Snf5 directly represses Ezh2 transcription in mouse embryonic fibroblasts

To determine whether the elevated levels of Ezh2 detected in Snf5-deficient tumors was a primary effect of Snf5 inactivation, we next evaluated PcG expression in mouse embryonic fibroblasts (MEFs) conditional for Snf5. We first utilized whole-genome expression data sets that we generated from Snf5-deficient MEFs compared to control MEFs to evaluate changes in PcG gene expression caused by Snf5 loss (Isakoff et al., 2005). The PcG gene Ezh2 was reproducibly upregulated in all samples following Snf5 depletion (p = 0.004), whereas, the expression of other PcG transcripts, Eed, (p = 0.50), Suz12 (p = 0.76) and Bmi1 (p = 0.15), did not show consistent patterns of upregulation (Figure 1E and Figure S1K–O). Ezh2 protein levels also increased following Snf5 inactivation (Figure 1F). To gain insight into whether the SWI/SNF complex directly regulates EZH2 expression we tested for binding of Snf5 at the genomic locus of Ezh2 in MEFs. Using chromatin immunoprecipitation (ChIP) we examined Snf5 and RNA Polymerase II occupancy at Ezh2 compared to three negative control locations and observed enrichment of Snf5 at the Ezh2 gene, but not at control genes (Figure S1P,Q).

Ezh2 drives epigenetic silencing of p16^INK4a following SNF5 loss

Downregulation of the p16^INK4a tumor suppressor occurs following inactivation of SNF5 and may contribute to oncogenesis (Isakoff et al., 2005; Oruetxebarria et al., 2004). p16^INK4a has also been shown to be a target of EZH2 and to be repressed by PcG mediated silencing (Kia et al., 2008; Kotake et al., 2007; Shen et al., 2008). Further, re-expression of SNF5 in human MRT cell lines leads to accumulation of SWI/SNF at the p16^INK4a promoter and is associated with loss of PcG proteins (Kia et al., 2008). Therefore, we sought to utilize p16^INK4a as a model target to investigate the functional relationship between EZH2 and SNF5 in primary cells. We crossed Snf5-conditional mice to Ezh2-conditional mice and isolated MEFs of 3 genotypes: Snf5-conditional, Ezh2-conditional and Snf5-Ezh2 doubly conditional. We evaluated p16^INK4a expression after inactivation of Ezh2 or Snf5 or both. Consistent with previous reports, Snf5 inactivation alone resulted in silencing of p16^INK4a (Isakoff et al., 2005). In contrast, inactivation of Ezh2 led to upregulation of p16^INK4a (Figure 2A). Finally, inactivation of Ezh2 abrogated the downregulation effect of Snf5 loss upon p16^INK4a expression and resulted in wild type p16^INK4a levels in double deficient MEFs (Figure 2A). To test whether this antagonism was reversible, three days after inactivation of Snf5 and Ezh2, we re-introduced Snf5 and found that p16^INK4a expression was restored to a high level, demonstrating reversibility (Figure S2). Since Ezh2 is thought to mediate epigenetic gene silencing through the addition of tri-methyl groups to lysine 27 of histone H3, we evaluated whether this histone modification was elevated at the p16^INK4a locus after Snf5 inactivation. Using chromatin immunoprecipitation (ChIP), we quantified the relative levels of H3K27 tri-methylation at the p16^INK4a locus after Snf5 inactivation in MEFs. Snf5 inactivation led to elevated levels of H3K27 trimethylation at the p16^INK4a gene, consistent with a role for Ezh2 in driving epigenetic gene silencing after Snf5 inactivation (Figure 2B).

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Figure 2

EZH2 and SNF5 have antagonistic roles in the control of expression of the model target p16^INK4a. (A) Immunoblot analysis of p16^INK4a and p19^ARF after inactivation of Snf5 and Ezh2 in MEFs. Actin was used as a loading control. (B) ChIP analysis of H3K27me3 levels at the INK4a/ARF locus after Snf5 inactivation in MEFs. Primers were designed at the p19^ARF and p16^INK4a loci (primers A, B and C), as indicated in the schematic illustration in the bottom panel, and at several negative control regions (Actin promoter (Actin P.) and Actin intron (Actin In.). Data are represented as mean +/− SEM from 3 biological replicates. (C) Immunoblot analysis of p16^INK4a and p14^ARF after EZH2 knockdown in the G401 MRT cell line. Actin was used as a loading control. See also Figure S2.

