MDS.

HHS Public Access Author manuscript Author Manuscript

Br J Haematol. Author manuscript; available in PMC 2017 November 01. Published in final edited form as: Br J Haematol. 2016 November ; 175(3): 427–439. doi:10.1111/bjh.14244.

Epigenetic landscape of the TERT promoter: a potential biomarker for high risk AML/MDS Xin Zhao1, Xin Tian2, Sachiko Kajigaya1, Caroline R. Cantilena1, Stephen Strickland3, Bipin N. Savani3, Sanjay Mohan3, Xingmin Feng1, Keyvan Keyvanfar1, Neil Dunavin1, Danielle M. Townsley1, Bogdan Dumitriu1, Minoo Battiwalla1, Katayoun Rezvani4, Neal S. Young1, A. John Barrett1, and Sawa Ito1,*

Author Manuscript

1Hematology

Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA

2Office

of Biostatistics Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA

3Division 4Stem

of Hematology and Oncology, Vanderbilt University Medical Center, Nashville, TN, USA

Cell Transplantation and Cellular Therapy, MD Anderson Cancer Centre, Houston, TX,

USA

Abstract Author Manuscript

Although recent observations implicate the importance of telomerase activity in acute myeloid leukaemia (AML), the roles of epigenetic regulations of the TERT gene in leukaemogenesis, drug resistance and clinical prognosis in AML are not fully understood. We developed a quantitative pyrosequencing-based methylation assay covering the TERT proximal promoter and a partial exon 1 (hTERTpro/Ex1) region and tested both cell lines and primary leukaemia cells derived from AML and AML with preceding myelodysplastic syndrome (AML/MDS) patients (n = 43). Prognostic impact of methylation status of the upstream TERT promoter region was assessed by the Kaplan-Meier method. The activity of the telomerase inhibitor, imetelstat, was measured using leukaemia cell lines. The TERTpro/Ex1 region was highly methylated in all cell lines and primary leukaemia cells showed diverse methylation profiles. Most cases showed hypermethylated regions at the upstream TERTpro/Ex1 region that were associated with inferior patient survival. TERTpro/Ex1 methylation status was correlated with the cytotoxicity to imetelstat and its combination with hypomethylating agent enhanced the cytotoxicity of imetelstat. AML cell lines and primary blasts harbour distinct TERTpro/Ex1 methylation profiles that could serve as a

Author Manuscript

*

Correspondence: Dr S Ito, Hematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, 10 Center Drive, Bethesda, MD 20892, USA, Tel: +1 3013265233, Fax: +1 3018273228, [email protected]. Author Contributions Study concept and design (S.I, X.Z, S.K, A.J.B., N.S.Y); in vitro experiment and data collection (X.Z., S.I., S.K., X.F. K.K) analysis and interpretation of data (X.Z., S.I., X.T., N.D., S.K., X.F., P.M., D.M.T, B.D, A.J.B., N.S.Y.); drafting of the manuscript (X.Z, S.I, X.T., S.K, N.S.Y, A.J.B.); statistical analysis (X.Z., N.D., S.I., X.T.); clinical data collection (S.I., N.D., S.S., B.N.S., M.B., S.M., K.R.); and obtained funding and study supervision (S.S., A.J.B., N.S.Y.).

Competing Interest All authors declare no conflict of interest.

Zhao et al.

Page 2

Author Manuscript

prognostic biomarker of AML. However, validation in a large cohort of patients is necessary to confirm our findings.

Keywords

TERT promoter; methylation profile; mutation analysis; AML; survival curve

INTRODUCTION

Author Manuscript Author Manuscript

Telomerase reverse transcriptase (TERT) is a catalytic subunit of telomerase (Cohen et al, 2007) and transcriptional regulation of its gene, TERT, is a rate-limiting determinant of telomerase activity (Bodnar et al, 1998, Ducrest et al, 2002). Impaired telomerase activity and extremely short telomeres induce chromosomal instability, causing bone marrow failure, fibrosis of the lungs and liver, and tumourigenesis (Calado et al, 2011, Calado et al, 2012). In general, malignant cells have high telomerase activity, protecting them from proliferation arrest, senescence and apoptosis (Hanahan & Weinberg, 2011). Human TERT expression is tightly controlled in normal somatic cells while high TERT expression is observed in 80– 95% of malignant cells and cell lines and is associated with poor outcomes in several solid tumours (Gertler et al, 2004, Sanders et al, 2004, Tabori et al, 2006). The dysregulation of TERT expression in malignant cells can be explained by alteration of the TERT promoter (TERTpro) structure through somatic mutations, epigenetic modifications or aberrant chromatin environments. Recently, novel TERTpro mutations were discovered in up to 70% of primary melanoma by multipoint linkage analysis and whole-genome sequencing (Horn et al, 2013, Huang et al, 2013). Further, genome-wide methylation array analysis revealed that the specific TERTpro region upstream of the transcription start site (TSS) is highly methylated in paediatric cancers and the TERTpro methylation status is associated with tumour progression and poor prognosis in paediatric brain tumours (Castelo-Branco et al, 2013). TERT exon mutations are also associated with aplastic anemia and various human malignancies (Yamaguchi et al, 2005, Bojesen et al, 2013). Genetic and epigenetic regulations of TERT expression thus seem to play important roles in pathophysiology and clinical outcome in human cancers.

Author Manuscript

Acute myeloid leukaemia (AML) is characterized by various cytogenetic and molecular abnormalities associated with biological and clinical heterogeneity. Recently, Bruedigam et al (2014) reported that telomerase activity was a critical pro-survival factor for AML stem cells. Aberrant hypermethylation of CpG islands in a variety of gene promoters is the hallmark epigenetic changes in both AML and myelodysplastic syndrome (MDS) (Jiang et al, 2009, Cancer Genome Atlas Research 2013). Clinical responses to DNA methyltransferase inhibitors, such as 5-azacytidine (5-Aza), support epigenetic alterations as a fundamental pathophysiology in MDS and subsets of AML (Silverman et al, 2006, Fenaux et al, 2009, Traina et al, 2014). However the roles of epigenetic regulations of TERT in leukaemogenesis, drug resistance and overall clinical outcome are not well defined. Several groups have reported that high TERT expression is associated with a hypermethylated TERTpro, but others have described high TERT expression with a hypomethylated TERTpro (Devereux et al, 1999, Dessain et al, 2000, Guilleret et al, 2002, Shin et al, 2003). These

Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 3

Author Manuscript

contradictory findings could relate to differences in the methylation status of CpG islands in the TERTpro. Hitherto, the quantitative evaluation of methylation status of the TERTpro region has not been standardized. Therefore, we developed a quantitative pyrosequencingbased methylation assay to examine a region encompassing the TERT proximal promoter and partial exon 1 (TERTpro/Ex1) to characterize in depth the epigenetic landscape of the region. Here, we report a distinct epigenetic spectrum of the TERTpro/Ex1 region in patients with AML and AML/MDS and its prognostic value. We also evaluated the association between epigenetic changes of the TERTpro/Ex1 and sensitivity to a telomerase inhibitor.

MATERIALS AND METHODS Subject characteristics and sample collection

Author Manuscript

Peripheral blood (PB) samples or bone marrow (BM) aspirates were collected from 33 patients with AML, 10 AML/MDS and 4 healthy volunteers (Supplementary Table 1). Secondary AML was defined as antecedent diagnosis of MDS or myeloproliferative neoplasm. Disease risk was classified by European Leukaemia Net (ELN) recommendations (Rollig et al, 2011). Subjects without molecular test results were assigned by cytogenetic profile alone. Written informed consent was obtained in accordance with Declaration of Helsinki for the use of samples for research under the protocol approved by the Institutional Review Board of the National Heart, Lung, and Blood Institute, Vanderbilt University of Medical Center and MD Anderson Cancer Center. Peripheral blood mononuclear cells (PBMCs) or BM mononuclear cells were isolated by Ficoll-Hypaque density gradient centrifugation (Organon Teknika, Durham, NC, USA), cryopreserved and stored in liquid nitrogen until further use.

