HDAC1 and HDAC6 are essential for driving growth in IDH1 mutant glioma

Low-grade and secondary high-grade gliomas frequently contain mutations in the IDH1 or IDH2 metabolic enzymes that are hypothesized to drive tumorigenesis by inhibiting many of the chromatin-regulating enzymes that regulate DNA structure. Histone deacetylase inhibitors are promising anti-cancer agents and have already been used in clinical trials. However, a clear understanding of their mechanism or gene targets is lacking. In this study, the authors genetically dissect patient-derived IDH1 mutant cultures to determine which HDAC enzymes drive growth in IDH1 mutant gliomas. A panel of patient-derived gliomasphere cell lines (2 IDH1 mutant lines, 3 IDH1 wildtype lines) were subjected to a drug-screen of epigenetic modifying drugs from different epigenetic classes. The effect of LBH (panobinostat) on gene expression and chromatin structure was tested on patient-derived IDH1 mutant lines. The role of each of the highly expressed HDAC enzymes was molecularly dissected using lentiviral RNA interference knock-down vectors and a patient-derived IDH1 mutant in vitro model of glioblastoma (HK252). These results were then confirmed in an in vivo xenotransplant model (BT-142). The IDH1 mutation leads to gene down-regulation, DNA hypermethylation, increased DNA accessibility and H3K27 hypo-acetylation in two distinct IDH1 mutant over-expression models. The drug screen identified histone deacetylase inhibitors (HDACi) and panobinostat (LBH) more specifically as the most selective compounds to inhibit growth in IDH1 mutant glioma lines. Of the eleven annotated HDAC enzymes (HDAC1-11) only six are expressed in IDH1 mutant glioma tissue samples and patient-derived gliomasphere lines (HDAC1-4, HDAC6, and HDAC9). Lentiviral knock-down experiments revealed that HDAC1 and HDAC6 are the most consistently essential for growth both in vitro and in vivo and target very different gene modules. Knock-down of HDAC1 or HDAC6 in vivo led to a more circumscribed less invasive tumor. The gene dysregulation induced by the IDH1 mutation is wide-spread and only partially reversible by direct IDH1 inhibition. This study identifies HDAC1 and HDAC6 as important and drug-targetable enzymes that are necessary for growth and invasiveness in IDH1 mutant gliomas.

www.nature.com/scientificreports/ act as a competitive inhibitor leading to DNA and histone hypermethylation with resulting wide-spread gene down-regulation 2 . Since that discovery, the majority of research has focused on the effect of the IDH1 and IDH2 mutations on TET2 and DNA hypermethylation leaving histones relatively under-studied [3][4][5] . TET2 and IDH mutations are common and mutually exclusive in acute myelogenous leukemia 6 (AML) and Tet2 and IDH1 knockout mice both spontaneously develop leukemia 7,8 . This suggests that in the case of AML, the IDH1 mutation is working primarily through inhibition of TET2 function. However, the tumorigenic mechanism of the IDH mutations in gliomas is less clear. TET2 mutations are rare in glioma and neither Tet2 nor IDH1 knockout mice spontaneously generate brain tumors. Sequencing studies from histologically similar pediatric low-grade diffuse intrinsic pontine gliomas (DIPG) have revealed a single lysine to methionine substitution in the H3 histone subunit (H3K27M) [9][10][11] . In normal circumstances, the H3K27 lysine can either be acetylated (H3K27ac) or methylated (H3K27me3) with resulting opening or closing of the nucleosome respectively 11,12 . Mouse models show that the H3K27M mutation leads to increased histone acetylation and increased gene expression 9,10 . Interestingly, these studies also showed that the levels of H3K27 acetylation correlate with intracellular concentrations of alpha-ketoglutarate leading to the hypothesis that the IDH1/2 mutations, which cause alpha-ketoglutarate depletion, may lead to a corresponding H3K27 deacetylation 13 .
Following the discovery of the IDH1 mutation, it was hoped that inhibiting this mutant enzyme and decreasing the intra-cellular concentrations of 2-HG might lead to reversal of the epigenetic changes induced by the mutation and improved survival. Since then, several effective and highly specific IDH1/2 inhibitors have been developed 14 . Initial results from clinical trials in AML have been highly encouraging with both mouse models and clinical trials showing reversal of epigenetic changes and improved survival 15,16 . Unfortunately, data from gliomas has been more mixed. An initial study using an IDH1 mutant inhibitor in a xenotransplant model found increased survival and demethylation of the GFAP gene 17 . However, a follow-up study found no changes in growth or DNA/histone methylation after a prolonged treatment period 18 . Clinical trials in glioma have also been underwhelming with some reports of tumor stability but no reports of consistent tumor shrinkage 19 . In the case of glioma, it appears that additional therapies are needed to reverse the epigenetic dysregulation induced by the IDH1 mutant enzyme.