To evaluate the relevance to human cancers, we next investigated whether EZH2 was essential for maintaining the epigenetic silencing of p16^INK4a in a human SNF5-deficient MRT cell line. Using a shRNA against EZH2 we were able to achieve greater than 90% knockdown of EZH2, as determined at the protein level. Expression of the EZH2 shRNA, but not the non-silencing shRNA, led to increased expression of p16^INK4a (Figure 2C), showing that EZH2 is required for epigenetic silencing of p16^INK4a.

Repression of Polycomb signatures in Snf5-deficient tumors and following Snf5 inactivation in MEFs

The findings at the p16^INK4a locus were supportive of epigenetic antagonism between SNF5 and EZH2. However, downregulation of p16^INK4a is unlikely to be the full mechanism by which SNF5 loss drives cancer formation as tumor onset occurs much more quickly, with higher penetrance, and in different a spectrum following Snf5 inactivation than p16^INK4a inactivation (Krimpenfort et al., 2001; Sharpless et al., 2001). Also, humans with biallelic p16^INK4a mutations are not predisposed to develop MRT (Kim and Sharpless, 2006; Roberts and Biegel, 2009). Lastly, both SWI/SNF and PcG bind the genome at many loci rather than just at p16^INK4a. Consequently, we sought to determine whether the epigenetic antagonism between SNF5 and EZH2 was more broad. We began with an analysis of the expression levels of PcG targets using Gene Set Enrichment Analysis (GSEA). PcG targets vary substantially by lineage, and as the cell of origin of MRTs is unknown but the tumors are poorly differentiated, we chose to utilize a gene set of PcG targets that had been defined in embryonic stem cells (Ben-Porath et al., 2008). We found that these PRC2 targets were downregulated in MRTs compared to normal brain (Figure 3A; p < 0.001). Consistent with this, a gene set consisting of H3K27me3 modified targets defined from embryonic stem cells (Ben-Porath et al., 2008; Lee et al., 2006) was similarly negatively enriched in rhabdoid tumors (Figure S3A; p < 0.001). We next used a gene set that we generated by performing ChIP-chip of H3K27me3 from primary murine cerebellum to identify H3K27me3 bound targets that were expressed to some degree to determine whether this gene set was downregulated in SNF5-deficient rhabdoid tumors. These genes were even more strongly downregulated in MRTs (Figure 3B; p < 0.001).

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Figure 3

SNF5 loss leads to broad repression of PcG targets and activation of stem cell-associated programs. GSEA is a method that determines whether a set of genes shows differences between two biological states. The normalized enrichment score (NES) reflects the degree to which a gene set is upregulated (positive NES) or downregulated (negative NES). Corresponding p-values are indicated. (A)GSEA of PRC2 targets from stem cells (Ben-Porath et al., 2008) and (B) H3K27me3 enriched genes from cerebellum in expression data from human MRT samples compared to normal cerebellum. (C) GSEA of T-cell specific Ezh2-regulated genes (Su et al., 2005) in expression data from purified CD8+ Snf5-deficient lymphomas compared to CD8+ T-cells purified from a wild type mouse. (D) GSEA of human-fibroblast specific EZH2-regulated genes (Bracken et al., 2006) and (E) MEF-specific EZH2-regulated genes in expression data from Snf5-deficient MEFs compared to control MEFs. (F) GSEA of MEF-specific EZH2-regulated genes in expression data from Snf5 Ezh2-deficient MEFs compared to control MEFs. (G) GSEA of stem cell associated-program in expression data from human MRT samples compared to normal cerebellum, (H) purified CD8+ Snf5-deficient lymphomas compared to CD8+ T-cells purified from a wild type mouse, (I) Snf5-deficient MEFs compared to control MEFs, (J) human fibroblasts where EZH2 levels have been knocked down compared to control fibroblasts, (K) Ezh2-deficient MEFs compared to control MEFs, and (L) Snf5 Ezh2-deficient MEFs compared to control MEFs. The stem cell-associated expression signatures (Ben-Porath et al., 2008; Wong et al., 2008) and EZH2 knock down expression data (Bracken et al., 2006) were previously published. See also Figure S3. Gene sets are listed in Table S1.

