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. Author manuscript; available in PMC: 2014 May 23.
Published in final edited form as: Chem Biol. 2013 May 23;20(5):713–725. doi: 10.1016/j.chembiol.2013.03.020

Selective HDAC1/HDAC2 Inhibitors Induce Neuroblastoma Differentiation

Stacey M Frumm 1, Zi Peng Fan 1, Kenneth N Ross 2, Jeremy R Duvall 2, Supriya Gupta 2, Lynn VerPlank 2, Byung-Chul Suh 2, Edward Holson 2, Florence F Wagner 2, William B Smith 3, Ronald M Paranal 3, Christopher F Bassil 1, Jun Qi 3, Giovanni Roti 1, Andrew L Kung 4, James E Bradner 3,5, Nicola Tolliday 2, Kimberly Stegmaier 1,2,*
PMCID: PMC3919449  NIHMSID: NIHMS471509  PMID: 23706636

Summary

While cytotoxic chemotherapy remains the hallmark of cancer treatment, intensive regimens fall short in many malignancies, including high-risk neuroblastoma. One alternative strategy is to therapeutically promote tumor differentiation. We created a gene expression signature to measure neuroblast maturation, adapted it to a high-throughput platform, and screened a diversity oriented synthesis-generated small-molecule library for differentiation inducers. We identified BRD8430, containing a nine-membered lactam, an ortho-amino anilide functionality, and three chiral centers, as a selective Class I histone deacetylase (HDAC) inhibitor (HDAC1>2>3). Further investigation demonstrated that selective HDAC1/HDAC2 inhibition using compounds or RNA interference induced differentiation and decreased viability in neuroblastoma cell lines. Combined treatment with 13-cis retinoic acid augmented these effects and enhanced activation of retinoic acid signaling. Therefore, by applying a chemical genomic screening approach we identified selective HDAC1/HDAC2 inhibition as a strategy to induce neuroblastoma differentiation.

Introduction

To date, cytotoxic agents have dominated the arsenal of drugs used to treat patients with cancer. Great progress has been made in treating patients with these compounds, but progress has slowed and alternate approaches will be needed to continue to advance patient care. Many cancer types have defects in both proliferation and differentiation, with the former being the target of current chemotherapies. Markedly less effort has gone into identifying compounds that target the differentiation defect, although some pro-differentiating agents have already proven efficacious in the clinic. For example, all-trans retinoic acid (ATRA) differentiation therapy has revolutionized the care of patients with acute promyelocytic leukemia (APL) (Abdel-Wahab and Levine, 2010; Ades et al., 2010). We thus embarked on the task of identifying novel differentiation therapies.

Historically, much of phenotype-based screening has focused on the endpoint of cell death. Screening for induction of differentiation is a markedly more challenging task because of the complexity of the target phenotype. In most cases, a single marker gene cannot be used as a read-out for differentiation. Current high-content imaging techniques have enabled screening for morphological changes. Here, however, we opted to use Gene Expression-based High Throughput Screening (GE-HTS), a method that uses gene expression signatures as proxies for biological state switches. The gene expression signatures can be detected in a high-throughput screening platform that involves ligation-mediated amplification of the genes of interest and a fluorescent bead-based detection (Peck et al., 2006; Stegmaier et al., 2004).

At the same time, small-molecule libraries and screening capabilities in academic centers have continued to evolve over the last decade. In the past, standard combinatorial libraries were largely populated by planar, achiral compounds, possibly due to the ease with which these compounds could be made. However, recent evidence has shown that complexity (as measured by sp3 content) and the inclusion of chiral centers are important factors in the transition from discovery through drug development (Lovering et al., 2009). Indeed, many compounds known to disrupt key protein-protein interactions are structurally complex natural products (Koehn and Carter, 2005). Diversity Oriented Synthesis (DOS) is a strategy that yields collections of small molecules with structural complexity and diversity mimicking that of natural products (Schreiber, 2000). We thus opted to screen a DOS library of small molecules (Marcaurelle et al., 2010). Furthermore, the DOS library selected for screening was biased for chromatin modification by the incorporation of moieties that bind zinc. Broad transcriptional changes regulate differentiation, and epigenetic alterations have been implicated in the differentiation block observed in cancer cells (Helman et al., 2012; Lotem and Sachs, 2006; Ramirez and Hagman, 2009; Scaffidi and Misteli, 2010), suggesting that chromatin modifying small molecules might effectively induce cellular differentiation.

For our study, we chose to look at neuroblastoma, a disease where differentiation therapy has been successful but not yet fully explored. Neuroblastoma is the most common extracranial pediatric solid tumor (Modak and Cheung, 2010). Although cure rates for patients with low-risk disease are greater than 90%, the prognosis for patients with high-risk neuroblastoma remains dismal, with cure rates as low as 35% despite the incorporation of aggressive chemotherapy, surgery, radiation, transplant, and consolidation therapy (Modak and Cheung, 2010). The differentiating agent 13-cis retinoic acid (cisRA) is presently used to treat minimal residual disease in the high-risk patient group after autologous stem cell transplantation (Matthay et al., 1999). However, the full therapeutic benefit of pro-differentiating agents has not been thoroughly explored.

Here, we report the development of a robust gene expression signature for neuroblastoma differentiation. We screened a DOS library for induction of the neuroblastoma differentiation signature. We identified a novel pro-differentiating compound, BRD8430, and subsequently characterized it as a selective inhibitor of Class I histone deacetylases (HDACs; HDAC1 > 2 > 3). Subsequent investigation honed in on selective HDAC1/HDAC2 inhibition as important in inducing neuroblastoma differentiation and cell death.