The histone deacetylase family is comprised of eleven genes (HDAC 1-11) and is responsible for removing acetyl groups from histone residues e.g. H3K27. Histone deacetylases (HDAC) are highly expressed in a wide-range of cancers and are highly drug-targetable making them a frequent topic for research studies [20][21][22][23] . Early clinical studies found that use of valproic acid (a well-known HDAC inhibitor and anti-seizure drug) was associated with improved survival in glioma patients 24 . Follow-up studies have been encouraging but mixed [25][26][27][28][29][30] . Interestingly, three recent studies found that HDAC inhibitors may be specifically effective in IDH1 mutant gliomas [31][32][33] . Histone deacetylases are ubiquitously expressed in various cell types and regulate multiple cellular processes. An effective cancer therapeutic would need to have some degree of specificity to slow tumor growth with tolerable side effects. In this study we investigate the effect of the IDH1 mutation on H3K27 acetylation and determine which HDAC genes are essential for growth in patient derived IDH1 mutant glioma cells.

Results
The IDH1 mutant enzyme leads to gene down-regulation, DNA hypermethylation, increased DNA accessibility and histone hypo-acetylation. Shortly after the discovery of the IDH1 mutation and the inhibitory effects of 2-HG on alpha-ketoglutarate dependent enzymes, it was widely hypothesized that the IDH1 mutation leads to tumorigenesis via chromatin dysregulation 2,34-36 . It was also thought that inhibition of the IDH1 mutation and 2-HG depletion might reverse this dysregulation. While clinical trials with IDH mutant inhibitors are ongoing, initial results are disappointing 19 . To address this shortcoming and find alternative therapeutic targets, we began with a multi-omics approach to characterize the multiple effects of the IDH mutation on chromatin structure using two previously published and validated models of IDH glioma: (1) IDH1 mutant over-expression on E12 murine embryonic neurospheres 37 . (2) An IDH1 murine knock-in glioma model (IDH1WT/NRAS/G12V-shp53,shATRX vs. IDH1mut-R132H, NRAS G12V-sh53, shATRX) 38 . Mouse and human models of IDH1 mutant glioma were validated by measuring 2-HG levels ( Supplementary Fig. 1A).
Given the role of the H3K27M mutation in diffuse intrinsic pontine glioma 13 we elected to focus on the H3K27 histone residue. Consistent with other reports, over-expression of the IDH1 mutant enzyme led to gene downregulation and DNA hyper-methylation in both mouse models (Fig. 1A,B). We also saw a non-significant increase in DNA accessibility using ATAC-seq in both models (Fig. 1C). Effects of the IDH1 mutant enzyme on H3K27 methylation showed equal amounts of hyper-and hypo-methylation (Fig. 1D). Regarding H3K27 acetylation, over-expression of the IDH1 mutant enzyme led to a decrease in histone acetylation (Fig. 1E). A panel of surgically resected samples (IDH1 wild-type glioma N = 4, IDH1 mutant glioma N = 4 and Control/Epilepsy tissue N = 4) were assayed with ChIP-seq for H3K27 modifications (H3K27me3 and H3K27ac). Unsupervised clustering of differential peaks revealed that H3K27ac peaks (but not H3K27me3 peaks) segregated IDH1 wildtype and IDH1 mutant samples into different groups, however we did not see a trend towards hypoacetylation in the IDH1 mutant samples ( Supplementary Fig. 1B).
Histone deacetylase inhibitors (HDACi) are selectively effective against endogenous IDH1 mutant lines. As seen in the previous results, the IDH mutation has multiple effects on different aspects of chromatin structure. To determine which of these effects are essential for growth and potentially drug-targetable, we undertook a drug screen of 106 chromatin modifying compounds. Previous studies indicate that endogenous serum-free glioma-sphere lines are the most accurate in vitro model 39 Fig. 2A,B). Drugs were ranked based on their selectivity for IDH1 mutant lines. Four of the top eight compounds that were most selective for IDH1 mutant cultures were histone deacetylase inhibitors (HDACi). Interestingly, triptolide, the second most selective compound, was independently verified by another group as effective against IDH1 mutant glioma cells 42 . Taken together these results indicate that the IDH1 mutant enzyme deacetylates histones and that the histone deacetylases may contribute essential and drugtargetable functions in IDH mutant glioma.