We next turned to our conditional mice to determine whether the cancers caused by ablation of Snf5 in this model system displayed similar alterations in PcG target genes. We thus examined the expression of a gene set consisting of genes regulated by Ezh2 within the T-cell lineage (Su et al., 2005) and found that they are also repressed in Snf5-deficient CD8+ T-cell lymphomas compared to normal CD8+ T-cells (Figure 3C; p < 0.001,).

A key question is whether repression of PcG regulated genes is simply a consequence of oncogenic transformation or whether it is a primary consequence of Snf5 inactivation. We therefore utilized Snf5-conditional embryonic fibroblasts to evaluate the effect of Snf5 inactivation upon PcG regulated gene expression in primary non-transformed cells. We found that a gene set consisting of genes regulated by EZH2 in human fibroblasts (Bracken et al., 2006) was repressed following Snf5 inactivation in MEFs (Figure 3D; p < 0.001). We next utilized our Ezh2 conditional MEFs to identify an independently derived set of Ezh2 regulated genes (Table S1) and found that this gene set was also downregulated in Snf5-deficient MEFs (Figure 3E; p < 0.001). To evaluate specificity and to rule out a general repressive effect caused by Snf5 inactivation, we examined expression of Ezh2 regulated genes from an unrelated differentiated lineage, T- cells, and found them not to be repressed following Snf5 inactivation in MEFs (Figure S3B) indicating lineage specificity. Lastly, we analyzed MEFs derived from Snf5^fl/fl-Ezh2^fl/fl double conditional embryos and found that the absence of Ezh2 indeed blocked the downregulation of these targets otherwise caused by Snf5 inactivation (Figure 3F). Taken together, these results show that Snf5 inactivation leads to broad repression of lineage-specific PcG regulated genes and that this repression is dependent upon the presence of Ezh2.

Snf5 inactivation causes elevated levels of H3K27me3 at lineage-specific PcG targets

The antagonism between Snf5 and Ezh2 in the control of gene expression programs prompted us next to investigate the underlying mechanism by using ChIP to test whether increased levels of histone H3K27 trimethylation were present. We thus performed ChIP-PCR for H3K27me3 from both Snf5-deficient CD8+ T-cell lymphomas and from wild type CD8+ T-cells to ask whether increased levels of H3K27me3 were present at genes downregulated by Snf5. We tested 25 downregulated and 5 non-downregulated control genes. Eighteen of the 25 experimental genes demonstrated statistically significant increases in H3K27me3 in the Snf5-deficient lymphomas; an additional 4 of the 25 genes had increased H3K27me3 levels but were not statistically significant; 2 of the 25 genes were unchanged and only 1 of the 25 displayed reduced levels of H3K27me3 in the lymphoma (Figure 4A). In contrast, H3K27me3 levels were not significantly altered in any of the 5 control genes. Consequently, increased levels of H3K27me3 are present at the promoters of genes downregulated in Snf5-deficient lymphomas.

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Figure 4

Elevated levels of Ezh2 and H3K27me3 at PcG target genes following Snf5 loss. (A) ChIP analysis of H3K27me3 in Snf5-deficient lymphomas compared to wild type CD8+ T-cells. The experimental genes represent a random set of genes downregulated in Snf5-deficient lymphomas whereas the control genes are a random set expressed in both CD8+ T-cells and lymphomas. Relative enrichment is calculated by dividing the H3K27me3 enrichment to input DNA after normalization to a negative binding region in an Actb intron. Data are represented as mean +/− SEM from three biological replicates. * = p < 0.05. GSEA enrichment plot of H3K27me3 modified genes in wild type MEFs in expression data from (B) Ezh2-deficient MEFs, (C) Snf5-deficient MEFs or (D) Snf5 Ezh2-deficient MEFs. (E) GSEA enrichment plot of a random set of non-H3K27me3 genes in expression data from Snf5-deficient MEFs. (F) H3K27 ChIP-chip at individual gene promoters displayed using the Affymetrix Integrated Genome Browser. (G) H3K27me3 and Ezh2 ChIP-chip signal intensities near the transcription start sites (TSS) of 85 genes most significantly upregulated in Ezh2^−/− MEFs and (H) 132 randomly chosen control repressed genes not altered in Snf5-deficient or Ezh2-deficient expression data. See also Figure S4.

