Acute Leukemias

CpG methylation patterns and decitabine treatment response in acute myeloid leukemia cells and normal hematopoietic precursors

Abstract

The DNA hypomethylating drug decitabine maintains normal hematopoietic stem cell (HSC) self-renewal but induces terminal differentiation in acute myeloid leukemia (AML) cells. The basis for these contrasting cell fates, and for selective CpG hypomethylation by decitabine, is poorly understood. Promoter CpGs, with methylation measured by microarray, were classified by the direction of methylation change with normal myeloid maturation. In AML cells, the methylation pattern at maturation-responsive CpGs suggested at least partial maturation. Consistent with partial maturation, in gene expression analyses, AML cells expressed high levels of the key lineage-specifying factor CEBPA, but relatively low levels of the key late-differentiation driver CEBPE. In methylation analysis by mass spectrometry, CEBPE promoter CpGs that are usually hypomethylated during granulocyte maturation were significantly hypermethylated in AML cells. Decitabine-induced hypomethylation was greatest at these and other promoter CpGs that are usually hypomethylated with myeloid maturation, accompanied by cellular differentiation of AML cells. In contrast, decitabine-treated normal HSCs retained immature morphology, and methylation significantly decreased at CpGs that are less methylated in immature cells. High expression of lineage-specifying factor and aberrant epigenetic repression of some key late-differentiation driver genes distinguishes AML cells from normal HSCs, and could explain the contrasting differentiation and methylation responses to decitabine.

Introduction

An important goal in myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) research is to develop a treatment that is more selectively detrimental to MDS/AML cells and relatively sparing of normal hematopoietic stem cells (HSCs). One such potential therapeutic is the deoxycytidine analog decitabine, which at low, non-cytotoxic concentrations can deplete the chromatin-modifying enzyme DNA methyltransferase-1 (DNMT1) and hypomethylate DNA CpGs:1, 2, 3, 4, 5 in a number of studies from different groups, decitabine and histone deacetylase inhibitors (another class of drug that inhibit chromatin-modifying enzymes) have been shown to maintain or increase normal HSC self-renewal;6, 7, 8, 9, 10, 11, 12, 13, 14, 15 in contrast, decitabine and histone deacetylase inhibitors induce terminal differentiation of AML primary cells and cell lines encompassing the wide morphological and cytogenetic spectrum of disease.5, 16, 17, 18, 19, 20, 21, 22, 23, 24 The basis for these contrasting cell-fate responses of AML cells and normal HSCs to chromatin-relaxing drugs is incompletely defined, impeding optimal clinical translation of this mode of therapy. As a major effect of decitabine is to hypomethylate DNA, pre- and post-decitabine patterns of DNA methylation could provide an insight into underlying mechanisms. However, changes in promoter CpG methylation are also an important and usual aspect of hematopoietic differentiation.25 Therefore, to better understand and interpret DNA methylation patterns before and after treatment with decitabine, promoter CpGs, with methylation measured by microarray and mass spectrometry, were categorized by the direction of methylation change with normal myeloid maturation. The methylation levels of maturation-responsive CpGs were then compared in normal, MDS and AML cells at baseline, and in normal and AML cells treated with decitabine. The methylation analyses were complemented by gene expression measurements of key lineage-specifying and late-differentiation transcription factors (TFs), which together drive progressive myeloid maturation. These analyses exposed differences in baseline maturation and epigenetic context between AML cells and normal HSCs that likely contribute to and explain contrasting cell fate and methylation responses to decitabine.

Materials and methods

Cells from human subjects and cell lines

Informed consent for sample and data collection was obtained according to protocols approved by the Cleveland Clinic Institutional Review Board. Bone marrow aspirates were collected from MDS and AML patients between 2002 and 2007. High-risk disease was defined as MDS or AML with 5% myeloblasts (n=130), and low-risk disease as MDS with <5% myeloblasts (n=27). Clinical annotation of samples used for promoter CpG methylation analysis by microarray was described in detail in a previous publication.26 Normal total bone marrow (NBM) were aspirates from healthy individuals (n=42). Six AML cell lines were studied, of which K-562 and TF1 are described as erythroleukemia cell lines, and KG1, TF1 and Kasumi-1 express CD34. A model of ‘first-hit’ abnormality or (preleukemia) was also examined: cord blood CD34+ cells transduced with retrovirus to express the leukemia fusion protein RUNX1–ETO, as previously described and characterized.27

