A microarray-based DNA methylation study of glioblastoma multiforme

[Epigenetics 4:4, 255-264; 16 May 2009]; ©2009 Landes Bioscience

Research Paper

A microarray-based DNA methylation study of glioblastoma multiforme Ramon Martinez,1,* Jose I. Martin-Subero,2 Veit Rohde,1 Matthias Kirsch,4 Miguel Alaminos,5 Agustin F. Fernandez,2 Santiago Ropero,3 Gabriele Schackert4 and Manel Esteller2,6,* 1Department

of Neurosurgery; University of Goettingen; Goettingen, Germany; 2Cancer Epigenetics and Biology Program (PEBC); Bellvitge Biomedical Research Institute (IDIBELL); Barcelona, Catalonia Spain; 3Department of Biochemistry and Molecular Biology; University of Alcala; Madrid, Spain; 4Department of Neurosurgery; University of Dresden; Dresden, Germany; 5Department of Histology; University of Granada; Granada, Spain; 6Institucio Catalana de Recerca i Estudis Avançats (ICREA); Barcelona, Catalonia Spain

Abbreviations: GBM, glioblastoma multiforme; TSG, tumor suppressor gene; ESC, embryonic stem cell; PRC2, polycomb repressive complex 2; NB, normal brain; GO, gene ontology; OS, overall survival; MGMT, O-6-methylguanine-DNA methyltransferase; GATA6, GATA-binding protein 6; FZD9, Frizzled homolog 9; TNFRSF10A, tumor necrosis factor receptor superfamily, member 10a; MEST, mesoderm-specific transcript homolog; TES, testis-derived transcript; PRKCDBP, protein kinase c, delta binding protein; CD81, CD81 antigen; HOXA11, homeobox a11; TNFRSF10D, tumor necrosis factor receptor superfamily, member 10d; HOXA9, homeobox a9; TES, testis-derived transcript; HLA-F, major histocompatibility complex, class I, F; EMR3, EGF-like module-containing, mucin-like hormone receptor 3 Key words: DNA methylation, glioblastoma multiforme, epigenetics, microarray, O-6-methylguanine-DNA methyltransferase

Glioblastoma multiforme (GBM) is the most frequent and devastating primary brain tumor in adults. The presence of epigenetic lesions, like hypermethylation of known tumor suppressor genes such as MGMT, has been widely described in GBM, but to our knowledge, a genome-wide profile of DNA methylation changes in these lethal tumors is not yet available. In the present analysis, we have quantified the DNA methylation level of 1,505 CpG dinucleotides (807 genes) in 87 consecutive GBMs using universal BeadArrays. Supervised cluster analyses identified 25 and seven genes that were respectively hypermethylated and hypomethylated in more than 20% of the cases studied. The most frequently hypermethylated genes were HOXA11, CD81, PRKCDBP, TES, MEST, TNFRSF10A and FZD9, being involved in more than half of the cases. Studying the biological features of hypermethylated genes, we found that the group of genes hypermethylated in GBM was highly enriched (41%, p < 0.001) for targets of the PRC2 (Polycomb repressive complex 2) in embryonic stem cells. This suggests that GBM might be derived from precursor cells with stem cell-like features. *Correspondence to: Ramón Martínez; Department of Neurosurgery; University of Goettingen; Robert Koch Str. 40; Goettingen D-37075 Germany; Email: ramon. [email protected]/ Manel Esteller; Cancer Epigenetics and Biology Program (PEBC); 3rd Floor; Hospital Duran i Reynals; Av. Gran Via de L’Hospitalet 199-203; 08907-L’Hospitalet de Llobregat; Barcelona, Spain; Email: mesteller@ iconcologia.net Submitted: 05/29/09; Accepted: 05/29/09 Previously published online as an Epigenetics E-publication: http://www.landesbioscience.com/journals/epigenetics/article/9130

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DNA methylation profiles were associated with overall survival in GBM, and we confirmed the favorable prognostic impact of MGMT methylation in patients treated with alkylating agents. Furthermore, we identified that promoter hypermethylation of the transcription factor gene GATA6 (occurring in 30% of GBM) was significantly associated with unfavorable patient survival.

