Expression of myeloperoxidase in acute myeloid leukemia blasts mirrors the distinct DNA methylation pattern involving the downregulation of DNA methyltransferase DNMT3B

Establishment and validation of a gene mutation-based risk model for predicting prognosis and therapy response in acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is a malignant clonal proliferative disease of hematopoietic system. Despite tremendous progress in uncovering the AML genome, only a small number of mutations have been incorporated into risk stratification and used as therapeutic targets. In this research, we performed to construct a predictive prognosis risk model for AML patients according to gene mutations.

Methods

Next-generation sequencing (NGS) technology was utilized to detect gene mutation from 118 patients. mRNA expression profiles and related clinical information were mined from TCGA and GEO databases. Consensus cluster analysis was applied to obtain molecular subtypes, and differences in clinicopathological features, prognosis, and immune microenvironment of different clusters were systematically compared. According to the differentially expressed genes (DEGs) between clusters, univariate and LASSO regression analysis were applied to identify gene signatures to build a prognostic risk model. Patients were classified into high-risk (HR) and low-risk (LR) groups according to the median risk score (RS). Differences in prognosis, immune profile, and therapeutic sensitivity between two groups were analyzed. The independent predictive value of RS was assessed and a nomogram was developed.

Results

NGS detected 24 mutated genes, with higher mutation frequencies in CBL (63 %) and SETBP1 (49 %). Two clusters exhibited different immune microenvironments and survival probability (p = 0.0056) were identified. A total of 444 DEGs were screened in two clusters, and a mutation-associated risk model was constructed, including MPO, HGF, SH2B3, SETBP1, HLA-DRB1, LGALS1, and KDM5B. Patients in LR had a superior survival time compared to HR. Predictive performance of this model was confirmed and the developed nomogram further improved the applicability of the risk model with the AUCs for predicting 1-, 3-, 5-year survival rate were 0.829, 0.81 and 0.811, respectively. HR cases were more sensitive to erlotinib, CI-1040, and AZD6244.

Conclusion

These findings supplemented the understanding of gene mutations in AML, and constructed models had good application prospect to provide effective information for predicting prognosis and treatment response of AML.

Single-cell analysis reveals altered tumor microenvironments of relapse- and remission-associated pediatric acute myeloid leukemia

Acute myeloid leukemia (AML) microenvironment exhibits cellular and molecular differences among various subtypes. Here, we utilize single-cell RNA sequencing (scRNA-seq) to analyze pediatric AML bone marrow (BM) samples from diagnosis (Dx), end of induction (EOI), and relapse timepoints. Analysis of Dx, EOI scRNA-seq, and TARGET AML RNA-seq datasets reveals an AML blasts-associated 7-gene signature (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH), which we validate on independent datasets. The analysis reveals distinct clusters of Dx relapse- and continuous complete remission (CCR)-associated AML-blasts with differential expression of genes associated with survival. At Dx, relapse-associated samples have more exhausted T cells while CCR-associated samples have more inflammatory M1 macrophages. Post-therapy EOI residual blasts overexpress fatty acid oxidation, tumor growth, and stemness genes. Also, a post-therapy T-cell cluster associated with relapse samples exhibits downregulation of MHC Class I and T-cell regulatory genes. Altogether, this study deeply characterizes pediatric AML relapse- and CCR-associated samples to provide insights into the BM microenvironment landscape.

Super-enhancer profiling identifies novel critical and targetable cancer survival gene LYL1 in pediatric acute myeloid leukemia

Background

Acute myeloid leukemia (AML) is a myeloid neoplasm makes up 7.6% of hematopoietic malignancies. Super-enhancers (SEs) represent a special group of enhancers, which have been reported in multiple cell types. In this study, we explored super-enhancer profiling through ChIP-Seq analysis of AML samples and AML cell lines, followed by functional analysis.

Methods

ChIP-seq analysis for H3K27ac was performed in 11 AML samples, 7 T-ALL samples, 8 B-ALL samples, and in NB4 cell line. Genes and pathways affected by GNE-987 treatment were identified by gene expression analysis using RNA-seq. One of the genes associated with super-enhancer and affected by GNE-987 treatment was LYL1 basic helix-loop-helix family member (LYL1). shRNA mediated gene interference was used to down-regulate the expression of LYL1 in AML cell lines, and knockdown efficiency was detected by RT-qPCR and western blotting. The effect of knockdown on the growth of AML cell lines was evaluated by CCK-8. Western blotting was used to detect PARP cleavage, and flow cytometry were used to determine the effect of knockdown on apoptosis of AML cells.

