scholarly journals Significant Features of DNA Methylation at Bivalent Promotor and Repressed Polycomb Regions in Pediatric AML-the Jccg Study, JPLSG AML-05-

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 2739-2739
Author(s):  
Genki Yamato ◽  
Tomoko Kawai ◽  
Norio Shiba ◽  
Yusuke Hara ◽  
Kentaro Ohki ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Hierarchical Clustering ◽  
Pediatric Patients ◽  
Normal Karyotype ◽  
Genetic Alterations ◽  
Promoter Regions ◽  
Cpg Sites ◽  
Genome Wide ◽  
Equity Ownership ◽  
Biallelic Mutations

Introduction Acute myeloid leukemia (AML) is a clinically and biologically heterogeneous hematologic malignancy characterized by various genetic alterations. Currently, DNA methylation patterns were reported to be associated with molecular subtypes, chromosomal abnormalities, gene fusion, and prognosis in AML. Furthermore, previous study reported that aberrant cancer-associated DNA hypermethylation targets CpG islands characterized by bivalent chromatin in human embryonic stem cells (hESCs), and the bivalent chromatin signature in hESCs was a key determinant of the instructive program for aberrant DNA methylation. Thus, we analyzed genome-wide DNA methylation in 64 pediatric patients with AML to reveal its association with clinical features, genetic alterations, and prognostic impact. Methods Between 2006 and 2010, 443 pediatric patients with de novo AML (0-17 years) participated in the Japanese AML-05 trial conducted by the Japanese Pediatric Leukemia/Lymphoma Study Group. Of these, 64 patients were enrolled in this study. The cytogenetic features of 64 patients were as follows: normal karyotype, 28; RUNX1-RUNX1T1, 8; KMT2A rearrangement, 15; complex karyotype, 6; and other cytogenetics, 7. This cohort included 15 patients with FLT3-internal tandem duplication (ITD), 8 with CEBPA biallelic mutations, 5 with high MECOM (EVI1) expression, and 17 with high PRDM16 (MEL1) expression. We performed genome-wide DNA methylation analysis using Infinium MethylationEPIC BeadChip (Illumina) in 64 pediatric patients. Results and Discussion 824,848 methylation sites per sample were analyzed in 64 pediatric patients with AML. To capture DNA methylation differences across samples, we selected 567 CpG sites which showed most variable methylation values between 64 individuals such as standard deviations across samples were more than 0.3. The unsupervised hierarchical clustering of DNA methylation data from 567 CpG sites generated 4 clusters (clusters 1-4) with distinct molecular and clinical characteristics. Cluster 1 or 2 was the lowest or highest methylation level, respectively. Clusters 3 and 4 showed intermediate methylation level. Cluster 1 was characterized by RUNX1-RUNX1T1 and KMT2A rearrangement with low MECOM expression, which are known as favorable prognostic factors. Clusters 2 and 4 were composed of patients with the molecular features showing adverse outcome such as FLT3-ITD, KMT2A-PTD and/or normal karyotype with high PRDM16 expression. Interestingly, KMT2A rearrangement with high MECOM expression, considered as the adverse prognostic factor, were included in clusters 2 or 4. As for KMT2A rearrangement, nine of 15 patients with KMT2A rearrangement harbored KMT2A-MLLT3. Of these, five of nine classified into the hypomethylation group, and all five patients had no event. On the other hand, remaining four patients with KMT2A-MLLT3 all relapsed. All patients with normal karyotype with CEBPA biallelic mutations considered as the favorable factor were found in cluster 3. When we focused on CpG sites with significant difference in their methylation values between patients with and without FLT3-ITD, 15 FLT3-ITD patients were divided into two clusters (clusters A and B) by the hierarchical clustering. Remarkably, 8 FLT3-ITD positive patients in cluster A showed significantly worse overall survival (OS) and event-free survival (EFS) when compared with those in cluster B (5-year OS, 13% vs. 100%, P = 0.002; 5-year EFS 0% vs. 86%, P < 0.001). Next, 244 CpG sites significantly associated with PRDM16 expression were extracted to investigate the relationship between PRDM16 expression and DNA methylation profiles. Interestingly, patients with high and low PRDM16 expression showed distinct methylation pattern, respectively. Furthermore, most of hypermethylated sites gene were PRDM16 gene body in patients with high PRDM16 expression and located at important regions which were the targets of repressed polycomb in reference cells. As for 567 CpG sites which were used for the unsupervised hierarchical clustering, 168 of 567 (30%) CpG sites colocalized at bivalent promoter regions in reference leukemic blast cells, and the hypermethylation of bivalent promoter regions tended to be related to worse outcome. These results indicate DNA methylation plays key role for leukemogenesis and is remarked as a novel biomarker to predict prognosis. Disclosures Ogawa: ChordiaTherapeutics, Inc.: Consultancy, Equity Ownership; RegCell Corporation: Equity Ownership; Kan Research Laboratory, Inc.: Consultancy; Asahi Genomics: Equity Ownership; Qiagen Corporation: Patents & Royalties; Dainippon-Sumitomo Pharmaceutical, Inc.: Research Funding.