Introduction Glioblastoma multiforme (GBM) is the most frequent primary brain tumor in adults. The median survival of patients is only 15 months despite aggressive multimodal therapy. This has not significantly changed in the last 20 years despite advances in surgery, radio- and chemotherapy.1,2 A link between MGMT hypermethylation and improved outcome of patients in response to alkylating drugs in malignant gliomas was first reported by Esteller and coworkers.3 This milestone has dramatically changed the therapy concept for GBM, whereby an improvement of the 2-year survival rate has been achieved after therapy with the adjuvant alkylating drug temozolomide in GBM with hypermethylated MGMT, compared with the rate in those with the unmethylated gene (46 versus 26%).1,4,5 Epigenetic alterations in DNA without mutations in the coding regions of associated cancer genes have been shown to be common events in the genesis and progression of tumors, especially the methylation-mediated silencing of tumor suppressor genes (TSGs).6,7 In cancer cells, aberrant methylation of CpG islands located in the promoter regions of genes involved in cell cycle, invasion, apoptosis or DNA repair is frequently associated with transcriptional silencing.6,7 Such epigenetic inactivation of TSGs

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DNA methylation profiling of glioblastoma multiforme

is thought to provide the tumor clone with a selective advantage. However, recent reports indicate that DNA methylation is not only driven by a selective force; it also appears that hypermethylated genes belong to specific functional categories, have common sequence motifs and cluster at particular chromosomal regions.8 Moreover, a highly significant proportion of genes that become hypermethylated in solid and hematological tumors are already repressed at the embryonic stem cell (ESC) stage by the Polycomb repressive complex 2 (PRC2).9-12 These findings are considered to support the “cancer stem cell theory” in which aberrant epigenetic changes of Polycomb target genes occurring in a cell with stem cell features might be the first event in tumorigenesis. The pattern of epigenetic gene silencing remains diffusely characterized in GBM, although it is one of the most intensively investigated human cancers. Silencing by DNA hypermethylation in GBM affects genes involved in key cellular functions like cell cycle (p16INK4a, p15INK4b), tumor suppression (RB1, VHL, EMP3, RASSF1A and BLU), DNA repair and genome integrity (MGMT and MLH1) as well as tumor invasion and apoptosis (DAPK, TIMP3, CDH1, PCDH-gamma-A11 and TMS1/ASC).13-18 With respect to the recurrence process of GBM, which is one of its inherent clinical features, we have recently proposed that the DNA methylation pattern is different in relapsed GBM compared with the corresponding primary tumor in about two-thirds of cases.19 In particular, a change in the methylation status of the pro-apoptotic CASP8 appears to be associated with relapsed GBM. In this paper we report investigations aimed at developing a more comprehensive understanding of the nature of the GBM epigenome and its biological and clinical significance. Using microarray-based analysis of the DNA methylation status of 1,505 sequences from 807 genes, we have examined the epigenetic signatures of 87 consecutive GBMs that had undergone standard therapy with surgery, radio- and chemotherapy with alkylating drugs. Our results demonstrate that GBM are characterized by a heterogeneous DNA methylation profile, and that differentially methylated genes belong to specific functional categories and are highly enriched for PRC2 targets in ESCs. Furthermore, we confirm previously published findings about the clinical impact of MGMT methylation in GBMs and identify new genes whose epigenetic regulation is possibly associated with overall survival (OS) of GBM patients.

Results Clinico-pathological features of the analyzed patients. The male/female ratio was 1:0.73. The median age at diagnosis of the primary tumor was 60.6 ± 10.8 years (range: 33–89 years). Upon relapse, 37 patients had undergone a second surgical procedure and only nine patients a third operation. Fractionated radiotherapy was performed with a mean dose of 59 Gy. Stereotactic radiotherapy was performed upon relapse in four patients who had previously received fractionated radiotherapy. Chemotherapy regimens included standard doses of temozolomide, ACNU or teniposide. Upon relapse, BCNU wafers were locally implanted after tumor resection in six patients whereas standard chemotherapy regimens 256