Results

We identified a total of 200 genes which were commonly associated with super-enhancers in ≧10 AML samples, and were found enriched in regulation of transcription. Using the BRD4 inhibitor GNE-987, we assessed the dependence of AML cells on transcriptional activation for growth and found GNE-987 treatment predominantly inhibits cell growth in AML cells. Moreover, 20 candidate genes were selected by super-enhancer profile and gene expression profile and among which LYL1 was observed to promote cell growth and survival in human AML cells.

Conclusions

In summary, we identified 200 common super-enhancer-associated genes in AML samples, and a series of those genes are cancer genes. We also found GNE-987 treatment downregulates the expression of super-enhancer-associated genes in AML cells, including the expression of LYL1. Further functional analysis indicated that LYL1 is required for AML cell growth and survival. These findings promote understanding of AML pathophysiology and elucidated an important role of LYL1 in AML progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02428-9.

Comprehensive comparison between azacytidine and decitabine treatment in an acute myeloid leukemia cell line

Azacytidine (AzaC) and decitabine (AzadC) are cytosine analogs that covalently trap DNA methyltransferases, which place the important epigenetic mark 5-methyl-2'-deoxycytidine by methylating 2'-deoxycytidine (dC) at the C5 position. AzaC and AzadC are used in the clinic as antimetabolites to treat myelodysplastic syndrome and acute myeloid leukemia and are explored against other types of cancer. Although their principal mechanism of action is known, the downstream effects of AzaC and AzadC treatment are not well understood and the cellular prerequisites that determine sensitivity toward AzaC and AzadC remain elusive. Here, we investigated the effects and phenotype of AzaC and AzadC exposure on the acute myeloid leukemia cell line MOLM-13. We found that while AzaC and AzadC share many effects on the cellular level, including decreased global DNA methylation, increased formation of DNA double-strand breaks, transcriptional downregulation of important oncogenes and similar changes on the proteome level, AzaC failed in contrast to AzadC to induce apoptosis efficiently in MOLM-13. The only cellular marker that correlated with this clear phenotypical outcome was the level of hydroxy-methyl-dC, an additional epigenetic mark that is placed by TET enzymes and repressed in cancer cells. Whereas AzadC increased hmdC substantially in MOLM-13, AzaC treatment did not result in any increase at all. This suggests that hmdC levels in cancer cells should be monitored as a response toward AzaC and AzadC and considered as a biomarker to judge whether AzaC or AzadC treatment leads to cell death in leukemic cells.

Identifying Gene Network Rewiring Based on Partial Correlation

It is an important task to learn how gene regulatory networks change under different conditions. Several Gaussian graphical model-based methods have been proposed to deal with this task by inferring differential networks from gene expression data. However, most existing methods define the differential networks as the difference of precision matrices, which may include false differential edges caused by the change of conditional variances. In addition, prior information about the condition-specific networks and the differential networks can be obtained from other domains. It is useful to incorporate prior information into differential network analysis. In this study, we propose a new differential network analysis method to address the above challenges. Instead of using the precision matrices, we define the differential networks as the difference of partial correlations, which can exclude the spurious differential edges due to the variants of conditional variances. Furthermore, prior information from multiple hypothesis testing is incorporated using a weighted fused penalty. Simulation studies show that our method outperforms the competing methods. We also apply our method to identify the differential network between luminal A and basal-like subtypes of breast cancers and the differential network between acute myeloid leukemia tumors and normal samples. The hub genes in the differential networks identified by our method carry out important biological functions.

Targeting acute myeloid leukemia cells by CD33 receptor-specific MoS2-based nanoconjugates

