Purpose:

Histone deacetylase inhibitors (HDACi) are epigenome-targeting small molecules approved for the treatment of cutaneous T-cell lymphoma and multiple myeloma. They have also demonstrated clinical activity in acute myelogenous leukemia, non–small cell lung cancer, and estrogen receptor–positive breast cancer, and trials are underway assessing their activity in combination regimens including immunotherapy. However, there is currently no clear strategy to reliably predict HDACi sensitivity. In colon cancer cells, apoptotic sensitivity to HDACi is associated with transcriptional induction of multiple immediate-early (IE) genes. Here, we examined whether this transcriptional response predicts HDACi sensitivity across tumor type and investigated the mechanism by which it triggers apoptosis.

Experimental Design:

Fifty cancer cell lines from diverse tumor types were screened to establish the correlation between apoptotic sensitivity, induction of IE genes, and components of the intrinsic apoptotic pathway.

Results:

We show that sensitivity to HDACi across tumor types is predicted by induction of the IE genes FOS, JUN, and ATF3, but that only ATF3 is required for HDACi-induced apoptosis. We further demonstrate that the proapoptotic function of ATF3 is mediated through direct transcriptional repression of the prosurvival factor BCL-XL (BCL2L1). These findings provided the rationale for dual inhibition of HDAC and BCL-XL, which we show strongly cooperate to overcome inherent resistance to HDACi across diverse tumor cell types.

Conclusions:

These findings explain the heterogeneous responses of tumor cells to HDACi-induced apoptosis and suggest a framework for predicting response and expanding their therapeutic use in multiple cancer types.

Translational Relevance

The study identifies a novel mechanism by which HDAC inhibitors induce apoptosis in tumor cells through induction of the ATF3 transcription factor and subsequent repression of BCL-XL. This mechanism transcends tumor type, is measurable in patient samples in vivo, and defines the basis for sensitivity or resistance to HDAC inhibitors. These findings establish a strategy for overcoming inherent resistance to HDACi by rational combination with BCL-XL inhibitors, and define a framework for the identification of biomarkers predictive of HDACi response, including rapid assessment of ATF3 induction. These findings have the potential to directly affect the clinical use of HDACi for the approved indications of cutaneous T-cell lymphoma and multiple myeloma and for their ongoing clinical development in multiple malignancies.

Histone deacetylase inhibitors (HDACi) are epigenome-targeting anticancer therapeutics with established clinical activity in several hematological malignancies (1). A number of distinct chemical classes of HDACi have been identified or developed including short-chain fatty acids (butyrate, valproic acid), hydroxamic acids (trichostatin A, vorinostat, belinostat, panobinostat, and pracinostat), tetrapeptides (romidepsin), and benzamidines (entinostat; ref. 2). Vorinostat and romidepsin are approved for the treatment of cutaneous T-cell lymphoma (CTCL; ref. 3), and belinostat is approved for the treatment of peripheral T-cell lymphoma (PTCL). In addition, combinatorial use of panobinostat with the proteasome inhibitor bortezomib is approved for refractory multiple myeloma (4), and pracinostat was recently granted breakthrough therapy designation with azacytidine in acute myelogenous leukemia (AML; ref. 5). Although responses to single-agent HDACi are limited in solid tumors (6), studies in non–small cell lung cancer and estrogen receptor–positive advanced breast cancer suggest they may have efficacy in combination therapy regimens (7, 8).

HDACis inhibit class I (HDACs 1, 2, 3, and 8) and class II HDACs (HDACs 4, 5, 6, 7, 9, and 10), which deacetylate lysine residues on target proteins (2). HDACis activate gene expression by inducing hyperacetylation of DNA-bound core histones, thereby increasing accessibility of the core transcriptional apparatus to DNA (1), or by hyperacetylating transcription factors, which can either increase or decrease their transcriptional activity (1). In addition, HDACi can elicit cellular effects independent of transcription by acetylating cytoplasmic proteins such as Hsp90 and tubulin (9, 10).

