A glycolysis-based ten-gene signature correlates with the clinical outcome,molecular subtype and IDH1 mutation in glioblastoma

Reprogrammed metabolism is a hallmark of cancer. Glioblastoma (GBM) tumor cells predominantly utilize aerobic glycolysis for the biogenesis of energy and intermediate nutrients. However, in GBM, the clinical significance of glycolysis and its underlying relations with the molecular features such as IDH1 mutation and subtype have not been elucidated yet. Herein, based on glioma datasets including TCGA (The Cancer Genome Atlas), REMBRANDT (Repository for Molecular Brain Neoplasia Data) and GSE16011, we established a glycolytic gene expression signature score (GGESS) by incorporating ten glycolytic genes. Then we performed survival analyses and investigated the correlations between GGESS and IDH1 mutation as well as the molecular subtypes in GBMs. The results showed that GGESS independently predicted unfavorable prognosis and poor response to chemotherapy of GBM patients. Notably, GGESS was high in GBMs of mesenchymal subtype but low in IDH1-mutant GBMs. Furthermore, we found that the promoter regions of tumor-promoting glycolytic genes were hypermethylated in IDH1-mutant GBMs. Finally, we found that high GGESS also predicted poor prognosis and poor response to chemotherapy when investigating IDH1-wildtype GBM patients only. Collectively, glycolysis represented by GGESS predicts unfavorable clinical outcome of GBM patients and is closely associated with mesenchymal subtype and IDH1 mutation in GBMs.     

The global DNA methylation surrogate LINE-1 methylation is correlated with MGMT promoter methylation and is a better prognostic factor for glioma

Gliomas are the most frequently occurring primary brain tumor in the central nervous system of adults. Glioblastoma multiformes (GBMs, WHO grade 4) have a dismal prognosis despite the use of the alkylating agent, temozolomide (TMZ), and even low grade gliomas (LGGs, WHO grade 2) eventually transform to malignant secondary GBMs. Although GBM patients benefit from promoter hypermethylation of the O(6)-methylguanine-DNA methyltransferase (MGMT) that is the main determinant of resistance to TMZ, recent studies suggested that MGMT promoter methylation is of prognostic as well as predictive significance for the efficacy of TMZ. Glioma-CpG island methylator phenotype (G-CIMP) in the global genome was shown to be a significant predictor of improved survival in patients with GBM. Collectively, we hypothesized that MGMT promoter methylation might reflect global DNA methylation. Additionally in LGGs, the significance of MGMT promoter methylation is still undetermined. In the current study, we aimed to determine the correlation between clinical, genetic, and epigenetic profiles including LINE-1 and different cancer-related genes and the clinical outcome in newly diagnosed 57 LGG and 54 GBM patients. Here, we demonstrated that (1) IDH1/2 mutation is closely correlated with MGMT promoter methylation and 1p/19q codeletion in LGGs, (2) LINE-1 methylation levels in primary and secondary GBMs are lower than those in LGGs and normal brain tissues, (3) LINE-1 methylation is proportional to MGMT promoter methylation in gliomas, and (4) higher LINE-1 methylation is a favorable prognostic factor in primary GBMs, even compared to MGMT promoter methylation. As a global DNA methylation marker, LINE-1 may be a promising marker in gliomas.     

G-Cimp Status Prediction Of Glioblastoma Samples Using mRNA Expression Data

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.     

Prognosis of Glioblastoma With Oligodendroglioma Component is Associated With the IDH1 Mutation and MGMT Methylation Status