scholarly journals Genome-wide DNA Methylation Analysis in Pediatric Acute Myeloid Leukemia

2022 ◽  
Author(s):  
Genki Yamato ◽  
Tomoko Kawai ◽  
Norio Shiba ◽  
Junji Ikeda ◽  
Yusuke Hara ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Acute Myeloid Leukemia ◽  
Adverse Events ◽  
Myeloid Leukemia ◽  
Genetic Alterations ◽  
Binding Motif ◽  
Cpg Sites ◽  
Genome Wide ◽  
Methylation Patterns ◽  
Acute Myeloid

We investigated genome-wide DNA methylation patterns in 64 pediatric patients with acute myeloid leukemia (AML). Based on unsupervised clustering with 567 most variably methylated CpG sites, patients were categorized into four clusters associated with genetic alterations. Clusters 1 and 3 were characterized by the presence of known favorable prognostic factors, such as RUNX1-RUNX1T1 fusion and KMT2A rearrangement with low MECOM expression, and biallelic CEBPA mutations (all 8 patients), respectively. Clusters 2 and 4 comprised patients exhibiting molecular features associated with adverse outcomes, namely FLT3-ITD, KMT2A-PTD, and high PRDM16 expression. Depending on the methylation values of the 1243 CpG sites that were significantly different between FLT3-ITD positive and negative AML, patients were categorized into three clusters: A, B, and C. The STAT5-binding motif was most frequently found close to the 1,243 CpG sites. All eight patients with FLT3-ITD in Cluster A harbored high PRDM16 expression and experienced adverse events, whereas only one of seven patients with FLT3-ITD in the other clusters experienced adverse events. PRDM16 expression levels were also related to DNA methylation patterns, which were drastically changed at the cutoff value of PRDM16/ABL1 = 0.10. The assay for transposase-accessible chromatin sequencing of AMLs supported enhanced chromatin accessibilities around genomic regions, such as HOXB cluster genes, SCHIP1, and PRDM16, which were associated with DNA methylation changes in AMLs with FLT3-ITD and high PRDM16 expression. Our results suggest that DNA methylation levels at specific CpG sites are useful to support genetic alterations and gene expression patterns of patients with pediatric AML.

scholarly journals DNA methylation mediates the association between breastfeeding and early-life growth trajectories

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Laurent Briollais ◽  
Denis Rustand ◽  
Catherine Allard ◽  
Yanyan Wu ◽  
Jingxiong Xu ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Signaling Pathway ◽  
Exclusive Breastfeeding ◽  
Child Growth ◽  
Postnatal Period ◽  
Overweight And Obesity ◽  
Breastfeeding Duration ◽  
Ampk Signaling ◽  
Cpg Sites ◽  
Genome Wide