were continued. Overall, 44 patients (51.16%) had undergone chemotherapy with temozolomide (patients treated during 2003– 2007), whereas 43 patients treated during the period 1995–2003 had not. The OS rates were 53.8% at 12 months and 12.3% at 24 months. Younger age was significantly associated with survival, as expected (log-rank test, p = 0.009). Six patients were alive at the time of the last contact. Four patients (three females, one male) with long-term OS of more than three years; their median age at diagnosis was 56.5 years (range: 45–72; SD: 11.4 years), which was not significantly different from that of the whole population. Seventeen patients were lost to follow-up and were therefore censored in the statistical analysis of survival. Tumors were mainly localized in frontal, temporal and parietal brain lobes. Five percent of cases were truly multifocal. Patients with tumors extending to more than two brain lobes and with multifocal GBM showed a significantly poorer OS (log-rank test, p = 0.002) than those in whom GBM affected one or two lobes. The median time to tumor recurrence (TTR) was 8 months (range: 1–86 months; SD: 14.22; 95% CI: 5.3–8.0 months). There was no significant relationship between age, gender and chemotherapy modalities with TTR (Spearman correlation tests, all p > 0.05). Delineation of genome-wide DNA methylation profiles in GBM. A hierarchical cluster analysis of methylation values of 1,390 CpGs in 87 GBMs, two GBM cell lines and one normal brain (NB) as negative control is shown in Figure 1. This analysis shows that the DNA methylome of the GBM under study is rather heterogeneous, ranging from cases with a methylation profile similar to NB, to cases with high levels of DNA hypermethylation or hypomethylation. GBM cell lines showed DNA methylation profiles different from GBM patients, and clustered in a clearly different branch of the dendrogram. Detection of genes differentially methylated in GBM. To identify genes differentially methylated in GBM patients compared with the NB sample, we initially classified CpGs according to their methylation status in NB and GBM (Fig. 2). Thus, 591 CpGs (406 genes) and 203 CpGs (153 genes) were classified as unmethylated or methylated both in NB and GBM, respectively. We then identified CpGs showing differential methylation patterns in GBM and NB. A total of 268 CpGs (189 genes) and 112 CpGs (94 genes) were hypermethylated or hypomethylated in at least one GBM relative to the NB, respectively (Table 1). The bar-charts in Figure 3 indicate that most of the CpGs were differentially methylated in a few GBMs and that a restricted number of CpGs are consistently hyper- or hypomethylated in a large fraction of GBM patients. We identified 25 genes as being hypermethylated in more than 20% of the cases (Table 2), seven of which (HOXA11, CD81, PRKCDBP, TES, MEST, TNFRSF10A and FZD9) were hypermethylated in more than 50% of cases. Only seven genes were hypomethylated in more than 20% of cases (Table 3). The same strategy was used to identify differentially methylated genes in the two GBM cell lines under study. We observed that 236 CpGs (173 genes) and 144 CpGs (107 genes) were hypermethylated or hypomethylated in GBM cell lines compared with NB,

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We also questioned whether genes frequently hypermethylated in GBMs were more enriched for PRC2 targets than genes that are rarely hypermethylated. We arranged all hypermethylated CpGs and GBM cases according to their level of aberrant DNA methylation and then annotated the PRC2 status in ESCs. Figure 4 shows that the proportion of PRC2 target genes is independent of the frequency with which a given gene is hypermethylated in GBM. Gene ontology (GO) analysis of groups of genes differentially methylated in GBM patients. As genes studied with the methylation-specific BeadArray were selected for their involvement in cancer, by definition they will be enriched for functions deregulated in cancer. Even taking this limitation into consideration, we found that those genes hypermethylated in GBM were mostly enriched for GO terms associated with physiological functions of the central nervous system whereas hypomethylated genes were mostly involved in immune response. A list of significantly enriched GO terms is provided in Table 4. Clinical impact of differential DNA methylation in GBM. We initially studied the clinical outcome of patients with different levels of MGMT methylation. As NB showed a mean methylation (beta) value of 0.02, we decided to define cases with beta values below 0.1 as lacking MGMT methylation. GBMs with MGMT beta values above 0.5 were defined as methylated and those cases with beta values between 0.1 and 0.5 as partially methylated. As previously observed, GBMs treated with the alkylating drug temozolomide in which MGMT was methylated had better OS than patients with unmethylated MGMT (median: 1,357 vs 512 days) (the log-rank test showed a trend towards statistical significance, p = 0.09; Fig. 5A). Interestingly, cases with only partially methylated MGMT were not associated with a better clinical Figure 1. Hierarchical cluster analysis of DNA methylation data in 87 GBM patient biopsies (yellow), two GBM cell lines (orange) and normal brain (blue). outcome (Fig. 5A). The dendrogram identifies five groups of patients (with at least five patients each) To identify new genes potentially associated with survival with a homogeneous DNA methylation profile. GBM: Glioblastoma multiforme. in GBM, we studied whether patients with better survival (OS above percentile 90, 722 days) and worse survival (OS respectively (Table 1). Comparing lists of genes in GBM patients below percentile 10, 167 days) showed differentially methylated and cell lines, we found that a large number of genes were differen- genes. We did not identify any gene with consistent differential tially methylated in GBM patient biopsies and cell lines (Table 1). methylation between these groups. However, we further studied This epigenetic difference between GBM patients and cell lines is the clinical impact of 18 genes that had a mean beta value differalso reflected in the cluster analysis presented in Figure 1. ence between these groups above 0.2. Although none of these Genes hypermethylated in GBM are frequent targets of genes was significantly associated with OS, three of them showed a the Polycomb repressive complex in embryonic stem cells. In trend towards shorter OS: hypomethylation of EMR3 (p = 0.07), order to obtain insights into the mechanisms underlying DNA and hypermethylation of HLA-F (p = 0.08) and TES (p = 0.09). methylation in GBM, we investigated whether genes showing In addition to single genes, we also studied whether patients differential DNA methylation were repressed by Polycomb repres- with different levels of DNA hypermethylation (Fig. 4B) or groups sive complex 2 (PRC2) in embryonic stem cells (ESCs).20 As of patients with similar methylation profiles (i.e., the five groups shown in Figure 4A, 41% of the hypermethylated genes in GBM of cases identified by the hierarchical cluster analysis shown in Fig. 1) are PRC2 targets in ESCs. Compared with the 21% of PRC2 were associated with OS. The levels of aberrant hypermethylatargets in all the genes included in the array, such enrichment was tion were not associated with clinical outcome (p = 0.64, Fig. 5B). statistically significant (Fisher’s exact test, p < 0.001). With regard However, we identified a significant association between OS and to genes unmethylated in both GBM and NB, 22% of them were different DNA methylation clusters (p = 0.03, Fig. 5C). The PRC2 targets. Of the genes hypomethylated in GBM and methy- association was mostly caused by the different clinical outcome lated in both GBM and NB, only 9 and 7% were PRC2 targets of patients from clusters 2 and 5 (p < 0.001). We then identified in ESCs, respectively. 18 genes (25 CpGs) with differential aberrant DNA methylation www.landesbioscience.com