Histone deacetylase inhibitors increase DNA accessibility and restore gene expression suppressed by mutant IDH1 while c227 (IDH1 mutant inhibitor) has minimal effect. With the finding that histone deacetylase inhibitors may be promising therapeutics, we performed a multi-omics approach to determine the effect of HDAC inhibitors on the chromatin structure of IDH1 mutant gliomas. As an initial validation step, we confirmed that a collection of patient-derived IDH1 mutant lines recapitulated the gene downregulation and DNA hypermethylation seen in their parent tumors ( Fig. 2A,B). Consistent with other published reports 18 pharmacological inhibition (c227) and genetic knock-down (shIDH1) of the IDH1 mutant protein had little effect on gene expression (Fig. 2C). In contrast, treatment with panobinostat (LBH) as well as valproic acid (a well-known and clinically used anti-epileptic and HDAC inhibitor) showed wide-spread gene up-regulation (Fig. 2D) and specifically showed significant up-regulation of published down-regulated and methylated genes (e.g. Noushmehr genes 43 ) (Fig. 2E). There was also an observed increase in DNA accessibility based on ATACseq analysis (Fig. 2F). Differential analysis of CUT&RUN peaks showed that LBH treatment led to decreased numbers of H3K27me3 peaks and a smaller increase in H3K27ac peaks. Western blot analysis showed a dose dependent increase in total H3K27 acetylation indicating that there may be additional acetylation of existing H3K27 loci as opposed to the creation of new loci (Supplementary Fig. 1C-E). Taken together these results imply that histone deacetylase inhibitors are more effective than IDH mutant inhibition at reversing the genetic down-regulation that accompanies the IDH1 mutant gene.
Histone deacetylase expression in IDH1 mutant gliomas. Clinical trials investigating the effects of non-specific pan-HDAC inhibitors on IDH WT gliomas have been limited by non-specific toxicity [20][21][22]44 . There   www.nature.com/scientificreports/ are eleven documented histone deacetylases in the mammalian genome (HDAC1-11). By determining which of these HDAC genes are the most critical for growth it should be possible to identify more specific HDAC inhibitors that might be able to slow growth with more limited side effects. As an initial step, we determined which HDAC genes are highly expressed in IDH1 mutant gliomas. Ten glioma samples (5 IDH1 wildtype and 5 IDH1 mutant) were stained for various HDAC genes using internally validated antibodies (HDAC1, HDAC2, HDAC3, HDAC4, HDAC5, HDAC6 and HDAC7) and scored by a blinded neuropathologist (AK). Additional testing from multiple vendors was unable to find any specific staining with antibodies for HDAC8-11. This data was supplemented by RNA expression data from our collection of patient derived glioma lines. Staining of surgical samples and expression data showed high expression of HDAC1, HDAC2, HDAC3, HDAC4 and HDAC6 at the RNA and protein level (Fig. 3A,B). Short hairpin interference lentiviral vectors (shRNA) were obtained against the highly expressed HDAC genes and tested in three endogenous IDH1 mutant lines (211, 252, and BT-142). Cells were plated at equal density, infected with lentivirus, and then counted on day 14. Knock-down efficiency as well as the possibility of gene cross-regulation was tested with RNA-seq analysis and western blot (Supplementary Fig. 3A-D). Lentiviruses directed against HDAC1 and HDAC6 saw the greatest decrease in cell number (Fig. 3C). Two additional independent constructs against HDAC1 and HDAC6 were tested to rule out non-specific effects and confirmed decreased growth ( Supplementary Fig. 3E).

Gene targets of histone deacetylases and histone deacetylase inhibitors.