Author Manuscript

Leukaemia blast isolation and flow cytometry analysis For isolation of leukaemic blasts and CD3+ cells from primary leukaemia samples, PBMC or BM mononuclear cells were labelled with monoclonal antibodies (mAbs) against CD38FITC (Beckman Coutler, Brea, CA, USA), CD34-APC, CD11b-APCCy7 (BD Biosciences, Franklin Lakes, NJ, USA), CD3-Brilliant violet 605 (Biolegend, San Diago, CA, USA), CD14-Pacific Blue, (Invitrogen, Carlsbad, CA, USA) and Propidium Iodide (PI; Molecular Probe, Eugene, OR, USA). Leukaemic blasts in different phenotypic compartments (CD34+CD38−, CD34+CD38+ and CD14+CD11b+) and CD3+ T cells were sorted into PInegative, viable populations on a FACS Aria™ II cell sorter (BD Biosciences). Primary cells and cell lines

Author Manuscript

A total of 14 haematopoietic cell lines and two other cell lines (Figure 1) were obtained from American Type Culture Collection (Manassas, VA, USA) and cultured, according to the manufacturer’s instructions. We also used one myeloid leukaemia cell derived from an AML patient (UPN 21), which were established by our laboratory. These leukaemia cell lines were cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum and antibiotics.


Zhao et al.

Page 4

DNA isolation and methylation analysis

Author Manuscript Author Manuscript Author Manuscript

DNA was extracted from various kinds of specimens from patients or healthy donors using the QIAamp DNA Blood Mini kit or the QIAamp DNA Micro kit (Qiagen, Valencia, CA, USA). Methylation status of CpG sites in the TERTpro/Ex1 region (~ 670 bp spanning from nt −520 to nt +150, relative to ATG) was examined by a pyrosequencing-based methylation assay using the PyroMark Q24 instrument (Qiagen). Briefly, primers for the polymerase chain reaction (PCR) and pyrosequencing were designed based on a bisulfite-converted lower strand of the TERTpro/Ex1 region using PyroMark Assay Design Software 2.0 (Qiagen). DNA samples (300 ng) modified with the EpiTect Bisulfite kit (Qiagen) were amplified using the PyroMark PCR kit (Qiagen) with proper PCR primer sets. Pyrosequencing was performed in duplicate using the PyroMark Q24 instrument with adequate sequence primers. These primers are shown in Supplementary Table 2; individual reverse PCR primers were biotin-labelled at their 5’ ends for subsequent pyrosequencing analysis. PCR was performed using the following conditions: one cycle of 95°C for 15 min, 48 cycles of 94°C for 30 s, 60°C for 30 s and 72°C for 30 s, followed by one cycle of 72°C for 10 min. Data analysis was carried out with PyroMark Q24 Software (Qiagen) and average methylation levels calculated from duplicate experimental data were used in this study: each duplicate value passed the pyrosequencer quality control (i.e., labelled as “pass” or “pass” after editing). Of note, as CpG sites are densely localized in the TERTpro/Ex1 region with relatively few large “gaps” between the CpG sites, we encountered some difficulties designing PCR and pyrosequencing primers for the entire TERTpro/Ex1 methylation assay (Region A excepted) to completely fulfill the criteria recommended by the manufacturer (Supplementary Table 2). As ultimately optimized pyrosequencing primers could not be created for some CpG sites, “editing” was required to pass the pyrosequencer quality control, whereby methylation levels of certain CpG sites might not precisely reflect their exact values. However, the methylation assay worked sufficiently to obtain overall methylation signatures of the manufacturers control genomic DNA (unmethylated and methylated), some hypermethylated cell lines and unmethylated normal PBMCs. Telomere length analysis To examine telomere lengths, telomere restriction fragment (TRF) analysis was performed with genomic DNA (300 ng) using the TeloTAGGG Telomere Length Assay kit (Roche, Nutley, NJ, USA), according to the manufacturer’s protocols. A mean TRF length was calculated using the ImageQuant TL software (GE Healthcare Life Sciences, Pittsburgh, PA) by comparing signals relative to a molecular weight standard. Chemosensitivity assay

Author Manuscript

Imetelstat is a 13-mer oligonucleotide complementary to the active site of TERT and inhibits telomerase activity. An inert mismatched oligonucleotide was used as a control. Both imetelstat and the mismatched oligonucleotide control were produced by Geron Corporation (Menlo Park, CA, USA). Three cell lines (Ramos, K562 and THP1) with different methylation patterns of TERTpro/Ex1 were cultured for 48 h with either the active imetelstat or the inert control at various concentrations from 5 µM to 40 µM. For the combined chemosensitivity assay, cells were pre-treated with 5-Aza (Sigma Aldrich, St. Louis, MO,


Zhao et al.

Page 5

Author Manuscript

USA) at 50 µM for 24 h and thereafter 20 µM of either imetelstat or the inert oligonucleotide control was added for 48 h. At the time of specific killing evaluation, cells were further stained with Annexin-V APC (BD Biosciences) and PI, and subjected to analysis by flow cytometry to measure cell viability, apoptosis and necrosis. A degree of specific killing viability was calculated by the equation: Specific killing viability= a/b*, where “a” is the % viability in the presence of target drug, and “b” is the % viability in the absence of any drugs. Statistical analysis

Author Manuscript

Wilcoxon rank-sum tests were used to compare methylation among patient groups. Overall survival probabilities were estimated by the Kaplan-Meier method and compared among methylation subgroups by the log-rank test. Survival time was calculated from the time of sample collection to death or the last follow-up. A prognostic value of methylation status was analysed by the univariate and multivariate Cox proportional hazards regression to adjust for confounding factors. For chemosensitivity assays, the Spearman’s rank correlation rho was used to examine the correlation between methylation status of the TERTpro/Ex1 region in leukaemia cell lines and a degree of specific killing viability, and Welch’s unpaired t-test was used to compare between each treatment condition within a cell line. All tests were two-sided and a P-value < 0.05 was considered statistically significant. Data analyses were performed using Prism Version 5.04 software (GraphPad Software, Inc. La Jolla, CA, USA) and R statistical software 3.2.2 (R Foundation for Statistical Computing, Vienna, Austria).

RESULTS Author Manuscript

Pyrosequencing-based methylation assay is established to quantify the methylation status of the TERTpro/Ex1 region

Author Manuscript

A unique methylation profile of the TERTpro/Ex1 region is commonly observed in haematopoietic and other cancer cell lines

We sought to establish a pyrosequencing-based methylation assay for the TERTpro/Ex1 region to examine methylation status of the region in clinical specimens. For the entire TERTpro/Ex1 methylation assay for certain CpG sites, we encountered difficulties in generating PCR and pyrosequencing primers that perfectly matched the manufacturer’s criteria. This was attributed to the presence of extremely condensed CpG sites (Supplementary Table 2). Nonetheless, the pyrosequencing-based methylation assay effectively screened an overall methylation profile of the entire TERTpro/Ex1 region (total 80 CpG sites). Based on TERTpro/Ex1 methylation levels in normal PB cell populations, 1 15% methylation was considered as the normal range in this study.

For an initial assessment, methylation status of the entire TERTpro/Ex1 region was examined in 14 commercially available haematopoietic cell lines of 7 different cell types and 2 other tissue-derived cell lines (cervical cancer and embryonic kidney cells) using the pyrosequencing-based methylation assay (Figure 1) as entire TERTpro/Ex1 methylation profiles in these cell lines had not previously been quantitated by pyrosequencing-based methylation analysis. Individual cell lines exhibited certain specific methylation signatures:


Zhao et al.