Promoter CpG methylation measurement by methylation array

The Methylation Cancer Panel I and GoldenGate Assay kit with UDG (Illumina, San Diego, CA, USA) was used for microarray methylation analysis of 1505 CpG sites mostly in the 5′-regulatory regions of 807 genes (known oncogenes, tumor suppressor, X-linked and imprinted, DNA repair, cell cycle control, differentiation and apoptosis genes).28 DNA was bisulfite converted using the EZ DNA methylation kit (Zymo Research, Orange, CA, USA). For each CpG site, there were two pairs of probes corresponding to either the methylated or unmethylated state of the CpG site. Through allele-specific extension and ligation, PCR templates were generated and then amplified by PCR using fluorescently labeled common primers. The resulting PCR products were hybridized to a bead array at sites bearing complementary address sequences. These hybridized targets contained a fluorescent label that denotes a methylated or unmethylated state for a given locus. Methylation status of the interrogated CpG site was then calculated as the ratio of fluorescent signal from one allele relative to the sum of both methylated and unmethylated alleles (β-value).

Our verification of the precision of the array, by analyzing technical replicate samples on two separate arrays, and our validation of microarray results with another method for measuring methylation levels, has been published previously.26

The β-value provides a continuous measure of levels of DNA methylation at a CpG site, ranging from 0 for completely unmethylated sites to 1 in completely methylated sites.28 Three categories of CpG sites were defined (raw methylation data uploaded to GEO Datasets, GSE29047):

  1. 1)

    CpGs that undergo a significant (P<0.001, t-test) increase in methylation from normal bone marrow CD34+ (NCD34, n=9), with 95–99% immature CD34+ cells, to NBM (n=42), with <2% immature CD34+ cells (‘hypomethylated in NCD34’, 108 CpGs, Supplementary Table S1);

  2. 2)

    CpGs that undergo a significant (P<0.001, t-test) decrease in methylation from NCD34 to NBM (‘hypermethylated in NCD34’, 162 CpGs, Supplementary Table S1);

  3. 3)

    CpGs that do not undergo a statistically significant change in methylation status between normal NCD34 and NBM (‘no methylation change’, 1236 CpGs).

The image extraction and statistical analysis were done with Beadstudio and Genomestudio Methylation Module (Illumina). All Illumina recommended control oligos were used. Statistical significance of the difference between mean and median values of methylation level for different samples/groups was assessed using Beadstudio Methylation Module software (Illumina) and SAS V8 (SAS, Cary, NC, USA). Hierarchical clustering was performed by Euclidean distance metric and centroid linkage (ArrayStar 3, DNAStar, Madison, WI, USA).

CEBPE promoter CpG methylation analyses

CEBPE promoter methylation was measured with the Sequenom MassARRAY Compact System (http://www.sequenom.com/). Gene-specific amplification of bisulfite-treated DNA was followed by in vitro transcription and analysis by matrix-assisted laser desorption ionization time-of-flight (MALDITOF) mass spectrometry.29 DNA (1 μg) was bisulfite converted using EZ DNA Methylation kit (Zymo Research). PCR primers specific for bisulfite-converted DNA were designed (Epidesigner Online Tool—http://www.epidesigner.com/). Each reverse primer contained a T7-promoter tag for in vitro transcription (5′-CAGTAATACGACTCACTATAGGGAGAAGGCT-3′), and the forward primer was tagged with a 10mer to balance Tm (5′-AGGAAGAGAG-3′). Primer sequences used for the CEBPɛ promoter are CEBPɛ forward (5′-AGGAAGAGAGTGGGTTTGGTTAAAGTATTTGGTTA-3′) and CEBPɛ reverse (5′-CAGTAATACGACTCACTATAGGGAGAAGGCTAAACTTCTCAAACCTCACAAAAAAA-3′). The genomic coordinates for the CEBPɛ promoter region analyzed are chr14:23 588 987–14:23 589 309. Mass spectra were acquired using a MassARRAY MALDI-TOF MS (Bruker-Sequenom, Bruker Daltonics Inc., Billerica, MA, USA), and peak detection, signal-to-noise calculations and quantitation of CpG methylation performed using proprietary EpiTyper software v1.0 (Sequenom). Differentiation-responsive CpGs within this region were identified by time-course analyses of normal CD34+ hematopoietic precursors treated with granulocyte colony-stimulating factor. Putative TF binding sites in the analyzed region were identified by TFSEARCHv1.3 (‘TFSEARCH: Searching Transcription Factor Binding Sites’, http://www.cbrc.jp/research/db/TFSEARCH.html).30