Glioblastoma (GBM) with oligodendroglioma component (GBMO) is a newly described GBM subtype in the 2007 World Health Organization classification. However, its biological and genetic characteristics are largely unknown. We investigated the clinicopathological and molecular features of 34 GBMOs and compared the survival rate of these patients with those of patients with astrocytoma, oligodendroglioma, anaplastic oligoastrocytoma (AOA), and conventional GBMs in our hospital. GBMO could be divided into two groups based on the presence of an IDH1 mutation. The IDH1 mutation was more frequently found in secondary GBMO, which had lower frequencies of EGFR amplification but higher MGMT methylation than the wild type IDH1 group, and patients with mutant IDH1 GBMO were on average younger than those with wild-type IDH1. Therefore, GBMO is a clinically and molecularly heterogeneous subtype, largely belonging to a proneural and classical subtype of GBM. The survival rate of GBMO patients itself was worse than that of AOA patients but not significantly better than that of conventional GBM patients. GBMO survival was independent of the dominant histopathological subtype i.e., astrocyte-dominant or oligodendroglioma -dominant, but it was significantly associated with the IDH1 mutation and MGMT methylation status. Therefore, GBMO should be regarded as a separate entity from AOA and must be classified as a subtype of GBM. However, further study is needed to determine whether it is a pathologic variant or a pattern of GBM because GBMO has a similar prognosis to conventional GBMs.     

Prognostic Stratification of GBMs Using Combinatorial Assessment of IDH1 Mutation,MGMT Promoter Methylation,and TERT Mutation Status: Experience from a Tertiary Care Center in India

This study aims to establish the best and simplified panel of molecular markers for prognostic stratification of glioblastomas (GBMs). One hundred fourteen cases of GBMs were studied for IDH1, TP53, and TERT mutation by Sanger sequencing; EGFR and PDGFRA amplification by fluorescence in situ hybridization; NF1expression by quantitative real time polymerase chain reaction (qRT-PCR); and MGMT promoter methylation by methylation-specific PCR. IDH1 mutant cases had significantly longer progression-free survival (PFS) and overall survival (OS) as compared to IDH1 wild-type cases. Combinatorial assessment of MGMT and TERT emerged as independent prognostic markers, especially in the IDH1 wild-type GBMs. Thus, within the IDH1 wild-type group, cases with only MGMT methylation (group 1) had the best outcome (median PFS: 83.3 weeks; OS: not reached), whereas GBMs with only TERT mutation (group 3) had the worst outcome (PFS: 19.7 weeks; OS: 32.8 weeks). Cases with both or none of these alterations (group 2) had intermediate prognosis (PFS: 47.6 weeks; OS: 89.2 weeks). Majority of the IDH1 mutant GBMs belonged to group 1 (75%), whereas only 18.7% and 6.2% showed group 2 and 3 signatures, respectively. Interestingly, none of the other genetic alterations were significantly associated with survival in IDH1 mutant or wild-type GBMs.Based on above findings, we recommend assessment of three markers, viz., IDH1, MGMT, and TERT, for GBM prognostication in routine practice. We show for the first time that IDH1 wild-type GBMs which constitute majority of the GBMs can be effectively stratified into three distinct prognostic subgroups based on MGMT and TERT status, irrespective of other genetic alterations.     

Genome-wide aberrant DNA methylation of microRNA host genes in hepatocellular carcinoma

Mature microRNAs (miRNAs) are a class of small non-coding RNAs involved in posttranslational gene silencing. Previous studies found that downregulation of miRNAs is a common feature observed in solid tumors, including hepatocellular carcinoma (HCC). We employed a genome-wide approach to test the hypothesis that DNA methylation alterations in miRNA host genes may cause deregulated miRNA expression in HCC. We analyzed tumor and adjacent non-tumor tissues from 62 Taiwanese HCC cases using Infinium HumanMethylation27 DNA Analysis BeadChips that include 254 CpG sites covering 110 miRNAs from 64 host genes. Expression levels of three identified miRNAs (miR-10a, miR-10b and miR-196b) were measured in a subset of 37 HCC tumor and non-tumor tissues. After Bonferroni adjustment, a total of 54 CpG sites from 27 host genes significantly differed in DNA methylation levels between tumor and adjacent non-tumor tissues with 53 sites significantly hypermethylated in tumor tissues. Among the 54 significant CpG sites, 15 sites had more than 2-fold tumor/non-tumor changes, 17 sites had differences > 10%, and 10 sites had both features [including 8 significantly hypermethylated CpG sites in the host genes of miR-10a, miR-10b and miR-196b (HOXB4, HOXD4 and HOXA9, respectively)]. Significant downregulation of miR-10a was observed in tumor compared with non-tumor tissues (0.50 vs. 1.73, p = 0.031). The concordance for HOXB4 methylation alteration and dysregulation of miR-10a was 73.5%. No significant change was observed for miR-10b expression. Unexpectedly, miR-196b was significantly upregulated in tumor compared with non-tumor tissues (p = 0.0001). These data suggest that aberrant DNA methylation may lead to dysregulation of miR-10a in HCC tumor tissues.     