Results

A gene expression signature for neuroblastoma differentiation

Identifying small-molecule inducers of neuroblastoma differentiation via high-throughput screening is a challenging task because of the complexity of the target phenotype. Therefore, we developed a gene expression signature representing differentiation and adapted it for GE-HTS, a previously described method that uses ligation-mediated amplification and fluorescent bead-based detection to measure gene expression levels (Peck et al., 2006; Stegmaier et al., 2004). Two neuroblastoma cell lines, BE(2)-C, which harbors MYCN amplification, and SH-SY5Y, MYCN non-amplified, were treated with the pro-differentiating agent(s) cisRA and/or phorbol 12-myristate 13-acetate (PMA) or the appropriate vehicle control. Whole-genome expression analysis was then performed using Affymetrix microarrays. A 59-gene signature for neuroblastoma differentiation was derived; it included 40 up-regulated genes in the chemically differentiated cells relative to the undifferentiated neuroblastoma cells, 11 down-regulated genes in the differentiated cells, and eight reference genes with stable expression across the two biological states (see Supplemental Experimental Procedures for a full description of the signature creation and Table S1 for a list of the signature genes and probes). Two known differentiation agents, ATRA and cisRA, were confirmed to induce the differentiation signature in a dose-dependent manner in BE(2)-C cells after two days of treatment (Figure 1A). The combined expression of the signature genes can be represented by a single value (i.e., the weighted summed score), which will heretofore be referred to as the “differentiation score.” Absolute scores are not directly comparable across experiments, but compound performance can be evaluated within an experiment relative to positive and negative controls. The differentiation signature was further validated by treating the SH-SY5Y cell line with both cisRA and PMA, and by treating three additional MYCN amplified neuroblastoma cell lines not used in the development of the GE-HTS signature (Kelly, LAN-1, and NGP) with cisRA (Figures S1A-D). Finally, we confirmed in BE(2)-C cells that at doses which induced the differentiation signature, differentiation was detected by another experimental approach: immunofluorescent labeling for the differentiation marker NF-M (neurofilament medium; Figure S1E) in extended neurite projections.

Figure 1.

Figure 1

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A DOS library was screened for the induction of a 59-gene neuroblastoma differentiation signature. (A) BE(2)-C cells were treated with either ATRA or cisRA across a range of doses. After 48 hours, the cells were lysed and the expression levels of the 59 signature genes (see Table S1 for gene list) were measured using GE-HTS. The heat map depicts the relative gene expression with blue denoting low expression and red denoting high expression (fold change range: -3 to 3). Four poorly performing genes were removed from the analysis and the eight reference genes are not shown. (B) In BE(2)-C cells, 1,916 DOS compounds were screened in duplicate. DMSO served as the negative control and 1 μM cisRA as the positive control. The summed score and weighted summed score for each compound or control are plotted. Compounds in red were retested in the primary assay across a range of compound concentrations. (C-D) Dose-responsive induction of the differentiation score (weighted summed score) for the strongest and weakest performing compounds in the confirmatory screen (i.e., BRD8430 and BRD3259, respectively). Error bars represent the mean ± SD for two replicates per compound condition, 143 1 μM cisRA replicates, and 336 DMSO replicates. *P < 0.01, **P < 0.001 calculated using a one-way ANOVA, with Bonferroni correction, comparing each condition to DMSO. See also Figure S1.

Screening of a DOS library identifies a novel inducer of neuroblastoma differentiation

The compound library used to screen for the induction of the differentiation signature was created through DOS (Marcaurelle et al., 2010) and biased for chromatin modification via incorporation of a zinc-chelating ortho-amino anilide group. BE(2)-C cells were treated in duplicate with 10 μM of 1,916 members of the DOS library. DMSO treatment was used as the negative control, and 1 μM of cisRA as the positive control. After incubating for two days, the GE-HTS assay was performed. The ability of each compound to induce differentiation was evaluated by five complementary scoring methods (Figure S1F). Their performance in two of the five methods is shown in Figure 1B. The 32 top-scoring compounds were selected to be rescreened across a range of concentrations.

To confirm the activity observed in the primary screen, eight concentrations of each compound were evaluated in duplicate in BE(2)-C cells after two days of incubation. Again, all 32 compounds induced the differentiation score at 10 μM but differed in their overall concentration-response profiles, with the best-performing compound, BRD8430, significantly inducing the signature at all eight concentrations tested and the worst-performing compound, BRD3259, significantly inducing the signature with five of the eight concentrations (Figures 1C-D). To incorporate the performance across the full concentration range, a curve was fitted to the differentiation score across the eight concentrations and the area under the curve (AUC) was calculated (Figures S1G-H). BRD8430 had the highest AUC value of the 32 compounds evaluated.

Key stereochemical and structural features of BRD8430 elucidated through analog testing

One advantage of working with a small molecule derived from a DOS pathway is the ease in accessing and evaluating stereochemical and structural variants. Therefore, we were able to investigate features of BRD8430 that were important for its pro-differentiating activity by evaluating stereochemical and structural analogs using the GE-HTS assay. In addition to the ortho-amino anilide functionality, BRD8430 contains a nine-membered lactam, a para-ether dimethylaniline, and three stereocenters, two within the macrocycle and one outside of the ring (Figure 2A). BRD8430 and its stereoisomers were synthesized as outlined in the Supplemental Experimental Procedures, and as illustrated by the scheme in Figure S2A.

Figure 2.

Figure 2

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Stereo/structure-activity relationships for BRD8430 analogs. (A) The structure of BRD8430 with its three stereocenters denoted 1, 2, and 3. This compound has a nine-membered lactam, para-ether dimethylaniline, and R,SR stereochemistry (9-para; R,SR). (B) BE(2)-C cells were treated in duplicate with eight concentrations of BRD8430 and its seven stereoisomers for two days. Cells were then screened for induction of the differentiation signature. The heatmap represents AUC values calculated for each compound, with red denoting high AUC, yellow denoting intermediate AUC, and green denoting low AUC. (C-D) The signature induction for stereoisomers BRD8430 (9-para; R,SR) and BRD4586 (9-para; S,SR). (E) Differentiation score for BRD6819, a structural analog of BRD8430 with an eight-membered lactam (8-para; R,SR). (F) Differentiation score for BRD6332, a structural analog of BRD8430 with an eight-membered lactam and ortho-ether dimethylaniline (8-ortho; R,SR). In C-F, error bars represent the mean ± SD of two replicates for each compound dose, 261 replicates for DMSO, and 34 replicates for cisRA at 1 μM. *P < 0.01, **P < 0.001 calculated using a one- way ANOVA, with Bonferroni correction, comparing each condition to DMSO. See also Figure S2 and Table S2.