Pyrosequencing analysis of methylation at repetitive element CpGs

DNA was purified from cells using the Wizard Genomic DNA Purification Kit (Promega, Madison, WI, USA), and DNA (1 μg) was bisulfite converted using EZ DNA Methylation kit (Zymo Research). The PCR primers were 10 pmol of 5′-TTTTTTGAGTTAGGTGTGGG-3′ and 10 pmol of biotinylated 5′-TTGTTTGGTATTTTTTAGTGAGA-3′. PCR cycling conditions were cycle temperature of 94 °C for 30 s, 60 °C for 30 s and 72 °C for 30 s, for 45 cycles to consume all the biotinylated primers. The biotinylated strand was captured on streptavidin sepharose beads (Amersham Biosciences, Uppsala, Sweden) and annealed with the sequencing primer 5′-GGGTGGGAGTGAT-3′. The methylation degree of LINE-1 was computed as the average of four CpG sites pyrosequenced with the Pyromark Q24 Pyrosequencer (Qiagen, Valencia, CA, USA).

Additional methods are provided in Supplementary Materials and methods.

Results

Methylation at maturation-responsive CpGs in MDS and AML bone marrow cells

Three categories of CpG sites were defined: (1) CpGs that undergo a significant (P<0.001, t-test) increase in methylation from normal bone marrow CD34+ precursors (NCD34, 95–99% CD34+ immature cells, n=9) to NBM (<2% CD34+ immature cells, n=42; ‘hypomethylated in NCD34’, 108 CpGs; Supplementary Table S1); (2) CpGs that undergo a significant (P<0.001, t-test) decrease in methylation from NCD34 to NBM (‘hypermethylated in NCD34’, 162 CpGs; Supplementary Table S1); (3) CpGs that do not undergo a statistically significant change in methylation status between NCD34 and NBM (‘no methylation change’, 1236 CpGs). In gene ontology analyses, gene expression in blood, leukocyte, neutrophil, platelet, leukemia, liver and spleen was significantly associated with maturation-responsive CpGs (hypo- and hypermethylated in normal CD34) compared with ‘no methylation change’ CpGs (Supplementary Table S2). In a comparison of pathway associations, hematopoietic pathways (for example, hematopoietic cell lineage) were the pathways most frequently associated with maturation-responsive CpGs; this was not the case with ‘no methylation change’ CpGs (Supplementary Table S3). In unbiased hierarchical cluster analysis of methylation data from an independent study,31 clusters generated using maturation-responsive CpGs discriminated best between NCD34 and NBM, despite seven- to eightfold more CpG sites in the ‘no methylation change’ category (Supplementary Figure S1).

CpG sites that became more methylated with normal myeloid maturation (hypomethylated in NCD34) were even more methylated in bone marrow cells from patients with low-risk MDS (n=27) and high-risk MDS/AML (5% myeloblasts, n=130) (Figure 1, red box plots). CpG sites that became less methylated with normal myeloid maturation (hypermethylated in NCD34) were less methylated in low-risk MDS and high-risk MDS/AML bone marrow (Figure 1, blue box plots). CpG sites that do not undergo significant methylation changes with normal myeloid maturation (‘no methylation change’) were individually selected based on no significant difference in methylation between NCD34 (n=9) and NBM (n=42). However, when combined for analysis, these 1236 CpG sites were significantly more methylated in NBM compared with NCD34, although the increase was small in magnitude (Figure 1, gray box plots). These CpG sites were also significantly more methylated in MDS and AML bone marrow compared with NCD34; however, the increase was substantially smaller than the methylation shifts in maturation-responsive CpGs (Figure 1, gray box plots).

Figure 1
figure1

Methylation at maturation-responsive CpG sites in MDS and AML bone marrow compared with CD34+ precursors from normal bone marrow. Methylation levels are represented by a β-value between 0 (unmethylated) and 1 (fully methylated). Promoter CpG sites were classified into three categories: CpG sites that undergo a significant (P<0.001, t-test) increase in methylation from normal CD34+ cells (NCD34; n=9) to NBM (n=42; 108 CpGs, ‘hypomethylated in NCD34+’; red box plots); CpG sites that undergo a significant (P<0.001, t-test) decrease in methylation from NCD34 to NBM (162 CpG, ‘hypermethylated in NCD34+’; blue box plots); CpG sites that do not undergo a change in methylation between NCD34 and NBM (1236 CpG, ‘no met. change during normal diffn.’; gray box plots). Box-plot boundaries, interquartile range; HiRisk, bone marrow from high-risk MDS/AML patients (n=130); horizontal line, median; LoRisk, bone marrow from low-risk MDS patients (n=27); +, mean; small boxes, outlying values; whiskers, range of values.26 Asterisks represent statistically significant (P<0.0001) differences between the median in the sample group compared with the NCD34+ group (median one-way). The color reproduction of this figure is available at the Leukemia journal online.