Abstract Background The role of breastfeeding in modulating epigenetic factors has been suggested as a possible mechanism conferring its benefits on child development but it lacks evidence. Using extensive DNA methylation data from the ALSPAC child cohort, we characterized the genome-wide landscape of DNA methylation variations associated with the duration of exclusive breastfeeding and assessed whether these variations mediate the association between exclusive breastfeeding and BMI over different epochs of child growth. Results Exclusive breastfeeding elicits more substantial DNA methylation variations during infancy than at other periods of child growth. At the genome-wide level, 13 CpG sites in girls (miR-21, SNAPC3, ATP6V0A1, DHX15/PPARGC1A, LINC00398/ALOX5AP, FAM238C, NATP/NAT2, CUX1, TRAPPC9, OSBPL1A, ZNF185, FAM84A, PDPK1) and 2 CpG sites in boys (IL16 and NREP), mediate the association between exclusive breastfeeding and longitudinal BMI. We found enrichment of CpG sites located within miRNAs and key pathways (AMPK signaling pathway, insulin signaling pathway, endocytosis). Overall DNA methylation variation corresponding to 3 to 5 months of exclusive breastfeeding was associated with slower BMI growth the first 6 years of life compared to no breastfeeding and in a dose–response manner with exclusive breastfeeding duration. Conclusions Our study confirmed the early postnatal period as a critical developmental period associated with substantial DNA methylation variations, which in turn could mitigate the development of overweight and obesity from infancy to early childhood. Since an accelerated growth during these developmental periods has been linked to the development of sustained obesity later in life, exclusive breastfeeding could have a major role in preventing the risks of overweight/obesity and children and adults through DNA methylation mechanisms occurring early in life.

Abstract P098: An Epigenome-wide Study of Obesity in African American Youth and Young Adults: Novel Findings, Replication in Neutrophils and Relationship With Gene Expression

Circulation ◽  
2017 ◽  
Vol 135 (suppl_1) ◽  
Author(s):  
Xiaoling Wang ◽  
Yue Pan ◽  
Haidong Zhu ◽  
Guang Hao ◽  
Xin Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Older Adults ◽  
Dna Methylation ◽  
Young Adults ◽  
Methylation Data ◽  
Middle Aged ◽  
Cpg Sites ◽  
Genome Wide ◽  
Obesity Status ◽  
Youth And Young Adults

Background: Several large-scale epigenome wide association studies on obesity-related DNA methylation changes have been published and in total identified 46 CpG sites. These studies were conducted in middle-aged and older adults of Caucasians and African Americans (AAs) using leukocytes. To what extend these signals are independent of cell compositions as well as to what extend they may influence gene expression have not been systematically investigated. Furthermore, the high prevalence of obesity comorbidities in middle-aged or older population may hide or bias obesity itself related DNA methylation changes. Methods: In this study of healthy AA youth and young adults, genome wide DNA methylation data from leukocytes were obtained from three independent studies: EpiGO study (96 obese cases vs. 92 lean controls, aged 14-21, 50% females, test of interest is obesity status), LACHY study (284 participants from general population, aged 14-18, 50% females, test of interest is BMI), and Georgia Stress and Heart study (298 participants from general population, aged 18-38, 52% females, test of interest is BMI) using the Infinium HumanMethylation450 BeadChip. Genome wide DNA methylation data from purified neutrophils as well as genome wide gene expression data from leukocytes using Illumina HT12 V4 array were also obtained for the EpiGO samples. Results: The meta-analysis on the 3 cohorts identified 76 obesity related CpG sites in leukocytes with p<1х10 -7 . Out of the 46 previously identified CpG sites, 36 can be replicated in this AA youth and young adult sample with same direction and p<0.05. Out of the 107 CpG sites including the 36 replicated ones and the 71 newly identified ones, 71 CpG sites (66%) had their relationship with obesity replicated in purified neutrophils (p<0.05). The analysis on the cis regulation of the 107 CpG sites on gene expression showed that 59 CpG sites had at least one gene within 250kb having expression difference between obese cases and lean controls. Furthermore, out of the 59 CpG sites, 6 showed significantly negative correlations and 1 showed significantly positive correlation with the differentially expressed genes. These CpG sites located in SOCS3, CISH, ABCG1, PIM3 and PTGDS genes. Conclusion: In this study of AA youth and young adults, we identified novel CpG sites associated with obesity and replicated majority of the CpG sites previously identified in middle-aged and older adults. For the first time, we showed that majority of the obesity related CpG sites identified from leukocytes are not driven by cell compositions and provided the direct link between DNA methylation-gene expression-obesity status for 7 CpG sites in 5 genes.