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Figure 2. Heatmap displaying the different groups of genes according to their DNA methylation profile in NB and GBM.

between clusters 2 and 5, of which only the methylation status of two CpGs located in the promoter region of GATA6 was significantly associated with OS (p < 0.05) in the present series of GBMs (Fig. 5D).

Table 1 Number of genes present in each of the different groups identified by methylation profiling of GBM patients and normal brain

Discussion

Methylation GBM group patients

GBM Shared cell genes* lines

HyperM

189

173

In this paper we have reported a genome-wide DNA methylation analysis carried out to identify genes differentially methylated in a large series of glioblastomas and to establish their clinical and biological significance in this lethal disease. An unsupervised cluster analysis showed that the methylome of GBM patients is rather heterogeneous (Fig. 1). Interestingly, it also revealed clear epigenetic differences between primary GBM biopsies and two immortalized GBM cell lines (Table 1, Fig. 1). Given that extensive in vitro passaging may have epigenetic consequences, cell lines might not be representative of primary biopsies, which are the preferred material for study. Supervised analyses identified 189 and 94 genes that were hyper- or hypomethylated in at least one GBM patient, respectively. Of these, only seven genes were epigenetically deregulated in more than 50% of the cases studied: hypermethylation of FZD9, TNFRSF10A, MEST, TES, PRKCDBP, CD81 and HOXA11. 258

HypoM

Only in patients**

Only in cell lines***

122

67

51

94

107

64

30

43

UM

406

424

369

37

55

M

153

132

108

45

24

M: methylated, UM: unmethylated, *genes with a similar methylation pattern in GBM patients and cell lines, **genes present exclusively in patients, ***genes present exclusively in cell lines.

To our knowledge, of these seven genes, only TNFRSF10A and TES have previously been described as being hypermethylated in GBM. The gene most frequently hypermethylated gene in our GBM series was FZD9, which was involved in 80% of cases. This gene is one of the Frizzled (FZD) family receptors that transduces canonical WNT signals to the β-catenin signaling

Epigenetics



Figure 3. Bar-chart showing that most GBMs studied showed hypermethylation (A) or hypomethylation (B) of a small number of genes, and that a few cases were characterized by a large number of differentially methylated genes.

cascade for cell-fate determination and noncanonical WNT signals to the DVL-dependent (Rho family GTPases and JNK) or the Ca2+-dependent (NLK and NFAT) signaling cascades for control of cell movement and tissue polarity (reviewed in ref. 21). Hypermethylation of FZD9 was reported recently in more than 70% of patients with acute myeloid leukemia and was significantly associated with a decreased 12-month survival rate.22 Further WNT signaling cascade-related genes observed to be epigenetically silenced in human cancer include SFRP1, SFRP2, DKK1, WIF1 and AXIN2.23,24 TNFRSF10A (tumor necrosis factor receptor superfamily member 10a, also known as death receptor 4, DR4) is a receptor activated by tumor necrosis factor-related apoptosis inducing ligand TNFSF10 (also known as TRAIL), which transduces cell death signal, induces cell apoptosis and is a potential target for development of agonistic TRAIL-like chemotherapeutics. Its inactivation has been previously reported in osteosarcomas,25 gastric carcinomas26 and also in GBM.19 The observed epigenetic silencing of CASP8 might lead to inactivation of the Fas-apoptotic pathway, which favors the survival of remaining tumor cells after radio- and chemotherapy, through extension of the time required for cellular dismantling. MEST (mesoderm-specific transcript homolog) promoter was hypermethylated in 67% of primary GBM biopsies. MEST, which is an imprinted gene, is an endogenous TIF1 primary-target gene in embryonal carcinoma F9 cells.27 MEST and nine other imprinted genes were observed to be aberrantly methylated in human osteosarcoma,28 suggesting that changes in expression of imprinted genes caused by changes in methylation status might be involved in tumorigenesis. Hypermethylation of TES in GBM has been previously identified by pharmacological inhibition of DNA methylation coupled with gene expression microarray analysis.29 In the present analysis we have shown that hypermethylation of TES promoter is a frequent epigenetic change in GBM, where it is involved in 60% of cases. Inactivation of TES through promoter hypermethylation is also a frequent finding in cancer cell lines.30 www.landesbioscience.com

