Detailed Genome-Wide DNA-Mapping of CD34+ Cells Purified from Patients with MDS Using High-Resolution SNP Arrays Identifies Significant Regions of Genomic Alterations.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2635-2635
Author(s):  
Daniel Nowak ◽  
Florian Wagner ◽  
Claudia C. Baldus ◽  
Olaf Hopfer ◽  
Maximilian Mossner ◽  
...  

Abstract Identification of common genomic lesions in progenitor cells of MDS Patients could lead to the discovery of new target genes in this disease and may be of prognostic value. Therefore, we carried out a detailed genome-wide mapping of genomic DNA from highly purified CD34+ progenitor cells from MDS patients and healthy individuals with high-resolution single nucleotide polymorphism (SNP) microarrays which scan 500,000 SNPs with a median inter-SNP distance of approximately 2.5 kb. Bone marrow aspirates were obtained from 14 MDS patients (IPSS low risk n=6, high risk n=8) and 6 healthy individuals after informed consent. CD34+ cells were purified by high gradient magnetic cell separation. Genomic DNA and RNA were extracted with standard TRIZOL technique and quality controlled with the Agilent Bioanalyzer 2100 and Nanodrop ND-1000 systems. 500 ng of each of the genomic DNA were processed according to the protocol of the Affymetrix 500 k NspI and StyI genomic mapping protocol, hybridized to 500 k NspI/StyI chip sets and scanned on an Affymetrix GeneChip scanner 3000. The median SNP call rate of analysed samples was 88.6% and ranged from 76.3% to 95.4%. One sample from the MDS patients and two samples from the healthy donors were excluded from analysis due to insufficient call rates. Raw signal intensity data was generated by the GCOS 4.0 software and imported into Partek Genomics 6.2 software. The control samples of healthy individuals were assigned a copy number of two and used as a reference baseline to calculate copy numbers in MDS samples. On the calculated values genomic smoothing was performed with a window width of 0.5 Mbps and a Gaussian width at half maximum 50% of window width. Significant regions of copy number alterations were calculated with a test region width of 0.5 Mbp and contiguous regions set to contain at least 1 Mbp (p<0.01). In addition, gene expression profiling (HG-U133 plus 2.0) was performed by standard Affymetrix technique. Numerous so far unknown significant regions of putative deletion or amplification which are not detectable by standard genomic analysis were discovered in MDS samples. Commonly deleted or amplificated regions appeared on chromosomes 1, 2, 3, 4, 5, 6, 11, 17, 19, 21 and 22. Gene lists of significant regions were created and subsequently used to perform a supervised analysis of gene expression data generated from the same bone marrow samples. This integration of genomic copy number analysis with global gene expression data showed that alterations of copy number directly affects gene expression patterns. In conclusion, this is the first high-density genomic mapping of CD34+ bone marrow cells from patients with MDS which could identify a number of so far unknown DNA-deletions/amplifications. These data contribute substantially to the understanding of the pathophysiology of MDS in greater detail and furthermore can be used to identify genes/regions which could resemble targets of new specific treatment options.

Blood ◽  
2002 ◽  
Vol 100 (10) ◽  
pp. 3553-3560 ◽  
Author(s):  
Wolf-K. Hofmann ◽  
Sven de Vos ◽  
Martina Komor ◽  
Dieter Hoelzer ◽  
William Wachsman ◽  
...  

Gene patterns of expression in purified CD34+ bone marrow cells from 7 patients with low-risk myelodysplastic syndrome (MDS) and 4 patients with high-risk MDS were compared with expression data from CD34+ bone marrow cells from 4 healthy control subjects. CD34+ cells were isolated by magnetic cell separation, and high-density oligonucleotide microarray analysis was performed. For confirmation, the expression of selected genes was analyzed by real-time polymerase chain reaction. Class membership prediction analysis selected 11 genes. Using the expression profile of these genes, we were able to discriminate patients with low-risk from patients with high-risk MDS and both patient groups from the control group by hierarchical clustering (Spearman confidence). The power of these 11 genes was verified by applying the algorithm to an unknown test set containing expression data from 8 additional patients with MDS (3 at low risk, 5 at high risk). Patients at low risk could be distinguished from those at high risk by clustering analysis. In low-risk MDS, we found that the retinoic-acid–induced gene (RAI3), the radiation-inducible, immediate-early response gene (IEX1), and the stress-induced phosphoprotein 1 (STIP1) were down-regulated. These data suggest that CD34+cells from patients with low-risk MDS lack defensive proteins, resulting in their susceptibility to cell damage. In summary, we propose that gene expression profiling may have clinical relevance for risk evaluation in MDS at the time of initial diagnosis. Furthermore, this study provides evidence that in MDS, hematopoietic stem cells accumulate defects that prevent normal hematopoiesis.