scholarly journals Changes in DNA Methylation and Gene Expression of Insulin and Obesity-Related Gene PIK3R1 after Roux-en-Y Gastric Bypass

2020 ◽  
Vol 21 (12) ◽  
pp. 4476
Author(s):  
Marcela A S Pinhel ◽  
Natália Y Noronha ◽  
Carolina F Nicoletti ◽  
Vanessa AB Pereira ◽  
Bruno AP de Oliveira ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Weight Loss ◽  
Gastric Bypass ◽  
Related Gene ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genetically Determined ◽  
Methylation Patterns ◽  
Weight Loss Interventions

Weight regulation and the magnitude of weight loss after a Roux-en-Y gastric bypass (RYGB) can be genetically determined. DNA methylation patterns and the expression of some genes can be altered after weight loss interventions, including RYGB. The present study aimed to evaluate how the gene expression and DNA methylation of PIK3R1, an obesity and insulin-related gene, change after RYGB. Blood samples were obtained from 13 women (35.9 ± 9.2 years) with severe obesity before and six months after surgical procedure. Whole blood transcriptome and epigenomic patterns were assessed by microarray-based, genome-wide technologies. A total of 1966 differentially expressed genes were identified in the pre- and postoperative periods of RYGB. From these, we observed that genes involved in obesity and insulin pathways were upregulated after surgery. Then, the PIK3R1 gene was selected for further RT-qPCR analysis and cytosine-guanine nucleotide (CpG) sites methylation evaluation. We observed that the PI3KR1 gene was upregulated, and six DNA methylation CpG sites were differently methylated after bariatric surgery. In conclusion, we found that RYGB upregulates genes involved in obesity and insulin pathways.

scholarly journals Genome-wide DNA methylation profile of early-onset endometrial cancer: its correlation with genetic aberrations and comparison with late-onset endometrial cancer

2019 ◽  
Vol 40 (5) ◽  
pp. 611-623 ◽  
Author(s):  
Takeshi Makabe ◽  
Eri Arai ◽  
Takuro Hirano ◽  
Nanako Ito ◽  
Yukihiro Fukamachi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Endometrial Cancer ◽  
Early Onset ◽  
Late Onset ◽  
Methylation Profile ◽  
Cancer Tissue ◽  
Cpg Sites ◽  
Genome Wide ◽  
Dna Methylation Profile ◽  
Endometrioid Endometrial Cancer