The full complement of eight stereoisomers was tested across a range of compound concentrations. The differentiation score across the concentration range was fitted with a curve and the AUC was calculated and used as a metric of the overall compound performance. BRD4586, which differs from BRD8430 only at the exo-cyclic stereocenter, retained the full differentiation-inducing activity (Figures 2B-D and Table S2). The six other stereoisomers displayed markedly reduced activity (Figure 2B and Table S2).

We also assessed the differentiation-inducing activity of two structural analogs of BRD8430: BRD6819, which contains an eight-membered lactam, and BRD6332, which also contains an eight-membered lactam but with an ortho-ether dimethylaniline. BRD6819 induced the differentiation signature in a manner similar to BRD8430, while BRD6332 exhibited greatly dampened differentiation activity (Figures 2E-F). The three most active compounds (i.e., BRD8430, BRD4586, and BRD6819) were confirmed to induce the differentiation signature in a second cell line, SH-SY5Y (Figure S2B-D).

BRD8430 induces differentiation and decreases viability across neuroblastoma cell lines

Upon the identification of BRD8430 as a top-scoring compound, it was repurified to ≥ 95% purity (by LC/MS) and retested in four neuroblastoma cell lines: Kelly, LAN-1, BE(2)-C, and SH-SY5Y. BRD8430 was confirmed to induce the differentiation signature in a concentration-dependent manner in all four cell lines at both the two day and five day time points (Figures 3A and S3). Furthermore, BRD8430 induced morphologic changes, including neurite outgrowth, consistent with differentiation (Figure 3B). BRD8430 also reduced the viability of these four lines after five days of treatment, an expected finding when neuroblastoma cells undergo differentiation (Figure 3C and Table S3).

Figure 3.

Figure 3

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BRD8430 induces differentiation and decreases viability in four neuroblastoma cell lines. (A) Concentration-dependent induction of the differentiation score after a five-day incubation with BRD8430 in four cell lines. Error bars represent the mean ± SD of four replicates. *P < 0.01, **P < 0.001 calculated using a one-way ANOVA, with Bonferroni correction, comparing each condition to DMSO. See Figure S3 for day two time point. (B) BE(2)-C cells were treated with vehicle (DMSO) or BRD8430 at the indicated concentrations and labeled for NF-M (red) and DAPI (blue). (C) Cells were treated with BRD8430 across a 9-point concentration range for five days and then viability was measured using an ATP-based assay. The values relative to the DMSO-treated controls are displayed with error bars representing the mean ± SEM of four replicates. See Table S3 for IC50 values.

BRD8430 is a selective HDAC inhibitor

BRD8430 includes an ortho-amino anilide metal chelation moiety making it a putative inhibitor of HDACs, which require zinc atoms for their enzymatic activity. Presumably, the ortho-amino anilide serves as the zinc chelating moiety and the nine-membered central ring extends to the solvent exposed surface binding region of the HDAC enzyme (Bressi et al., 2010). Indeed, in BE(2)-C cells, BRD8430 increased histone H3 acetylation in a concentration-dependent manner after six hours of treatment (Figure 4A). To determine if this HDAC inhibitory activity is required for the induction of neuroblastoma differentiation, an analog lacking the chelation functionality, BRD8703, was synthesized and tested in BE(2)-C cells. The analog did not induce the differentiation signature at concentrations of up to 20 μM (Figure 4B). Three analogs in which the chelation moiety was substituted also failed to induce the signature (Figure S4A-C).

Figure 4.

Figure 4

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BRD8430 is a selective HDAC inhibitor. (A) Immunoblot for acetylated histone H3 (AcH3) in nuclear extracts from BE(2)-C cells treated with BRD8430 or DMSO for six hours. (B) The differentiation score in BE(2)-C cells treated for two days with BRD8703, a BRD8430 analog lacking the metal chelation functionality. Error bars represent the mean ± SD of six replicates. See Figure S4A-C for additional compounds with substitutions for the chelation functionality. (C) Effects of BRD8430 on the enzymatic activity of HDACs 1, 2, and 3. See Figure S4D for effects on the activity of HDACs 4-9. Error bars represent the mean ± SD of three replicates. (D) Viability relative to DMSO-treated controls for BE(2)-C cells treated with one of the 12 HDAC inhibitors for two (top) or five (bottom) days. Error bars represent the mean ± SD of four replicates. The HDACs selectively inhibited by each compound are indicated in parenthesis beside each compound name in the key. A pan-HDAC inhibitor is defined as an inhibitor of HDACs 1, 2, 3, and other HDACs. See Figure S4E for effects of the HDAC inhibitor panel on the viability of Kelly cells. (E-F) The differentiation score of BE(2)-C cells treated for two days with the indicated compounds. Error bars represent the mean ± SD of four replicates for each HDAC inhibitor dose, 72 DMSO replicates, and 24 replicates of 1 μM cisRA. (B, E-F) *P < 0.05, **P < 0.01, ***P < 0.001 calculated using a one-way ANOVA, with Bonferroni correction, comparing each condition to DMSO.