We next investigated whether increased H3K27 trimethylation and elevated levels of Ezh2 were directly contributing to changes in gene expression programs following Snf5 inactivation in the MEF model system. We utilized ChIP-chip to define a set of 508 high confidence genes bound by H3K27me3 modified histones in wild type MEFs and then evaluated how this gene set was affected by inactivation of Ezh2 and Snf5. Examination of the list revealed several gene families including Hox, Pax and Fox genes that have previously been shown to be regulated by PcG proteins (Bracken et al., 2006) (Table S1). As expected, given that Ezh2 and the PRC2 complex trimethylate H3K27, these targets were up-regulated in Ezh2 deficient MEFs (Figure 4B). In contrast, Snf5 inactivation led to further downregulation of the targets (Figure 4C). Co-inactivation of Ezh2 blocked the downregulation of these genes otherwise caused by Snf5 loss, demonstrating an essential role for Ezh2 in this process (Figure 4D). Of note, the effects of Snf5 inactivation were specific as genes not bound by H3K27me3 modified histones in wild type MEFs were not downregulated (Figure 4E). We next evaluated the effect of Snf5 inactivation upon the prevalence of genes modified by H3K27me3 and found that it led to a 1.9 fold increase (Figure S4).

To gain insight into levels of H3K27me3 at specific genes we evaluated its density at promoters. Interestingly, while a 2-fold elevation of H3K27me3 was present at p16^Ink4a, the effect was even more pronounced at numerous other targets (Figure 4F). At a few polycomb targets, such as Hoxb1, there appeared to be minimal change (Figure 4F). To evaluate the effect of Snf5 loss upon Ezh2 targets overall, we examined the set of genes that are upregulated following Ezh2 inactivation. Inactivation of Snf5 led to increased signal intensity of both H3K27me3 and Ezh2 binding overlying the TSS and upstream portion of these genes (Figure 4G), an effect not seen at control genes such as actin and Rps8 (Figure 4F) or at a randomly chosen set of repressed genes not expressed in wild type MEFs (Figure 4H).

Balanced expression of stem cell-associated programs by Ezh2 and Snf5

We next sought to investigate the mechanistic basis by which disruption of the SNF5-PcG balance drives oncogenic transformation. PcG genes have been implicated in the control of stem cell identity via the repression of lineage-specific targets (Boyer et al., 2006; Lee et al., 2006). Similarly, the SWI/SNF complex has recently been implicated in the control of stem cell self-renewal and pluripotency (Ho et al., 2009; Kidder et al., 2009). It has been proposed that oncogenic transformation may depend upon aberrant ectopic activation of stem cell-related self-renewal programs (Ben-Porath et al., 2008; Wong et al., 2008). Therefore, we evaluated the expression gene signatures associated with identity of embryonic stem cells in Snf5-deficient tumors. We utilized previously published embryonic stem cell-associated gene sets and found that these genes are significantly upregulated in both human MRTs (p < 0.001) and in murine Snf5-deficient lymphomas (p < 0.001)((Figure 3G,H and S3C,D)(Wong et al., 2008) (Ben-Porath et al., 2008). As a higher fraction of tumor cells than control cells are proliferating, we sought to determine whether proliferation associated genes were driving this enrichment. Therefore, we used a previously published “proliferation-corrected” gene set from which the proliferation associated genes had been removed (Somervaille et al., 2009). Significant enrichment remained intact using this gene set as well (MRT, p < 0.001; Snf5-deficient lymphomas, p < 0.001, Figure S3E,F). Again, we sought to determine whether activation of the stem cell-associated signature was simply a secondary consequence of oncogenic transformation or whether it was a primary effect due to Snf5 loss. Therefore, we examined the expression of these gene sets in Snf5-conditional MEFs and found enrichment of both the stem cell-associated signatures (p < 0.001) and proliferation deficient stem cell-associated signatures (p < 0.001) in Snf5-deficient MEFs (Figure 3I, S3G,H). Consequently, the upregulation of stem cell-like programs occurs in primary cells following Snf5 depletion and is not simply a consequence of transformation.