Abstract The present study was performed to clarify the significance of DNA methylation alterations during endometrial carcinogenesis. Genome-wide DNA methylation analysis and targeted sequencing of tumor-related genes were performed using the Infinium MethylationEPIC BeadChip and the Ion AmpliSeq Cancer Hotspot Panel v2, respectively, for 31 samples of normal control endometrial tissue from patients without endometrial cancer and 81 samples of endometrial cancer tissue. Principal component analysis revealed that tumor samples had a DNA methylation profile distinct from that of control samples. Gene Ontology enrichment analysis revealed significant differences of DNA methylation at 1034 CpG sites between early-onset endometrioid endometrial cancer (EE) tissue (patients aged ≤40 years) and late-onset endometrioid endometrial cancer (LE) tissue, which were accumulated among ‘transcriptional factors’. Mutations of the CTNNB1 gene or DNA methylation alterations of genes participating in Wnt signaling were frequent in EEs, whereas genetic and epigenetic alterations of fibroblast growth factor signaling genes were observed in LEs. Unsupervised hierarchical clustering grouped EE samples in Cluster EA (n = 22) and samples in Cluster EB (n = 12). Clinicopathologically less aggressive tumors tended to be accumulated in Cluster EB, and DNA methylation levels of 18 genes including HOXA9, HOXD10 and SOX11 were associated with differences in such aggressiveness between the two clusters. We identified 11 marker CpG sites that discriminated EB samples from EA samples with 100% sensitivity and specificity. These data indicate that genetically and epigenetically different pathways may participate in the development of EEs and LEs, and that DNA methylation profiling may help predict tumors that are less aggressive and amenable to fertility preservation treatment.

scholarly journals Testing cell-type-specific mediation effects in genome-wide epigenetic studies

2020 ◽  
Author(s):  
Xiangyu Luo ◽  
Joel Schwartz ◽  
Andrea Baccarelli ◽  
Zhonghua Liu
Keyword(s):  
Dna Methylation ◽  
Mediation Analysis ◽  
Methylation Data ◽  
Cell Type ◽  
Multiple Testing Procedure ◽  
Mediation Effects ◽  
Cpg Sites ◽  
Genome Wide ◽  
A Cell ◽  
Cell Type Specific

Abstract Epigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.

scholarly journals Methyltransferase DnmA is responsible for genome-wide N6-methyladenosine modifications at non-palindromic recognition sites in Bacillus subtilis

2020 ◽  
Vol 48 (10) ◽  
pp. 5332-5348
Author(s):  
Taylor M Nye ◽  
Lieke A van Gijtenbeek ◽  
Amanda G Stevens ◽  
Jeremy W Schroeder ◽  
Justin R Randall ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Bacillus Subtilis ◽  
Consensus Sequence ◽  
Dna Uptake ◽  
Cellular Functions ◽  
Promoter Regions ◽  
Gram Positive Bacteria ◽  
Genome Wide ◽  
Domains Of Life ◽  
Reporter Assays

Abstract The genomes of organisms from all three domains of life harbor endogenous base modifications in the form of DNA methylation. In bacterial genomes, methylation occurs on adenosine and cytidine residues to include N6-methyladenine (m6A), 5-methylcytosine (m5C), and N4-methylcytosine (m4C). Bacterial DNA methylation has been well characterized in the context of restriction-modification (RM) systems, where methylation regulates DNA incision by the cognate restriction endonuclease. Relative to RM systems less is known about how m6A contributes to the epigenetic regulation of cellular functions in Gram-positive bacteria. Here, we characterize site-specific m6A modifications in the non-palindromic sequence GACGmAG within the genomes of Bacillus subtilis strains. We demonstrate that the yeeA gene is a methyltransferase responsible for the presence of m6A modifications. We show that methylation from YeeA does not function to limit DNA uptake during natural transformation. Instead, we identify a subset of promoters that contain the methylation consensus sequence and show that loss of methylation within promoter regions causes a decrease in reporter expression. Further, we identify a transcriptional repressor that preferentially binds an unmethylated promoter used in the reporter assays. With these results we suggest that m6A modifications in B. subtilis function to promote gene expression.

scholarly journals PSVIII-39 Genome-wide DNA methylation alteration in prenatally stressed Brahman heifer calves with the advancement of age

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 263-264
Author(s):  
Kubra Z Cilkiz ◽  
Emilie C Baker ◽  
Penny K Riggs ◽  
Ronald D Randel ◽  
David G Riley ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Embryonic Stem ◽  
Control Group ◽  
Promoter Regions ◽  
Cpg Sites ◽  
Transcriptional Regulatory ◽  
Canonical Pathways ◽  
Prenatally Stressed