There are 11 zinc-dependent HDACs. To determine which are inhibited by BRD8430, the compound was evaluated in a biochemical HDAC activity assay (Bradner et al., 2010b). BRD8430 was determined to inhibit HDAC1 with an IC50 value of 0.069 μM (95% confidence interval (CI): 0.062 - 0.077), HDAC2 with an IC50 value of 0.56 μM (95% CI: 0.47 – 0.66), and HDAC 3 with an IC50 value of 1.3 μM (95% CI: 1.1 – 1.6). Across the same concentration range, we were not able to determine IC50 values for inhibition of the other HDACs (Figures 4C and S4D). Ortho-amino anilides are known to be selective binders for HDACs 1, 2, and 3 (Moradei et al., 2007), but BRD8430 further demonstrated a narrow margin of selectivity for HDACs 1 and 2 over HDAC3, and for HDAC1 in particular. This observation prompted us to further investigate the effects of selective HDAC inhibitors on neuroblastoma cell lines.

Selective inhibition of HDAC1 and HDAC2 decreases viability and induces differentiation of neuroblastoma cell lines

For more than a decade, HDAC inhibitors have been known to decrease viability and induce differentiation in neuroblastoma models (Coffey et al., 2001; Coffey et al., 2000; Hahn et al., 2008; Muhlethaler-Mottet et al., 2008; Panicker et al., 2010). The majority of these studies have focused on the so-called HDAC pan-inhibitors, which are small molecules that non-selectively bind to most of the 11 zinc-dependent HDACs.

Given the intriguing HDAC-selectivity profile observed with BRD8430, we evaluated the ability of a diverse collection of HDAC inhibitors with different selectivity profiles to decrease viability and induce differentiation in neuroblastoma cell lines. This collection included pan-HDAC inhibitors (having activity against more than HDACs 1, 2, and 3): ITF-2357 (Leoni et al., 2005), vorinostat (Kelly and Marks, 2005), apicidin (Darkin-Rattray et al., 1996), and BRD7914 (Jones et al., 2006); selective HDAC1/2/3 inhibitors: MS-275 (Suzuki et al., 1999) and CI-994 (el-Beltagi et al., 1993); selective HDAC1/2 inhibitors: BRD5298 (Wilson et al., 2011), compound 60 (Methot et al., 2008; Moradei et al., 2007), and BRD5100 (Wilson et al., 2011); a selective HDAC6 inhibitor: BRD8148 (Wilson et al., 2011); a selective HDAC8 inhibitor: PCI-34051 (Balasubramanian et al., 2008); and a selective HDAC3 inhibitor: inhibitor 106 (Chou et al., 2008).

Two neuroblastoma cell lines, BE(2)-C and Kelly, were treated with each inhibitor at four concentrations, and cell viability was measured at days two and five (Figures 4D and S4E). The selective HDAC6 and HDAC8 inhibitors did not significantly decrease viability, and the selective HDAC3 inhibitor only decreased viability at the highest concentration (10 μM) at both time points. All three selective HDAC1/2 inhibitors had little effect on viability after two days of treatment but greatly decreased viability after five days of treatment. In contrast, the effects of the pan-HDAC inhibitors and the selective HDAC1/2/3 inhibitors were comparable at all time points analyzed.

The ability of several of the compounds to induce the differentiation signature in BE(2)-C cells after two days of treatment was also assessed. Neither the selective HDAC6 inhibitor nor the selective HDAC8 inhibitor significantly induced the signature at any of the concentrations tested, and the selective HDAC3 inhibitor only significantly induced the signature at the highest concentration (10 μM) (Figures 4E). Vorinostat, a pan-HDAC inhibitor, compound 60, a selective HDAC1/2 inhibitor, and MS-275 and CI-994, both selective HDAC1/2/3 inhibitors, all significantly induced differentiation at multiple concentrations (Figure 4F). Compound 60 is a commonly used tool compound that selectively inhibits both HDAC1 and HDAC2. We confirmed the selective activity profile of this compound (Figure 5A), and demonstrated that, similar to BRD8430, compound 60 induced the differentiation signature across multiple neuroblastoma cell lines at multiple different time points (Figures 5B and S5). It also decreased the viability of these cell lines after five days of treatment (Figure 5C and Table S4).

Figure 5.

Figure 5

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Compound 60, a selective HDAC1/2 inhibitor, induces differentiation and decreases viability in four neuroblastoma cell lines. (A) Effects of compound 60 on the enzymatic activity of HDACs 1, 2, and 3. Error bars represent the mean ± SD of three replicates. (B) Concentration-dependent induction of the differentiation score after a five-day incubation with compound 60 in four cell lines. Error bars represent the mean ± SD of four replicates. *P < 0.001 calculated using a one-way ANOVA, with Bonferroni correction, comparing each condition to DMSO. See Figure S5 for day two time point. (C) Cells were treated with compound 60 across a range of concentrations for five days and then cell viability was measured using an ATP-based assay. The values relative to the DMSO-treated controls are displayed with error bars representing the mean ± SEM of four replicates. See Table S4 for IC50 values.

Simultaneous genetic knockdown of HDAC1 and HDAC2 inhibits neuroblastoma growth and induces differentiation

To confirm the sensitivity of neuroblastoma cell lines to HDAC1 and HDAC2 inhibition, and to determine if the inhibition of HDAC1 or HDAC2 is preferentially responsible for the observed differentiation phenotype, we used small interfering RNA (siRNA). Two cell lines, Kelly and BE(2)-C, were transfected with a non-targeting siRNA pool, an siRNA pool targeting HDAC1, an siRNA pool targeting HDAC2, or the HDAC1 and HDAC2 targeting pools combined (Figure 6A). The differentiation signature was only induced upon concurrent knockdown of both HDAC1 and HDAC2, with the majority of the marker genes' expression levels changing in the expected direction in both cell lines (Figures 6B-C). Simultaneous knockdown of HDAC1 and HDAC2 also significantly decreased cell growth in both lines (Figure 6D).

Figure 6.