The Promoter Hypermethylation Status of GATA6, MGMT, and FHIT in Glioblastoma

Glioblastoma (GBM) is an aggressive and lethal cancer, accounting for the majority of primary brain tumors in adults. GBMs are characterized by large and small alterations in genes that control cell growth, apoptosis, angiogenesis, and invasion. Epigenetic alterations also affect the expression of cancer genes, either alone or in combination with genetic mechanisms. The current evidence suggests that hypermethylation of promoter CpG islands is a common epigenetic event in a variety of human cancers. A subset of GBMs is also characterized by a locus-specific and genome-wide decrease in DNA methylation. Epigenetic alterations are important in the molecular pathology of GBM. However, there are very limited data about these epigenetic alterations in GBM. Alterations in promoter methylations are important to understand because histone deacetylases are targets for drugs that are in clinical trial for GBMs. The aim of the current study was to investigate whether the promoter hypermethylation of putative tumor suppressor genes was involved in GBM. We examined the methylation status at the promoter regions of GATA6, MGMT, and FHIT using the methylation-specific polymerase chain reaction in 61 primary GBMs. Our results reveal that there is no promoter hypermethylation of FHIT in the examined GBM tissue specimens. In contrast, the promoter hypermethylation of GATA6 and MGMT was detected in 42.8 and 11.11% of GBMs, respectively. The frequency of MGMT promoter hypermethylation was low in the group of patients we evaluated. In conclusion, our study demonstrates that promoter hypermethylation of MGMT is a common event in GBMs, whereas GATA6 is epigenetically affected in GBMs. Furthermore, inactivation of FHIT by epigenetic mechanisms in GBM may not be associated with brain tumorigenesis.     

MTSS1 is epigenetically regulated in glioma cells and inhibits glioma cell motility

Epigenetic silencing by DNA methylation in brain tumors has been reported for many genes, however, their function on pathogenesis needs to be evaluated. We investigated the MTSS1 gene, identified as hypermethylated by differential methylation hybridization (DMH). Fifty-nine glioma tissue samples and seven glioma cell lines were examined for hypermethylation of the MTSS1 promotor, MTSS1 expression levels and gene dosage. GBM cell lines were treated with demethylating agents and interrogated for functional consequences of MTSS1 expression after transient transfection. Hypermethylation was significantly associated with IDH1/2 mutation. Comparative SNP analysis indicates higher incidence of loss of heterozygosity of MTSS1 in anaplastic astrocytomas and secondary glioblastomas as well as hypermethylation of the remaining allele. Reversal of promoter hypermethylation results in an increased MTSS1 expression. Cell motility was significantly inhibited by MTSS1 overexpression without influencing cell growth or apoptosis. Immunofluorescence analysis of MTSS1 in human astrocytes indicates co-localization with actin filaments. MTSS1 is down-regulated by DNA methylation in glioblastoma cell lines and is part of the G-CIMP phenotype in primary glioma tissues. Our data on normal astrocytes suggest a function of MTSS1 at focal contact structures with an impact on migratory capacity but no influence on apoptosis or cellular proliferation.     

IDH1 mutations is prognostic marker for primary glioblastoma multiforme but MGMT hypermethylation is not prognostic for primary glioblastoma multiforme

Purpose

To establish the frequency of IDH1 mutations and MGMT methylation in primary glioblastomas.

Experimental design

We screened primary glioblastoma multiforme (GBM) in a population-based study for IDH1 mutations and MGMT methylation and correlated them with clinical data.

