Histone tail analysis reveals H3K36me2 and H4K16ac as epigenetic signatures of diffuse intrinsic pontine glioma

Pediatric DIPG tumor tissue (n = 9, H3.3K27M mutant) was collected postmortem (IRB #Pro00001339). H3.3K27 wild-type (WT) adult glioma tumor tissue specimens (n = 2), and one non-tumor frontal lobe tissue specimen were collected during the course of treatment (IRB# STU00095863). All diagnoses were made radiographically by a neuroradiologist, then confirmed by neuropathological evaluation upon tissue collection. Patient identifiers were removed and a single sequential numerical identifier assigned to each specimen (Table 1). Tissues were stored at − 80 °C prior to proteomic analysis (IRB #STU00202063).

Patient-derived pediatric DIPG cell lines SF8628, SF7761, DIPG007 (H3.3K27M mutant) and high-grade glioma cells KNS42 (H3.3G34V mutant) and SF9427 (H3.3G34 wild-type) were provided by Dr. Rintaro Hashizume (Northwestern University) as previously described [17‐19]. H3 wild-type adult glioma cells (U87) and normal human astrocytes (NHA) were obtained from American Type Culture Collection and ScienCell (#1800), respectively. Cells were treated with 300 nM JQ1 (Selleckchem S7110) or DMSO (Sigma D2650) for 24 and 48 h. Cell irradiation (9 Gy) was performed with the RadSOURCE-2000 X-Ray Irradiator, and cells analyzed at 24 and 48 h. Cell pellets were generated by harvesting with trypsin and washing twice with PBS, then stored at − 80 °C prior to proteomic analysis.

Histones were extracted from cell pellets using Histone Extraction Kit (ab113476, Abcam) according to the manufacturer’s protocol. 0.5 μg Histones were loaded and separated by SDS-PAGE using a 12% Mini-PROTEAN® TGX™ Precast Protein Gels and transferred by using Trans-Blot Turbo Mini 0.2 μm PVDF Transfer Packs at 2.5A, 25 V for 3 min in a Trans-Blot Turbo™ Transfer Systems (Bio-Rad). The membrane was blocked prior to the addition of the primary antibody with 5% milk in Tris buffered saline with 0.1% of Tween 20. The membrane was incubated overnight with primary antibody in TBS buffer with 0.1% Tween and 5% milk. The dilution of primary antibody was as follows: Rabbit monoclonal anti-Histone H3 (mutated K27M) antibody (ab190631) at a dilution of 1:1000, Rabbit mAb Acetyl-Histone H3 (Lys27) (D5E4) XP ((#8173, Cell Signaling Technology) at a dilution of 1:1000, Mouse mAb Histone H3 (1B1B2) (#14269, Cell Signaling Technology) at a dilution of 1:1000. The membrane was washed 3 times with TBS/0.1% Tween and incubated with an anti-rabbit or anti-mouse IgG conjugated to horse radish peroxidase (7074 and 7076, Cell Signaling Technology) at a 1:2000 dilution in TBS/0.1% Tween and 5% milk. Pierce ECL Plus Western Blotting Substrate (CN: 32132, Thermo Scientific) was used according to the manufacturer’s protocol to visualize proteins and quantify band intensity. Experiments were performed in triplicate for statistical analysis. The intensity of protein bands were analyzed by ImageJ, with the relative protein value expressed via the ratio of specific protein/H3.

Total cell RNA was extracted for gene expression profiling based on manufacturer protocol (Qiagen). All samples were adjusted to a concentration of 20 ng/μl RNA prior to submission for gene expression analysis using the NanoString nCounter Plexset Analysis System DNA damage repair 96 gene codeset (NanoString Technologies, Seattle, WA). Gene expression values were determined and converted to fold change in expression level for each treatment condition compared to DMSO controls in order to determine statistically significant differences in gene expression levels between groups (NanoString). Functional pathways and gene ontology analysis was then performed on fold change expression values (Inginuity Pathways Analysis, Qiagen).

Nuclei were isolated in buffer (15 mM Tris-HCl pH 7.5, 60 mM KCl, 15 mM NaCl, 5 mM MgCl₂, 1 mM CaCl₂, 250 mM sucrose; 1 mM DTT, 1:100 HALT protease inhibitor (Thermo Scientific)), and 10 mM sodium butyrate added immediately prior to use containing 0.3% NP-40. Nuclei were centrifuged at 600 x g for five minutes at 4 °C and washed twice with nuclear isolation buffer. Histones were extracted by via five volumes of H₂SO₄ and incubated at room temperature one hour. Debris was removed by centrifugation at 4000 x g for five minutes. Trichloroacetic acid was added to the supernatant at a final concentration of 20% (v/v) and incubated overnight at 4 °C. Precipitated histones were pelleted at 10,000 x g for five minutes, washed once with ice-cold acetone with 0.1% HCl and twice with acetone at 15,000 x g for five minutes. Residual acetone was dried in a fume hood, and samples stored at − 20 °C until further processing. Histones were derivatized with a single round of propionylation, digested with 1 μg trypsin (Promega, Madison, WI), and derivatized again with a single round of propionylation according to Garcia et al. [20].