Figure 6

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Genetic knockdown of HDAC1 and/or HDAC2 in neuroblastoma cell lines. (A) Immunoblots illustrating knockdown of HDAC1 and HDAC2 in Kelly and BE(2)-C cells two days after transfection with siRNAs targeting these genes. Control cells were transfected with pooled non-targeting siRNAs. (B) Differentiation score at day four (BE(2)-C) or day six (Kelly) after transfection with non-targeting siRNAs (NT), siRNAs targeting HDAC1, siRNAs targeting HDAC2, or the combined HDAC1- and HDAC2-targeting siRNA pools. Error bars represent the mean ± SEM of six replicates. ***P < 0.001 calculated using a one-way ANOVA, with Bonferroni correction, comparing each siRNA condition to NT. (C) Heatmaps displaying the relative expression of the 34 differentiation signature genes changing in the anticipated direction in both Kelly cells at day six post-transfection and BE(2)-C cells at day four post-transfection. Blue indicates low expression and red indicates high expression (fold change range: -3 to 3). (D) Viability of Kelly and BE(2)-C cells relative to the viability at the time of seeding (day two post-transfection). *P < 0.05, **P < 0.01, ***P < 0.001 calculated using a two-way repeated measures ANOVA, with Bonferroni correction, comparing each condition to NT at each time-point. Error bars represent the mean ± SD of six replicates.

Combined treatment with selective HDAC inhibitors and cisRA enhances differentiation, reduces viability, and activates retinoic acid signaling

Combining the pan-HDAC inhibitor vorinostat with cisRA was previously shown to strongly induce differentiation and synergistically affect viability (Hahn et al., 2008). To determine if the combination of more selective HDAC inhibitors and cisRA is likewise effective, Kelly and BE(2)-C cells were treated with compound 60 plus cisRA and BRD8430 plus cisRA. These combinations caused significantly greater induction of the differentiation signature than any of the single agents (Figures 7A and S6A and Table S5), and it had a synergistic effect on viability (Figures 7B and S6B).

Figure 7.

Figure 7

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Combined treatment of selective HDAC1/2 inhibitors and cisRA in BE(2)-C cells. (A) BE(2)-C cells were treated with an HDAC inhibitor (compound 60 or BRD8430) and cisRA alone and in combination for two days and then the differentiation score was measured. The whiskers indicate the maximum and minimum values of four replicates per condition. Each condition was significantly different from DMSO and each combination was significantly different from the corresponding single-agent treatments; the relevant comparisons are included in Table S5. (B) Isobolograms of the effect of the combined treatment of compound 60 and cisRA or BRD8430 and cisRA on the viability of BE(2)-C cells at four or five days, respectively. Each circle on the plot represents one of the compounds at a fixed dose and the concentration of the second compound in combination to produce 50% viability compared to the vehicle control. Synergy appears as points below the line of additivity. (C) Activation of a retinoic acid signaling reporter, RARE3-tk-luc, with compound 60 ± cisRA or BRD8430 ± cisRA treatment in BE(2)-C cells. Displayed are the normalized values, luciferase:renilla, relative to the ratio in the DMSO-treated control cells. *P < 0.05, **P < 0.001 calculated using a one-way ANOVA, with Bonferroni correction, comparing each condition to DMSO. See Figure S6 for results of these experiments in a second cell line, Kelly. Error bars represent the mean ± SD of two replicates for the compound 60 experiment, and the mean ± SD of three replicates for the BRD8430 experiment.

The retinoic acid (RA) pathway is a reported target of HDAC inhibition, and the combination of a pan-HDAC inhibitor plus ATRA synergistically activates RA signaling (Epping et al., 2007). To determine if this pathway is targeted in neuroblastoma cells, the activation of a RA receptor-dependent reporter, RARE3-tk-luc, was assessed. The combinations of compound 60 plus cisRA and BRD8430 plus cisRA displayed greater activity on RARE3-tk-luc than the effects of any agent alone (Figures 7Cand S6C).

Discussion

Neuroblastoma is the most common extra-cranial solid tumor of childhood. It is a highly heterogeneous disease; some cases resolve without intervention, while others remain refractory despite aggressive treatment with chemotherapy, surgery, radiation, autologous stem cell transplantation, and consolidation with cisRA and immunotherapy (Modak and Cheung, 2010). Clinically, we have reached toxicity limits in using standard cytotoxic chemotherapy, thus alternative modalities for treating patients with high-stage neuroblastoma are greatly needed. Differentiation therapy is a strategy that has shown promise but has not been fully explored in neuroblastoma. It has been demonstrated that cisRA, a pro-differentiating agent, is beneficial when administered to patients with minimal residual disease following consolidation chemotherapy and/or autologous stem cell transplantation (Matthay et al., 1999). However, it has not proven beneficial in patients with measurable disease (Kohler et al., 2000). In another disease, APL, ATRA differentiation therapy has been a highly effective front-line treatment (Abdel-Wahab and Levine, 2010; Ades et al., 2010). Consequently, the identification of novel differentiating agents to be used in treating patients with neuroblastoma, either alone or in combination with cisRA, is warranted.

However, efforts to identify new differentiation agents have been hampered due to minimal industry interest in leading such efforts, lack of high-throughput phenotypic assays to measure neuroblast maturation, and limited chemical diversity in current combinatorial libraries. We sought to overcome these challenges by integrating the screening of a structurally diverse, small-molecule library with a gene expression-based differentiation assay. We identified a 59-gene signature for the differentiation of neuroblastoma cells, adapted it to the GE-HTS platform, and screened a DOS library of small molecules. Through our screening efforts, we identified a novel pro-differentiating compound, BRD8430.

The structure of BRD8430 includes a nine-membered lactam, para-ether dimethylaniline, defined stereochemistry at three positions, and an ortho-amino aniline functional group that imparts HDAC-inhibitory activity. To our knowledge, this is the first study to use a gene expression signature as a read-out in a stereo/structure-activity relationship (SSAR) evaluation. The SSAR analysis revealed that the stereochemistry at the two endo-cyclic stereocenters is critical for BRD8430's activity; however, the stereochemistry at the exo-cyclic stereocenter is not. Furthermore, the size of the central ring can be reduced by one atom without affecting the activity, but changing the substitution pattern of the dimethylaniline markedly decreased activity. Gene expression data was thus successfully used to detail how structural changes to a compound influence its ability to induce a complex phenotype.