Promoter hypermethylation of PRKCDBP (protein kinase C, delta binding protein, also known as hSRBC) was observed as well. Stable expression of the tumor suppressor gene hSRBC leads to G1 cell cycle arrest and apoptosis of tumor cells, and suppresses colony forming ability and xenograft tumor growth. In addition, hSRBC elevates apoptotic sensitivity of tumor cells to genotoxic agents, such as 5-FU, etoposide and ultraviolet radiation. Moreover, hSRBC has been observed to increase the protein stability of p53 and expression of p53 target genes. hSRBC was initially isolated in a two-hybrid screen for protein interacting with the product of the breast cancer susceptibility gene BRCA1, which suggests that hSRBC may participate in DNA damage response including DNA repair processes.31 Identification of hSRBC as a BRCA1-interacting protein also raises the possibility that epigenetic inactivation of hSRBC may compromise BRCA1-mediated tumor-suppression functions. Hypermethylation-induced lack of expression of hSRBC was previously reported in gastric,31 breast and ovarian cancer.32 The CD81 antigen gene showed promoter hypermethylation in 54% of the GBM samples investigated. This gene is a member of the membranal-embedded tetraspanin superfamily (a group of cell-surface proteins expressed in humans as well as primitive organisms in a wide variety of tissues and cells) and was observed also to be hypermethylated in multiple myeloma.33 Tetraspanins associate with integrins and signaling proteins modulate fundamental biological functions, such as signal transduction cascades, cell migration and apoptosis, which supports the role of CD81 as a tumor metastasis suppressor.34 We detected promoter hypermethylation of HOXA11 in 51% of the analyzed GBM specimens. Hypermethylation of this gene has previously been found in ovarian cancer and its significance as a poor prognosis parameter has also been noted.35 It has been proposed that homeobox genes are unlikely to act as classic oncogenes or tumor suppressors, and are modulators rather than the driving force of tumorigenesis. There are homeobox genes whose expression during development is restricted to undifferentiated precursors of developing tissues while their expression is reactivated in neoplasias of these tissues (such as Oct-4). The second category

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of homeobox genes, in which we tend to include HOXA11 in GBM, include those normally expressed in differentiated adult tissues, but which are then downregulated in cancer (including Nkx3.1 in the prostate and Cdx2 in the colon).36 An interesting issue raised by our investigation is that a significant fraction of the genes hypermethylated in GBM (41%) was already repressed by the PRC2 in ESCs, which might link GBM pathogenesis to stem cells. Cancer heterogeneity and shared features of normal stem cells and cancer cells have recently given rise to the concept of cancer stem cells.37 Stems cells rely on Polycomb group (PcG) proteins to reversibly repress genes encoding transcription factors required for differentiation.38 It was previously suggested that acquisition of promoter DNA methylation at these repressed genes could lock in stem cell phenotypes and initiate abnormal clonal expansion.39 Our findings are in line with previous reports in other solid tumors10-12 and lymphomas,9 and therefore, it seems that hypermethylation in cancer is frequently mediated by the PRC2. Concerning GBM, a striking question is whether GBM derives from cells with stem cell-like features that bear the functional characteristics expected of stem cells, including the capacity for tumor generation, as previously suggested,40,41 or if differentiated cells undergoing malignant transformation acquire this stem cell chromatin structure in the process of dedifferentiation.42 Alternatively, it might also be the case that genes hypermethylated in GBM are also marked by PRC2 proteins in normal brain cells, although genome-wide analyses of PRC2 binding sites in nonmalignant human brain biopsies are not currently available to validate this hypothesis. In any case, it is clear that genes targeted by PRC2 are prone to acquiring de novo DNA methylation during the development of GBM. Furthermore, as shown in Figure 4B, our results indicate that the proportion of PRC2 target genes is not higher in frequently hypermethylated genes than in those hypermethylated in only a few GBMs. Gene ontology analyses indicated that the group of hypermethylated genes was enriched for proteins involved in functions of the central nervous system (Table 4). This suggests that neoplastic transformation in GBM is associated with silencing of genes important for normal CNS processes. The group of hypomethylated genes was enriched for gene ontology terms associated with the immune system. Patients with GBM are known to exhibit broad suppression of cell-mediated immunity.43 Whether this phenomenon is associated with the presence of promoter hypomethylation of genes involved in the immune system is currently unknown, but warrants further research. One of the major goals of our investigation was to identify genes whose aberrant methylation could be of prognostic significance in GBM. Thus, we were able to confirm the well accepted data regarding methylation of MGMT and improved survival in GBM patients who had undergone alkylating chemotherapy with temozolomide (Fig. 5A). We were also able to identify genes showing a trend towards shorter OS: hypomethylation of EMR3 (EGF-like module-containing, mucin-like hormone receptor 3), and hypermethylation of HLA-F (major histocompatibility complex, class I, F) and TES. 260