We next evaluated whether the gene expression signatures associated with stem cells were oppositely regulated by EZH2. To test this we examined the expression of these gene signatures in previously published microarray data from human embryonic fibroblasts in which EZH2 had been knocked down (Bracken et al., 2006). We found that the stem cell-associated signatures and a proliferation-deficient stem cell-associated signature were downregulated following EZH2 knockdown in primary cells, an effect opposite to that caused by Snf5 loss (Figure 3J, S3I,J). We next utilized our Ezh2-conditional MEFs and similarly found that these stem cell-associated signatures were downregulated following Ezh2 inactivation (Figure 3K, S3K,L). Finally, we utilized MEFs from Snf5^fl/fl-Ezh2^fl/fl double conditional embryos and found that inactivation of Ezh2 entirely blocked enrichment of the stem cell-associated signature otherwise caused by Snf5 loss (Figure 3L, S3M,N).

Ezh2 is required for growth of SNF5-deficient tumor cells

The antagonism between SNF5 and EZH2 in the control of gene expression prompted us to ask whether PcG activity is a key driver of oncogenic transformation following Snf5 loss. We began by evaluating the effect of EZH2 knockdown in human SNF5-deficient MRT lines and found that shRNA-mediated knockdown of EZH2 caused a decrease in cell proliferation (Figure 5A, S5). To confirm that the slowed proliferation was not due to off-target effects conferred by expressing the shRNA we monitored proliferation after knocking down EZH2 using a different system. We transiently transfected a smartpool of siRNAs that target EZH2 and then monitored growth by counting cells after 72 hours. Using this siRNA-mediated technology we were also able to achieve greater than 90% knockdown of EZH2 and similarly observed a reproducible reduction in proliferation compared to cells that were treated with control siRNAs (Figure 5B). Thus, EZH2 is required for proliferation of SNF5-deficient cancer cells.

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Figure 5

EZH2 is required for the proliferation of MRT cell lines. (A) Slowed proliferation of the G401 MRT cell line after EZH2 knockdown using shRNAs. Immunoblotting was used to determine the efficiency of EZH2 knockdown. Cell proliferation was determined using the WST-1 cell proliferation reagent. Data are represented as mean +/− SEM from 3 biological replicates. (B) Slowed proliferation of the G401 MRT cell line after EZH2 knockdown using siRNAs. Immunoblotting was used to determine the efficiency of EZH2 knockdown. Cells were counted 72 hours after treatment with the indicated siRNAs. Data are represented as mean +/− SEM from 3 biological replicates. *p = 0.01. (C) The reduced proliferation after shRNA mediated knockdown of EZH2 is not due to apoptosis. Apoptosis in EZH2 knockdown or control is measured via PARP1 cleavage. HeLa cells treated with doxyrubicin were used as a positive control for PARP1 cleavage. (D) EZH2 knockdown leads to cellular senescence. Cellular senescence was determined by measuring the expression of β-galactosidase. See also Figure S5.

To gain further insight into how EZH2 is driving tumor formation, we next evaluated whether the decreased proliferation following EZH2 knockdown was a result of either apoptosis or cellular senescence. While EZH2 knockdown revealed no detectable apoptotic phenotype as measured by cleavage of PARP1 (Figure 5C), a significant increase in senescence-associated β-galactosidase expression was detected (Figure 5D). Further, these cells were larger and flatter, consistent with senescent morphology. These results suggested that EZH2 contributes to tumorigenesis, at least in part, by preventing the activation of cellular senescence.