Histone peptides were resuspended in Loading Buffer (0.1% TFA in water) and analyzed on a Thermo TSQ Quantiva (Thermo Scientific) in-line with a Dionex nano-LC (Sunnyvale, CA). Peptides were loaded onto a trapping column (3 cm × 150 μm, packed with ProntoSIL C18-AQ, 3 μm, 200 Å resin (New Objective, Woburn, MA)) for 10 min at 2.5 μL/min with 100% Loading Buffer. Elution from the trapping column and separation on a PicoChip analytical capillary column (10 cm × 75 μm packed with ProntoSIL C18-AQ, 3 μm, 200 Å resin (New Objective)) was achieved by decreasing the percentage of Solvent A (0.1% formic acid in water) and increasing the percentage of Solvent B (0.1% formic acid in 95% acetonitrile) from 1 to 35% at a flow rate of 0.30 μL/min over 45 min. The peptides were introduced into the triple quadrupole mass spectrometer by electrospray from an emitter with a 10 μm tip. The instrument settings were as follows: collision gas pressure of 1.5 mTorr; Q1 peak width of 0.7 (FWHM); cycle time of 3 s; skimmer offset of 10 V; electrospray voltage of 2.5 kV. All injections were performed in technical triplicate. Targeted methods were performed as previously published [21]. A list of monitored peptide transitions is provided (Supplementary material 1).

Raw data were imported into Skyline with Savitzky-Golay smoothing for analysis. Peak area assignments were manually confirmed, and total peak areas used to determine the percent relative abundance of histone modifications. The percent relative peptide abundance was determined by dividing the area under the curve for a given peptide of interest by the sum of the areas under the curve for all peptides with the same sequence, then multiplying by 100. Heatmaps were generated with R using gplots package, and show modifications that were above the limit of detection in all samples.

Differences in peptide abundance were analyzed using independent-sample t test for between-group comparisons, or one-way ANOVA and Tukey’s post hoc test for multi-group analyses using SPSS (IBM, Version 25), and expressed as mean ± standard deviation (SD). Pearson Correlation was performed to analyze the relationship between H3.3K27M mutation and detected histone codes. Multivariable analysis was performed using linear regression with Stepwise entry (p = 0.05) and removal (p = 0.10). All p values were two-sided, with p < 0.05 considered statistically significant.

Using MRM, we determined histone N-terminal tail signatures (histone codes) in H3.3K27M mutant and wild type (WT) glioma cell lines and astrocytes (Supplementary material 2, Table 1). Histone codes were distinct by H3 mutation status (Fig. 1a). K27 di- and tri-methylation (K27me2/3) were significantly decreased in H3.3K27M mutant cells on H3.1 and H.3.3 isoforms (Fig. 1a, Supplementary material 3, 4). A significant difference in H3.1K27me3 was also observed, with a mean relative abundance of 15.9% versus 1.4% in mutant versus WT lines (Fig. 1b). A similar trend was observed on H3.3, with H3.3K27me3 relative abundance of 5.6% in H3.3K27 WT cells and only 0.6% in mutants (Fig. 1c). We observed greater K36 di- and tri-methylation in mutants, coupled with less abundant H3.1K36me (Fig. 1d, e). H3K79me2 was less abundant in H3.3K27M mutant cells compared to WT (mean = 8.3 and 16.3%, respectively, Fig. 1f).

Histone acetylation also differed based on mutation status. Acetylation at H4K16 was lower in H3.3K27 WT cells compared to mutant (31.5 and 48.2%, respectively Fig. 1g). H3.1K27me2 and H3.1K36me2 were the most common PTMs associated with H3.3K27M mutant peptide on multivariate analysis (F = 428.7, p < 0.01). Importantly, because the H3F3A mutation yielding the H3.3K27M mutant protein is heterozygous, we quantified relative abundance of H3.3K27 WT and H3.3K27M peptides in a given cell sample: 29.2% of H3.3K27 peptides in our mutant cell lines were H3.3K27M (SD = 6.6, range 22.2–35.4%, n = 3. Figure 1c). As expected, the H3.3K27M peptide was not detected in H3.3K27 WT cells.