Results

IDH1 mutations were detected in 5 of 40 primary glioblastomas (12,5%). Primary GBM patients carrying IDH1 mutations were significantly younger, mean age of 41 ± 5.06 years, than patients with wild-type IDH1, mean age of 57 ± 2,29 years, p = 0.011. The mean survival time of all GBM patients with and without IDH1 mutations was 19 months (5 cases) and 16 months (35 cases), respectively (p > 0,05). MGMT methylation was detected in 13 of the 40 patients (32,5%). MGMT-promoter methylation did not correlate with overall survival (OS; p > 0,05).

Conclusion

In summary, our study is the first study to investigate the IDH1 mutation status and MGMT methylation in primary GBMs in Turkish population and confirmed IDH1 mutation as a genetic marker for also primary GBMs. Our data are still insufficient for definite ascertainment; and our preliminary results suggest: IDH1 status shows an association with younger age and there is a lack of association between IDH1 mutation and survival time. Furthermore MGMT promoter methylation had no prognostic value and lower frequency in primary glioblastomas.     

Prognostic Value of PLAGL1-Specific CpG Site Methylation in Soft-Tissue Sarcomas

Soft tissue sarcomas (STS) are rare, complex tumors with a poor prognosis. The identification of new prognostic biomarkers is needed to improve patient management. Our aim was to determine the methylation status of the 118 CpG sites in the PLAGL1 tumor-suppressor gene P1 CpG island promoter and study the potential prognostic impact of PLAGL1 promoter methylation CpG sites in STS. Training cohorts constituted of 28 undifferentiated sarcomas (US) and 35 leiomyosarcomas (LMS) were studied. PLAGL1 mRNA expression was investigated by microarray analysis and validated by RT-qPCR. Pyrosequencing was used to analyze quantitative methylation of the PLAGL1 promoter. Associations between global promoter or specific CpG site methylation and mRNA expression were evaluated using Pearson’s product moment correlation coefficient. Cox univariate and multivariate proportional hazard models were used to assess the predictive power of CpG site methylation status. Sixteen CpG sites associated with PLAGL1 mRNA expression were identified in US and 6 in LMS. Statistical analyses revealed an association between CpG107 methylation status and both overall and metastasis-free survival in US, which was confirmed in a validation cohort of 37 US. The exhaustive study of P1 PLAGL1 promoter methylation identified a specific CpG site methylation correlated with mRNA expression, which was predictive for both metastasis-free and overall survival and may constitute the first US-specific biomarker. Such a biomarker may be relevant for identifying patients likely to derive greater benefit from treatment.     

A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression

Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.     

Genome-wide methylation profiling identifies novel methylated genes in neuroblastoma tumors

Neuroblastoma is a very heterogeneous tumor of childhood. The clinical spectra range from very aggressive metastatic disease to spontaneous regression, even without therapy. Aberrant DNA methylation pattern is a common feature of most cancers. For neuroblastoma, it has been demonstrated both for single genes as well as genome-wide, where a so-called methylator phenotype has been described. Here, we present a study using Illumina 450K methylation arrays on 60 neuroblastoma tumors. We show that aggressive tumors, characterized by International Neuroblastoma Risk Group (INRG) as stage M, are hypermethylated compared to low-grade tumors. On the contrary, INRG stage L tumors display more non-CpG methylation. The genes with the highest number of hypermethylated CpG sites in INRG M tumors are TERT, PCDHGA4, DLX5, and DLX6-AS1. Gene ontology analysis showed a representation of neuronal tumor relevant gene functions among the differentially methylated genes. For validation, we used a set of independent tumors previously analyzed with the Illumina 27K methylation arrays, which confirmed the differentially methylated sites. Top candidate genes with aberrant methylation were analyzed for altered gene expression through the R2 platform (http://r2.amc.nl), and for correlations between methylation and gene expression in a public dataset. Altered expression in nonsurvivors was found for the genes B3GALT4 and KIAA1949, CLIC5, DLX6-AS, TERT, and PIRT, and strongest correlations were found for TRIM36, KIAA0513, and PIRT. Our data indicate that methylation profiling can be used for patient stratification and informs on epigenetically deregulated genes with the potential of increasing our knowledge about the underlying mechanisms of tumor development.     