Table 2 List of genes hypermethylated in more than 20% of the GBMs studied FZD9

Gene

Percentage*

frizzled homolog 9

80

TNFRSF10A 8p21

tumor necrosis factor receptor superfamily, member 10a

68

MEST 7q32

mesoderm-specific transcript homolog

67

testis-derived transcript

60

protein kinase c, delta binding protein

55

11p15.5

CD81 antigen

54

7p15

homeobox a11

51

tumor necrosis factor receptor superfamily, member 10d

46

7p15-p14

homeobox a9

44

7p15

aryl hydrocarbon receptor

39

5-hydroxytryptamine (serotonin) receptor 1b

34

TES

7q11.23

7q31.2

PRKCDBP 11p15.4 CD81 HOXA11

TNFRSF10D 8p21 HOXA9 AHR

HTR1B 6q13 FLT3

13q12

IRAK3 12q14.3 PENK

8q23-24

TAL1 1p32

fms-related tyrosine kinase 3

31

interleukin-1 receptor-associated kinase 3

31

proenkephalin

31

t-cell acute lymphocytic leukemia 1

31

GATA6

18q11.1-2

gata binding protein 6

30

TFAP2C

20q13.2

transcription factor ap-2 gamma

28

HOXA5

7p15-p14.2

homeobox a5

26

insulin-like growth factor binding protein 1

26

NEFL 8p21

neurofilament, light polypeptide 68 kda

24

MOS 8q11

v-mos moloney murine sarcoma viral oncogene homolog

23

20q11-q12

hemopoietic cell kinase

21

1q42

mixed-lineage kinase 4

21

ZNF215

11p15

zinc finger protein 215

21

DSC2

18q12

desmocollin 2

20

IGFBP1 7p14-p12

HCK KIAA1804

The complete list of hypermethylated genes is shown in the Suppl. material. *Percentage of GBM patients showing hypermethylation.

Univariate analyses of methylation clusters (Fig. 1) and patient survival revealed a significant association between aberrant hypermethylation and clinical outcome (p = 0.03, Fig. 5C). We then established that this association was mostly caused by the methylation status of two CpGs located in the promoter region of GATA6 (GATA binding protein 6) (p < 0.05, Fig. 5D). GATA factors constitute a family of transcriptional regulatory proteins expressed with tissue-specific profiles and are thought to regulate cell-restricted programs of gene expression.44 GATA6 is one of six members of the mammalian GATA family of transcription factors, all containing two highly conserved zinc finger DNA binding domains that interact with a canonical DNA motif, and is present

Epigenetics



Table 3 List of genes hypomethylated in more than 20% of the investigated GBM

Gene

S100A2

1q21

s100 calcium binding protein a2

33

MMP9

20q11-q13

matrix metallopeptidase 9

29

CCL3

17q12

chemokine (c-c motif) ligand 3

26

tumor necrosis factor superfamily, member 10

25

interleukin 8

24

TNFSF10 3q26 IL8

4q12-q13

Percentage

PSCA

8q24

prostate stem cell antigene

21

PRSS1

7q35

protease, serine, 1 (trypsin 1)

20

(The complete list of hypomethylated genes is shown in the Suppl. material).

in a variety of adult murine and human cells of the nervous system, including the choroid plexus epithelium, neurons, astrocytes and endothelial cells.45 Recently, GATA6 was isolated from a murine astrocytoma model, and was found to have features of a novel tumor suppressor gene that is a direct target of mutations during malignant progression of murine and human astrocytomas. Inactivation of GATA6 through mutation and simultaneous LOH at GATA6 locus were found in human malignant astrocytoma specimens but not in lower-grade astrocytomas or normal adult astrocytes.46 In the former study, 22 GBM samples were investigated through RT-PCR and immunohistochemistry and loss of expression of GATA6 was observed in 90% of the cases. GATA4 and GATA5, but not GATA6, were observed to be hypermethylated in lung cancer cell lines and primary lung cancers.47 Identical findings were reported in ovarian primary cancer and cell lines by Wakana et al.48 Later on, Caslini et al.49 observed silencing of GATA4 and GATA6 genes in ovarian carcinomas through hypoacetylation of histones H3 and H4 and loss of histone H3/lysine K4 trimethylation at their promoters. In our panel of GBM we observed for the first time hypermethylation of the GATA6 promoter in 30% of the cases. Taking into account that losses of chromosome 18q (as assessed by FISH, CGH and high-resolution CGH) is one of the frequently reported imbalances in GBM,50,51 further hypermethylation of GATA6 would lead to gene inactivation. Our results strongly suggest that GATA6 might also be a tumor suppressor gene in GBM and that hypermethylated GATA6 is significantly associated with patient outcome.