Acute myeloid leukemia (AML) is a highly aggressive type of cancer caused by the uncontrolled proliferation of undifferentiated myeloblasts, affecting the bone marrow and blood. Systemic chemotherapy is considered the primary treatment strategy; unfortunately, healthy cells are also affected to a large extent, leading to severe side effects of this treatment. Targeted drug therapies are becoming increasingly popular in modern medicine, as they bypass normal tissues and cells. Two-dimensional MoS₂-based nanomaterials have attracted attention in the biomedical field as promising agents for cancer diagnosis and therapy. Cancer cells typically (over)express distinctive cytoplasmic membrane-anchored or -spanning protein-based structures (e.g., receptors, enzymes) that distinguish them from healthy, non-cancerous cells. Targeting cancer cells via tumor-specific markers using MoS₂-based nanocarriers loaded with labels or drugs can significantly improve specificity and reduce side effects of such treatment. SKM-1 is an established AML cell line that has been employed in various bio-research applications. However, to date, it has not been used as the subject of studies on selective cancer targeting by inorganic nanomaterials. Here, we demonstrate an efficient targeting of AML cells using MoS₂nanoflakes prepared by a facile exfoliation route and functionalized with anti-CD33 antibody that binds to CD33 receptors expressed by SKM-1 cells. Microscopic analyses by confocal laser scanning microscopy supplemented by label-free confocal Raman microscopy proved that (anti-CD33)-MoS₂conjugates were present on the cell surface and within SKM-1 cells, presumably having been internalized via CD33-mediated endocytosis. Furthermore, the cellular uptake of SKM-1 specific (anti-CD33)-MoS₂conjugates assessed by flow cytometry analysis was significantly higher compared with the cellular uptake of SKM-1 nonspecific (anti-GPC3)-MoS₂conjugates. Our results indicate the importance of appropriate functionalization of MoS₂nanomaterials by tumor-recognizing elements that significantly increase their specificity and hence suggest the utilization of MoS₂-based nanomaterials in the diagnosis and therapy of AML.

The Enzymatic and Non-Enzymatic Function of Myeloperoxidase (MPO) in Inflammatory Communication

Myeloperoxidase is a signature enzyme of polymorphonuclear neutrophils in mice and humans. Being a component of circulating white blood cells, myeloperoxidase plays multiple roles in various organs and tissues and facilitates their crosstalk. Here, we describe the current knowledge on the tissue- and lineage-specific expression of myeloperoxidase, its well-studied enzymatic activity and incoherently understood non-enzymatic role in various cell types and tissues. Further, we elaborate on Myeloperoxidase (MPO) in the complex context of cardiovascular disease, innate and autoimmune response, development and progression of cancer and neurodegenerative diseases.

Oxidative Stress and ROS-Mediated Signaling in Leukemia: Novel Promising Perspectives to Eradicate Chemoresistant Cells in Myeloid Leukemia

Myeloid leukemic cells are intrinsically under oxidative stress due to impaired reactive oxygen species (ROS) homeostasis, a common signature of several hematological malignancies. The present review focuses on the molecular mechanisms of aberrant ROS production in myeloid leukemia cells as well as on the redox-dependent signaling pathways involved in the leukemogenic process. Finally, the relevance of new chemotherapy options that specifically exert their pharmacological activity by altering the cellular redox imbalance will be discussed as an effective strategy to eradicate chemoresistant cells.

LINC00649 underexpression is an adverse prognostic marker in acute myeloid leukemia

BACKGROUND

Long noncoding RNAs (lncRNA) play a role in leukemogenesis, maintenance, development, and therapeutic resistance of AML. While few studies have focused on the prognostic significance of LINC00649 in AML, which we aim to investigate in this present study.

METHODS

We compared the expression level of LINC00649 between AML patients and healthy controls. The Kaplan-Meier curves of AML patients expressing high versus low level of LINC00649 was performed. The LINC00649 correlated genes/miRNAs/lncRNAs and methylation CpG sites were screened by Pearson correlation analysis with R (version 3.6.0), using TCGA-LAML database. The LINC00649 associated ceRNA network was established using lncBase 2.0 and miRWalk 2.0 online tools, combining results from correlation analysis. Finally, a prediction model was constructed using LASSO-Cox regression.

RESULTS

LINC00649 was underexpressed in bone marrow of AML group than that in healthy control group. The patients of LINC00649-low group have significantly inferior PFS and OS. A total of 154 mRNAs, 31 miRNAs, 28 lncRNAs and 1590 methylated CpG sites were identified to be significantly correlated with LINC00649. Furthermore, the network of ceRNA was established with 6 miRNAs and 122 mRNAs. The Lasso-Cox model fitted OS/PFS to novel prediction models, which integrated clinical factors, ELN risk stratification, mRNA/miRNA expression and methylation profiles. The analysis of time-dependent ROC for our model showed a superior AUC (AUC = 0.916 at 1 year, AUC = 0.916 at 3 years, and AUC = 0.891 at 5 years).

CONCLUSIONS

Low expression of LINC00649 is a potential unfavorable prognostic marker for AML patients, which requires the further validation. The analysis by LASSO-COX regression identified a novel comprehensive model with a superior diagnostic utility, which integrated clinical and genetic variables.