Abstract This study investigated whether DNA methylation patterns changed over the first five yr of life within prenatally stressed (PNS) heifer calves compared to change within a Control group. Prenatal stress was induced by the transportation of pregnant Brahman cows for 2-hr periods at 60±5, 80± 5, 100±5, 120±5, and140±5d of gestation. White blood cells were sampled from the same 6 PNS heifer calves and 8 Control heifer calves at 28 d and 5 yr of age. The DNA methylation data were generated through Reduced Representation Bisulfite Sequencing. Based on results of mapping and bioinformatics analyses, 73,758 hypermethylated and 73,367 hypomethylated CpG sites, 375 hypermethylated and 377 hypomethylated CHG sites, 735 hypermethylated and 842 hypomethylated CHH (C = cytosine; G = guanine; H = either adenine, thymine, or cytosine) sites were obtained from 28-d-old PNS calves compared to when they had matured into 5-yr-old PNS cows (P ≤ 0.05). The 28-d-old Control heifer calves contained 53,005 hypermethylated and 57,103 hypomethylated CpG sites, 200 hypermethylated and 202 hypomethylated CHG sites, 439 hypermethylated and 535 hypomethylated CHH sites compared to when they matured into 5-yr-old Control cows (P ≤ 0.05). As DNA methylation of gene promoter regions is associated with reduced transcription activity, strongly hypermethylated and hypomethylated CpG sites located in promoter regions underwent Ingenuity Pathway Analysis. The top canonical pathways altered by strongly hypermethylated and hypomethylated CpG sites between 28-d-old and 5-yr-old PNS cows were 4-1BB Signaling in T Lymphocytes (P = 0.00169) and Transcriptional Regulatory Network in Embryonic Stem Cells (P = 0.000744). Mineralocorticoid Biosynthesis (P = 0.00901) and Transcriptional Regulatory Network in Embryonic Stem Cells (P = 0.000804) were the other top canonical pathways altered between 28-d-old and 5-yr-old Control cows. PNS calves appeared to develop an altered epigenome compared to Control group calves during the first five yr from birth.

Impact of Expression of BAALC, CDKN1B, ERG, EVI1, and MN1 on Prognosis and Their Association with Karyotype, FLT3-ITD, NPM1 and MLL-PTD Status In Adult AML: A Comprehensive Study on 286 Cases

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 953-953
Author(s):  
Claudia Haferlach ◽  
Alexander Kohlmann ◽  
Sonja Schindela ◽  
Tamara Alpermann ◽  
Wolfgang Kern ◽  
...  
Keyword(s):  
Molecular Genetic ◽  
Normal Karyotype ◽  
Genetic Alterations ◽  
Complex Karyotype ◽  
Employment Equity ◽  
Aberrant Expression ◽  
Cox Regression Analysis ◽  
Total Cohort ◽  
Equity Ownership ◽  
Low Expression