To strengthen these observations, the analyses were repeated in a data set of promoter CpG methylation generated by other investigators.31 Ninety-five CpG sites from ‘hypomethylated in NCD34’, 157 CpG sites from ‘hypermethylated in NCD34’ and 1157 CpG sites from ‘no methylation change’ were present in the independent data set. Methylation of maturation-responsive CpGs (hypo- and hypermethylated in NCD34) changed in the expected directions from independent NCD34 to NBM (Supplementary Figure S2, red and blue box plots). Although ‘no methylation change’ was significantly more methylated in NBM compared with NCD34, the methylation increase was smaller in magnitude than the methylation changes at maturation-responsive CpGs (Supplementary Figure S2, gray box plots). CpG sites that become more methylated with normal myeloid maturation were not significantly more methylated in independent data set MDS/myeloproliferative disease (n=13) or AML bone marrow (n=116; Supplementary Figure S2). Nonetheless, of the 25 CpG sites that were >20% more methylated in AML cells than NCD34, 11 were from the category of 95 CpG sites that become more methylated with normal myeloid maturation and 14 were from the 1157 ‘no change in methylation’ CpG sites (Supplementary Figure S3). Therefore, maturation-responsive CpG sites were over-represented among the most hypermethylated CpG sites in AML bone marrow (P<0.0001, χ2-test). As expected, CpG sites that become less methylated with normal myeloid maturation were significantly less methylated in the MDS/myeloproliferative disease and AML cells (Supplementary Figure S2). All six CpG sites that were >20% less methylated in AML cells than NCD34 were from the category of 157 CpG sites that become less methylated with normal myeloid maturation (Supplementary Figure S3). ‘No methylation change’ CpGs were significantly more methylated in MDS/myeloproliferative disease and AML (Supplementary Figure S2).

Methylation at maturation-responsive CpG in CD34+ and CD34− AML cell lines

To extend the analyses to more homogenous populations of AML cells, including CD34+ AML cells, promoter CpG methylation, with CpG sites classified as above, was analyzed in a model of first-hit or preleukemia (CD34+ cells retrovirally transduced to express the leukemia fusion protein RUNX1–ETO (CD34 RUNX1–ETO), phenotype previously described27) and six AML cell lines, including the CD34+ cell lines KG1, TF1 and Kasumi-1. The control sample was normal CD34+ cells isolated from cord blood (NCD34).

CpG sites that become more methylated with normal myeloid maturation were significantly more methylated in three of the AML cell lines compared with NCD34 (Figure 2, red box plots). CpG sites that become less methylated with normal myeloid maturation were significantly less methylated in five of the cell lines compared with NCD34 (Figure 2, blue box plots). ‘No methylation change’ CpGs were significantly hypermethylated in six of the cell lines compared with NCD34 (Figure 2, gray box plots); however, the increase in methylation was substantially smaller in magnitude than the changes in methylation in the categories of myeloid maturation-responsive CpGs (Figure 2). Therefore, the AML cell lines recapitulated the methylation pattern observed in primary MDS and AML cells.

Figure 2
figure2

Methylation at maturation-responsive CpG sites in AML cell lines (including CD34+ cell lines KG1, TF1 and Kasumi-1) compared with normal CD34+ precursors. Methylation at maturation-responsive (red and blue box plots) and non-responsive (gray box plots) promoter CpGs was analyzed in a model of first-hit or preleukemia (CD34+ cells retrovirally transduced to express the leukemia fusion protein RUNX1–ETO27), and six AML cell lines. The control sample was normal CD34+ cells isolated from cord blood. Asterisks represent statistically significant differences between the medians in the cell line compared with NCD34 (median one-way). Asterisks indicate P<0.0001 or at the following comparisons: ‘hypo-met in NCD34’: NCD34 versus KG1, P=0.0042; NCD34 versus Kasumi-1, P=0.0002 and ‘hyper-met in NCD34’: NCD34 versus KG1, P=0.0086. Box-plot boundaries, interquartile range; horizontal line, median; +, mean; small boxes, outlying values; whiskers, range of values. The color reproduction of this figure is available at the Leukemia journal online.

Effects of non-cytotoxic concentrations of decitabine on CD34+ normal, preleukemia and leukemia cell lines

CD34+ normal, preleukemia (CD34 RUNX1–ETO) and leukemia cells (Kasumi-1) were treated with identical concentrations of decitabine to compare the cell fate with promoter CpG methylation response.