To dissect the genetic contribution of each HDAC gene, line HK252 was infected with each of the lentiviral HDAC knockdowns (HDAC1-4, HDAC6, and HDAC9) before undergoing RNA-seq analysis. Expression data from each knockdown was compared to an empty vector. Differentially expressed genes underwent gene set enrichment analysis. The number of up-regulated and down-regulated genes are plotted (Fig. 4A, Supplementary Fig. 3F,G). Despite the previous finding that pan-histone deacetylase inhibitors lead to wide-spread gene up-regulation ( Fig. 2D), data from the individual knockdowns indicate that the HDAC genes have both activating and repressive functions (Fig. 4A). Gene set enrichment analysis (GSEA) revealed a large set of gene modules that were positively regulated by the HDAC genes (Fig. 4B). Most of these enriched gene sets were heavily over-lapping and involved  showing that the HDAC knockdowns and the drug-treated samples clustered separately (Fig. 4D). Using bioinformatic methods to dissect the gene changes seen following drug treatment, each significant gene change (twofold change) seen after drug treatment was assigned into one of the following groups: unique to one HDAC gene, "non-unique" (i.e. common to more than one HDAC gene), or "unaccounted" (i.e. gene was not seen in any of the HDAC knockdowns). Following this analysis, it was noted that the majority of the down-regulated genes seen in the drug-treated samples could be accounted for with one or several of the HDAC genes with HDAC6 being the greatest contributor. In contrast, most of the up-regulated genes in the drug-treated samples could not be accounted for with the available HDAC knockdown data suggesting that more complex interactions may be involved (Fig. 4C).
HDAC1 and HDAC6 lead to more infiltrative and diffuse tumor growth. Following up on the in vitro growth data, BT-142 cells were infected with one of three lentiviral constructs (empty vector/shControl, shHDAC1, shHDAC6) before being injected into the striatum of nod-SCID-gamma null mice (10,000 cells/ mouse, N = 5 mice per cohort). Mice were euthanized upon development of neurological symptoms. shHDAC1 mice showed a significant survival advantage over shControl. shHDAC6 showed a trend towards improved survival that did not reach statistical significance (Fig. 5A). Interestingly the phenotypic observations indicated that shControl mice tended to develop seizure symptoms, while shHDAC1 and shHDAC6 developed weakness and weight-loss symptoms (Fig. 5B). Following euthanasia, the brains were extracted, sectioned, and stained with hematoxylin and eosin. The slides were then scored by a blinded neuropathologist (MH) who determined that shControl tumors were more invasive than shHDAC1 and shHDAC6 tumors (Fig. 5B,C.). The previous findings identify HDAC6 as a potential specific target for IDH1 mutant gliomas. To test this hypothesis, two reported specific HDAC6 inhibitors (10 μM Ricolinostat, 10 μM ACY-738) were tested on a panel of IDH1 mutant glioma lines and showed high efficacy against these lines (Fig. 5D).

Discussion
Despite being only a single amino acid substitution, the R132H IDH1 mutation has multiple far-reaching effects on the immunogenicity, metabolic and epigenetic state of the cell. Given these alterations to cellular behavior it is tempting to design specific therapy that might exploit these cellular effects. Studies indicate that the IDH1 www.nature.com/scientificreports/ mutation may be the initial mutation that initiates tumorigenesis and thus resides in every tumor cell 45 . This makes it a promising vaccine target and to that end vaccine clinical trials are ongoing 46,47 . Working against this strategy is evidence that the IDH1 mutation and 2-HG are immune suppressive and may blunt an immune response 48,49 . Despite being an oncogene, the IDH1 mutant enzyme causes significant metabolic strain on numerous cellular pathways. Subsequently over-expression 50 and mouse knock-in studies 51 have found that the IDH1 mutation leads to slower growth and cell death. This presents an opportunity to exploit these vulnerabilities. Seltzer et al. 52 found that the IDH1 mutant enzyme depletes cellular stores of glutamate and makes cells vulnerable to glutaminase inhibitors. Tateishi et al. 18 found that the IDH1 mutant enzyme depletes the cell of NAD+ making cells vulnerable to NAMPT inhibition. The efficacy of radiation on IDH1 mutant tumors is controversial 53 and in vitro studies on the effect of the IDH1 mutation on DNA repair pathways and radiation sensitivity have been mixed 3,37,38,54 . While the tumorigenic mechanism of the IDH1 mutation has never been definitively proven, the most accepted hypothesis is that 2-HG-based inhibition of chromatin-modifying enzymes leads to pathologic gene expression 55,56 . While there was initial hope that inhibition