TGF-β induces global changes in DNA methylation during the epithelial-to-mesenchymal transition in ovarian cancer cells

A key step in the process of metastasis is the epithelial-to-mesenchymal transition (EMT). We hypothesized that epigenetic mechanisms play a key role in EMT and to test this hypothesis we analyzed global and gene-specific changes in DNA methylation during TGF-β-induced EMT in ovarian cancer cells. Epigenetic profiling using the Infinium HumanMethylation450 BeadChip (HM450) revealed extensive (P < 0.01) methylation changes after TGF-β stimulation (468 and 390 CpG sites altered at 48 and 120 h post cytokine treatment, respectively). The majority of gene-specific TGF-β-induced methylation changes occurred in CpG islands located in or near promoters (193 and 494 genes hypermethylated at 48 and 120 h after TGF-β stimulation, respectively). Furthermore, methylation changes were sustained for the duration of TGF-β treatment and reversible after the cytokine removal. Pathway analysis of the hypermethylated loci identified functional networks strongly associated with EMT and cancer progression, including cellular movement, cell cycle, organ morphology, cellular development, and cell death and survival. Altered methylation and corresponding expression of specific genes during TGF-β-induced EMT included CDH1 (E-cadherin) and COL1A1 (collagen 1A1). Furthermore, TGF-β induced both expression and activity of DNA methyltransferases (DNMT) -1, -3A, and -3B, and treatment with the DNMT inhibitor SGI-110 prevented TGF-β-induced EMT. These results demonstrate that dynamic changes in the DNA methylome are implicated in TGF-β-induced EMT and metastasis. We suggest that targeting DNMTs may inhibit this process by reversing the EMT genes silenced by DNA methylation in cancer.     

Molecular Predictors of Long-Term Survival in Glioblastoma Multiforme Patients

Glioblastoma multiforme (GBM) is the most common and aggressive adult primary brain cancer, with <10% of patients surviving for more than 3 years. Demographic and clinical factors (e.g. age) and individual molecular biomarkers have been associated with prolonged survival in GBM patients. However, comprehensive systems-level analyses of molecular profiles associated with long-term survival (LTS) in GBM patients are still lacking. We present an integrative study of molecular data and clinical variables in these long-term survivors (LTSs, patients surviving >3 years) to identify biomarkers associated with prolonged survival, and to assess the possible similarity of molecular characteristics between LGG and LTS GBM. We analyzed the relationship between multivariable molecular data and LTS in GBM patients from the Cancer Genome Atlas (TCGA), including germline and somatic point mutation, gene expression, DNA methylation, copy number variation (CNV) and microRNA (miRNA) expression using logistic regression models. The molecular relationship between GBM LTS and LGG tumors was examined through cluster analysis. We identified 13, 94, 43, 29, and 1 significant predictors of LTS using Lasso logistic regression from the somatic point mutation, gene expression, DNA methylation, CNV, and miRNA expression data sets, respectively. Individually, DNA methylation provided the best prediction performance (AUC = 0.84). Combining multiple classes of molecular data into joint regression models did not improve prediction accuracy, but did identify additional genes that were not significantly predictive in individual models. PCA and clustering analyses showed that GBM LTS typically had gene expression profiles similar to non-LTS GBM. Furthermore, cluster analysis did not identify a close affinity between LTS GBM and LGG, nor did we find a significant association between LTS and secondary GBM. The absence of unique LTS profiles and the lack of similarity between LTS GBM and LGG, indicates that there are multiple genetic and epigenetic pathways to LTS in GBM patients.     