Abstract Abstract 953 Introduction: The WHO classification in 2008 listed for the first time aberrant expression of genes as molecular genetic alterations affecting outcome in AML. High expression of BAALC, ERG and MN1 were shown thus far to be associated with unfavorable outcome in normal karyotype AML (AML-NK). In addition high EVI1 expression was suggested to predict poor outcome. Recently, our group identified low expression of CDKN1B as a favorable prognostic marker. The aim of this study was to evaluate the expression of BAALC, CDKN1B, ERG, EVI1 and MN1 in AML comprising all cytogenetic risk groups with respect to their association with distinct cytogenetic and known molecular genetic subgroups and their impact on prognosis. Patients/Methods:: Expression levels of BAALC, CDKN1B, ERG, EVI1 and MN1 were determined by oligonucleotide microarrays (HG-U133 Plus 2.0, Affymetrix) in 286 AML (t(15;17) n=15; t(8;21) n=16; inv(16) n=7; normal karyotype n=99; 11q23/MLL-rearrangements n=10; complex karyotype n=51; other abnormalities n=88). Patients were further analyzed for mutations in NPM1, FLT3-ITD, CEPBA and MLL-PTD. Results: Expression of BAALC, CDKN1B, ERG, EVI1 and MN1 varied significantly between genetic subgroups: While t(15;17), t(8;21) and 11q23/MLL-rearrangements were associated with low CDKN1B expression, AML-NK and NPM+ cases showed a higher CDKN1B expression. Lower BAALC expression was observed in AML with t(15;17), 11q23/MLL-rearrangement and AML-NK as well as in FLT3-ITD+ AML and in NPM1+ AML, while in AML with other abnormalities a higher BAALC expression was observed. ERG expression was lower in AML with 11q23/MLL-rearrangement and normal karyotype, while it was higher in AML with complex karyotype. Low EVI1 expression was observed in AML with t(15;17), t(8;21), inv(16) and AML-NK, while it was higher in AML with 11q23/MLL-rearrangements. Low MN1 expression was associated with t(15;17), t(8;21) and AML-NK, while it was increased in cases with inv(16) or other abnormalities. Next, Cox regression analysis was performed with respect to overall survival (OS) and event free survival (EFS). In the total cohort high BAALC and ERG expression as continuous variables were associated with shorter OS and EFS while CDKN1B, EVI1 and MN1 had no impact. Furthermore the cohort was subdivided into quartiles of expression for each gene. After inspection of the survival curves the cut-off for high vs low expression was set as follows: BAALC: 75th percentile, CDKN1B: 25th percentile, ERG and MN1: 50th percentile. For EVI1 expression pts were separated into expressers (n=44) and non-expressers (n=242). Low CDKN1B expression was associated with longer OS and EFS in the total cohort (p=0.005, not reached (n.r.) vs 14.9 months (mo); p=0.013, 31 vs 9.7 mo). High BAALC expression had no impact on OS, but was associated with shorter EFS in the total cohort as well as in AML with intermediate cytogenetics and AML with other abnormalities (p=0.032, 6.2 vs 13.0 mo; p=0.027, 5.1 vs 11.3 mo; p=0.006, 2.3 vs 14.8 mo). High ERG expression was significantly associated with shorter OS and EFS in the total cohort (p=0.002, 12.5 mo vs n.r.; p=0.001, 8.1 vs 15.7 mo) as well as in AML-NK (p=0.001, 11.3 mo vs n.r.; p=0.010, 7.2 vs 22.1 mo). OS was also shorter in AML with unfavorable karyotype (p=0.048, median OS 9.3 mo vs n. r.). With respect to MN1 high expressers had a significantly shorter OS and EFS in the total cohort (p=0.004, 12.3 mo vs. n.r.; p=0.001, 8.1 vs 16.7 mo) as well as in AML-NK (p=0.001, 9.7 mo vs n.r.; p=0.001, 5.1 vs 22.1 mo). In a multivariate analysis including CDKN1B, ERG and MN1 all parameters retained their impact on OS as well as on EFS, while BAALC lost its impact on EFS. Adding MLL-PTD, NPM1+/FLT3-ITD-, favorable and unfavorable karyotype into the model demonstrated an independent significant adverse impact on OS for MLL-PTD (p=0.027, relative risk (RR): 2.38) and ERG expression (p=0.044, RR: 1.59) only. In the respective analysis for EFS only favorable karyotype showed an independent association (p=0.002, RR: 0.261). Conclusion: 1) Expression of BAALC, CDKN1B, ERG, EVI1 and MN1 varies significantly between cytogenetic subgroups. 2) BAALC as a continuous variable and CDKN1B, ERG and MN1 as dichotomized variables are independently predictive for OS and EFS in AML. 3) ERG expression even retains its independent prediction of shorter OS if cytogenetic and other molecular genetic markers are taken into account. Disclosures: Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Schindela:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Genome-Wide DNA Methylation Analysis Shows Enrichment of Differential Methylation in “Open Seas” and Enhancers and Reveals Hypomethylation in DNMT3A Mutated Cytogenetically Normal AML (CN-AML)