Although HDACis induce multiple effects on tumor cells, including inhibiting proliferation and inducing differentiation (1), their primary mechanism of antitumor activity is through the induction of apoptosis (2). In this regard, HDACis induce apoptosis primarily through the intrinsic/mitochondrial pathway (11), although in some tumor cell lines, the extrinsic/death receptor pathway is also activated (12, 13). HDACi-induced apoptosis has been linked with altered expression of key apoptotic regulators including upregulation of the proapoptotic molecules BAX (14), BAK (15), APAF1 (16), BMF (17), BIM (18), and DR5 (19), and downregulation of the antiapoptotic proteins SURVIVIN (20), BCL-XL (21), and c-FLIP (22). However, HDACi regulation of these factors varies between cell type, and has not been systematically linked to apoptotic response (23). Furthermore, the mechanisms by which HDACis regulate the expression of pro- and antiapoptotic genes are only partially understood.

We previously identified a robust transcriptional response specifically associated with HDACi-induced apoptosis in colorectal cancer cell lines. This response involved the coordinate induction of multiple immediate-early (IE) response genes (FOS, JUN, EGR1, EGR3, ATF3, ARC, and NR4A1) and stress response genes (NDRG4, MT1E, MT1F, and GADD45B; ref. 24). The goals of this study were to determine whether this represents a generic transcriptional response that defines HDACi-induced apoptosis across tumor types, including CTCL and multiple myeloma where these agents currently have the greatest clinical activity. Second, we sought to determine whether this transcriptional response underpins HDACi-induced apoptosis by regulating expression of key apoptotic regulators.

Herein, we demonstrate that HDACis robustly induce expression of the IE genes FOS, JUN, and ATF3 in multiple tumor cell types, which correlated significantly with the magnitude of HDACi-induced apoptosis. We also demonstrate induction of these genes in 2 patients with CTCL treated with panobinostat. Functional studies revealed that ATF3 but not FOS or JUN was required for HDACi-induced apoptosis across tumor cell lines, and that the effects of ATF3 were mediated through repression of the prosurvival gene BCL-XL (BCL2L1). These data provided a rationale for combining HDAC and BCL-XL inhibitors, which successfully overcame inherent resistance to HDACi in a range of tumor types. Our findings establish the induction of ATF3 and subsequent repression of BCL-XL as a consistent and key determinant of HDACi-induced apoptosis independent of tumor type. They also define the molecular basis for differential sensitivity to HDACi and identify avenues for predicting response and overcoming inherent resistance to HDACi through rational combination therapy.