Page 6

Author Manuscript

extreme hypermethylation across the entire region examined (KG1A, H9, RS4); hypermethylated in an upstream region with steadily reduced methylation levels toward TSS (REH); hypermethylated in both an upstream and a partial exon 1 regions with low or mildly methylated TSS (K562); hypermethylated in a partial exon 1 alone (RAMOS); and completely unmethylated in the entire region (MEG-01). Nonetheless, all the cell lines with hypermethylated TERTpro/Ex1 displayed the common feature of reduced methylation of CpG sites around TSS, compared with other sites. In these experiments, as reported elsewhere, the TERTpro region was unmethylated in normal PB cells. We found that granulocytes, T cells, B cells and monocytes sorted from bulk PB cells of healthy donors all displayed an unmethylated pattern almost identical to that of bulk PB cells. Evolution of TERTpro/Ex1 methylation profiles occurs in leukaemia cell lines derived from primary leukaemic blasts

Author Manuscript Author Manuscript Author Manuscript

Next, we examined TERTpro/Ex1 methylation profiles of CD34+ cell populations sorted from BM cells of AML patients by flow cytometry. Figure 2 shows representative TERTpro/Ex1 methylation profiles (three hypermethylated and three hypomethylated) in CD34+ cell populations. Similar to the haematopoietic cell lines there was a highly methylated upstream region (nt −520 to nt −230 region), with or without a hypermethylated 3’ end; and a hypomethylated region around TSS. To gain better insight of the TERTpro/Ex1 methylation profiles in primary leukaemic cells, PB populations were sorted from PBMCs of one patients (patient 21and subjected to methylation analysis (Figure 3a). We also had the opportunity to examine methylation profiles of leukaemia cell lines established in our laboratory from these primary cells. Overall methylation patterns in primary leukaemic cell CD34+CD38−, CD34+CD38+ and CD11b+CD14+ subpopulations were almost identical within the individual. Some differentiated leukaemic cells expressed CD11b+and/or CD14+ antigens, explaining why CD11b+CD14+ populations in the patients harboured hypermethylated CpG sites. However the entire region was unmethylated in patient’s CD3+ T cells. Overall CpG methylation rates were much higher in the cell lines than their corresponding primary leukaemic cells, in agreement with previous reports (Smiraglia et al, 2001, Zinn et al, 2007, Ahmed et al, 2013, Varley et al, 2013). Collectively, primary cells and their cell lines displayed a trend of increasing methylation intensity toward the 5’ end while the regions around TSS remained unmethylated in primary cell populations and relatively hypomethylated in the cell lines similar to other cell lines tested in Figure 1. Telomere lengths of the AML primary leukaemic cell populations and their corresponding cell lines were examined (Figure 3b). TRF lengths of the CD34+CD38−, CD34+CD38+ and CD11b+CD14+ populations were almost identical within the same patient. The CD34+CD38− AML cell line showed significantly shorter TRF length than the three populations of primary leukaemia cells, albeit longer than the TRF length of CD3+ T cells. These results provided further evidence of the complexity of the underlying genetic and molecular mechanisms controlling telomere length. Primary leukaemic blasts also possess distinct methylation profiles in the TERTpro/Ex1 region To address whether the epigenetic profile of the TERTpro region could serve as a prognostic marker, we performed a pilot study of pyrosequencing-based TERTpro/Ex1 methylation in Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 7


patients with haematopoietic disorders (33 AML and 10 AML/MDS) and 4 healthy controls, particularly focusing on AML. Clinical characteristics of AML and/or AML/MDS patients are summarized in Table I; detailed information is shown in Supplementary Table 1. For this assay, we selected representative 4 regions (Regions A - D) based on the entire TERTpro/Ex1 methylation patterns in primary leukaemic cells and their cell lines, sufficient to cover the methylation events of the entire region and fully characterize the epigenetic landscape (Figure 4a). CpG sites of Region A were significantly hypermethylated in most AML patients (median [interquartile range], 23% [16.8–57.3]; P < 0.001) and in all AML/MDS patients (56.4% [35.3–65.8]; P < 0.001), compared to healthy volunteers (8.6% [7.6–10.4]) as shown in Figure 4b. Region B was also significantly hypermethylated in both AML and AML/MDS patients, but less methylated than in Region A. The degree of methylation of Region A and Region B was highly correlated (Spearman’s rho =0.81, P< 0.001 for AML and Spearman’s rho = 0.84, P=0.004 for AML/MDS patients, respectively). In contrast, almost all CpG sites of Region C were unmethylated in both AML and AML/ MDS, similar to healthy controls. CpG sites of Region D were partially methylated in AML and AML/MDS patients and significantly different from normal control samples. Collectively, we identified a distinct epigenetic signature in the TERTpro region in primary leukaemic blasts, which had a unique and dramatically elevated CpG methylation at Region A, and a relatively hypomethylated region adjacent to TSS, indicating that Region A might serve as a prognostic biomarker. A hypermethylated TSS-upstream region of TERTpro/Ex1 is associated with poor prognosis AML/MDS

Author Manuscript

To investigate whether the Region-A methylation status was associated with overall survival of AML and AML/MDS patients, we compared the Kaplan-Meier survival estimates for subgroups dichotomized by the median value of methylation rate of the TERTpro-Region A (Figure 5). With a median follow-up of 1.6 years, the TERTpro-Region A methylation above the median of 28% was associated with increased risk of mortality (overall survival 16.4% vs 33.9%; hazard ratio for death 2.13; 95% confidence interval [CI], 1.01–4.52; P = 0.045, Figure 5), compared to those with a methylation rate < 28%. In multivariate analysis, the hypermethylated (above median) status of TERTpro-Region A remained a significant prognostic factor (adjusted hazard ratio 2.56; 95% CI 1.04–6.27; P = 0.040) after adjusting for potential confounding factors, such as age, gender, disease risk and prior treatment. These results suggest that the methylation status of the TERTpro-Region A could serve as a novel biomarker to predict the outcome of AML.

Author Manuscript

Methylation status of the TERTpro/Ex1 region correlates to the sensitivity to telomerase inhibitor We sought the biological significance of the methylation status of the TERTpro/Ex1 region by evaluating the sensitivity to the telomerase inhibitor, imetelstat, which specifically inhibits TERT activity. Three commercially available leukaemia cell lines (K562, Ramos and THP-1) were tested. Imetelstat showed dose-dependent cytotoxicity to leukaemia cell lines. Cell toxicity was specific to telomerase because the inert control had no or minimal toxicity at half inhibitory concentration (IC50) of imetelstat between 10 and 40 µM (Supplementary Figure 1). Higher methylation status of the TERTpro/Ex1 region in Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 8

Author Manuscript

leukaemia cell lines was significantly associated with less specific killing by imetelstat, especially at low to medium concentrations between 5 µM and 20 µM. This finding suggests hypermethylation of the TERTpro/Ex1 region may be a marker of resistance to imetelstat (Figure 6a). Next, we evaluated the impact of combining imetelstat with a hypomethylating agent (5-Aza). Specific viability ratios were significantly lower in the setting of coadministration of imetelstat (20 µM) and 5-Aza (50 µM), in contrast to either imetelstat only, or 5-Aza and an inert control in myeloid cell lines (Figure 6b), suggesting additive effects of the telomerase inhibitor and hypomethylating agent.

