SUPPLEMENTARY RESULTS

Hypomethylated promoters are neither mutated nor deleted in HCC samples

To rule out the possibility that the demethylation observed in gene promoters in our pyrosequencing assays (conversion of a C to T following bisulfite conversion) indicates a mutation of C to T rather than demethylation, we sequenced the unconverted DNA of

AKR1B10, CENPH, MMP2, MMP9, MMP12, NUPR1, PAGE4, PLAU, and S100A5 promoter regions using the pyrosequencing SNP assay (Supplementary Fig. S2). We show that in all cases the fraction of cytosines in the unconverted sequence is similar in normal liver and in HCC.

Therefore, the increase in the fraction of cytosines that were converted to thymidine in the tumor samples occurred only after bisulfite treatment and it was not due to mutations of Cs to

Ts. Loss of signal for methylated DNA in hypomethylated promoters in HCC did not result from loss of DNA by deletions since our method internally controls for loss of DNA. Our

MeDIP arrays are hybridized with both DNA immunoprecipitated with anti-5-methylcytosine antibody as well as total DNA. Thus, our assays measure both DNA methylation and DNA integrity. The DNA methylation signal reflects the ratio of signal for methylated DNA immunoprecipitation with the anti-5-methylcytosine antibody over total DNA in the sample at the indicated genome position. Loss of DNA by deletion would have increased the ratio of methylated DNA to total DNA to infinity and would have presented itself as hypermethylation rather than hypomethylation. Careful examination of the promoters that were demethylated in

HCC provides evidence for the absence of deletions/amplifications in the genes that are hypomethylated in HCC patients. We quantile-normalized the background channel across all inputs and computed a per-probe differential statistic between cancer and normal using a t-test.

The wilcoxon rank-sum test was used to identify enrichment of unusually high or low probe

1 differential statistics inside each demethylated promoter. The p-values from the rank-sum test were adjusted for multiple testing using the false discovery rate. Among 3,708 hypomethylated promoters, only 19 promoters corresponding to 12 genes (Supplementary Table S4) had a false discovery rate less than 0.05 indicating that the region may have been deleted/amplified. They have been excluded from the list of genes hypomethylated in HCC.

Pathways controlled by epigenetically induced genes

Functional analysis reveals that the epigenetically induced genes are enriched in pathways known to drive cellular transformation, cancer growth, angiogenesis and cancer metastasis

(Supplementary Fig. S3A). Example pathways include the prometastatic TGF-beta signaling (1), the potent angiogenic and prometastatic VEGF signaling (2-3), the JAK-STAT signal transduction pathway that mediates cytokine triggered signals such as IL6 which plays an important role in cancer growth and metastasis (4), and participates in cross talk with the mitogenic and oncogenic RAS-MAPK and TGF-beta signal transduction pathways (5), the

WNT signaling cascade that plays an important role in several cancers including colorectal, breast and prostate cancer and is upregulated in cancer metastasis (6-8), and finally the

HEDGEHOG signaling cascade that was reported to be aberrantly reactivated in liver cancer and its blocking resulted in a decrease in cancer cell viability (9). Activation of both Jak-STAT and Ras/MAPK were previously shown to be enhanced in HCC samples, and their inhibition led to a strong apoptotic response (10). Enrichment of epigenetically induced genes in the gycolysis/gluconeogenesis pathway is consistent with the remarkable propensity of highly malignant, poorly differentiated tumors, including hepatomas, to utilize glucose at a much higher rate than normal cells (11).

2 In general, the epigenetically induced genes are enriched in biological processes that are known to be critical for tumor progression, survival and motility, differentiation, transcription regulation and signal transduction (Table 2). Many of the epigenetically induced genes in these critical processes are known to play a role in cancer while at least 20 of these genes, to our knowledge, play unknown roles (Table 2A and B). These 20 genes are enriched in biological processes such as histone binding, positively regulating MAPK pathway, methyltransferase activity and involvement in base-excision repair, suggesting that these new candidates play a role in liver cancer and are regulated by epigenetic mechanisms. The roles of several of these genes, CCDC138, KCTD2, PAQR4 and RNMT, are poorly established. Other genes such as

CSPP1, FAM83D, EXOSC4 and NEIL3 have previously been linked to breast, colorectal cancer, renal carcinoma and glioblastoma through mutation and expression analyses (12-13).