Cell culture

All cell lines used for this study were obtained from the American Type Tissue Culture Collection or as gifts from collaborators listed in the Acknowledgments section. A total of 50 human cancer cell lines derived from multiple tumor types were used: Solid tumor cell lines used were PC-3, DU-145, LNCAP (prostate); HT-1197, HT-1376, 5637 (bladder); SK-MEL-3, SK-MEL-5, SK-MEL-28 (melanoma); MDA-MB-231, MDA-MB-468, MCF-7 (breast); A549, NCI-H292, NCI-H460, NCI-H358, NCI-H1650, NCI-H1975 (lung); RKO, LIM1215, Colo320, SW48, HCT116, SW948 (colon), IGROV1, SK-OV-3, JAM, OVCAR-8, OVCAR-5 (ovarian), OU-87 (glioblastoma); PANC-1 (pancreatic); ACHN (renal); 293T (embryonic kidney); A431 (epidermis); AGS (gastric), and Hep3B (hepatoma). Hematologic cancer cell lines used were HH, HuT-78, HuT-102, MJ (cutaneous T-cell lymphoma); Jurkat, Raji, U937 (lymphoma); LP-1, OPM-2, RPMI-8226, U266 (multiple myeloma); and K-562, KG-1, and KG-1A (leukemia). Cells were maintained at 37°C and 5% CO2 in base medium DMEM for solid tumor cell lines or RPMI for hematogic cancer cell lines. Base medium was supplemented with 10% FCS, 2 mmol/L l-glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin. Wild-type and Atf3−/− mouse embryonic fibroblasts were maintained in low-glucose DMEM supplemented with 10% FCS, 2 mmol/L l-glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin at 37°C in 10% CO2. Methods for cell maintenance have been previously described (25). WT and FLAG-tagged hBCL-XL–transduced mouse embryonic fibroblasts were maintained in DMEM, high-glucose media supplemented with 10% (v/v) FBS, 250 μmol/L l-asparagine, 50 μmol/L 2-mercaptoethanol, and 1 μmol/L HEPES. Cell lines were assessed for mycoplasma status using the MycoAlert assay (Lonza) and mycoplasma-negative frozen stocks used for a maximum of 2 months. Authenticity of frozen stocks of the A549, AGS, HCT116, PC3, U87, RPMI-8226, SKMEL28, MCF7, PANC1, HH, RKO, LIM1215, Colo320, SW48, and SW948 cell lines was determined by short-tandem repeat profiling using the GenePrint 10 system (Promega), and all found to be exact matches with published profiles.

Drug source

Sodium-butyrate (NaBu) and valproate were obtained from Sigma. Vorinostat, belinostat, depsipeptide, entinostat, ABT-737, and ABT-199 were obtained from Selleck Chemicals. ABT-263 was obtained from ApexBio. Synthesis of A-1331852 was as described previously (26).

Measurement of apoptosis

Apoptosis assays were performed as previously described by propidium iodide (PI) staining and FACS analysis (25). Cells were seeded in triplicate in 24-well plates. Seeding densities varied between 30,000 and 90,000 cells per well and were calculated such that control cell density approximated 80% confluence at the completion of the experimental period. Drug treatment was performed for 24 to 72 hours. Both attached and floating cells were harvested by scraping, washed in cold PBS, and resuspended in 50 μg/mL PI, 0.1% sodium citrate, and 0.1% Triton X-100. Cells were stained overnight at 4°C, and 10,000 cells were analyzed for DNA content using a BD FACS Canto II (BD Biosciences). The percentage of cells with a subdiploid DNA content was quantified using ModFit LT (Verity Software House).

Clinical trial samples

Whole blood was collected in sodium-heparin tubes from 2 patients diagnosed with cutaneous T-cell lymphoma who participated in a single-arm, open-label, institutional phase II panobinostat trial (Clinicaltrials.gov identifier: NCT01658241). Patients received 30 mg panobinostat orally, 3 times weekly for up to 4 weeks. Both patients had >70% tumor involvement in peripheral blood mononuclear cells (PBMC). PBMCs were isolated by density centrifugation (Lymphoprep), according to the manufacturer's instructions. RNA from PBMC was purified and subjected to gene expression analysis using qRT-PCR. The clinical protocol, informed consent form, and other relevant study documentation were approved by the Institutional Review Board of the Peter MacCallum Cancer Centre. All patients gave written informed consent prior to study entry.

Quantitative RT-PCR

Total RNA was extracted using the RNeasy Mini Kit (Qiagen) and reverse-transcribed using random hexamers and the Transcriptor High Fidelity cDNA Synthesis Kit (Roche), according to the manufacturer's instructions. Quantitative RT-PCR was performed using Power SYBR Green PCR Master Mix (Applied Biosystems) on a 7500 Fast Real-Time PCR System (Applied Biosystems) according to the manufacturer's instructions. cDNA (10 ng) was amplified with 75 nmol/L forward and reverse primers in a 15 μL reaction. Primers used are listed in Supplementary Table S1.