Normal CD34+ cells treated with decitabine 0.5 μM continued to proliferate exponentially, although cell counts were lower than in vehicle-treated control. In contrast, CD34+ RUNX1–ETO and CD34+ Kasumi-1 cells treated with decitabine 0.5 μM decreased in cell numbers (Figure 3a). A higher concentration of decitabine (1 μM) decreased normal CD34+, RUNX1–ETO and Kasumi-1 cell numbers. Cytarabine is another clinically utilized cytosine analog, which is the mainstay of AML chemotherapy. Unlike decitabine 0.5 μM, cytarabine 0.5 μM decreased cell numbers of normal CD34+, as well as RUNX1–ETO and Kasumi-1 (Figure 3a).

Figure 3
figure3

Decitabine, at levels that do not cause apoptosis, has opposite effects on the proliferation, differentiation and colony formation of AML cells and normal CD34+ cells. Normal cells: CD34+ cells from normal cord blood (NCD34+). Preleukemia and AML cells: (1) CD34+ cells transduced with RUNX1–ETO and (2) Kasumi-1 cell line. Treatment: decitabine (DAC) 0.5–1 μM or cytarabine (AraC) 0.5 μM on days 1, 4 and 7. (a) Effects of DAC and AraC on proliferation of normal and AML cells. Cell counts by automated cell counter. Experiments were performed in triplicate. Error bars=standard error. (b) Apoptosis induction by DAC and AraC. Annexin and 7-aminoactinomycin D (7AAD) measured by flow cytometry after 24 h. Annexin/7AAD data for Kasumi-1 in Supplementary Figure S4. (c) Effects of DAC on cell morphology. Giemsa-stained cytospin preparations on day 9 of liquid culture. All images are shown at × 600. (d) Effects of DAC on colony formation by normal and AML cells. Cells were plated in semisolid media after 7, 14 or 21 days in liquid culture (DAC 0.5 μM treatment was discontinued after day 7 of liquid culture). Phase-contrast images of colonies. All images are shown at × 40. A, AraC treated; D, DAC treated; U, untreated. Colony formation data for Kasumi-1 in Supplementary Figure S4.

Although decitabine 0.5 μM decreased RUNX1–ETO and Kasumi-1 cell numbers, this concentration of decitabine did not cause early apoptosis (measured by annexin/7-aminoactinomycin D staining 24 h after drug exposure; Figure 3b, Supplementary Figure S4, data not shown). Decitabine at 1 μM caused early apoptosis (Figure 3b, Supplementary Figure S4, data not shown), although not to the same extent as cytarabine 0.5 μM (Figure 3b, Supplementary Figure S4).

On day 9 of liquid culture, vehicle-treated normal CD34+ cells showed changes of early myeloid differentiation (decreased nuclear–cytoplasmic ratio, increase in pale blue cytoplasm and vacuolization); however, in the decitabine-treated wells, immature morphology was retained (high nuclear–cytoplasmic ratio and fine chromatin; Figure 3c). In contrast, RUNX1–ETO cells treated with decitabine 0.5 μM exhibited extensive myeloid differentiation (decreased nuclear–cytoplasmic ratio, nuclear condensation and segmentation, cytoplasmic granulation and vacuolation), whereas vehicle-treated cells demonstrated immature morphology (Figure 3c). Similarly, decitabine 0.5 μM induced morphological changes of differentiation in Kasumi-1 (nuclear segmentation and lobulation, increase in cell-size, and cytoplasmic vacuolization), although these changes were not as prominent as those noted in decitabine-treated RUNX1–ETO cells (Figure 3c).

Colony formation in semisolid media is an assay for stem cells and progenitors. Larger colony size and/or mixed character of the colony (more than one cell lineage) suggest greater immaturity of the colony-forming cell. Normal CD34+ cells treated with decitabine 0.5 μM produced fewer colonies than vehicle-treated normal cells; however, the colonies formed were larger and mixed. Furthermore, normal CD34+ cells treated with decitabine 0.5 μM retained colony-forming ability after extended liquid culture (14 and 21 days), whereas normal CD34+ cells cultured in the identical conditions without decitabine had rapidly diminished colony-forming ability (Figure 3d). RUNX1–ETO and Kasumi-1 cells treated with decitabine 0.5 μM lost their otherwise vigorous colony-forming ability (Figure 3d, Supplementary Figure S4).

