se Ryeon Lee ◽  
Yeo-Kyeoung Kim ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Plasma Cell ◽  
Light Chain ◽  
Salvage Treatment ◽  
Plasma Cell Leukemia ◽  
Cell Leukemia ◽  
Bortezomib Treatment ◽  
Relapse Pattern ◽  
Group A ◽  
Group B

Abstract Abstract 1869 Backgrounds & Aims: More intensive and novel therapy options in multiple myeloma (MM) improve the treatment outcome. However, disease evolution, induced with long disease duration and extensive pretreatment, has resulted in changes in the biological behavior of MM and unusual relapse emergence. Therefore, we studied the relapse pattern after bortezomib based salvage treatment in patients with MM and also we analyzed the prognostic significance according to relapse pattern. Methods: We have retrospectively analyzed the relapse pattern. Eligibility criteria included primary refractory or relapsed MM patients who must have received previous chemotherapy and they also received at least 2 cycles of bortezomib based salvage treatment. Immunoglobulin M type of MM, primary amyloidosis and plasma cell leukemia were excluded in this study. For evaluation of disease response, International Myeloma Working Group (IMWG) uniform response criteria were used. Results: Between November 2004 and August 2011, 132 patients received bortezomib based salvage chemotherapy. In 132 patients, 91 (68.9%) patients showed the disease relapse. The pattern of relapse after bortezomib salvage treatment was heterogeneous, the 14/91 (15.4%) patients relapsed as a novel manifestation comparison with the initiation of bortezomib (plasmacytoma: 7 patients, light chain escape pattern: 4 patients and, plasma cell leukemia: 2 patients). There was no statistical difference in the duration from diagnosis to bortezomib treatment according to novel (group A) vs isoform (group B) relapse. In the group B, the median overall survival after relapse was 16.1 months (95% CI: 11.4–20.8) and the group A was 2.5 months (95% CI: 0.0–5.7)(p=0.000). The 27 out of 132 patients received the retreatment of bortezomib and 23 out of 27 patients showed the disease progression. The 4/24 (16.7%) patients relapsed as a novel manifestation (plasmacytoma: 2 patients, light chain escape pattern: 1 patients and intact immunoglobulin secretion from plasmacytoma type: 1 patient). In patients received retreatment of bortezomib, novel relapsed group showed the trend of poor survival without statistical significance (2.2 months vs 10.0 months) (p=0.30). Conclusion: Our report suggests that bortezomib treatment contribute as a selective pressure and it has culminated in novel relapse manifestation. The relapsed patients as novel pattern after bortezomib treatment show the extreme poor prognosis. These findings suggest that these patients may be worth consideration for intensive treatment or early clinical trials. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Mitochondrial DNA Copy Number (mtDNA-CN) Can Influence Mortality and Cardiovascular Disease via Methylation of Nuclear DNA CpGs

2019 ◽  
Author(s):  
Christina A. Castellani ◽  
Ryan J. Longchamps ◽  
Jason A. Sumpter ◽  
Charles E. Newcomb ◽  
John A. Lane ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cardiovascular Disease ◽  
Mitochondrial Dna ◽  
Copy Number ◽  
Nuclear Dna ◽  
Dna Copy Number ◽  
Mitochondrial Dna Copy Number ◽  
Genome Wide ◽  
Genome Wide Significance ◽  
Experimental Modification

ABSTRACTBackgroundMitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation.MethodsTo investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2,507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings we assayed an additional 2,528 participants from the Cardiovascular Health Study (CHS) (N=533) and Framingham Heart Study (FHS) (N=1,995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9.ResultsThirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P<5×10-8). Meta-analysis across all cohorts identified six mtDNA-CN associated CpGs at genome-wide significance (P<5×10-8). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN directly drives changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the ‘neuroactive ligand receptor interaction’ KEGG pathway was found to be highly overrepresented in the ARIC cohort (P= 5.24×10-12), as well as the TFAM knockout methylation (P=4.41×10-4) and expression (P=4.30×10-4) studies.ConclusionsThese results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling.

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