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 653-653 ◽  
Author(s):  
Ying Qu ◽  
Andreas Lennartsson ◽  
Verena I. Gaidzik ◽  
Stefan Deneberg ◽  
Sofia Bengtzén ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Island ◽  
Cpg Islands ◽  
Differential Methylation ◽  
Methylation Analysis ◽  
Cpg Sites ◽  
Genome Wide ◽  
Genomic Regions ◽  
Methylation Patterns

Abstract Abstract 653 DNA methylation is involved in multiple biologic processes including normal cell differentiation and tumorigenesis. In AML, methylation patterns have been shown to differ significantly from normal hematopoietic cells. Most studies of DNA methylation in AML have previously focused on CpG islands within the promoter of genes, representing only a very small proportion of the DNA methylome. In this study, we performed genome-wide methylation analysis of 62 AML patients with CN-AML and CD34 positive cells from healthy controls by Illumina HumanMethylation450K Array covering 450.000 CpG sites in CpG islands as well as genomic regions far from CpG islands. Differentially methylated CpG sites (DMS) between CN-AML and normal hematopoietic cells were calculated and the most significant enrichment of DMS was found in regions more than 4kb from CpG Islands, in the so called open sea where hypomethylation was the dominant form of aberrant methylation. In contrast, CpG islands were not enriched for DMS and DMS in CpG islands were dominated by hypermethylation. DMS successively further away from CpG islands in CpG island shores (up to 2kb from CpG Island) and shelves (from 2kb to 4kb from Island) showed increasing degree of hypomethylation in AML cells. Among regions defined by their relation to gene structures, CpG dinucleotide located in theoretic enhancers were found to be the most enriched for DMS (Chi χ2<0.0001) with the majority of DMS showing decreased methylation compared to CD34 normal controls. To address the relation to gene expression, GEP (gene expression profiling) by microarray was carried out on 32 of the CN-AML patients. Totally, 339723 CpG sites covering 18879 genes were addressed on both platforms. CpG methylation in CpG islands showed the most pronounced anti-correlation (spearman ρ =-0.4145) with gene expression level, followed by CpG island shores (mean spearman rho for both sides' shore ρ=-0.2350). As transcription factors (TFs) have shown to be crucial for AML development, we especially studied differential methylation of an unbiased selection of 1638 TFs. The most enriched differential methylation between CN-AML and normal CD34 positive cells were found in TFs known to be involved in hematopoiesis and with Wilms tumor protein-1 (WT1), activator protein 1 (AP-1) and runt-related transcription factor 1 (RUNX1) being the most differentially methylated TFs. The differential methylation in WT 1 and RUNX1 was located in intragenic regions which were confirmed by pyro-sequencing. AML cases were characterized with respect to mutations in FLT3, NPM1, IDH1, IDH2 and DNMT3A. Correlation analysis between genome wide methylation patterns and mutational status showed statistically significant hypomethylation of CpG Island (p<0.0001) and to a lesser extent CpG island shores (p<0.001) and the presence of DNMT3A mutations. This links DNMT3A mutations for the first time to a hypomethylated phenotype. Further analyses correlating methylation patterns to other clinical data such as clinical outcome are ongoing. In conclusion, our study revealed that non-CpG island regions and in particular enhancers are the most aberrantly methylated genomic regions in AML and that WT 1 and RUNX1 are the most differentially methylated TFs. Furthermore, our data suggests a hypomethylated phenotype in DNMT3A mutated AML. Disclosures: No relevant conflicts of interest to declare.

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