These studies revealed that the HDAC inhibitory activity of BRD8430 is essential to the induced differentiation phenotype. The acetylation status of amino acids in histone tails dictates how tightly DNA is wound and thus how accessible the DNA is to transcription factors and other gene regulatory elements (Gregory et al., 2001). High histone acetylation is associated with active transcription, while low histone acetylation is associated with gene silencing. Acetyl groups are added by histone acetyl transferases (HATs) and removed by HDACs, which includes 18 enzymes divided into four classes (I-IV). It is hypothesized that defects in neuroblastoma differentiation are related to aberrant transcriptional regulation, and HDAC inhibitors have previously been shown to induce differentiation in neuroblastoma, presumably by enhancing the active transcription of genes critical to the differentiation program (Hahn et al., 2008). HDAC inhibitors also hold promise as effective anti-cancer agents more broadly. Indeed, the HDAC inhibitors vorinostat and romidepsin are approved therapies for cutaneous T-cell lymphoma (CTCL) (Mann et al., 2007; Piekarz et al., 2009; Whittaker et al., 2010), and several other HDAC inhibitors are currently in clinical trials (Rasheed et al., 2008).

However, the present inhibitors used clinically are largely non-specific, having activity against multiple HDACs across one or more classes. Vorinostat, which has been previously reported to decrease viability and induce differentiation in neuroblastoma, inhibits HDACs 1, 2, 3, and 6 at subnanomolar concentrations and HDAC8 at a low micromolar concentration. BRD8430, although a less potent inhibitor, exhibits greater selectivity for Class I HDACs (HDAC1 > 2 > 3) over all other HDACs, and it prompted further investigation through which we uncovered HDAC1 and HDAC2 as the critical targets for the induction of neuroblastoma differentiation and attenuation of cellular viability. Because the use of relatively non-selective HDAC inhibitors causes patient toxicity, morbidity may be mitigated by increasing isoenzyme selectivity of compounds. Indeed, there is a general movement towards more selective, targeted therapies for patients with cancer, such as PI3K isoform-specific inhibitors (Kong and Yamori, 2009) and the inhibition of BRAF V600E by PLX4720 (Tsai et al., 2008). Moreover, there has been a call for HDAC1/2 selective molecules for the treatment of patients with sickle cell disease (Bradner et al., 2010a).

Combination therapy has generally been the mode for curative treatment of patients with cancer. CisRA is a logical candidate to nominate for combination testing with selective HDAC inhibition for patients with neuroblastoma. CisRA differentiation therapy has already been incorporated into the standard of care for patients with high-risk neuroblastoma, and intriguingly, in a phase I trial evaluating vorinostat ± cisRA to treat pediatric patients with solid tumors, the one complete response was observed in a patient with neuroblastoma who received the combination therapy (Fouladi et al., 2010).

Retinoids and HDAC inhibitors have non-independent mechanisms of action. In the absence of ligand, retinoid receptors bind corepressors (NCoR and SMRT), which are found within a complex containing HDAC activity, and mediate transcriptional repression. When ligand bound, retinoid receptors recruit coactivators with histone acetylase activity (HATs) leading to activated transcription (Minucci and Pelicci, 1999). Thus, both RA receptors and HDACs are involved in the regulation of RA target genes. A relevant clinical example of RA receptors and HDACs acting in concert is the defining lesion of APL (i.e. PML-RARα fusion) that blocks cellular differentiation by recruiting the NCoR/HDAC complex and represses transcription (Minucci and Pelicci, 1999). More recently, Epping et al. (2007) identified RA signaling as a target of HDAC inhibitors using a functional genetic screen. They reported that HDAC inhibition activates RA signaling, which is repressed by the expression of either retinoic acid receptor α (RARα) or preferentially expressed antigen of melanoma (PRAME), a known repressor of RA signaling (Epping et al., 2007). Moreover, they observed a synergistic induction of RAR transactivation with the combination of ATRA and an HDAC inhibitor in a heterologous reporter assay. Similarly, we observed that in neuroblastoma cells, the combination of selective HDAC1/2 and HDAC1/2/3 inhibitors plus cisRA displayed greater activity on an RA receptor-dependent reporter than the effects of either agent alone.

These studies reveal the power of integrating expression-based screening with DOS chemistry to provide new biological insights. They illuminate the role of HDAC1/2 selective inhibition in activating retinoic acid receptor signaling to induce neuroblastoma differentiation. Our findings, in conjunction with other studies, support the need to develop HDAC1/2 inhibitors for clinical application.

Significance

The intersection of genomics with chemical screening has enabled new opportunity in the discovery of small-molecule perturbagens of complex biologica state switches. We leveraged a gene expression-based screening approach to discover new compounds inducing differentiation in a highly malignant pediatric solid tumor, neuroblastoma. The integration of cisRA differentiation therapy into consolidation treatment for these pediatric patients has shown promise, but the application of differentiation therapy has not been thoroughly explored. Focusing on a collection of DOS molecules, we demonstrate the success of this chemica genomics approach in both prioritizing lead compounds for inducing neuroblastoma differentiation and as a read-out in SSAR evaluation. This screen identified a novel compound, BRD8430, as a pro-differentiating agent. BRD8430 was characterized as a Class I HDAC inhibitor (HDAC1 > 2 > 3). Through investigation of more selective compounds, HDACs 1 and 2 were demonstrated to be the key targets for induction of differentiation in neuroblastoma Furthermore, the combination of a selective HDAC1/2 inhibitor and cisRA had an augmented effect on differentiation and a synergistic effect on viability, with enhanced activation of retinoic acid signaling as a contributing mechanism to the observed synergy. The HDAC inhibitors currently used clinically are largely pan inhibitors, having activity against many of the 11 zinc-dependent HDACs. This work supports the need to develop selective HDAC1/2 inhibitors for clinical application and, more broadly, illuminates the power of integrating expression-based screening with DOS chemistry to provide new biological insights.