Normal CD34+ cells treated with decitabine 0.5 μM demonstrated significant decreases in methylation in both categories of myeloid maturation-responsive CpGs (hypo- and hypermethylated in NCD34; Figure 4, red and blue box plots). However, CpGs that are not responsive to normal myeloid maturation (‘no methylation change’) were not significantly hypomethylated by decitabine (Figure 4, gray box plots). In RUNX1–ETO and Kasumi-1 cells treated with decitabine 0.5 μM, consistent with the morphological response, the largest and statistically significant decreases in methylation were at CpGs that become less methylated with normal myeloid maturation (‘hypermethylated in NCD34’, Figure 4, blue box plots). Although decitabine also decreased methylation at CpGs that become more methylated with normal myeloid maturation (‘hypomethylated in NCD34’), this decrease was smaller in magnitude and not statistically significant (Figure 4, red box plots). CpGs that are not responsive to normal myeloid maturation (‘no change in methylation’) were also significantly hypomethylated by decitabine (Figure 4, gray box plots); however, the methylation shift was substantially smaller than the methylation change at ‘hypermethylated in NCD34’ (Figure 4).

Figure 4
figure4

Methylation at maturation-responsive CpG sites before and after DAC treatment of normal CD34+ precursors and CD34+ AML cell lines. DNA for promoter CpG methylation analysis was isolated from the cells treated as per Figure 3. Promoter CpG sites were classified as per Figure 1, with myeloid maturation-responsive (red and blue box plots) and non-responsive (gray box plots) CpGs. Asterisks represent statistically significant differences between control versus treated median values (median one-way). Asterisks represent P<0.0001, except at the comparisons ‘no met. change’ RUNX1–ETO Ctrl versus DAC, P=0.0286; Kasumi Ctrl versus DAC, P=0.0083. Box-plot boundaries, interquartile range; horizontal line, median; +, mean; small boxes, outlying values; whiskers, range of values. The color reproduction of this figure is available at the Leukemia journal online.

Primary AML samples (n=5) and the erythromegakaryoblastic AML cell lines UT7 and K562 were also treated with decitabine (the classification and chromosome abnormalities in the primary cells are listed in Supplementary Table S4, the cell lines contain complex chromosome abnormalities). Compared with vehicle treatment, decitabine 0.5 μM on days 1, 4 and 7 decreased cell numbers, accompanied by cellular changes of differentiation (decreased nuclear–cytoplasmic ratio, nuclear condensation, segmentation or lobulation, cytoplasmic granulation or vacuolization; Figure 5).

Figure 5
figure5

Effects of decitabine (DAC) 0.5 μM (full lines) and vehicle treatment (dashed lines) on cell counts and cellular morphology in AML patient samples and additional AML cell lines. DAC 0.5 μM on days 1, 4 and 7 or vehicle control was added to primary leukemia cells from five patients (classification and detected chromosome abnormalities in Supplementary Table S4), and the UT7 and K562 erythromegakaryoblastic AML cell lines. Cell counts by automatic cell counter on day 8. Giemsa-stained cytospins were generated on day 8. All images are shown at × 600.

High expression of lineage-specifying TFs, but epigenetic repression of key late-differentiation driver TFs, in MDS and AML cells

Lineage commitment and maturation is driven by and absolutely requires key DNA-binding TFs.32, 33, 34 Therefore, differentiation of AML cells by decitabine suggests high baseline and/or induced expression of key myeloid differentiation-driving TFs.

Using quantitative reverse transcriptase-PCR, the levels of the key myeloid lineage-specifying TF CEBPA (CEBPα), which is essential for producing granulocytes, and the lineage-specifying TF PU.1 (SPI1), which is essential for producing monocytes and B cells,32 were measured in bone marrow from healthy controls (n=8), low-risk MDS (n=4) and high-risk MDS/AML (average myeloblasts 40%, n=12; MDS and AML subtypes listed in Supplementary Table S5). Compared with normal CD34+ and total bone marrow, both MDS and AML bone marrow cells expressed significantly higher levels of CEBPA, and a trend toward higher PU.1 (P=0.026 and P=0.06, respectively; Figure 6a). To restrict the comparison to cells with a similar precursor surface phenotype, CD34+ cells were isolated from AML (n=3) and normal donor bone marrow (n=3; AML subtypes listed in Supplementary Table S6). Compared with CD34+ normal cells, CD34+ AML cells expressed 10- to 100-fold higher CEBPA (Figure 6b). CEBPA levels in the AML cells were 2- to 30-fold higher than HOXB4 levels in the same cells (Figure 6b). These observations were extended and recapitulated in analyses of public gene expression data (Supplementary Figure S5).35, 36, 37, 38, 39, 40