Tissue histone PTM profiles also clustered by H3.3K27M mutation status (Fig. 2a). The relative abundance of 16 PTMs were statistically significantly different between H3.3K27M mutant and WT tissues (Supplementary material 5). As with cell lines, the greatest differences in PTMs between H3.3K27M mutant and WT tissues were K27 and K36 methylation states (Fig. 2b-e, Supplementary material 5). We also detected significantly greater acetylation of H2AK5, H4K5, H4K8, H4K12, and H4K16 (Fig. 2f). H3.3K27me1 and H4K16ac were the most common PTM states associated with H3.3K27M peptide abundance on multivariate analysis (F = 214.0, p < 0.01).

As the greatest difference in relative abundance of PTM states in H3.3K27M mutant specimens were observed at H3K27, H3K36 and multiple H4 tail amino acids, we queried for the predominant modification states at these residues to determine correlations between specific modification states at these locations (Fig. 3). Overall, K27me1 and K36me2 were the predominant modifications observed on H3.1 and H3.3 isoforms (Fig. 3a), while acetylation was greatest at H4K16 (Fig. 3b). H3.3K36me2 abundance positively correlated with H3.1K36me2 levels, and negatively correlated with H3.3K27me1 (Fig. 3c, d). Also, H4K16ac abundance correlated positively with H3.3K36me2, and negatively with H3.3K27me1 (Fig. 3e, f).

Lastly, we compared DIPG cell and tumor tissue epiproteomic profiles. Overall, modifications on the H3.1/H3.3K27 N-terminal tail were similar in DIPG cell lines and tumor tissues. Specifically, there was no significant difference in abundance of the majority of H3.1/H3.3K27 peptides quantified, with differential fold change (FC) in abundance > 2 or < 0.5 for only six peptide modification states between DIPG cells and tissues (Table 2, Supplementary material 6). Significant differences in peptide modification states between groups were observed on H1.4K25, H3.3K36, H3K79, H3K9, and H4K20 peptides. Importantly, no difference in relative H3.3K27M peptide abundance was detected between DIPG tissue and cell lines (mean = 26.4 and 29.2, respectively, p = 0.686). Of note, unmodified peptides and modifications with < 5% relative abundance were excluded from this comparative analysis to ensure biological significance.

Because our method requires protein digestion for subsequent peptide mass spectrometry, determination of co-occurring PTMs at distant amino acid residues along the N-terminal tail is not possible. However, PTMs at proximal amino acids on the same peptide can be assessed. Therefore, to further explore the relationship between the H3.3K27M mutant peptide and histone PTM states, we investigated the PTMs of H3K27/K36 and H4K5/K8/K12/K16 peptides. The relative abundance of ten combinations of PTM states along these peptides were significantly different by tissue H3.3K27M mutation status (Fig. 4a, Supplementary material 7). Of these, H3.1K27me1K36me2, H3.3K27MK36me2, and H4K5unK8acK12unK16ac were increased in mutants compared to WT. These findings are consistent with the single amino acid analysis presented above. Further, we observed a positive correlation between H3.1K27me1K36me2 and H3.3K27M peptide abundance, and a negative correlation between H3.1K27me1K36me3 and H3.3K27M peptide abundance (Fig. 4b, c, Supplementary material 7). The abundance of the H4K5unK8acK12unK16ac peptide also positively correlated with H3.3K27M peptide abundance (Fig. 4d, Supplementary material 7). In contrast, H3.1K27me2K36me1, H3.1K27me3K36me1, H3.3K27me1K36me2/3 and H3.3K27me2K36me1 peptide abundance negatively correlated with H3.3K27M abundance (Supplementary material 7). On multivariate analysis, K36me2/3 were the most common modification states on the mutant H3.3K27MK36 peptide (F = 18,444.8, p < 0.01). As such, H3.3K27MK36me2 and H3.3K27MK36me3 peptide abundance also positively correlated with H3.3K27M abundance (Fig. 4e, f, Supplementary material 7). Importantly, di-methylation was the predominant modification state of the K36 residue on the H3.3K27MK36 peptide, while K36Ac was least abundant (Fig. 4g).

As radiation treatment (RT) is the standard therapy for DIPG, we examined the effects of RT on the glioma histone code in vitro. We treated H3.3K27M mutant DIPG cells (SF8628, DIPG007), H3.3K27 WT glioma cells (U87) and normal astrocytes (NHA) with 9 Gy radiation, and performed targeted histone mass spectrometry at 24 and 48 h post-treatment. Cell histone codes clustered first by origin, then by treatment condition (Fig. 5a). Comparative analysis revealed distinct differences in relative peptide abundance after RT, most notably in acetylated peptides (Supplementary material 8). In DIPG007 cells, the relative abundance of H2AK5ac decreased with RT at 48 h (Fig. 5b). In contrast, H2AK5ac abundance increased in NHA at 24 and 48 h, with no significant change in SF8628 or U87 (Fig. 5b). At 24 and 48 h post-RT, all lines except DIPG007 showed a significant increase in H4K16ac (Fig. 5c, Supplementary material 7). H3K9me3 also significantly increased in NHA, U87, and DIPG007, and trended towards a significant increase in SF8628, after RT (Fig. 5d, Supplementary material 8).