2020 ◽  
Vol 14 ◽  
Author(s):  
Mette Soerensen ◽  
Dominika Marzena Hozakowska-Roszkowska ◽  
Marianne Nygaard ◽  
Martin J. Larsen ◽  
Veit Schwämmle ◽  
...  

2017 ◽  
Vol 117 (04) ◽  
pp. 758-768 ◽  
Author(s):  
Sebastian Armasu ◽  
Bryan McCauley ◽  
Iftikhar Kullo ◽  
Hugues Sicotte ◽  
Jyotishman Pathak ◽  
...  

SummaryTo identify novel single nucleotide polymorphisms (SNPs) associated with venous thromboembolism (VTE) in African-Americans (AAs), we performed a genome-wide association study (GWAS) of VTE in AAs using the Electronic Medical Records and Genomics (eMERGE) Network, comprised of seven sites each with DNA biobanks (total ~39,200 unique DNA samples) with genome-wide SNP data (imputed to 1000 Genomes Project cosmopolitan reference panel) and linked to electronic health records (EHRs). Using a validated EHR-driven phenotype extraction algorithm, we identified VTE cases and controls and tested for an association between each SNP and VTE using unconditional logistic regression, adjusted for age, sex, stroke, site-platform combination and sickle cell risk genotype. Among 393 AA VTE cases and 4,941 AA controls, three intragenic SNPs reached genome-wide significance: LEMD3 rs138916004 (OR=3.2; p=1.3E-08), LY86 rs3804476 (OR=1.8; p=2E-08) and LOC100130298 rs142143628 (OR=4.5; p=4.4E-08); all three SNPs validated using internal cross-validation, parametric bootstrap and meta-analysis methods. LEMD3 rs138916004 and LOC100130298 rs142143628 are only present in Africans (1000G data). LEMD3 showed a significant differential expression in both NCBI Gene Expression Omnibus (GEO) and the Mayo Clinic gene expression data, LOC100130298 showed a significant differential expression only in the GEO expression data, and LY86 showed a significant differential expression only in the Mayo expression data. LEMD3 encodes for an antagonist of TGF-β-induced cell proliferation arrest. LY86 encodes for MD-1 which down-regulates the pro-inflammatory response to lipopolysaccharide; LY86 variation was previously associated with VTE in white women; LOC100130298 is a non-coding RNA gene with unknown regulatory activity in gene expression and epigenetics.Supplementary Material to this article is available online at www.thrombosis-online.com.


2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Ieva Rauluseviciute ◽  
Finn Drabløs ◽  
Morten Beck Rye

Abstract Background Prostate cancer (PCa) has the highest incidence rates of cancers in men in western countries. Unlike several other types of cancer, PCa has few genetic drivers, which has led researchers to look for additional epigenetic and transcriptomic contributors to PCa development and progression. Especially datasets on DNA methylation, the most commonly studied epigenetic marker, have recently been measured and analysed in several PCa patient cohorts. DNA methylation is most commonly associated with downregulation of gene expression. However, positive associations of DNA methylation to gene expression have also been reported, suggesting a more diverse mechanism of epigenetic regulation. Such additional complexity could have important implications for understanding prostate cancer development but has not been studied at a genome-wide scale. Results In this study, we have compared three sets of genome-wide single-site DNA methylation data from 870 PCa and normal tissue samples with multi-cohort gene expression data from 1117 samples, including 532 samples where DNA methylation and gene expression have been measured on the exact same samples. Genes were classified according to their corresponding methylation and expression profiles. A large group of hypermethylated genes was robustly associated with increased gene expression (UPUP group) in all three methylation datasets. These genes demonstrated distinct patterns of correlation between DNA methylation and gene expression compared to the genes showing the canonical negative association between methylation and expression (UPDOWN group). This indicates a more diversified role of DNA methylation in regulating gene expression than previously appreciated. Moreover, UPUP and UPDOWN genes were associated with different compartments — UPUP genes were related to the structures in nucleus, while UPDOWN genes were linked to extracellular features. Conclusion We identified a robust association between hypermethylation and upregulation of gene expression when comparing samples from prostate cancer and normal tissue. These results challenge the classical view where DNA methylation is always associated with suppression of gene expression, which underlines the importance of considering corresponding expression data when assessing the downstream regulatory effect of DNA methylation.


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