Figure 6
figure6

The pattern of expression of key myeloid differentiation-driving transcription factors (TFs) in MDS/AML cells suggests impaired differentiation of lineage-committed cells. (a) Lineage-specifying TFs are expressed at higher levels in MDS and AML compared with normal CD34+ hematopoietic precursors or total bone marrow. CEBPA (CEBPα), and PU.1 levels were measured by quantitative reverse transcriptase-PCR (QRT-PCR). (b) CD34+ AML cells (n=3) express 10- to 100-fold higher CEBPA, but lower levels of late-differentiation TF CEBPE (CEBPɛ), than normal CD34+ hematopoietic precursors (n=3). HOXB4 is a stem cell-associated TF. CEBPA/HOXB4 (index of lineage commitment) and CEBPE/A ratio (index of progressive maturation) calculated in each individual sample. Box-plot displays distribution of these ratios (Wilcoxon two-sample test). Box boundaries, interquartile range; horizontal line in box, median; whiskers, range of values. Gene expression was measured by QRT-PCR.

As AML cells express high levels of CEBPA, levels of CEBPE (CEBPɛ), a key late-differentiation TF necessary for progressive maturation, and a gene target of CEBPA, were measured (normally, CEBPE levels peak relative to CEBPA in the transition from proliferating promyelocytes to non-proliferating myelocytes33, 34, 41). CD34+ AML cells expressed 2- to 10-fold lower CEBPE levels than CD34+ normal cells, despite expressing substantially higher levels of CEBPA (Figure 6b). These observations were extended and recapitulated in analyses of public gene expression data (Supplementary Figure S5).35, 36, 37, 38, 39, 40

The CEBPE locus on chromosome 14 is not cytogenetically deleted in AML, suggesting that the repression may be caused by epigenetic means. Using mass spectrometry, CEBPE promoter CpG that become less methylated during granulocyte colony-stimulating factor-induced differentiation of normal CD34+ precursors into granulocytes were identified (Figure 7a). Notably, the three identified CEBPE promoter CpGs were in proximity to putative CEBPA and RUNX1 binding sites (Supplementary Figure S6). The methylation levels of these CpG sites were compared in bone marrow samples from normal volunteers, AML in remission, AML, and promyelocytic leukemia (cytogenetic abnormalities in the AML samples are listed in Supplementary Table S7). Two of the three CpG sites were significantly hypermethylated in AML compared with normal and/or remission bone marrow (Figure 7b), but were not hypermethylated in promyelocytic leukemia cells, which express higher levels of CEBPE than other AML subtypes (Figure 7b, Supplementary Figure S7). In contrast to the CEBPE promoter CpG, methylation levels at LINE-1 repetitive DNA element CpGs were similar in normal, remission and AML bone marrow (Figure 7c). The effect of decitabine treatment on CEBPE promoter and LINE-1 CpG methylation was examined in an AML cell line (THP1). Decitabine 0.5 μM decreased CEBPE promoter CpG methylation to a much greater extent (>40–60%) than the 20% decrease in methylation at LINE-1 CpG (Figure 7d, Supplementary Figure S8). Decitabine-induced hypomethylation at CEBPE promoter CpG was accompanied by a substantial increase in CEBPE protein levels (Figure 7d).

Figure 7
figure7

Maturation-responsive CpGs in the CEBPE (CEBPɛ) promoter are aberrantly hypermethylated in AML cells. (a) CpG sites in the CEBPE promoter that undergo hypomethylation during granulocyte colony-stimulating factor treatment of normal CD34+ precursors were identified. Methylation was measured by mass spectrometry. The identified CpG sites were in proximity to putative CEBPA and RUNX1 binding sites (Supplementary Figure S6). SR, no G-CSF; DF, G-CSF. (b) Methylation levels of these CpG sites in normal volunteer, AML in remission, AML, and promyelocytic leukemia (M3) bone marrow. M3 leukemia cells express higher levels of CEBPE than other AML subtypes (Supplementary Figure S7). P-values from Wilcoxon two-sample test. (c) LINE-1 repetitive DNA element CpG methylation in normal, remission, AML and M3 bone marrow. Methylation measured by pyrosequencing. (d) Effect of decitabine treatment on methylation of CEBPE promoter CpG and on DNMT1 and CEBPE protein levels. LINE-1 methylation changes in Supplementary Figure S8. THP1 AML cells treated with decitabine 0.5 μM on days 1 and 4. DNA harvested on 48 h (day 3) after the first decitabine treatment and 24 h after the second decitabine treatment (day 5). Cells were harvested for western blot at the same time points as for DNA analysis.