Patients and Methods

Figure 4. (A) Bar-chart of the different DNA methylation subsets showing the percentage of genes containing and lacking PcG marks in ESCs. This analysis shows that the hypermethylated group of genes is highly enriched for PcG target genes in ESCs. (B) Heatmap of hypermethylated CpGs arranged according to their methylation frequency in GBM patients, from cases with low levels of aberrant hypermethylation on the left to cases with large numbers of hypermethylated genes on the right. The bar on the right indicates whether a gene is a target of PRC2 in ESCs (black) or not (white). Grey indicates that the PRC2 status in ESCs is unknown.

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Patient samples and controls. All patients had undergone surgery with the goal of maximal possible tumor resection followed by fractionated radiotherapy and standard chemotherapy including alkylating drugs (temozolomide, ACNU, BCNU). Tumor samples from 87 GBM patients who had undergone surgery between 1995 and 2006 were frozen in liquid nitrogen and stored at -80°C. Tumor tissue was evaluated by experienced pathologists according to the 2000 WHO classification criteria. DNA from tumor specimens was isolated applying the QIAamp® DNA Mini Kit (Qiagen, Hilden, Germany). Informed consent for samples and data analysis was obtained from each patient or the patient’s carer. Survival times were collected for all cases and were calculated from the time of diagnosis to death, or last contact in the case of living patients. A normal human adult brain tissue sample was included in the study as a normal control. Two GBM cell lines (U87 and T98G) were also studied. DNA methylation profiling using universal beadarrays. Microarray-based DNA methylation profiling was performed with the GoldenGate Methylation Cancer Panel I (Illumina, Inc.,) on a total of 87 GBM patient biopsies, two GBM cell lines and one normal brain as control. The panel was developed to assay 1,505 CpG sites selected from 807 genes, including oncogenes and tumor suppressor genes, previously reported differentially methylated or differentially expressed genes, imprinted genes, genes involved in various signaling pathways and those responsible for

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DNA repair, cell cycle control, metastasis, cell migration and invasion, differentiation and apoptosis. Methylation assay was performed as described previously.52 Briefly, for each CpG site, four probes were designed: two allelespecific oligos (ASOs) and two locus-specific oligos (LSOs). Each ASO-LSO oligo pair corresponded to either the methylated or unmethylated state of the CpG site. Bisulfite conversion of DNA samples was done using the EZ DNA methylation kit (Zymo Research, Orange, CA). After bisulfite treatment, the remaining assay steps were identical to those of the GoldenGate genotyping assay53 using Illumina-supplied reagents and conditions. The array was hybridized under a temperature gradient program, and arrays were imaged using a BeadArray Reader (Illumina Inc.,). Image processing and intensity data extraction software were used as described previously.54,55 Each methylation data point is represented by fluorescent signals from the M (methylated) and U (unmethylated) alleles. Background intensity computed from a set of negative controls was subtracted from each analytical data point. The ratio of fluorescent signals was then computed from the two alleles according to the following formula: β = [Max(M,0)]/[Max(U,0) + Max(M,0) + 100] The beta value is a quantitative measure of DNA methylation levels of specific CpGs, and ranges from 0 (completely unmethylated) to 1 (completely methylated). Before analyzing data, we excluded possible sources of biological and technical biases that could have affected the results. As one copy of chromosome X is methylated in women, we excluded all 84 CpGs on chromosome X to avoid a gender-specific bias. Additionally, we evaluated the detection probabilities (comparing signal intensities against background noise) for all CpGs and excluded those CpGs with values of p > 0.01 in more than 10% of cases. After excluding 84 gender-specific CpGs and 35 low-quality CpGs (31 in autosomes and four in chromosome X), 1,390 CpGs from 762 genes were used in the subsequent statistical analyses. Hierarchical cluster analysis and definition of DNA methylation groups. Hierarchical clustering was performed on all 87 cases and one control using the Cluster Analysis tool of the BeadStudio software (version 3.2). Only the 1,390 autosomal CpGs that met our quality criteria were used in this analysis. As only one normal brain was available as a control sample we used strict criteria to define hyper- and hypomethylated genes. A gene was classified as hypermethylated when at least one CpG had a value of beta less than 0.25 in NB and greater than 0.75 in at least one GBM. Conversely, hypomethylated genes were defined as those in which at least one CpG had a value of beta greater than 0.75 in NB and less than 0.25 in at least one GBM. CpGs were classified as unmethylated or methylated in both NB and GBM when all these samples showed beta values below 0.25 and above 0.75, respectively. CpGs that could not be assigned to any of these groups, i.e., CpGs with values between 0.25 and 0.75 (partially methylated) in NB, were grouped as unclassifiable. As some CpGs might have consistently elevated levels of DNA methylation in GBM (but less than 0.75) but be unmethylated in NB, an additional criterion was used, i.e., CpGs with a difference between mean beta values in GBM and NB of more than 0.3 were also 262