DNA methyltransferase inhibitor alleviates bleomycin-induced pulmonary inflammation

Acute lung injury (ALI) is a severe disease characterized by several inflammatory responses in the lung with high mortality. We applied a mouse model of the pulmonary inflammation induced by the intratracheal instillation of bleomycin which is widely used to induce ALI and fibrosis in animal models. We hypothesized that DNA methyltransferase inhibitor, 5-azacytidine (5-Aza), with its anti-inflammatory benefits, might attenuate bleomycin-induced ALI through the alleviation of inflammation in the lung. We quantified white blood cells with cell blood count (CBC) test, lung inflammation by analyzing cells in the collected bronchoalveolar lavage fluid (BALF) and histological analysis of the lung tissues, and gene expression levels by real-time PCR. Intratracheal administration of bleomycin in mice induced pulmonary inflammation, characterized by increased neutrophil infiltration and inflammatory cytokine expression in the lungs. Mice treated with 5-Aza showed a significant reduction of lung neutrophilia, together with lower expressions of CXCL2 and MCP-1. Furthermore, 5-Aza treatment decreased the expression of proinflammatory cytokines in the lung tissue. Collectively, our data show that DNA methyltransferase inhibitor can alleviate the lung inflammation of bleomycin-induced ALI, indicating an alternative treatment option for the inflammation-triggered lung injury.

Methyltransferase DNMT3B in leukemia

DNA methyltransferases (DNMTs) are highly conserved DNA-modifying enzymes that play important roles in epigenetic regulation and they are involved in cell proliferation, differentiation, and apoptosis. In mammalian cells, three active DNMTs have been identified: DNMT1 acts as a maintenance methyltransferase to replicate preexisting methylation patterns, whereas DNMT3A and DNMT3B primarily act as de novo methyltransferases that are responsible for establishing DNA methylation patterns by adding a methyl group to cytosine bases. The expression of DNMT3B is widespread in a variety of hematological cells and it is altered in each type of leukemia, which is associated with its pathogenesis, progression, treatment, and prognosis. Here, we review current information on DNMT3B in leukemia, including its expression, single-nucleotide polymorphisms, mutations, regulation, function, and clinical value for anti-leukemic therapy and prognosis.

Oncogenic Roles and Inhibitors of DNMT1, DNMT3A, and DNMT3B in Acute Myeloid Leukaemia

Epigenetic alteration has been proposed to give rise to numerous classic hallmarks of cancer. Impaired DNA methylation plays a central role in the onset and progression of several types of malignancies, and DNA methylation is mediated by DNA methyltransferases (DNMTs) consisting of DNMT1, DNMT3A, and DNMT3B. DNMTs are frequently implicated in the pathogenesis and aggressiveness of acute myeloid leukaemia (AML) patients. In this review, we describe and discuss the oncogenic roles of DNMT1, DNMT3A, and DNMT3B in AML. The clinical response predictive roles of DNMTs in clinical trials utilising hypomethylating agents (azacitidine and decitabine) in AML patients are presented. Novel hypomethylating agent (guadecitabine) and experimental DNMT inhibitors in AML are also discussed. In summary, hypermethylation of tumour suppressors mediated by DNMT1 or DNMT3B contributes to the progression and severity of AML (except MLL-AF9 and inv(16)(p13;q22) AML for DNMT3B), while mutation affecting DNMT3A represents an early genetic lesion in the pathogenesis of AML. In clinical trials of AML patients, expression of DNMTs is downregulated by hypomethylating agents while the clinical response predictive roles of DNMT biomarkers remain unresolved. Finally, nucleoside hypomethylating agents have continued to show enhanced responses in clinical trials of AML patients, and novel non-nucleoside DNMT inhibitors have demonstrated cytotoxicity against AML cells in pre-clinical settings.

Gene expression of hENT1, dCK, CDA, dCMPD and topoisomerase IIα as an indicator of chemotherapy response in AML treated with cytarabine and daunorubicin

Purpose

Acute myeloid leukemia patients are commonly treated with cytarabine (Ara-C) and anthracyclines but the sustained remission rate is not very promising. We explored the role of drug-metabolizing enzymes and transporters in the therapeutic response.

Patients and methods

Bone marrow and peripheral blood samples of 90 newly diagnosed acute myeloid leukemia patients treated with standard 3+7 regimen were analyzed through real-time PCR for expression of human equilibrative nucleoside transporter 1, deoxycytidine kinase, cytidine deaminase (CDA), deoxycytidine monophosphate deaminase (dCMPD) and topoisomerase IIα (Topo-IIa). The expression of these markers was studied in relationship with good (persistent remission) and poor therapeutic response (relapse/resistance).