of the IDH1 mutant enzyme might be able to reverse these changes, this study and others have found the effects on gene expression and growth underwhelming 19 . The purpose of the current study is to find additional compounds that could potentially reverse some of the pathologic epigenetic changes induced by the IDH1 mutation. To that end, an unbiased drug screen identified LBH/Panobinostat, a pan-HDAC inhibitor, as the most selectively effective compound against IDH1 mutant glioma lines. Follow-up experiments revealed that LBH up-regulates many of the repressed genes and increases chromatin accessibility. The DNA methylation status of the MGMT promoter in gliomas was the first clinically used epigenetic biomarker and since that time much of the focus on glioma epigenetics has been on DNA methylation. However, the discovery of the H3K27M mutation in diffuse intrinsic pontine gliomas has highlighted the importance of histone modification and the H3K27 locus specifically in gliomagenesis. While the exact mechanism of the H3K27M mutation is not known, mouse knock-in models show that the H3K27M mutation is associated with histone hyper-acetylation and is interestingly incompatible with the R132H IDH1 mutation 13 . Chung et al. also reported that levels of H3K27 acetylation were correlated with levels of alpha-ketoglutarate. The IDH1 mutant enzyme is known to deplete cellular levels of alpha-ketoglutarate 37 and thus it would be predicted this would lead to H3K27 hypo-acetylation. In the current study we used two IDH1 over-expression models to determine the effect of the IDH1 mutant enzyme on chromatin. Similar to previous reports we found that the IDH1 mutation was associated with gene down-regulation, DNA hypermethylation 43   www.nature.com/scientificreports/ increased DNA accessibility 57 . Consistent with our prediction, the IDH1 mutation was associated with H3K27 hypoacetylation. Contrary to predictions from other in vitro over-expression studies we did not observe increased H3K27 hyper-methylation (Fig. 1D). There are several explanations for this. One explanation is that previous studies used western blots which measures the total amount of H3K27me3 molecules while in this study we used ChIP-seq which measures the number of H3K27me3 loci. It might be that the IDH1 mutation leads to more deposition of H3K27me3 without leading to any additional methylated loci. A similar phenomenon was observed in DIPG where H3K27M mutation led to histone hyper-acetylation but no new enhancer sites 11 . In general, this study finds that the magnitude of the effects on H3K27 modification are noticeably smaller than the effects on DNA methylation. However, the relative size of the effect may conceal its biological importance. DNA methylation changes are thought to be slow requiring multiple cell divisions 34 . Studies have investigated the possibility of restoring the methylation state of IDH1 gliomas by inhibiting the DNMT family of DNA methylases with decitabine 58 . While eventually effective, the therapy is slow with non-specific off-target toxicity. In contrast, targeting histone architecture has the potential to yield faster efficacy with less toxicity. Consistent with this idea, sub-group analysis from the Stupp 59 trial found that valproic acid use (a known HDAC inhibitor) was associated with improved survival 24 . Follow-up studies investigating the survival benefits of valproic acid in glioma have been mixed but generally encouraging [25][26][27][28][29][30] . It should be noted that these studies used mixed populations of IDH1 wildtype and IDH1 mutant gliomas with IDH1 wildtype likely being the majority. Recently three studies have confirmed our findings that HDAC inhibitors have specific efficacy against IDH1 mutant gliomas 31-33 providing a rationale for a follow-up clinical study restricted to the IDH1 mutant sub-group. Interestingly, phase I and II clinical trials with newer non-selective pan-HDAC inhibitors (e.g. vorinostat 22,60 , panobinostat 44 and romidepsin 61 ) have been less encouraging with no demonstrated efficacy and dose-limiting side effects. Histone deacetylase activity is likely essential for cellular function and non-selective inhibition of all histone deacetylases will likely be associated with unwanted toxicity. To address this limitation, this study identifies the specific members of the HDAC family that are essential for IDH1 mutant glioma growth (i.e. HDAC1 and HDAC6). While many of the HDAC target genes and gene modules were heavily over-lapping, HDAC6 seemed to target more unique genes and gene modules. The unique structure and gene targets of the HDAC6 enzyme lends itself to specific inhibitors and several specific HDAC6 inhibitors have been developed as anti-cancer agents in clinical trials (clinicaltrials.gov NCT03008018, NCT02935790, NCT01323751).