DISCUSSION


Aberrant gene methylation patterns are characteristic of haematological malignancies and often associated with dynamic alterations in gene expression profiles.(Shaknovich et al, 2014) Given that the TERTpro region resides within a large CpG island, epigenetic regulation has been postulated as a key mechanism controlling TERT expression (Horikawa et al, 1999, Takakura et al, 1999). Using our pyrosequencing-based quantitative methylation assay, we found that almost all cell lines shared a unique methylation pattern of TERTpro/ Ex1, consisting of hypermethylation in the upstream promoter region followed by a relatively hypomethylated region around the TSS (Zinn et al, 2007). We also identified, for the first time, qualitative and quantitative differences in TERTpro/Ex1 methylation status between a primary malignant cell and its derived cell line in direct comparison. This finding can be explained by the evolution of specific TERTpro/Ex1 methylation patterns in regions occurring in cancer cell lines during the process of transformation from the original primary leukaemic cell (Smiraglia et al, 2001, Ahmed et al, 2013, Varley et al, 2013). Our results indicate that methylation profiling of leukaemia cell lines does not represent the methylation pattern observed in the original primary leukaemic cells. Quantitative methylation assay could be a powerful technique to elucidate the heterogeneity of methylation profiles in the TERTpro/Ex1 region and to explore the epigenetic biology of leukaemia.

Author Manuscript

In classic dogma, hypermethylation of CpG islands correlates inversely with gene expression (Baylin et al, 1998, Jones & Laird 1999, Jaenisch &Bird 2003, Benayoun et al, 2015). However, conflicting reports exist on the relationships of TERTpro methylation and TERT expression (Dessain et al, 2000, Guilleret et al, 2002, Shin et al, 2003). For example, the TERTpro region was universally hypermethylated in both telomerase-negative and telomerase-positive cancers cell lines (Guilleret et al, 2002, Zinn et al, 2007). Zinn et al (2007) analysed single clones of cancer cell lines and found that a substantial number of TERT alleles maintain hypomethylated CpGs around TSS. Renaud et al (2007) reported the dual role of DNA methylation in TERT transcriptional regulation in which sufficient hypermethylation of the CTCF binding site and hypomethylation of a certain core promoter region are required for TERT expression to inhibit CTCF binding and formation of the transcription complex, respectively. Another study found that transcription factors protect their binding sites from DNA methylation and loss of protection consequently leads to aberrant DNA methylation at the respective sites (Thurman et al, 2012). These studies support the importance of locus-specific epigenetic alterations of the promoter region for TERT expression, rather than its global methylation status. Our study successfully revealed the full epigenetic landscape of the TERTpro/Ex1 region in leukaemia, which was Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 9


characterized by the heterogeneous upstream TERTpro methylation profile with conservative hypomethylated TSS alleles. This distinct epigenetic change of TERTpro/Ex1 implies alteration of the secondary or tertiary structure of the TERT promoter region, which can in turn modify configurational interactions with transcription factors and control TERT expression in leukaemia cells. For example, Guanine-quadruplexes (GQ) are special secondary structures generated by G-rich sequences based on the formation of G-quartets. GQ structures within the promoters in cancer related genes, such as MYC, KIT, KRAS and TERT, lead to down-regulation of gene expression (Bidzinska et al, 2013). Involvement of the GQ structure in the epigenetic transcriptional regulation has been also reported (Halder et al, 2010, Lin et al, 2013). In addition, the TERT chromatin environment has been suggested as a crucial player for the TERT expression regulation (Wang et al, 2009). Thus, various layers of molecular mechanisms, including transcription factors, epigenetic status, GQ structures and chromatin environments, cooperatively serve to regulate TERT expression.


Emerging evidence from genome-wide methylation studies has revealed consistent aberrant methylation of a small common set of genes in AML. Furthermore, DNA methylation signatures can identify biologically distinct AML subtypes and predict patient survival (Bullinger et al, 2010, Figueroa et al, 2010). To evaluate the prognostic impact of TERTpro/Ex1 methylation signatures in leukaemic patients, we performed a pilot study on a cohort of AML patients with defined clinical outcomes (n = 43) and identified that high risk AML samples harbour the most representative domain of hypermethylated CpG sites in the upstream TERTpro (Region A) (Bullinger et al, 2010, Figueroa et al, 2010). Similar observations have been recently reported in several other cancer patient cohorts. The first such study demonstrated an association of the hypermethylated upstream region (UTSS region = our Region A) with tumour progression and poor prognosis in paediatric brain tumours (Castelo-Branco et al, 2013). The authors also described a highly methylated upstream region in four of five AML patients, but relationships between methylation status and patient outcome were not explored (Castelo-Branco et al, 2013). The second study reported that the hypermethylated UTSS region (our Region A) is associated with highly elevated TERT expression and a poor prognosis in hepatocellular carcinoma (Ko et al 2016). Our study was the first to report a possible correlation of the upstream TERTpro/Ex1 methylation status with overall survival in AML patients, which held even after adjustment of disease risk scores (Castelo-Branco et al, 2013; Ko et al 2016). This readily detectable methylation feature could therefore serve as a novel biomarker for high-risk AML patients. However our sample size is too small to establish the prognostic significance of upstream TERTpro/Ex1 methylation status, therefore larger number of samples from multi-centre cohorts would be needed to validate our findings. Future study should also investigate the TERTpro/Ex1 methylation status in other haematological malignancies, such as myeloproliferative disorders with or without myelodysplastic features, CML and acute lymphoblastic leukaemia. Finally, we demonstrated that sensitivity to the telomerase inhibitor, imetelstat, correlated with the methylation status of the TERTpro/Ex1 region, suggesting that methylation status can also be used as a marker of resistance to telomerase inhibitor treatments. Growing evidence supports the efficacy of telomerase inhibitors in various haematological Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 10

Author Manuscript

malignancies. Bruedigam et al (2014) reported that imetelstat effectively targets human AML stem cells and Tefferi et al (2015) recently demonstrated the efficacy of imetelstat for high risk myelofibrosis patients. We describe here, for the first time, a possible therapeutic benefit of combining telomerase inhibitors and hypomethylating agents in myeloid malignancies. Our findings justify further studies to explore the clinical application of telomerase inhibitors in high-risk AML/MDS patients.

Supplementary Material Refer to Web version on PubMed Central for supplementary material.

Acknowledgments Author Manuscript

We thank Samantha Miner, Fariba Chinian, and Yasutaka Ueda (Hematology Branch, NHLBI, NIH, USA) for their technical support. We also thank all patients who donated the samples to this study. This research was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute at the National Institutes of Health, Vanderbilt-Ingram Cancer Center, and MD Anderson Cancer Center. Imetelstat was obtained through Material Cooperative Research and Development Agreement (MCRADA) between Geron Corporation and National, Heart, Lung, and Blood Institute, National Institutes of Health.