Results

High Topo-IIa expression in peripheral blood was associated with good response (P=0.006). Relapse was higher among low expressors of Topo-IIa in peripheral blood (OR: 26.25). Bone marrow Topo-IIa expression followed a similar trend but did not reach statistical significance. In contrast, patients with high bone marrow dCMPD expression had poor response (OR: 3; P=0.043). One-year disease-free survival (DFS) was better among those with high bone marrow Topo-IIa (P=0.04) or CDA (P=0.03) expression. High bone marrow Topo-IIa expression also had better DFS at 6 months (P=0.04) and at 12 months (P=0.04).

Conclusion

High expression of Topo-IIa in peripheral blood is a favorable indicator of persistent remission, good therapeutic response and DFS. High dCMPD and low CDA expression in bone marrow is associated with poor therapeutic outcome.

Demethylator phenotypes in acute myeloid leukemia

Acute myeloid leukemia (AML) often harbors mutations in epigenetic regulators, and also has frequent DNA hypermethylation, including the presence of CpG island methylator phenotypes (CIMPs). Although global hypomethylation is well known in cancer, the question of whether distinct demethylator phenotypes (DMPs) exist remains unanswered. Using Illumina 450k arrays for 194 patients from The Cancer Genome Atlas, we identified two distinct DMPs by hierarchical clustering: DMP.1 and DMP.2. DMP.1 cases harbored mutations in NPM1 (94%), FLT3 (71%) and DNMT3A (61%). Surprisingly, only 40% of patients with DNMT3A mutations were DMP.1, which has implications for mechanisms of transformation by this mutation. In contrast, DMP.2 AML was comprised of patients with t(8;21), inv(16) or t(15;17), suggesting common methylation defects connect these disparate rearrangements. RNA-seq revealed upregulated genes functioning in immune response (DMP.1) and development (DMP.2). We confirmed these findings by integrating independent 450k data sets (236 additional cases), and found prognostic effects by DMP status, independent of age and cytogenetics. The existence of DMPs has implications for AML pathogenesis and may augment existing tools in risk stratification.

Distinct gene alterations with a high percentage of myeloperoxidase-positive leukemic blasts in de novo acute myeloid leukemia

The myeloperoxidase (MPO)-positivity of blasts in bone marrow smears is an important marker for not only the diagnosis, but also the prognosis of acute myeloid leukemia (AML). To investigate the relationship between genetic alterations and MPO-positivity, we performed targeted sequencing for 51 genes and 10 chimeric gene transcripts in 164 newly diagnosed de novo AML patients; 107 and 57 patients were classified as AML with >50% MPO-positive blasts (MPO-high group) and ≤50% MPO-positive blasts, (MPO-low group), respectively. The univariate analysis revealed that RUNX1-RUNX1T1 (P < 0.001), the KIT mutation (P < 0.001), and CEBPA double mutation (P = 0.001) were more likely to be found in the MPO-high group, while the DNMT3A mutation (P = 0.001), FLT3 tyrosine kinase domain mutation (P = 0.004), and TP53 mutation (P = 0.020) were more likely to be present in the MPO-low group. Mutations in genes related to DNA hypermethylation signatures (IDH1, IDH2, TET2, and WT1 genes) were more frequent in the MPO-high group (P = 0.001) when patients with fusion genes of core-binding factors were excluded from the analysis. Our results suggest that MPO-positivity of blasts was related with the distinct gene mutation patterns among de novo AML patients.

Domain retention in transcription factor fusion genes and its biological and clinical implications: a pan-cancer study

Genomic rearrangements involving transcription factors (TFs) can form fusion proteins resulting in either enhanced, weakened, or even loss of TF activity. Functional domain (FD) retention is a critical factor in the activity of transcription factor fusion genes (TFFGs). A systematic investigation of FD retention in TFFGs and their outcome (e.g. expression changes) in a pan-cancer study has not yet been completed. Here, we examined the FD retention status in 386 TFFGs across 13 major cancer types and identified 83 TFFGs involving 67 TFs that retained FDs. To measure the potential biological relevance of TFs in TFFGs, we introduced a Major Active Isofusion Index (MAII) and built a prioritized TFFG network using MAII scores and the observed frequency of fusion positive samples. Interestingly, the four TFFGs (PML-RARA, RUNX1-RUNX1T1, TMPRSS2-ERG, and SFPQ-TFE3) with the highest MAII scores showed 50 differentially expressed target genes (DETGs) in fusion-positive versus fusion-negative cancer samples. DETG analysis revealed that they were involved in tumorigenesis-related processes in each cancer type. PLAU, which encodes plasminogen activator urokinase and serves as a biomarker for tumor invasion, was found to be consistently activated in the samples with the highest MAII scores. Among the 50 DETGs, 21 were drug targetable genes. Fourteen of these 21 DETGs were expressed in acute myeloid leukemia (AML) samples. Accordingly, we constructed an AML-specific TFFG network, which included 38 DETGs in RUNX1-RUNX1T1 or PML-RARA positive samples. In summary, this study revealed several TFFGs and their potential target genes, and provided insights into the clinical implications of TFFGs.