EZH2 and oncogenesis

Accumulating evidence has suggested that EZH2 contributes to cancer formation. This evidence comes from studies examining the expression of EZH2 in different tumors, where the highest levels correlate with the most aggressive tumors and the worst prognosis (Sparmann and van Lohuizen 2006; Simon and Lange 2008). Additional studies in a variety of tumor cell lines have shown that reducing the levels of EZH2 leads to slowed proliferation and a decreased capacity to form tumors when transplanted into mice, leading to the proposal of Ezh2 as a possible therapeutic target (Bracken et al., 2003; Croonquist and Van Ness, 2005; Kleer et al., 2003; Simon and Lange, 2008; Varambally et al., 2002). However, it has remained unclear whether hyperactivation of EZH2 has roles in the initiation and maintenance of primary cancers in vivo and whether targeted inactivation of EZH2 or its downstream function would be therapeutically useful. Using an in vivo cancer model, we show that inactivation of Ezh2 is sufficient to block tumor formation that occurs after Snf5 loss. A formal possibility is that Ezh2 could be an essential gene whose absence prevents cell growth. Several lines of evidence argue against this and for a specific relationship between PcG and SWI/SNF. First, as noted above, PcG and SWI/SNF serve antagonistic roles in control of Hox gene expression (Tamkun et al. 1992; Kennison 1995). Second, PcG blocks chromatin remodeling mediated by SWI/SNF in in vitro assays (Francis et al., 2001; Shao et al., 1999). Third, re-expression of SNF5 leads to PcG eviction from the INK4a/ARF locus (Kia et al., 2008). Fourth, Ezh2 loss does not have a negative effect upon T-cell number in vivo (Su et al., 2005). Lastly, we have found that the effects of Ezh2 inactivation in vivo to be quite specific. For instance, in a model of osteosarcoma, Ezh2 is largely dispensable for bone development and Ezh2 inactivation does not ablate cancer formation (J. Perry and S. Orkin, unpublished communication). Consequently, EZH2 does not serve an essential role in all cancers but rather likely drives cancer formation via specific activation.

Our results also provide mechanistic insight into the regulation of EZH2 expression. The SWI/SNF complex is thought to regulate activation or repression of genes via alterations in nucleosome positioning. Our work shows that Snf5 binds directly to the Ezh2 promoter and serves to prevent high-level expression. That Snf5 is an important regulator of Ezh2 expression is also supported by genome-wide ChIP-Chip analyses of Brg1 binding in embryonic stem cells where it was found that Ezh2 is a target of the SWI/SNF complex (Ho et al. 2009). Thus, our work establishes that Ezh2 is bound and regulated by Snf5, and required for tumor formation after Snf5 loss. In addition to Ezh2, several other PcG genes including Suz12, Eed, and Bmi1 are bound by Brg1 in embryonic stem cells, and these genes are also upregulated in some primary human cancers lacking SNF5, although to a lesser degree than EZH2. Therefore, SNF5 inactivation may lead to overexpression of other PcG genes which also contribute to oncogenesis. Indeed, while clear evidence linking SUZ12 and EED to oncogenic transformation is still lacking, BMI1 has been shown to possess clear oncogenic properties (Sparmann and van Lohuizen 2006; Simon and Lange 2008). Collectively, our work establishes that the regulatory relationship between SWI/SNF and PcG complexes extends across multiple cell types and that perturbation of this relationship can contribute to disease.

Hyperactivated stem cell-associated programs: a potential mechanism underlying tumors that arise following Snf5 inactivation or overexpression of PcG proteins