REFERENCES


Ahmed D, Eide PW, Eilertsen IA, Danielsen SA, Eknaes M, Hektoen M, Lind GE, Lothe RA. Epigenetic and genetic features of 24 colon cancer cell lines. Oncogenesis. 2013; 2:e71. [PubMed: 24042735] Baylin SB, Herman JG, Graff JR, Vertino PM, Issa JP. Alterations in DNA methylation: a fundamental aspect of neoplasia. Adv Cancer Res. 1998; 72:141–196. [PubMed: 9338076] Benayoun BA, Pollina EA, Brunet A. Epigenetic regulation of ageing: linking environmental inputs to genomic stability. Nat Rev Mol Cell Biol. 2015; 16:593–610. [PubMed: 26373265] Bidzinska J, Cimino-Reale G, Zaffaroni N, Folini M. G-quadruplex structures in the human genome as novel therapeutic targets. Molecules. 2013; 18:12368–12395. [PubMed: 24108400] Bodnar AG, Ouellette M, Frolkis M, Holt SE, Chiu CP, Morin GB, Harley CB, Shay JW, Lichtsteiner S, Wright WE. Extension of life-span by introduction of telomerase into normal human cells. Science. 1998; 279:349–352. [PubMed: 9454332] Bojesen SE, Pooley KA, Johnatty SE, Beesley J, Michailidou K, Tyrer JP, Edwards SL, Pickett HA, Shen HC, Smart CE, Hillman KM, Mai PL, Lawrenson K, Stutz MD, Lu Y, Karevan R, Woods N, Johnston RL, French JD, Chen X, Weischer M, Nielsen SF, Maranian MJ, Ghoussaini M, Ahmed S, Baynes C, Bolla MK, Wang Q, Dennis J, McGuffog L, Barrowdale D, Lee A, Healey S, Lush M, Tessier DC, Vincent D, Bacot F, Australian Cancer Study; Australian Ovarian Cancer Study; Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab); Gene Environment Interaction and Breast Cancer (GENICA); Swedish Breast Cancer Study (SWEBRCA); Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON); Epidemiological study of BRCA1 & BRCA2 Mutation Carriers (EMBRACE); Genetic Modifiers of Cancer Risk in BRCA1/2 Mutation Carriers (GEMO). Vergote I, Lambrechts S, Despierre E, Risch HA, González-Neira A, Rossing MA, Pita G, Doherty JA, Alvarez N, Larson MC, Fridley BL, Schoof N, Chang-Claude J, Cicek MS, Peto J, Kalli KR, Broeks A, Armasu SM, Schmidt MK, Braaf LM, Winterhoff B, Nevanlinna H, Konecny GE, Lambrechts D, Rogmann L, Guénel P, Teoman A, Milne RL, Garcia JJ, Cox A, Shridhar V, Burwinkel B, Marme F, Hein R, Sawyer EJ, Haiman CA, Wang-Gohrke S, Andrulis IL, Moysich KB, Hopper JL, Odunsi K, Lindblom A, Giles GG, Brenner H, Simard J, Lurie G, Fasching PA, Carney ME, Radice P, Wilkens LR, Swerdlow A, Goodman MT, Brauch H, Garcia-Closas M, Hillemanns P, Winqvist R, Dürst M, Devilee P, Runnebaum I, Jakubowska A, Lubinski J, Mannermaa A, Butzow R, Bogdanova NV, Dörk T, Pelttari LM, Zheng W, Leminen A, Anton-Culver H, Bunker CH, Kristensen V, Ness RB, Muir K, Edwards R, Meindl A, Heitz F, Matsuo K, du Bois A, Wu AH, Harter P, Teo SH, Schwaab I, Shu


Zhao et al.

Page 11

Author Manuscript Author Manuscript Author Manuscript Author Manuscript

XO, Blot W, Hosono S, Kang D, Nakanishi T, Hartman M, Yatabe Y, Hamann U, Karlan BY, Sangrajrang S, Kjaer SK, Gaborieau V, Jensen A, Eccles D, Høgdall E, Shen CY, Brown J, Woo YL, Shah M, Azmi MA, Luben R, Omar SZ, Czene K, Vierkant RA, Nordestgaard BG, Flyger H, Vachon C, Olson JE, Wang X, Levine DA, Rudolph A, Weber RP, Flesch-Janys D, Iversen E, Nickels S, Schildkraut JM, Silva Idos S, Cramer DW, Gibson L, Terry KL, Fletcher O, Vitonis AF, van der Schoot CE, Poole EM, Hogervorst FB, Tworoger SS, Liu J, Bandera EV, Li J, Olson SH, Humphreys K, Orlow I, Blomqvist C, Rodriguez-Rodriguez L, Aittomäki K, Salvesen HB, Muranen TA, Wik E, Brouwers B, Krakstad C, Wauters E, Halle MK, Wildiers H, Kiemeney LA, Mulot C, Aben KK, Laurent-Puig P, Altena AM, Truong T, Massuger LF, Benitez J, Pejovic T, Perez JI, Hoatlin M, Zamora MP, Cook LS, Balasubramanian SP, Kelemen LE, Schneeweiss A, Le ND, Sohn C, Brooks-Wilson A, Tomlinson I, Kerin MJ, Miller N, Cybulski C, Henderson BE, Menkiszak J, Schumacher F, Wentzensen N, Le Marchand L, Yang HP, Mulligan AM, Glendon G, Engelholm SA, Knight JA, Høgdall CK, Apicella C, Gore M, Tsimiklis H, Song H, Southey MC, Jager A, den Ouweland AM, Brown R, Martens JW, Flanagan JM, Kriege M, Paul J, Margolin S, Siddiqui N, Severi G, Whittemore AS, Baglietto L, McGuire V, Stegmaier C, Sieh W, Müller H, Arndt V, Labrèche F, Gao YT, Goldberg MS, Yang G, Dumont M, McLaughlin JR, Hartmann A, Ekici AB, Beckmann MW, Phelan CM, Lux MP, Permuth-Wey J, Peissel B, Sellers TA, Ficarazzi F, Barile M, Ziogas A, Ashworth A, Gentry-Maharaj A, Jones M, Ramus SJ, Orr N, Menon U, Pearce CL, Brüning T, Pike MC, Ko YD, Lissowska J, Figueroa J, Kupryjanczyk J, Chanock SJ, DansonkaMieszkowska A, Jukkola-Vuorinen A, Rzepecka IK, Pylkäs K, Bidzinski M, Kauppila S, Hollestelle A, Seynaeve C, Tollenaar RA, Durda K, Jaworska K, Hartikainen JM, Kosma VM, Kataja V, Antonenkova NN, Long J, Shrubsole M, Deming-Halverson S, Lophatananon A, Siriwanarangsan P, Stewart-Brown S, Ditsch N, Lichtner P, Schmutzler RK, Ito H, Iwata H, Tajima K, Tseng CC, Stram DO, van den Berg D, Yip CH, Ikram MK, Teh YC, Cai H, Lu W, Signorello LB, Cai Q, Noh DY, Yoo KY, Miao H, Iau PT, Teo YY, McKay J, Shapiro C, Ademuyiwa F, Fountzilas G, Hsiung CN, Yu JC, Hou MF, Healey CS, Luccarini C, Peock S, Stoppa-Lyonnet D, Peterlongo P, Rebbeck TR, Piedmonte M, Singer CF, Friedman E, Thomassen M, Offit K, Hansen TV, Neuhausen SL, Szabo CI, Blanco I, Garber J, Narod SA, Weitzel JN, Montagna M, Olah E, Godwin AK, Yannoukakos D, Goldgar DE, Caldes T, Imyanitov EN, Tihomirova L, Arun BK, Campbell I, Mensenkamp AR, van Asperen CJ, van Roozendaal KE, Meijers-Heijboer H, Collée JM, Oosterwijk JC, Hooning MJ, Rookus MA, van der Luijt RB, Os TA, Evans DG, Frost D, Fineberg E, Barwell J, Walker L, Kennedy MJ, Platte R, Davidson R, Ellis SD, Cole T, Bressac-de Paillerets B, Buecher B, Damiola F, Faivre L, Frenay M, Sinilnikova OM, Caron O, Giraud S, Mazoyer S, Bonadona V, CauxMoncoutier V, Toloczko-Grabarek A, Gronwald J, Byrski T, Spurdle AB, Bonanni B, Zaffaroni D, Giannini G, Bernard L, Dolcetti R, Manoukian S, Arnold N, Engel C, Deissler H, Rhiem K, Niederacher D, Plendl H, Sutter C, Wappenschmidt B, Borg A, Melin B, Rantala J, Soller M, Nathanson KL, Domchek SM, Rodriguez GC, Salani R, Kaulich DG, Tea MK, Paluch SS, Laitman Y, Skytte AB, Kruse TA, Jensen UB, Robson M, Gerdes AM, Ejlertsen B, Foretova L, Savage SA, Lester J, Soucy P, Kuchenbaecker KB, Olswold C, Cunningham JM, Slager S, Pankratz VS, Dicks E, Lakhani SR, Couch FJ, Hall P, Monteiro AN, Gayther SA, Pharoah PD, Reddel RR, Goode EL, Greene MH, Easton DF, Berchuck A, Antoniou AC, Chenevix-Trench G, Dunning AM. Multiple independent variants at the TERT locus are associated with telomere length and risks of breast and ovarian cancer. Nat Genet. 2013; 45:371–384. 384e371-372. [PubMed: 23535731] Bruedigam C, Bagger FO, Heidel FH, Paine Kuhn C, Guignes S, Song A, Austin R, Vu T, Lee E, Riyat S, Moore AS, Lock RB, Bullinger L, Hill GR, Armstrong SA, Williams DA, Lane SW. Telomerase inhibition effectively targets mouse and human AML stem cells and delays relapse following chemotherapy. Cell Stem Cell. 2014; 15:775–790. [PubMed: 25479751] Bullinger L, Ehrich M, Dohner K, Schlenk RF, Dohner H, Nelson MR, van den Boom D. Quantitative DNA methylation predicts survival in adult acute myeloid leukemia. Blood. 2010; 115:636–642. [PubMed: 19903898] Calado RT, Brudno J, Mehta P, Kovacs JJ, Wu C, Zago MA, Chanock SJ, Boyer TD, Young NS. Constitutional telomerase mutations are genetic risk factors for cirrhosis. Hepatology. 2011; 53:1600–1607. [PubMed: 21520173] Calado RT, Cooper JN, Padilla-Nash HM, Sloand EM, Wu CO, Scheinberg P, Ried T, Young NS. Short telomeres result in chromosomal instability in hematopoietic cells and precede malignant evolution in human aplastic anemia. Leukemia. 2012; 26:700–707. [PubMed: 22005790]