Systematic computation with functional gene-sets among leukemic and hematopoietic stem cells reveals a favorable prognostic signature for acute myeloid leukemia

Background

Genes that regulate stem cell function are suspected to exert adverse effects on prognosis in malignancy. However, diverse cancer stem cell signatures are difficult for physicians to interpret and apply clinically. To connect the transcriptome and stem cell biology, with potential clinical applications, we propose a novel computational “gene-to-function, snapshot-to-dynamics, and biology-to-clinic” framework to uncover core functional gene-sets signatures. This framework incorporates three function-centric gene-set analysis strategies: a meta-analysis of both microarray and RNA-seq data, novel dynamic network mechanism (DNM) identification, and a personalized prognostic indicator analysis. This work uses complex disease acute myeloid leukemia (AML) as a research platform.

Results

We introduced an adjustable “soft threshold” to a functional gene-set algorithm and found that two different analysis methods identified distinct gene-set signatures from the same samples. We identified a 30-gene cluster that characterizes leukemic stem cell (LSC)-depleted cells and a 25-gene cluster that characterizes LSC-enriched cells in parallel; both mark favorable-prognosis in AML. Genes within each signature significantly share common biological processes and/or molecular functions (empirical p = 6e-5 and 0.03 respectively). The 25-gene signature reflects the abnormal development of stem cells in AML, such as AURKA over-expression. We subsequently determined that the clinical relevance of both signatures is independent of known clinical risk classifications in 214 patients with cytogenetically normal AML. We successfully validated the prognosis of both signatures in two independent cohorts of 91 and 242 patients respectively (log-rank p < 0.0015 and 0.05; empirical p < 0.015 and 0.08).

Conclusion

The proposed algorithms and computational framework will harness systems biology research because they efficiently translate gene-sets (rather than single genes) into biological discoveries about AML and other complex diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0510-7) contains supplementary material, which is available to authorized users.

CBFB-MYH11 hypomethylation signature and PBX3 differential methylation revealed by targeted bisulfite sequencing in patients with acute myeloid leukemia

Background

Studying DNA methylation changes in the context of structural rearrangements and point mutations as well as gene expression changes enables the identification of genes that are important for disease onset and progression in different subtypes of acute myeloid leukemia (AML) patients. The aim of this study was to identify differentially methylated genes with potential impact on AML pathogenesis based on the correlation of methylation and expression data.

Methods

The primary method of studying DNA methylation changes was targeted bisulfite sequencing capturing approximately 84 megabases (Mb) of the genome in 14 diagnostic AML patients and a healthy donors’ CD34+ pool. Subsequently, selected DNA methylation changes were confirmed by 454 bisulfite pyrosequencing in a larger cohort of samples. Furthermore, we addressed gene expression by microarray profiling and correlated methylation of regions adjacent to transcription start sites with expression of corresponding genes.

Results

Here, we report a novel hypomethylation pattern, specific to CBFB-MYH11 fusion resulting from inv(16) rearrangement that is associated with genes previously described as upregulated in inv(16) AML. We assume that this hypomethylation and corresponding overexpresion occurs in the genes whose function is important in inv(16) leukemogenesis. Further, by comparing all targeted methylation and microarray expression data, PBX3 differential methylation was found to correlate with its gene expression. PBX3 has been recently shown to be a key interaction partner of HOX genes during leukemogenesis and we revealed higher incidence of relapses in PBX3-overexpressing patients.

Conclusions

We discovered new genomic regions with aberrant DNA methylation that are associated with expression of genes involved in leukemogenesis. Our results demonstrate the potential of the targeted approach for DNA methylation studies to reveal new regulatory regions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13045-014-0066-4) contains supplementary material, which is available to authorized users.