Experimental Procedures

Cell culture and viability assays

Neuroblastoma cell lines were maintained in DMEM (Cellgro, Manassas, VA, USA) supplemented with 10% fetal bovine serum (Sigma-Aldrich, St. Louis, MO, USA) and 1% penicillin-streptomycin with glutamine (Cellgro). BE(2)-C and SH-SY5Y were obtained from the American Type Culture Collection, and Kelly and LAN-1 were kindly provided by Dr. Rani George. The identity of all lines was verified by small tandem repeat profiling performed by the Shannon McCormack Advanced Molecular Diagnostics Laboratory at the Dana-Farber Cancer Institute (Boston, MA, USA). Cellular viability was assessed using CellTiter Glo (Promega, Madison, WI, USA) per the manufacturer's instructions.

Compounds

ATRA, cisRA, PMA, and VPA were purchased from Sigma-Aldrich. Compound 60 was synthesized by Dr. Jun Qi. DOS compounds were synthesized by the Broad Institute Chemical Biology Platform; synthetic protocols are included in Supplemental Experimental Procedures. Compounds included in the panel of non-selective and selective HDAC inhibitors (ITF-2357, vorinostat, apicidin, BRD7914, MS-275, CI-994, BRD5298, compound 60, BRD5100, BRD8148, PCI-34051, and inhibitor 106) were provided by the Broad Institute Chemical Biology Platform and Stanley Center for Psychiatric Research.

Gene Expression-based High-Throughput Screening (GE-HTS)

GE-HTS studies were performed as previously described (Peck et al., 2006; Stegmaier et al., 2004), including mRNA capture, reverse transcription, ligation-mediated amplification of the signature genes, and fluorescent bead-based detection (FlexMap Technology, Luminex, Austin, TX, USA). Probe sequences for the 59 neuroblastoma signature genes are included in Table S1. Signature performance was primarily evaluated using a weighted summed score (differentiation score) metric, calculated by dividing the expression levels of the signature genes by the mean expression of the control genes and then summing the ratios with weights and signs determined by the signal-to-noise ratio of cisRA-treated positive controls and DMSO-treated negative controls. As with other expression profiling platforms, scores can differ across experiments secondary to multiple features, including instrument variability, the dynamic nature of transcriptional alterations, and the bidirectional nature of the changes measured. Furthermore, genes that perform poorly in control conditions are omitted from the analysis on an experiment-by-experiment basis, leading to variation in the signature assessed. Finally, data from the low-throughput GE-HTS experiments did not undergo the same normalization as data from the larger screens, leading to variability in the absolute differentiation scores between experiments.

DOS library screen

BE(2)-C cells were plated at 2,000 cells per well in 384-well plates with 2 nM cisRA added as a differentiation enhancer. 1,916 compounds from the DOS library were added in duplicate by pin transfer to a final concentration of 10 μM. Each plate included 32 wells treated with 1 μM cisRA as the positive control and 32 wells treated with DMSO as the negative control. In addition, a control plate with a cisRA dose response was included in each run. After two days of incubation, the GE-HTS assay was performed.

The screen data were analyzed as follows. The control gene N4BP1 was used to eliminate poorly performing wells from the analysis. For the plate-by-plate analysis, we removed wells with an N4BP1 level greater than three median absolute deviations (MADs) from the median N4BP1 value of the DMSO-treated wells in that plate. For median-scaling analysis, we removed wells with an N4BP1 level greater than two MADs from the median N4BP1 value of the DMSO-treated wells across all the plates from each run. We then made a ratio of each marker gene to the mean of the eight reference genes within that well. For median-scaling analysis, plate-to-plate variability was corrected by median scaling. We normalized all of the plates by scaling each up- and down-regulated gene independently based on its median expression in the cisRA-treated and DMSO-treated wells, respectively, on each plate. The summed scores (sum of the expression ratios with the sign determined by the expected direction of regulation) were individually transformed into robust Z scores by using themedian and MAD of the chemical- and DMSO-treated wells together, including either all of the wells in a plate (plate-by-plate analysis) or all of the wells in a run (median-scaling analysis). To identify initial hits, we selected compounds for which both replicates had a robust Z score higher than three. Five additional metrics were used to identify pro-differentiating compounds: summed score, weighted summed score, K-nearest neighbor, naïve Bayes, and support vector machine (Hahn et al., 2009).

Thirty-two DOS compounds were selected to be retested at eight concentrations in duplicate in BE(2)-C cells with 2 nM cisRA as a differentiation enhancer, 1 μM cisRA as the positive control (32 wells per plate) and DMSO as the negative control (36 wells per plate). A control plate with a cisRA dose response was included in each run. The GE-HTS assay was performed after two days of incubation. The data were analyzed as above.

Area under the curve calculation

To quantize the relative efficacy of the compounds, total activity was summarized using the Area Under the Curve (AUC), defined as the area between the response curve and the zero score level (defined by the average differentiation score in DMSO-treated negative control wells). AUC was calculated using the R system for statistical computing (R Development Core Team, 2006, http://www.R-project.org) by taking the cubic natural spline for 50 points spread evenly across the log dose curve, summing up the areas of the 49 trapezoids formed between the 50 spline points and the zero response line, and normalizing the value by dividing by the range of log concentrations. As the AUC is a measurement summarizing the differentiation score across a concentration range, absolute AUC values suffer the same challenges as the differentiation score and cannot be compared directly between experiments, but can be used within an experiment to assess the relative activity of compounds.