Table 4 Gene ontology terms significantly enriched (p < 0.05) in the subset of genes hyper- or hypomethylated in GBM Biological process Hypermethylated genes

GO term

p*

Neurological system process

GO:0050877

0.020

Transmission of nerve impulse

GO:0019226

0.021

Synaptic transmission

GO:0007268

0.033

Generation of neurons

GO:0048699

0.039

Sperm motility

GO:0030317

0.042

Defense response

GO:0006952

0.001

Immune response

GO:0006955

0.001

Immune system process

GO:0002376

0.001

Immune effector process

GO:0002252

0.006

Innate immune response

GO:0045087

0.009

Secretion

GO:0046903

0.011

Regulation of multicellular organismal process

GO:0051239

0.014

Inflammatory response

GO:0006954

0.016

Leukocyte mediated immunity

GO:0002443

0.024

Cell activation

GO:0001775

0.039

Phagocytosis

GO:0006909

0.039

Mammary gland development

GO:0030879

0.040

Leukocyte activation

GO:0045321

0.041

Negative regulation of protein metabolic process

GO:0051248

0.044

Localization

GO:0051179

0.046

Hypomethylated genes

*Modified Fisher’s exact p value (EASE score).

considered hypermethylated. A second, similar criterion was also used for hypomethylated genes, i.e., CpGs methylated in NB with a difference in mean beta values between GBM and NB of more than 0.3. Enrichment for PRC2 marks in differentially methylated genes. Proportions of PRC2 target genes in genes differentially methylated in GBM and all genes included in the Illumina BeadArray were compared using Fisher’s exact test. A genome-wide map of PCR2 genes in embryonic stem cells was obtained from Lee and coworkers.20 Gene ontology analysis of differentially methylated genes. The “Database for Annotation, Visualization and Integrated Discovery” (DAVID, http://david.abcc.ncifcrf.gov/home.jsp) was used to determine the enrichment of individual ontology terms in the group of genes differentially methylated in GBM and NB. Lists of genes that are hyper- or hypomethylated in GBM were compared with the 762 genes included in the statistical analyses using a modified Fisher’s exact test. Statistical analysis. Mann-Whitney U-test, Student t-test, the Chi-square contingency test (with Mehta-Patel and Fisher-Yates corrections as appropriate) and Fisher’s exact test were performed to compare differences between groups, depending on the data

Epigenetics



Figure 5. Kaplan-Meier analyses showing that: (A) MGMT hypermethylation is associated with a favorable outcome in patients treated with the alkylating drug temozolomide, (B) the degree of DNA hypermethylation in patients with GBM is not associated with overall survival, (C) there is a significant association between different DNA methylation profiles in patients with GBM and clinical outcome, and (D) the overall survival of patients with GATA6 hypermethylation is significantly poorer than those lacking GATA6 hypermethylation.

types of the variables being examined. Spearman correlation test was used to assess the correlation between parameter pairs. 95% confidence intervals (CIs) were those associated with the parameter estimates obtained from logistic regression. Kendall’s rank correlation test and sign test were performed to evaluate differences of methylation status of given genes. Kaplan-Meier analysis and logrank tests were used to compare OS between the groups defined by DNA methylation profiling. A value of p < 0.05 was considered to be significant. Analyses were performed with SPSS (version 11.5, SPSS Inc., Chicago, IL, USA). Acknowledgements

Supported by the Health (FIS PI08 1345) and Education and Science (I + D + I MCYT08-03 and Consolider MEC09-05) Departments of the Spanish Government, the Health Department of the Catalan Government, the Spanish Association Against Cancer (AECC) and the Seventh Framework Programme of the European Union-CANCERDIP. M.E. is an ICREA (Institucio Catalana de Recerca i Estudis Avançats) Research Professor. Note

Supplementary materials can be found at: www.landesbioscience.com/supplement/ MartinezEPI4-4-Sup.pdf www.landesbioscience.com

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