To determine the potential biological impact of observed differences in histone modifications after RT relative to controls, we compared cell gene expression profiles in these same treatment groups. On functional pathways analysis of genes identified as statistically significantly differentially expressed by RT treated cells relative to controls (fold change in expression > 2 or < − 2, adjusted p-value < 0.05), we identified DNA double-strand break repair as a top canonical pathway activated in RT treated DIPG cell lines (p-value 1.10 × 10^− 21, Supplementary material 9). The top implicated molecular and cellular function in RT treated cells, as well as the top network of molecular interaction, was DNA replication, recombination and repair (p-value 2.06 × 10^− 6),

We previously reported pre-clinical efficacy of JQ1, a BET/Bromodomain inhibitor (BRDi), in DIPG [7]. We observed that BRD proteins are enriched at acetylated residues on histone H3 in DIPG cells and animal models, and that JQ1 treatment results in decreased global H3K27ac, with restoration of global H3K27 methylation [7]. To further elucidate the epigenetic effects of JQ1 in DIPG, we examined its effects on histone codes in SF8628, DIPG007, NHA, and U87 cells. As observed with RT, PTM profiles clustered by cell line, then treatment condition (Supplementary material 10). When analyzed individually, cell profiles cluster by treatment condition (Fig. 6a, Supplementary material 11). In DIPG007 cells, H3.3K27me1 decreased by 1.5% at 48 h after JQ1 treatment compared to vehicle control, representing the only significant change in modification state observed at that time point (Supplementary material 11). A small increase in H3.3K27M abundance was also detected in DIPG007 at 48 h (31.4% vs 26.9%, p = 0.067, Supplementary material 11). Surprisingly, in DIPG007, H3.3K27ac abundance was not significantly different from control at 48 h post-treatment, though a marginal decrease was observed at 24 h (1.65 and 1.95%, respectively, p = 0.065, Supplementary material 11). These results were validated in DIPG007 and SF8628 cells via western blot for H3K27M and H3K27ac (Supplementary material 12).

In contrast, we observed statistically significant differences in abundance of multiple PTMs in SF8628 cells in response to JQ1 (Supplementary material 11). Increased H3.1K27me1 and decreased H3.3K36ac were seen at both 24 h and 48 h (Fig. 6b, Table 3, Supplementary material 11). Additional changes in relative modification states were observed after either 24 or 48 h post-treatment. For example, increased abundance of H3.1/H3.3K27me2, H3.3K36me1, and H4K20me2 were seen 24 h (Fig. 6b-e, Table 3) and H3K79me2 at 48 h (Fig. 6f, Table 3, Supplementary material 11). In addition, acetylation of H3K18 significantly decreased at 24 h (Fig. 6g, Table 3, Supplementary material 11). Surprisingly, we also observed a significant increase in H3.3K27M peptides at 24 and 48 h after JQ1 treatment in SF8628 cells (Fig. 6b, Table 3, Supplementary material 11).

Changes in histone PTM profiles were also observed in H3.3K27 WT cell lines after exposure to JQ1. The relative abundance of multiple PTMs were observed in U87 cells, including H3.1K27me2/me3, H3.1K36me1/me3, H3.3K36me1/ac, H3K14ac, H3K79me1, H3K4me1, and H4K5ac (Table 4, Supplementary material 11). Lastly, distinct changes were observed in NHAs after JQ1 treatment, including methylation of H3.1K27, H3.1/3.3 K36, and H3K79me1, and acetylation of H2AK5, H3.3K36, H3K18, and H4K16ac (Table 5, Supplementary material 11).

To determine the potential biological impact of observed differences in histone modifications after BRD inhibition relative to controls, we also compared cell gene expression profiles in these treatment groups. On functional pathways analysis of genes identified as statistically significantly differentially expressed by JQ1 treated cells relative to controls (fold change in expression > 2 or < − 2, adjusted p-value < 0.05), we identified nucleotide excision repair as the top canonical pathway activated in JQ1 treated DIPG cell lines (p-value 2.51 × 10^− 48, Supplementary material 9). Other canonical pathways implicated by JQ1 treated cell gene expression profiles included DNA mismatch repair via non-homologous end joining (NEMJ, p-value 2.53 × 10^− 32), while G2/M DNA damage check point regulation was the top toxicology list match (p-value 2.68 × 10^− 6). Top upstream regulator effect networks implicated ANXA7 activation (resulting in DNA binding and conformational modification, score 9.615), and TP73 inhibition (resulting in apoptosis, score − 15.254) in JQ1 treated DIPG cells relative to controls.