Overall our analyses support the hypothesis that hypermethylation and hypomethylation target distinct cell functions involved in resetting the cellular gene expression program from that of a normal untransformed state to that of a highly transformed and invasive cancer. Promoter hypermethylation inhibits genes that block cellular growth and metastasis whereas hypomethylation drives promitogenic, metabolic and prometastatic processes.

5-aza-2’-deoxycytidine (5-azaCdR) induces “HCC demethylated genes” in human untransformed hepatocyte cell culture (NorHep)

In order to determine causal relationship between promoter hypomethylation and activation of genes epigenetically induced in HCC we determined whether the DNA methylation inhibitor 5- aza-2’-deoxycytidine (5-azaCdR) would induce these genes in a primary hepatocyte (NorHep) cell culture. To experimentally test causality between DNA methylation and expression we had

3 to resort to cell culture experiments. Since we used HepG2 hepatocellular carcinoma cell line as a model of transformed liver cells and NorHep cells as a model of normal liver cells we focused on genes that were hypomethylated (expressed) in HepG2 cells and hypermethylated (silent) in

NorHep cells. We then tested whether these genes would be induced in NorHep cells following treatment with the DNA demethylating agent 5-azaCdR. Most of the studied genes were also hypomethylated in HCC patients.

We examined by QPCR the expression of 84 genes following 5-azaCdR treatment of NorHep including 65 with high CpG-dense promoters (HCP). As shown in Fig. 2E, the most profound increase in gene expression among all promoters hypomethylated in HCC patients is observed for genes with HCP promoters where average expression differences are > 0. We therefore focused on this gene set for this analysis. Moreover, 38 out of these 84 genes belonged to the genes epigenetically induced in HCC patients that showed the most profound hypomethylation and/or induction and included genes known to be involved in cancer (e.g., CENPH, CKS2,

IPO7, MAP3K4, MAPRE1, PPARG, PRPF6, RELB, SERF2) as well as new cancer gene candidates (e.g., CSPP1, RASAL2, SENP6, RNMT, TMX2, NEIL3, NENF) as shown in Table

2. Since the experiment was performed in a primary hepatocyte (NorHep) cell culture we also tested a group of 46 genes in addition to 12 genes from the 38 genes described above that are hypomethylated in HepG2 cells compared to NorHep cells and represent families important in cancer such as members of WNT signaling pathway (WNT16), semaphorins (SEMA4C), S100 calcium binding proteins (S100A5), ubiquitin-conjugating enzymes (UBE2E1/2), ephrin receptors (EPHA3/B1), transcription factors (E2F2), growth factors (EGF, FGF). 24 out of these

46 genes are also significantly hypomethylated in HCC patients.

4 71 out of the 84 examined genes were induced upon treatment with 5-azaCdR at 1.0 µM concentration for either 5 or 20 days (Supplementary Table S6). The highest increase was observed for FGF20, BMP4, CABYR, CCL20, WNT16, MMP2, PLAU, and S100A5 (4-50 fold,

Supplementary Fig. S4B and Supplementary Table S6). As expected 5-azaCdR in NorHep cells led to global hypomethylation (Supplementary Fig. S4A) and a decrease in promoter methylation of MMP2, NUPR1, PLAU, and S100A5 genes (Supplementary Fig. S4C).

Using microarray data, we also compared fold change in expression with the extent of hypomethylation for 230 genes epigenetically induced in HCC patients. For each gene, we compared differential gene expression to differential promoter methylation between cancer and normal tissue across all patients. If promoter hypomethylation does have impact on the increase in gene expression, then we expect the gene expression differences to be negatively correlated with the promoter methylation differences. For both differential expression and differential methylation, we used the log-fold change of the microarray probe that the most significantly differentiated between cancer and normal for the given gene. We then calculated Pearson's correlation coefficient between our measures of differential expression and differential methylation. As expected, we found that the resulting correlation coefficients from the 230 genes were on average less than zero (Wilcoxon rank-sum test, P ≤ 0.005) (see Supplementary

Fig. S4D for a scatter plot).