Discussion

Promoter CpG methylation patterns reflect differentiation context and stage.25 In primary MDS and AML cells, the pattern of methylation at maturation-responsive promoter CpGs mimicked the pattern in mature myeloid elements, and was the opposite of that in normal CD34+ precursors. In high-risk MDS/AML samples, which contain more myeloblasts, and in uniformly morphologically immature CD34+ and CD34− AML cell lines, this pattern was emphasized. These observations suggest that MDS and AML cells are in at least some aspects maturation progressed from normal CD34+ precursors. Accordingly, MDS and AML cells express relatively high levels of key lineage-specifying TF CEBPA and PU.1 (SPI1), compared with normal CD34+ precursors or total bone marrow, and AML–initiating cells frequently have surface-phenotype features of lineage commitment (CD34+38+, CLL-1+, CD71+, CD90− and c-Kit).42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52 Despite high CEBPA expression, expression of CEBPE, a key downstream gene target of CEBPA, was relatively repressed in AML cells, accompanied by hypermethylation of differentiation-responsive CpG in the CEBPE promoter. Hypermethylation has also been reported for CpG in the promoter of CEBPD (CEBPδ), another late-differentiation gene target of CEBPA.53

Why are key late-differentiation genes such as CEBPE and CEBPD epigenetically repressed in AML cells, despite high expression of lineage-specifying TFs that should activate these genes? Genetic abnormalities in genes for lineage-specifying TFs (for example, CEBPA) or their cofactors (for example, RUNX1) that compromise transactivation by these differentiation drivers could have a role: in mice engineered to express mutated Cebpa (p30) with reduced transactivating capacity, the leukemia-initiating cells that arose were lineage committed, with impaired expression of key late-differentiation genes including Cebpd.43 Similarly, Runx1 haploinsufficiency, a common abnormality in MDS and AML, impairs the usual cooperative gene activation by Runx1 and the differentiation driver Pu.1/Spi1, producing increased corepressor recruitment to Pu.1 and epigenetic repression of late-differentiation target genes (for example, Gm-csfr and Mcsfr).54 Mutations in some chromatin-modifying enzyme genes (for example, ASXL1 and EZH2) increase in frequency from MDS to AML.55, 56, 57 Possibly, these genetic abnormalities additionally favor corepressor over coactivator recruitment at late-differentiation genes. DNMT1 depletion by decitabine, which not only hypomethylates DNA but disrupts DNMT1 containing histone-modifying protein complexes involved in transcription repression, can potentially redress such corepressor/coactivator imbalance, and thereby trigger late-differentiation gene expression in these cells already expressing high levels of lineage-specifying TFs. In contrast, in normal HSCs, which do not express high levels of lineage-specifying TFs, DNMT1 depletion prevents stem cell gene repression by differentiation stimuli, thereby maintaining stem cell phenotype.6, 7, 8, 9, 10, 11, 12, 13, 14, 15

An important goal in MDS and AML research is to identify differences between malignant cells and normal HSCs that can be exploited for therapy. In MDS/AML cells, the pattern of expression of key myeloid differentiation-driving TFs, and methylation patterns at myeloid maturation-responsive CpGs, suggests that differentiation is impaired after lineage commitment, mediated by aberrant epigenetic repression of some key late-differentiation driver genes. This maturation and epigenetic profile, distinct from that of normal HSCs, likely has a major role in the contrasting differentiation response of AML cells and normal HSCs to decitabine and other chromatin-relaxing drugs.

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Acknowledgements

We acknowledge the assistance of Dr Ying Jiang for bioinformatics analysis and sample preparation, Dr Pieter Faber and the Cleveland Clinic Genomics Core for processing of samples and the following gifts: Mary Laughlin and Nick Greco at the Abraham J and Phyllis Katz Cord Blood Foundation and Cleveland Cord Blood Center for cord blood samples. YS is supported by NIH (1R01CA138858, U54HL090513), Department of Defense (PR081404). KPN is supported by Scott Hamilton CARES Foundation.

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Correspondence to Y Saunthararajah.

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Supplementary Information accompanies the paper on the Leukemia website

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Negrotto, S., Ng, K., Jankowska, A. et al. CpG methylation patterns and decitabine treatment response in acute myeloid leukemia cells and normal hematopoietic precursors. Leukemia 26, 244–254 (2012). https://doi.org/10.1038/leu.2011.207

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Keywords

  • epigenetics
  • decitabine
  • acute myeloid leukemia
  • myelodysplastic syndrome
  • differentiation
  • therapy

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