Zhao et al.

Page 12


Cancer Genome Atlas Research N. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 2013; 368:2059–2074. [PubMed: 23634996] Castelo-Branco P, Choufani S, Mack S, Gallagher D, Zhang C, Lipman T, Zhukova N, Walker EJ, Martin D, Merino D, Wasserman JD, Elizabeth C, Alon N, Zhang L, Hovestadt V, Kool M, Jones DT, Zadeh G, Croul S, Hawkins C, Hitzler J, Wang JC, Baruchel S, Dirks PB, Malkin D, Pfister S, Taylor MD, Weksberg R, Tabori U. Methylation of the TERT promoter and risk stratification of childhood brain tumours: an integrative genomic and molecular study. Lancet Oncol. 2013; 14:534–542. [PubMed: 23598174] Cohen SB, Graham ME, Lovrecz GO, Bache N, Robinson PJ, Reddel RR. Protein composition of catalytically active human telomerase from immortal cells. Science. 2007; 315:1850–1853. [PubMed: 17395830] Dessain SK, Yu H, Reddel RR, Beijersbergen RL, Weinberg RA. Methylation of the human telomerase gene CpG island. Cancer Res. 2000; 60:537–541. [PubMed: 10676632] Devereux TR, Horikawa I, Anna CH, Annab LA, Afshari CA, Barrett JC. DNA methylation analysis of the promoter region of the human telomerase reverse transcriptase (hTERT) gene. Cancer Res. 1999; 59:6087–6090. [PubMed: 10626795] Ducrest AL, Szutorisz H, Lingner J, Nabholz M. Regulation of the human telomerase reverse transcriptase gene. Oncogene. 2002; 21:541–552. [PubMed: 11850779] Fenaux P, Mufti GJ, Hellstrom-Lindberg E, Santini V, Finelli C, Giagounidis A, Schoch R, Gattermann N, Sanz G, List A, Gore SD, Seymour JF, Bennett JM, Byrd J, Backstrom J, Zimmerman L, McKenzie D, Beach C, Silverman LR. International Vidaza High-Risk MDS Survival Study Group. Efficacy of azacitidine compared with that of conventional care regimens in the treatment of higher-risk myelodysplastic syndromes: a randomised, open-label, phase III study. Lancet Oncol. 2009; 10:223–232. [PubMed: 19230772] Figueroa ME, Lugthart S, Li Y, Erpelinck-Verschueren C, Deng X, Christos PJ, Schifano E, Booth J, van Putten W, Skrabanek L, Campagne F, Mazumdar M, Greally JM, Valk PJ, Lowenberg B, Delwel R, Melnick A. DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia. Cancer Cell. 2010; 17:13–27. [PubMed: 20060365] Gertler R, Rosenberg R, Stricker D, Friederichs J, Hoos A, Werner M, Ulm K, Holzmann B, Nekarda H, Siewert JR. Telomere length and human telomerase reverse transcriptase expression as markers for progression and prognosis of colorectal carcinoma. J Clin Oncol. 2004; 22:1807–1814. [PubMed: 15143073] Guilleret I, Yan P, Grange F, Braunschweig R, Bosman FT, Benhattar J. Hypermethylation of the human telomerase catalytic subunit (hTERT) gene correlates with telomerase activity. Int J Cancer. 2002; 101:335–341. [PubMed: 12209957] Halder R, Halder K, Sharma P, Garg G, Sengupta S, Chowdhury S. Guanine quadruplex DNA structure restricts methylation of CpG dinucleotides genome-wide. Mol Biosyst. 2010; 6:2439–2447. [PubMed: 20877913] Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011; 144:646–674. [PubMed: 21376230] Horikawa I, Cable PL, Afshari C, Barrett JC. Cloning and characterization of the promoter region of human telomerase reverse transcriptase gene. Cancer Res. 1999; 59:826–830. [PubMed: 10029071] Horn S, Figl A, Rachakonda PS, Fischer C, Sucker A, Gast A, Kadel S, Moll I, Nagore E, Hemminki K, Schadendorf D, Kumar R. TERT promoter mutations in familial and sporadic melanoma. Science. 2013; 339:959–961. [PubMed: 23348503] Huang FW, Hodis E, Xu MJ, Kryukov GV, Chin L, Garraway LA. Highly recurrent TERT promoter mutations in human melanoma. Science. 2013; 339:957–959. [PubMed: 23348506] Jaenisch R, Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet. 2003; 33(Suppl):245–254. [PubMed: 12610534] Jiang Y, Dunbar A, Gondek LP, Mohan S, Rataul M, O'Keefe C, Sekeres M, Saunthararajah Y, Maciejewski JP. Aberrant DNA methylation is a dominant mechanism in MDS progression to AML. Blood. 2009; 113:1315–1325. [PubMed: 18832655]


Zhao et al.