Stem cell-associated signatures have recently been found to be enriched in tumors with more aggressive behavior and poorer prognosis (Ben-Porath et al., 2008; Wong et al., 2008). While these signatures are upregulated in many cancers and are an important contributing factor during oncogenic transformation, the mechanisms underlying specific activation of these programs are not well understood. PcG proteins have a dynamic role in safeguarding stem cell identity by maintaining the repression of lineage-specific genes, and hyperactive PcG function may drive tumorigenesis through the repression of lineage-specific genes and reversion to a more stem cell like fate associated with an increased capacity for self-renewal and proliferation. The SWI/SNF complex has roles in lineage-specific differentiation and perturbations in SWI/SNF activity block differentiation, and thus may force cells to retain properties of a stem cell. Furthermore, while PcG and SWI/SNF complexes have opposing functions in the regulation of Hox gene expression in Drosophila, it is not clear whether this antagonistic relationship exists broadly during development or in the regulation of genetic programs in stem cells. Our results show stem cell-associated signatures are enriched in SNF5-deficient cancers and most importantly that Snf5 inactivation leads to upregulation of stem cell-associated programs in primary, untransformed cells. This thus identifies SNF5 as a key regulator of these genetic signatures. Conversely, PcG proteins regulate genetic programs in stem cells and PcG overexpression has been shown to promote increased proliferation and contribute to oncogenic transformation. We show that reduction of Ezh2 levels in primary cells leads to downregulation of stem cell-associated signatures, demonstrating antagonistic effects of Snf5 and Ezh2 upon stem cell-associated programs. Lastly, we show that activation of the stem cell-associated signature caused by Snf5 loss is dependent upon the presence of Ezh2. Collectively, our studies establish SNF5 as a regulator of stem cell-associated programs, show opposing functions for SWI/SNF and Polycomb in the regulation of these programs, and raise the possibility that imbalanced regulation of stem cell-associated programs maybe a key mechanism leading to oncogenesis following overexpression of EZH2 or SNF5 inactivation.

Immunoblots

The following antibodies were used: SNF5 (Bethyl, A301-087A), EZH2 (Cell Signalling; 3147), Actin-HRP (Abcam; 20272-200), p16^INK4a (Santa Cruz sc-1207 and sc-468), p19^ARF (Bethyl; A300-340A and Novus; NB200-106), PARP1 (Cell signaling; 9542), and HRP conjugated secondary antibodies (Jackson Immunoresearch). For details see supplemental procedures.

Murine models

All mouse experiments adhere to guidelines at the Animal Resources Children’s Hospital (ARCH) at the Children’s Hospital in Boston and have been approved by the Institutional Animal Care and Use Committee (IACUC).

Chromatin Immuoprecipitation and ChIP-chip

A two-step crosslinking method was done for the Snf5 ChIP according to (Nowak et al., 2005) with some slight modifications. The Bethyl, A301-087A Snf5 antibody, was used. p-values were determined using a paired t-test. The H3K27me3 and Ezh2 ChIP experiments were performed similarly to the above method using the H3K27me3 antibody (Upstate; 07-449) or the Ezh2 antibody (Millipore; 17-662) and a one-step crosslinking method where formaldehyde (1%) was added directly to the culture media and incubated for 10 minutes at 37C. p-values were determined using an unpaired t-test for the H3K27me3 ChIP experiments in lymphoma and CD8+ T-cell samples. In MEFs, MAT scores for all densely tiled genes at a region −500 and +2500 of the TSS were calculated. Differences between H3K27me3 enrichment in Snf5-deficient and WT MEFs were normally distributed (mean = 0.09). p-values were calculated as P(X > x) where X is the difference in MAT scores and x is the difference for the indicated gene. For details see supplemental procedures.

Grant support was from the American Cancer Society New England Division-SpinOdyssey Postdoctoral Fellowship #PF-07-261-01-DDC from the American Cancer Society and the Ruth L. Kirschstein National Research Service Award Fellowship 1 F32 CA130312-01A1 from the National Cancer Institute (B. Wilson). This work was supported in part by a U01 NCI Mouse Models of Cancer Consortium Award (S.H. Orkin and C.W.M Roberts) and a PHS award R01CA113794 (C.W.M. Roberts). C.W.M. Roberts is a recipient of an Innovative Research Grant from Stand Up 2 Cancer. The Garrett B. Smith Foundation, the Claudia Adams Barr Foundation, the Sarcoma Foundation of America (C.W.M.Roberts), and a R01 CA109467 research project grant (S.L. Pomeroy) provided additional support. S.H. Orkin is an Investigator of the HHMI.

We thank Jen Perry for helpful discussions and permission to cite unpublished data. We also thank Pablo Tamayo for help with cross-platform analysis of microarray data, Pengcheng Zhou for isolation of murine cerebellum cells and David James for the BT16 cell line.