Effect of KD on Gene Expression
This study has several limitations and unexpected findings that should be mentioned. First, BT-142 is one of the few IDH1 mutant cell lines that transplants into immune-deficient mice. However, the cell line is hemizygous for the IDH1 mutation and thus produces lower levels of 2-HG. Nevertheless, its gene expression pattern www.nature.com/scientificreports/ still clusters with other IDH1 mutant lines. Second, despite numerous attempts it appears that the IDH1 mutant lines used in this study are resistant to CRISPR manipulations, making genetic rescue experiments challenging. Interestingly, while over-expressing the IDH1 mutant enzyme did seem to decrease the number H3K27 acetylated loci, there was a fair amount of variability between samples indicating that this hypoacetylation may be affected by additional unidentified variables. Supporting that possibility, we did not see a consistent histone acetylation signature among a panel of IDH1 wildtype, IDH1 mutant and epilepsy surgical samples. In contrast the signal for DNA methylation is much stronger and surgical samples seem to have a more consistent DNA methylation signature 43 . Other studies have identified transcriptional repressor activity with histone deacetylases, however this study found that in an IDH1 mutant glioma model (HK252), the HDAC genes activate a set of chromosome organization and DNA replication gene modules. Interestingly, expression data from histone deacetylase inhibitors did reveal a set of up-regulated genes that were not seen in the HDAC knockdowns. One possible explanation for this observation is that because HDAC inhibitor compounds inhibit multiple HDAC proteins, there may be combinatorial effects that are not seen in single gene knock-down experiments. Consistent with this possibility is the observation that many of the HDAC enzymes are redundant and are therefore able to compensate for each other 62 . Another possibility is that HDAC enzymes have multiple biological functions in addition to histone deacetylation (e.g. protein modification). Gene knock-down and enzyme inhibition would likely affect these mechanisms differently.
In conclusion, histone deacetylase inhibitors offer a promising therapy for multiple cancers. Recent drug screens have shown that IDH1 mutant gliomas may be especially sensitive to these compounds. The key to success will be to tailor specific treatment to slow tumor growth while avoiding dose-limiting toxicities.

Methods
In vitro drug screen. A drug screen of 106 known epigenetic compounds targeting 35 genes and 19 epigenetic mechanisms (e.g. DNA methylation, DNA demethylation, histone methylation, histone demethylation, histone acetylation and histone deacetylation) was conducted against two IDH1 mutant (252 and BT-142) and three IDH1 wildtype lines (357, 385, 412) at four drug concentrations (10 nM, 100 nM, 1 μM, 10 μM) for 3 days. Viable cell number was estimated by MTT. Average IDH1mut viability was compared to average IDH1WT viability and displayed as area under the curve (IDH1WT/IDH1mut). Drugs were then ranked by compound.
Generation of E12 neural progenitor cell lines. Timed pregnant dams (C56Bl) were sacrificed on E12.
The embryos were removed from the uterus and the cortices were dissected free. Three distinct lines were created each by mincing three cortices per line and placing them in serum-free neurosphere media 63 until neurospheres appeared. These three neural progenitor lines were then infected with either an IDH1 mutant lentivirus 37 or a pUltra control. 2-HG levels for these lines as well as other IDH1 mutant lines were confirmed by LC-MS as previously described 37 . These lines were then maintained in culture for twelve passages before being processed for RNA-seq, ATAC-seq, methyl-seq and Chip-seq (H3K27ac, H3K72me and IgG).  Fig. 3A,B). Western blots were cropped for clarity. Full-length plots are shown to demonstrate antibody specificity ( Supplementary Fig. 3C,D). Based on preliminary in vitro experiments, drug doses of 15 nM LBH and 1 mM VPA were chosen to achieve a cell viability of ~ 60%. Cells underwent 3 days of drug treatment unless otherwise stated. Cells were treated with the HDAC6 inhibitors, 10 μm Ricolinostat or 10 μM ACY-738 for 7 days. All HDAC antibodies were obtained from Cell Signaling Technologies (HDAC1 10E2, HDAC2, 3F3, HDAC3 7G6C5, HDAC4 D15C3, HDAC6 D2B10).

Generation of libraries.
All human samples were provided by the University of Cincinnati Biorepository in a de-identified manner and were designated "Not human research" by the local IRB. All methods were carried out in accordance with relevant guidelines and regulations. All data is available at: https:// github. com/ TroyC arnwa th/ garre tt_ lab.