Page 13


Jones PA, Laird PW. Cancer epigenetics comes of age. Nat Genet. 1999; 21:163–167. [PubMed: 9988266] Ko E, Jung ES, Jung G. Telomerase reverse transcriptase promoter methylation is related to a risk of recurrence in hepatocellular carcinoma. Hepatology. 2016; 63:341–342. [PubMed: 25847141] Lin J, Hou JQ, Xiang HD, Yan YY, Gu YC, Tan JH, Li D, Gu LQ, Ou TM, Huang ZS. Stabilization of G-quadruplex DNA by C-5-methyl-cytosine in bcl-2 promoter: implications for epigenetic regulation. Biochem Biophys Res Commun. 2013; 433:368–373. [PubMed: 23261425] Renaud S, Loukinov D, Abdullaev Z, Guilleret I, Bosman FT, Lobanenkov V, Benhattar J. Dual role of DNA methylation inside and outside of CTCF-binding regions in the transcriptional regulation of the telomerase hTERT gene. Nucleic Acids Res. 2007; 35:1245–1256. [PubMed: 17267411] Rollig C, Bornhauser M, Thiede C, Taube F, Kramer M, Mohr B, Aulitzky W, Bodenstein H, Tischler HJ, Stuhlmann R, Schuler U, Stolzel F, von Bonin M, Wandt H, Schafer-Eckart K, Schaich M, Ehninger G. Long-term prognosis of acute myeloid leukemia according to the new genetic risk classification of the European LeukemiaNet recommendations: evaluation of the proposed reporting system. J Clin Oncol. 2011; 29:2758–2765. [PubMed: 21632498] Sanders RP, Drissi R, Billups CA, Daw NC, Valentine MB, Dome JS. Telomerase expression predicts unfavorable outcome in osteosarcoma. J Clin Oncol. 2004; 22:3790–3797. [PubMed: 15365076] Shaknovich R, De S, Michor F. Epigenetic diversity in hematopoietic neoplasms. Biochim Biophys Acta. 2014; 1846:477–484. [PubMed: 25240947] Shin KH, Kang MK, Dicterow E, Park NH. Hypermethylation of the hTERT promoter inhibits the expression of telomerase activity in normal oral fibroblasts and senescent normal oral keratinocytes. Br J Cancer. 2003; 89:1473–1478. [PubMed: 14562019] Silverman LR, McKenzie DR, Peterson BL, Holland JF, Backstrom JT, Beach CL, Larson RA. Cancer & Leukemia Group, B. Further analysis of trials with azacitidine in patients with myelodysplastic syndrome: studies 8421, 8921, and 9221 by the Cancer and Leukemia Group B. J Clin Oncol. 2006; 24:3895–3903. [PubMed: 16921040] Smiraglia DJ, Rush LJ, Fruhwald MC, Dai Z, Held WA, Costello JF, Lang JC, Eng C, Li B, Wright FA, Caligiuri MA, Plass C. Excessive CpG island hypermethylation in cancer cell lines versus primary human malignancies. Hum Mol Genet. 2001; 10:1413–1419. [PubMed: 11440994] Tabori U, Ma J, Carter M, Zielenska M, Rutka J, Bouffet E, Bartels U, Malkin D, Hawkins C. Human telomere reverse transcriptase expression predicts progression and survival in pediatric intracranial ependymoma. J Clin Oncol. 2006; 24:1522–1528. [PubMed: 16575002] Takakura M, Kyo S, Kanaya T, Hirano H, Takeda J, Yutsudo M, Inoue M. Cloning of human telomerase catalytic subunit (hTERT) gene promoter and identification of proximal core promoter sequences essential for transcriptional activation in immortalized and cancer cells. Cancer Res. 1999; 59:551–557. [PubMed: 9973199] Tefferi A, Lasho TL, Begna KH, Patnaik MM, Zblewski DL, Finke CM, Laborde RR, Wassie E, Schimek L, Hanson CA, Gangat N, Wang X, Pardanani A. A Pilot Study of the Telomerase Inhibitor Imetelstat for Myelofibrosis. N Engl J Med. 2015; 373:908–919. [PubMed: 26332545] Thurman RE, Rynes E, Humbert R, Vierstra J, Maurano MT, Haugen E, Sheffield NC, Stergachis AB, Wang H, Vernot B, Garg K, John S, Sandstrom R, Bates D, Boatman L, Canfield TK, Diegel M, Dunn D, Ebersol AK, Frum T, Giste E, Johnson AK, Johnson EM, Kutyavin T, Lajoie B, Lee BK, Lee K, London D, Lotakis D, Neph S, Neri F, Nguyen ED, Qu H, Reynolds AP, Roach V, Safi A, Sanchez ME, Sanyal A, Shafer A, Simon JM, Song L, Vong S, Weaver M, Yan Y, Zhang Z, Zhang Z, Lenhard B, Tewari M, Dorschner MO, Hansen RS, Navas PA, Stamatoyannopoulos G, Iyer VR, Lieb JD, Sunyaev SR, Akey JM, Sabo PJ, Kaul R, Furey TS, Dekker J, Crawford GE, Stamatoyannopoulos JA. The accessible chromatin landscape of the human genome. Nature. 2012; 489:75–82. [PubMed: 22955617] Traina F, Visconte V, Elson P, Tabarroki A, Jankowska AM, Hasrouni E, Sugimoto Y, Szpurka H, Makishima H, O'Keefe CL, Sekeres MA, Advani AS, Kalaycio M, Copelan EA, Saunthararajah Y, Olalla Saad ST, Maciejewski JP, Tiu RV. Impact of molecular mutations on treatment response to DNMT inhibitors in myelodysplasia and related neoplasms. Leukemia. 2014; 28:78–87. [PubMed: 24045501] Varley KE, Gertz J, Bowling KM, Parker SL, Reddy TE, Pauli-Behn F, Cross MK, Williams BA, Stamatoyannopoulos JA, Crawford GE, Absher DM, Wold BJ, Myers RM. Dynamic DNA Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 14

Author Manuscript

methylation across diverse human cell lines and tissues. Genome Res. 2013; 23:555–567. [PubMed: 23325432] Wang S, Zhao Y, Hu C, Zhu J. Differential repression of human and mouse TERT genes during cell differentiation. Nucleic Acids Res. 2009; 37:2618–2629. [PubMed: 19270068] Yamaguchi H, Calado RT, Ly H, Kajigaya S, Baerlocher GM, Chanock SJ, Lansdorp PM, Young NS. Mutations in TERT, the gene for telomerase reverse transcriptase, in aplastic anemia. N Engl J Med. 2005; 352:1413–1424. [PubMed: 15814878] Zinn RL, Pruitt K, Eguchi S, Baylin SB, Herman JG. hTERT is expressed in cancer cell lines despite promoter DNA methylation by preservation of unmethylated DNA and active chromatin around the transcription start site. Cancer Res. 2007; 67:194–201. [PubMed: 17210699]

Author Manuscript Author Manuscript Author Manuscript Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 15


Figure 1.

TERTpro/Ex1 methylation profiles in various cell lines and normal haematopoietic cells. (a) Pyrosequencing-based methylation analysiswas used to examine the entire TERTpro/Ex1 methylation profiles in 14 haematopoietic cell lines that originated from different cell lineages and two other cell lines (cervical cancer and embryonic kidney cells). (b) Normal peripheral blood (PB) cell populations (granulocytes, T cells, B cells and monocytes) were sorted from PB mononuclear cells of healthy donors by flow cytometry and subjected to the methylation analysis, in a similar manner. Cell types of individual cell lines are indicated.


Zhao et al.

Page 16

Author Manuscript

Average methylation percentages in duplicate assays were plotted for individual CpG sites. CpG sites were numbered relative to ATG: the first CpG site upstream or downstream from ATG was numbered as −1 or +1, respectively, and the others were labelled in a similar fashion.


Zhao et al.

Page 17


Figure 2.

TERTpro/Ex1 methylation status in primary leukaemic cell populations. CD34+ cell populations were sorted from bone marrow cells of AML or AML/MDS patients by flow cytometry, followed by pyrosequencing methylation analysis of the entire TERTpro/Ex1 region. Three representative hypermethylated (left panels) and three hypomethylated patterns (right panels) are shown. Characteristic features of individual patients are reported in Supplementary Table 1.


Zhao et al.

Page 18


Figure 3.

Distinct TERTpro/Ex1 methylation signatures between primary leukaemic cells and cell lines evolving from the corresponding primary cells. CD34+ CD38−, CD34+ CD38+ and CD11b+ CD14+ cell populations were sorted from peripheral blood mononuclear cells of one AML patient (Patient 21). One CD34+ CD38− cell line was established from primary leukaemic cells in the same patient. (a) Entire TERTpro/Ex1 methylation profiles of individual primary cell populations or evolved cell lines. (b) Telomere restriction fragment (TRF) length measurement of primary cells or cell lines by Southern blot analysis. Primary


Zhao et al.