Details on genes demethylated in liver, ovarian and breast cancers

Several of the genes that are demethylated in liver, ovarian and breast cancers have been implicated in cancer progression and metastasis. Examples include regulators of tight junction and cell-cell adhesion (CLAUDIN 4, CLDN4) (14), modulators of transmembrane signaling

5 systems (GUANINE NUCLEOTIDE-BINDING PROTEIN G(S) SUBUNIT ALPHA, GNAS) (15) and regulators of transcription (MICROPHTHALMIA-ASSOCIATED TRANSCRIPTION

FACTOR, MITF; METHYL-CPG BINDING DOMAIN PROTEIN 1, MBD1) (16-17). For others, their potential roles in cancer have not yet been elucidated, including TUFTELIN (TUFT1), implicated in the mineralization and structural organization of enamel, and CHROMOSOME 1

OPEN READING FRAME 124 (C2orf124), shown to be involved in DNA repair (Fig. 3B).

Although we identified only 42 such genes, these genes were enriched in several functions and pathways important to cancer including HEDGEHOG, WNT, GnRH and G-protein coupled receptor protein signaling pathways, cell adhesion, Gap and tight junction, cell-cell signaling, regulation of transcription, cell cycle and cell differentiation. The MAGE family has consistently been found activated and their promoters hypomethylated in cancer and testis. Interestingly, although the promoter of at least one member of the MAGE family is hypomethylated in each cancer type, there is not a specific member of the family that is commonly hypomethylated in the three cancers. The same was observed for other well-characterized gene families such as

SMALL NUCLEOLAR RNA H/ACA BOX A (SNORA) and KIAA PROTEINS. Thus, although the identity of a specific member of a gene family is cell type specific, the involvement of the gene family is common to several cancers. We suspect that this might be a general rule for other gene families, pathways and processes.

Hypomethylated gene family clusters

Hypomethylation is organized not only at the functional level through demethylation of several members of specific functional gene pathways but also at the structural level by demethylated gene promoter clusters in regions and chromosomes (Fig. 3C). We identified several

6 demethylated gene family clusters that were previously shown to be important in cancer. For example, the demethylated SULFOTRANSFERASE FAMILY, CYTOSOLIC 1A (SULT1A) family on chromosome 16 encodes sulfotransferase enzymes catalyzing the sulfate conjugation of many hormones, neurotransmitters, drugs, and xenobiotic compounds. One member of this family of genes SULT1A1 was shown to be dramatically up-regulated in patients with HCC secondary to chronic hepatitis B virus infection (18). The cadherin family located on chromosome 16 is another family of demethylated genes. Members include genes such as

CDH8, CDH11 and CDH5 that have been shown to be activated in several cancers and may have a role in cell invasiveness and cancer metastasis,CDH8 in renal cell carcinoma (19),

CDH11 in metastasis of prostate cancer cells to bone (20), and CDH5 in tumor angiogenesis by modulation of VEGF receptor functions and increasing cell proliferation via TGF-beta signaling pathway (21). Demethylated promoters of CYTOKINE, KERATIN and SOLUTE CARRIER

(SLC) gene families are clustered on chromosome 17. Cytokine expression has been observed at sites of tumor spread suggesting a role in metastasis (22). CCL2 expression in esophageal squamous cell carcinoma, HCC and prostate cancer cells is associated with macrophage infiltration, tumor cell invasion and tumor vascularity (23-24). A family of keratins on chromosome 17 contains several demethylated promoters including that of KRT20 which is overexpressed in HCC (25). Keratins in general are thought to be involved in cell migration and regulation of proliferation. SLC2A4 from demethylated SLC family cluster on chromosome 17 was shown to be overexpressed in various malignant cancer cell lines and to increase glucose transport activity and proliferation rate (26). On chromosome 19, SIALIC-ACID-BINDING

IMMUNOGLOBULIN-LIKE LECTINS (SIGLEC) and CARCINOEMBRYONIC ANTIGEN-

RELATED CELL ADHESION (CEACAM) families contain several demethylated promoters.

7 Both of these families belong to the immunoglobulin superfamily. SIGLEC3 is expressed on the surface of most acute myeloid leukemia (AML) cells and anti-SIGLEC3 antibody is approved for the treatment of AML (27). Elevated serum level of the CEA tumor marker is a classic colorectal marker (28) and a prognostic factor related to tumor extent in breast cancer (29), while CEACAM6 was shown to be a potential biomarker for pancreatic adenocarcinoma (30).