Biomarkers for detection and prognosis of breast cancer identified by a functional hypermethylome screen

Breast cancer (BC) is a disease with diverse tumor heterogeneity, which challenges conventional approaches to develop biomarkers for early detection and prognosis. To identify effective biomarkers, we performed a genome-wide screen for functional methylation changes in BC, i.e., genes silenced by promoter hypermethylation, using a functionally proven gene expression approach. A subset of candidate hypermethylated genes were validated in primary BCs and tested as markers for detection and prognosis prediction of BC. We identified 33 cancer specific methylated genes and, among these, two categories of genes: (1) highly frequent methylated genes that detect early stages of BC. Within that category, we have identified the combination of NDRG2 and HOXD1 as the most sensitive (94%) and specific (90%) gene combination for detection of BC; (2) genes that show stage dependent methylation frequency pattern, which are candidates to help delineate BC prognostic signatures. For this category, we found that methylation of CDO1, CKM, CRIP1, KL and TAC1 correlated with clinical prognostic variables and was a significant prognosticator for poor overall survival in BC patients. CKM [Hazard ratio (HR) = 2.68] and TAC1 (HR = 7.73) were the strongest single markers and the combination of both (TAC1 and CKM) was associated with poor overall survival independent of age and stage in our training (HR = 1.92) and validation cohort (HR = 2.87). Our study demonstrates an efficient method to utilize functional methylation changes in BC for the development of effective biomarkers for detection and prognosis prediction of BC.     

Elevated invasive potential of glioblastoma stem cells

Glioblastomas (GBMs) are the most lethal and common types of primary brain tumors. The hallmark of GBMs is their highly infiltrative nature. The cellular and molecular mechanisms underlying the aggressive cancer invasion in GBMs are poorly understood. GBM displays remarkable cellular heterogeneity and hierarchy containing self-renewing glioblastoma stem cells (GSCs). Whether GSCs are more invasive than non-stem tumor cells and contribute to the invasive phenotype in GBMs has not been determined. Here we provide experimental evidence supporting that GSCs derived from GBM surgical specimens or xenografts display greater invasive potential in vitro and in vivo than matched non-stem tumor cells. Furthermore, we identified several invasion-associated proteins that were differentially expressed in GSCs relative to non-stem tumor cells. One of such proteins is L1CAM, a cell surface molecule shown to be critical to maintain GSC tumorigenic potential in our previous study. Immunohistochemical staining showed that L1CAM is highly expressed in a population of cancer cells in the invasive fronts of primary GBMs. Collectively, these data demonstrate the invasive nature of GSCs, suggesting that disrupting GSCs through a specific target such as L1CAM may reduce GBM cancer invasion and tumor recurrence.     

Effects of TET2 mutations on DNA methylation in chronic myelomonocytic leukemia

TET2 enzymatically converts 5-methyl-cytosine to 5-hydroxymethyl-cytosine, possibly leading to loss of DNA methylation. TET2 mutations are common in myeloid leukemia and were proposed to contribute to leukemogenesis through DNA methylation. To expand on this concept, we studied chronic myelomonocytic leukemia (CMML) samples. TET2 missense or nonsense mutations were detected in 53% (16/30) of patients. In contrast, only 1/30 patient had a mutation in IDH1 or IDH2, and none of them had a mutation in DNMT3A in the sites most frequently mutated in leukemia. Using bisulfite pyrosequencing, global methylation measured by the LINE-1 assay and DNA methylation levels of 10 promoter CpG islands frequently abnormal in myeloid leukemia were not different between TET2 mutants and wild-type CMML cases. This was also true for 9 out of 11 gene promoters reported by others as differentially methylated by TET2 mutations. We found that two non-CpG island promoters, AIM2 and SP140, were hypermethylated in patients with mutant TET2. These were the only two gene promoters (out of 14,475 genes) previously found to be hypermethylated in TET2 mutant cases. However, total 5-methyl-cytosine levels in TET2 mutant cases were significantly higher than TET2 wild-type cases (median = 14.0% and 9.8%, respectively) (p = 0.016). Thus, TET2 mutations affect global methylation in CMML but most of the changes are likely to be outside gene promoters.Key words: TET2, DNA methylation, mutation, CMML, promoter