Protein extraction and immunoblotting

For whole cell protein extraction, cells were lysed with Cell Signaling Lysis Buffer (Cell Signaling Technology, Danvers, MA, USA) containing Complete, EDTA-free Protease Inhibitor Cocktail (Roche Diagnostics, Mannheim, Germany) and PhosSTOP Phosphatase Inhibitor (Roche Diagnostics). Nuclear protein extractions were performed using the cytoplasmic and nuclear extraction kit from Thermo Scientific (Rockford, IL, USA). Immunoblots were run as previously described (Banerji et al., 2012). Primary antibodies included anti-HDAC1 (Abcam ab7028, Cambridge, MA, USA), anti-HDAC2 (Abcam ab7029), anti-Vinculin (Abcam ab18058), and anti-acetylated histone H3 (Millipore 06-599, Billerica, MA, USA).

HDAC activity assay

HDAC1-9 activity was determined in vitro using an optimized homogenous assay performed in a 384-well plate (Bradner et al., 2010b). Compound was incubated with recombinant, full-length HDAC protein (BPS Biosciences, San Diego, CA, USA) for 3 hours prior to enzymatic reactions. The reactions were carried out with fluorophore conjugated substrate, MAZ1600 and MAZ1675, at Km = [S] (MAZ1600: 21 μM for HDAC1, 22 μM for HDAC2, 9 μM for HDAC3, 9 μM for HDAC6; MAZ1675: 10 μM for HDAC4, 40 μM for HDAC5, 22 μM for HDAC7, 282 μM for HDAC8, 26 μM for HDAC9). Reactions were performed in assay buffer (50 mM HEPES, 100 mM KCl, 0.001% Tween-20, 0.05% BSA, 200 μM TCEP, pH 7.4) and followed for fluorogenic release of 7-amino-4-methylcoumarin from substrate upon deacetylase and trypsin enzymatic activity. Fluorescence measurements were obtained every five minutes using a multilabel plate reader and plate-stacker (Envision; Perkin-Elmer, Waltham, MA, USA). Each plate was analyzed by plate repeat, and the first derivative within the linear range was imported into analytical software (Spotfire DecisionSite and GraphPad Prism). Replicate experimental data from incubations with inhibitor were normalized to DMSO controls ([DMSO] < 0.5%). IC50 is determined by logistic regression with unconstrained maximum and minimum values.

Immunofluorescence

BE(2)-C cells were treated in duplicate with either vehicle (DMSO) or the indicated compound concentration. After 72 hours, cell were washed, fixed (4% formaldeyhyde), permeabilized (0.2% Triton-X 100) and stained with a monoclonal antibody to NF-M (Santa Cruz Biotechnology sc20013) and species-specific secondary antibody linked to Alexa Fluor 568 (Invitrogen, Carlsbad, CA, USA). Slides were mounted with Prolong® Gold antifade reagents and counterstained with DAPI (Invitrogen).

siRNA studies

BE(2)-C and Kelly cells seeded in 6-well plates were transfected with siGENOME SMARTpool siRNAs from Dharmacon targeting HDAC1 (Thermo Scientific M-003493-02-0005), HDAC2 (Thermo Scientific M-003495-02-0005), or a negative control, non-targeting siRNA pool (Thermo Scientific D-001206-13-05) following the manufacturer's protocol. Briefly, we used 4 μL of Dharmafect Transfection Reagent I (Thermo Scientific T-2001) per well and a final concentration of 45 nM siRNA. After 48 hours, cells were harvested, counted, and replated in 384-well plates for viability and GE-HTS assays. Protein was collected to evaluate knockdown.

Dual reporter assay

BE(2)-C or Kelly cells were co-transfected with RARE3-tk-luc (de The et al., 1990) (kindly provided by Dr. Daniel G. Tenen) and pUbC-RL plasmids using Fugene 6 transfection reagent per the manufacturer's instructions (Roche). In the compound 60 experiments, the cells were harvested, counted, and re-plated in a 96-well plate 24 hours post-transfection, and then compounds were added. In the BRD8430 experiments, the cells were transfected in 96-well plates and thus were not re-plated before compound addition. Twenty-four hours later, levels of firefly luciferase and renilla luciferase were detected using the Dual Luciferase Reporter Assay System (Promega).

Statistical analyses

Statistical significance was determined by one-way ANOVA with Bonferroni correction when comparing more than two unmatched groups, and by two-way repeated-measures ANOVA with Bonferroni correction when comparing more than two unmatched groups over a time course. Analyses were done in GraphPad Prism 5.

Supplementary Material

01

Highlights.

  • Designed a complex gene-expression signature for neuroblastoma differentiation.

  • Screened a diversity oriented synthesis library for signature induction.

  • Identified a novel Class I HDAC inhibitor (HDAC1>2>3) as a differentiating agent.

  • Demonstrated in vitro efficacy of HDAC1/2 inhibitor + cisRA combination treatment.

Acknowledgments

We thank Rani George for providing neuroblastoma cell lines, Daniel G. Tenen for providing the reporter plasmid, and Brian Crompton and Aaron Thorner for their technical assistance. This work was funded by the Friends for Life Fellowship (KS), the Claudia Adams Barr Program in Cancer Research (KS), and a Howard Hughes Medical Institute Physician-Scientist Early Career Award (KS). The project has been funded in part with Federal funds from the National Cancer Institute's Initiative for Chemical Genetics, National Institutes of Health, under Contract No. N01-CO-12400. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Service, nor does mention of trade names, commercial products or organizations imply endorsement by the U.S. Government. This work was funded in part by the NIGMS-sponsored Center of Excellence in Chemical Methodology and Library Development (Broad Institute CMLD; P50 GM069721), as well as the NIH Genomics Based Drug Discovery U54 grants Discovery Pipeline RL1CA133834 (administratively linked to NIH Grants RL1HG004671, RL1GM084437, and UL1DE019585).

Footnotes

The authors have declared that no conflict of interest exists.

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