MAGE and GAGE families on chromosome X contain demethylated promoters and are known to be overexpressed in a wide variety of human cancers and involved in cancer progression (31-

33).

MBD2 overexpression leads to hypomethylation and induction of several genes

To further check whether MBD2 up-regulation affects methylation and expression of the genes affected by MBD2 depletion, we generated NorHep cells stably overexpressing MBD2B using lentiviral infection (Supplementary Fig. S8A, see Supplementary Methods for details). Since

MMP2, NUPR1, PLAU, and S100A5 are expressed at a lower level (see Fig. 5) and are hypermethylated in NorHep compared to HepG2 cells, NorHep cells were a suitable model for examining the effects of MBD2B overexpression. Our results indicate 1.5-2.5 fold decrease in

DNA methylation at certain CpG sites for all the four genes in cells overexpressing MBD2B compared to the cells expressing an empty vector. The reduced methylation is accompanied with an increase in expression of all the genes except NUPR1 (Supplementary Fig. S8).

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10 SUPPLEMENTARY FIGURES

Supplementary Fig. S1. Validation of MeDIP microarray results by pyrosequencing (A) and

Affymetrix expression array results by QPCR (B) for selected genes in cancer and normal samples from 11 HCC patients. The demethylated genes in liver cancer were identified based on methylation microarrays. The probes that demonstrated lower methylation levels in cancer compared to adjacent normal tissue as shown in the array tracks, were chosen for validation by pyrosequencing. The position of each CpG site relative to the transcription start site is depicted in a physical map for each of the genes. All results represent mean ± S.D. of two or three independent experiments; ***P < 0.001, **P < 0.01, *P < 0.05.

Supplementary Fig. S2. Percentage of cytosines at CpG sites in promoter regions of AKR1B10,

CENPH, MMP2, MMP9, MMP12, NUPR1, PAGE4, PLAU, and S100A5 in cancer and matched adjacent normal tissues from HCC patients as determined by pyrosequencing using SNP assay.

Non-bisulfite converted DNA was a template in this experiment. The results indicate that deletions and/or mutations cannot be responsible for promoter hypomethylation of these genes observed in the patients as shown in Figure 5 and Supplementary Fig. S1.

Supplementary Fig. S3. (A,B) Functional pathways controlled by genes epigenetically induced

(A) as well as epigenetically repressed (B) in liver cancer samples from 11 patients. The pathways were obtained from the KEGG database. For genes epigenetically induced, the analysis was conducted using a group of 111 genes with HCP promoters since they show the most profound increase in gene expression.

11 Supplementary Fig. S4. Methylation and expression of MMP2, NUPR1, S100A5, and PLAU in

NorHep treated with 5-azaCdR at 1.0 µM concentration. (A) Global methylation level estimated using luminometric methylation assay (LUMA) in NorHep treated with 5-azaCdR for 5 or 20 days. LUMA assay and treatment with 5-azaCdR were performed as described in the

Supplementary Methods. (B) Fold change in relative gene expression as measured by QPCR in cells treated with 5-azaCdR for 5 days except for NUPR1 where an increase in expression was observed after 20 days of treatment compared to the control cells cultured in the absence of the drug. (C) State of methylation as determined by pyrosequencing in the promoter region of

MMP2, NUPR1, S100A5, and PLAU in NorHep treated with 5-azaCdR for 5 days or 20 days

(NUPR1). Methylation level was estimated in the same CpGs as in the experiment with HepG2 cells after MBD2 depletion. All results represent mean ± S.D. of two or three independent experiments, measured in triplicate ***P < 0.001, **P < 0.01, *P < 0.05. (D) Correlation between the extent of promoter demethylation and gene induction for 230 genes epigenetically induced in HCC patients. Each point in the scatter plot represents a differential methylation and differential expression for every gene in each HCC patient. For both differential methylation and differential expression, we used the log-fold change of the microarray probe that the most significantly differentiated between cancer and normal for the given gene. The correlation is negative with Pearson's correlation coefficient -0.1 (P < 0.0019).

Supplementary Fig. S5. Expression and DNA methylation characteristics in normal liver cells of genes that become hypomethylated in HCC.