Page 19

Author Manuscript

cell populations indicated and the respective cell lines (CL) were subjected to TRF length assay to assess their telomere lengths. Molecular weight markers are indicated on the left.


Zhao et al.

Page 20


Figure 4.

Heat map representation of methylation rates of the four representative TERTpro/Ex1 regions. (a) Methylation status of the TERTpro/Ex1 region in 33 AML, 10 AML/MDS and 4 healthy donors were assessed by analysing the four representative regions (Regions A, B, C and D with five CpG sites, respectively). Methylation analysis was performed using CD34+ cells (closed circles), bone marrow (BM) cells (closed triangles) and PBMCs (no symbols). In two healthy donors, both BM cells (closed triangles) and peripheral blood mononuclear cells (PBMCs; no symbols) were obtained from the same individuals (each is highlighted


Zhao et al.

Page 21

Author Manuscript

with a vertical line) for methylation analysis. Methylation percentages were classified into five ranges that are represented by the indicated colours. Methylation percentages at individual CpG sites are indicated in the heat map. The bottom panel illustrates the TERTpro/Ex1 region: four representative regions used for pyrosequencing analyses are shown as open boxes and the corresponding nucleotide numbers relative to ATG are also shown. Detailed information of these four regions was described in the “MATERIALS AND METHOD” section. (b) Methylation data are displayed as box-and-whisker plots. The shaded box was drawn from the lower quartile to the upper quartile, a horizontal line indicates the median and the whiskers extend out from the box to the smallest and the largest data points.


Zhao et al.

Page 22

Author Manuscript Author Manuscript Author Manuscript Figure 5.

Author Manuscript

Kaplan-Meier survival analyses according to TERTpro methylation status for 43 cases (33 AML and 10 AML/MDS). Estimated overall survival in patients with > 28% methylation of the TERT-Region A (TERTA) was compared those with < 28% methylation of the region. The log-rank test showed a significant difference between the two groups (P = 0.045). The y- and x-axes represent the probability of survival and time in years since sample collection.


Zhao et al.

Page 23


Figure 6.

Author Manuscript

Chemosensitivity assay for the telomerase inhibitor, imetelstat. (a) Three cell lines (K562, THP1 and Ramos) with different TERTpro/Ex1 methylation patterns were cultured for 48 h with either imetelstat or the inert control at various concentrations (5 µM to 40 µM, as indicated). After staining cells with Annexin-V APC and PI, cell viability was measured by flow cytometry. An association between TERTpro/Ex1 methylation percentages and viability ratios (specific killing with imetelstat) was shown in three leukaemia cell lines. Spearman’s rank correlation rho with P-values was used to examine the association. Individual least squares fit in dash lines were drawn. (b) Effects of each reagent alone (5Aza or imetelstat) or co-administration (5-Aza + imetelstat or 5-Aza + inert control) on viabilities of the three cell lines were assessed as follows. For single administration, cells were treated with 5-Aza (50 µM) for 72 h or imetelstat (20 µM) alone for 48 h. For coadministration, cells were pre-treated with 5-Aza (50 µM) for 24 h and then cultured for another 48 h after addition of imetelstat (20 µM) or the inert control (20 µM). ** P < 0.01; *** P < 0.001.TERT

Author Manuscript Br J Haematol. Author manuscript; available in PMC 2017 November 01.

Zhao et al.

Page 24

Table I

Author Manuscript

Patient and disease characteristics Number of patients

43

Median age, years (range)

57

(18–80)

Male

22

(51)

Female

21

(49)

Secondary AML, n (%)

12

(28)

Abnormal cytogenetics, n (%)

28

(65)

Favourable

6

(14)

Intermediate 1

12

(28)

Intermediate 2

10

(23)

Adverse

15

(35)

AML NOS

19

(44)

AML NOS M1

3

(7)

AML NOS M2

4

(9)

AML NOS M5

7

(16)

AML NOS M6

2

(5)

AML inv 16

2

(5)

AML 11q23

1

(2)

AML with myelodysplasia-related changes

4

(9)

Mixed phenotype leukaemia

1

(2)

Yes

25

(58)

No

13

(30)

Gender, n (%)

Disease risk, n (%)

Author Manuscript

WHO/FAB classification, n (%)

CR with first induction, n (%)

Author Manuscript

5

(11)

Allogeneic stem cell transplantation, n (%)

Unknown

22

(51)

Median follow up of surviving patients, days (range)

580

(75–1016)

PBMC

35

(81)

BMC

5

(12)

CD34+

3

(7)

Sample source, n (%)

Abbreviations: AML, acute myeloid leukaemia; BMC, bone marrow cells; CR, complete remission; FAB, French-American-British; NOS, not otherwise specified; PBMC, peripheral blood mononuclear cells; WHO, World Health Organization.

Author Manuscript Br J Haematol. Author manuscript; available in PMC 2017 November 01.

p38 MAPK in MDS.

Clinical features of MDS.

Unraveling the Pathogenesis of MDS: The NLRP3 Inflammasome and Pyroptosis Drive the MDS Phenotype.

Charting the "Splice" Routes to MDS.

Which prognostic score in MDS? Both!

MDS-related mutations in aplastic anemia.

MPNs.

Norwegian MDs confront paradoxes of egalitarianism.

Morphology, cytogenetics and classification of MDS.

What came first: MDS or AML?

Dehydrated hereditary stomatocytosis masquerading as MDS.

Oil and medicine: Alberta MDs gain support.

IRAK1: oncotarget in MDS and AML.

Handling missing values in the MDS-UPDRS.

Legal fees nearly double for many MDs.

The GNAS1 gene in myelodysplastic syndromes (MDS).

Deletion 5q MDS: molecular and therapeutic implications.

Genes break barrier between MDS and AML.

MDS data should be used for research.

Cytogenetic findings in primary and secondary MDS.

Differential response to hypomethylating agents based on sex: a report on behalf of the MDS Clinical Research Consortium (MDS CRC).

Downregulation of MMP1 in MDS-derived mesenchymal stromal cells reduces the capacity to restrict MDS cell proliferation.

Low frequency of calreticulin mutations in MDS patients.

Military MDs used to peace prepare for war.

MDS.

Follow Us

Suggest Documents

p38 MAPK in MDS.

Clinical features of MDS.

Unraveling the Pathogenesis of MDS: The NLRP3 Inflammasome and Pyroptosis Drive the MDS Phenotype.

Charting the "Splice" Routes to MDS.

Which prognostic score in MDS? Both!

MDS-related mutations in aplastic anemia.

MPNs.

Norwegian MDs confront paradoxes of egalitarianism.

Morphology, cytogenetics and classification of MDS.

What came first: MDS or AML?

Dehydrated hereditary stomatocytosis masquerading as MDS.

Oil and medicine: Alberta MDs gain support.

IRAK1: oncotarget in MDS and AML.

Handling missing values in the MDS-UPDRS.

Legal fees nearly double for many MDs.

The GNAS1 gene in myelodysplastic syndromes (MDS).

Deletion 5q MDS: molecular and therapeutic implications.

Genes break barrier between MDS and AML.

MDS data should be used for research.

Cytogenetic findings in primary and secondary MDS.

Differential response to hypomethylating agents based on sex: a report on behalf of the MDS Clinical Research Consortium (MDS CRC).

Downregulation of MMP1 in MDS-derived mesenchymal stromal cells reduces the capacity to restrict MDS cell proliferation.

Low frequency of calreticulin mutations in MDS patients.

Military MDs used to peace prepare for war.

MDS.

Recommend Documents

Follow Us