ATAC-Seq. ATAC-seq libraries were created as described previously 64 . Briefly, 50,000 cells were spun down at 500×g for 5 min at 4 °C. Cells were resuspended in ATAC-resuspension buffer containing 0.1% NP40, 0.1% tween-20, and 0.01% digitonin and incubated on ice for 3 min. Cells were washed with ATAC-resuspension buffer containing 0.1% tween-20. Nuclei were pelleted at 500×g at 4 °C for 10 min. Nuclei were resuspended in transposition reaction mix containing TD 2× reaction buffer (Illumina, #20034197), TDE1 Nextera Tn5 Transposase (Illumina, #20034197), and nuclease free water. The reaction was incubated at 37 °C in a water bath for 30 min. Immediately following transposition, DNA was purified with a Qiagen MinElute PCR Purification Kit (Qiagen, #28004). Following purification, transposed DNA was mixed with NEBNext high-Fidelity 2× PCR Master Mix (NEB, #M0541S), AD1_noMX and AD2.1-2.16 barcoded primers, and nuclease free water. Samples were amplified for 12 cycles. Immediately following amplification, DNA was purified using a Qiagen MinElute PCR Purification Kit. ATAC-seq reads in FASTQ format were first subjected to quality control to DNA was recovered from the supernatant after a 5-min centrifugation at 16,000g and purified via Phenol-Chloroform-isoamyl alcohol (Sigma, #145 p3803) extraction and ethanol precipitation essentially as described 65,66 . The resulting DNA was constructed into a library using NEBNext Ultra DNA Library Prep Kit (New England Biolabs, #E7645) following the manufacturer's instructions. The libraries were sequenced in a 100-base pair pair-end run on the Next Seq 2000 (Illumina). The raw and processed data are provided at the Gene Expression Omnibus database (GEO, http:// www. ncbi. nlm. nih. gov/ geo). Read quality was assessed using FastQC v0.11.7. Adapter sequences and bad quality segments were removed using Trim Galore! v0.4.2 and cutadapt v1.9.1. The trimmed reads were aligned to the reference human genome version hg38 using Bowtie2 v2.3.4.1 with parameters "--dovetail --local --very-sensitive-local -I 10 -X 700 -p 12 --no-unal --no-discordant --no-mixed". Aligned reads in IgG samples were stripped of duplicate reads with the program sambamba v0.6.8. Peaks were called with MACS v2.1.4 using the parameters "-g hs -q 0.1" for H3K27ac samples and "--broad -g hs -q 0.1" for H3K27me3 samples. BEDtools v2.27.0 were used to obtain consensus peaks in two steps. In the first step, common peaks among samples from same group were obtained by selecting peaks which are detected in at least 75% of samples from same group. Common peaks in each group from first step were merged at 50% overlap to obtain unique consensus peaks from all groups. Consensus peaks, originally in BED format were converted to a Gene Transfer Format (GTF) and used for read quantification under the peaks with featureCounts v1.6.2 from Rsubread package. Peaks located on chromosomes X, Y and mitochondrial DNA are excluded from further analysis. Differential analysis between groups of samples were assessed with the R package DESeq2 v1.26.0. Plots were generated using the ggplot2 package and base graphics in R.
Xenotransplant model. Eight-week-old Nod-SICD-gamma null (NSG) mice were placed under isoflurane. The scalp was incised and 10,000 cells/3 μl of BT-142 cells (shControl, shHDAC1, shHDAC6) were injected into the striatum. Mice were monitored for the development of tumor symptoms. All methods were carried out in accordance with an approved protocol from the local IACUC of the University of Cincinnati with relevant guidelines and regulations. All surviving mice were sacrificed after 21 weeks. Following sacrifice, mice underwent transcardiac perfusion and the brains were removed and placed in 10% formalin for 3-7 days before being moved to a 30% sucrose solution. Brains were then sectioned and stained with hemotoxylin and eosin.
Sequencing data. The datasets generated and/or analyzed during the current study are available in the Garrett Lab Data Directory (https:// github. com/ TroyC arnwa th/ garre tt_ lab). All experimental protocols were approved by the University of Cincinnati IRB committee. This study used de-identified patient specimens and was designated "Not human research" 19-02-25-02 (5/3/2019). Consent is not applicable.
Human samples. All human samples are provided by the University of Cincinnati Biorepository which serves to provide de-identified patient specimens of the desired tissue type with clinical and demographic information. This project was submitted to the IRB of the University of Cincinnati and was designated "Not human research" (2019-0155). All methods were carried out in accordance with relevant guidelines and regulations. www.nature.com/scientificreports/