The distribution of promoter methylation levels (A) and gene expression (B) in normal liver tissue for genes that are hypomethylated and induced, hypomethylated but not induced, induced

12 but not hypomethylated in HCC in comparison with the distribution of the state of methylation and expression in the entire population of genes in normal liver. * The lists of genes hypomethylated and induced in liver cancer that are highly methylated (categories 6, 7, 8) and lowly expressed (categories 1, 2) in normal liver.

Supplementary Fig. S6. (A) Expression of MBD2 isoforms, A and A/B, in HepG2 and NorHep.

(B) MBD2A expression quantified by QPCR after third transfection (day 9) of HepG2 cancer cells with siCtrl or siMBD2A. (C) Effect on cell growth after first (day 3), second (day 6) and third (day 9) transfection with siCtrl or siMBD2A. (D, E) Effect on anchorage independent growth and cell invasion as measured by soft agar and Boyden chamber invasion assays, respectively, as described in Supplementary Methods after triple transfection with siRNA to

MBD2A. All results represent mean ± S.D. of two or three independent experiments; ***P <

0.001, **P < 0.01, *P < 0.05.

Supplementary Fig. S7. (A,B) Expression of genes that are affected by MBD2 depletion in addition to those shown in Fig. 5 in: (A) HepG2 and SkHep1 cancer cells and NorHep cells; (B)

HepG2 and SkHep1 cells after MBD2 knockdown. All results represent mean ± S.D. of two or three independent experiments; ***P < 0.001, **P < 0.01, *P < 0.05.

Supplementary Fig. S8. Methylation and expression of MMP2, NUPR1, S100A5, and PLAU in

NorHep overexpressing MBD2B. (A) MBD2 expression quantified by QPCR (B) Fold change in relative gene expression as measured by QPCR in cells stably transfected with lentivirus overexpressing MBD2B as described in Supplementary Methods. (C) State of methylation as

13 determined by pyrosequencing in the promoter region of MMP2, NUPR1, S100A5, and PLAU in

NorHep overexpressing MBD2B. Methylation level was estimated in the same CpGs as in the experiment with HepG2 cells after MBD2 depletion. All results represent mean ± S.D. of two or three independent experiments, measured in triplicate ***P < 0.001, **P < 0.01, *P < 0.05.

SUPPLEMENTARY TABLES

Supplementary Table S1. Primer sequences used in expression analysis (QPCR).

Supplementary Table S2. Primer sequences used in mathylation analysis by pyrosequencing.

Supplementary Table S3. Primer sequences used in MBD2 binding analysis (QPCR, ChIP-on- chip validation).

Supplementary Table S4. List of 19 promoters corresponding to 12 genes whose promoter hypomethylation may have been a result of deletion/amplification.

Supplementary Table S5. List of 230 genes epigenetically induced (hypomethylated and overexpressed) as well as 322 genes epigenetically repressed (hypermethylated and suppressed) in HCC compared to matched adjacent normal tissues.

Supplementary Table S6. Fold change in relative expression of 84 genes evaluated by QPCR in NorHep treated with 1.0 µM 5-azaCdR for 5 or 20 days compared to control cells treated in the absence of the drug. Only genes that did not show any changes in expression after 5 day-

14 treatment were subjected to QPCR after 20 days of treatment. Among 84 studied genes, there are 65 genes epigenetically induced in HCC that also bear high CpG-dense promoters since this group of genes shows the most profound increase in expression (Fig. 2E). The other genes included MMP2, NUPR1, PLAU, S100A5 that are studied in the manuscript in detail, as well as genes selected for their high level of promoter hypomethylation.

Supplementary Table S7. List of genes that are heavily methylated in normal liver and become demethylated in HCC.

Supplementary Table S8. List of genes derived from a comparison of demethylated genes between human liver, breast and ovarian cancers.

Supplementary Table S9. List of 83 genes whose expression was examined in HepG2 and

SkHep1 cells after MBD2 knockdown.

Supplementary Table S10. List of genes in the heatmap showing hierarchical clustering between cancer and normal samples in Fig. 1A.

Supplementary Table S11. List of genes in the heatmap shown in Fig. 2A.

Supplementary Table S12. List of genes in the heatmap in Fig. 3A.

15