Western blot

Western blot analysis was performed as previously described (27). The source and dilutions of antibodies used are as follows: Rabbit anti-ATF3 (sc-188, Santa Cruz Biotechnology, 1:1,000), rabbit anti-FOS (cst-4384, Cell Signaling Technology, 1:1,000), mouse anti–c-JUN (cst-2315, Cell Signaling Technology, 1:1,000), rabbit anti–Ac Histone H3 (06-599, Merck Millipore, 1:10,000), goat anti–Histone H3 (sc8654, Santa Cruz Biotechnology, 1:5,000), rabbit anti–beta Tubulin (ab6046, Abcam, 1:20,000), mouse anti-actin (A5316, SIGMA, 1:10,000), and rabbit–anti-BCL-XL (54H6, Cell Signaling Technology, 1:1,000 rat anti-FLAG antibody [WEHI, clone 9H1, 1:2500]).

Plasmids and luciferase reporter assays

The ATF3 overexpression vector was provided by Dr. Dakang Xu at Monash University (28). The AP-1 reporter construct was obtained from Clontech, Sp1/Sp3 reporter constructs were provided by Dr. Yoshihiro Sowa (Kyoto Prefectural University of Medicine), and pGL3-BCL-XL reporter constructs were kindly provided by Dr. Ni Chen, Sichuan University, Chengdu, China (29).

Cell lines were transiently transfected with reporter constructs using the Lipofectamine 2000 transfection reagent (Invitrogen). Transfected cells were treated with HDACi for 24 to 48 hours and luciferase reporter activity determined using the dual-luciferase reporter assay Kit from Promega. Due to the strong effects of HDCAi treatment on TK-Renilla luciferase activity, reporter activity was normalized to total protein.

RNAi-mediated knockdown

siRNAs targeting FOS, JUN, ATF3, and BCL-XL were obtained from Dharmacon. siRNA transfection was performed using Lipofectamine RNAiMAX (Invitrogen) according to the manufacturer's instruction. Cells were harvested 24, 48, or 72 hours after transfection for subsequent analysis.

Xenograft studies

Animal studies were performed with the approval of the Austin Health Animal Ethics Committee. Eight-week-old female BALB/c nu/nu mice weighing approximately 16 g were obtained from the Australian Resources Centre (ARC). U87 cells (3 × 106 cells) were injected subcutaneously into the right and left flank of each animal in a 150 μL suspension consisting of a 1:1 mixture of DMEM (Invitrogen) and BD Matrigel Basement Matrix (BD Biosciences). Once palpable tumors developed, mice were randomized into four groups to receive either vehicle [DMSO by intraperitoneal injection, and Phosal50 (60% Phosal PG, 30% PEG400, and 10% EtOH) by oral gavage], 50 mg/kg vorinostat via intraperitoneal injection, 25 mg/kg ABT-263 via oral gavage, or the combination. Mice were treated daily for 19 days. Tumor growth was monitored every second day by calliper measurement until the end of the experimental period or when tumors reached 1 cm3 in size. At this point, animals were euthanized, and tumors were excised and weighed.

Statistical analysis

In all cases, groups were compared using the Student's t test, with P < 0.05 considered to be statistically significant. Correlation analyses were performed using Pearson's correlation with P < 0.05 considered statistically significant.

HDACi sensitivity spectrum of human cancer cells

To identify the molecular mechanisms underlying HDACi-induced apoptosis, we first stratified vorinostat-induced apoptotic responses in 50 human cancer cell lines representing common tumor types, including those displaying significant clinical response to HDACi (CTCL, multiple myeloma, leukemia, breast, and lung cancers; refs. 3, 7, 8). Sensitivity of the cell lines to vorinostat was highly variable (ranging from 2.5% apoptosis in U87 cells to 97.4% in RPMI-8226 cells), enabling separation into strong or weak responders (Fig. 1A). As observed clinically (3), vorinostat more potently induced apoptosis in hematologic cell lines (Fig. 1B). Among the solid tumor models, ovarian cancer lines were most sensitive, whereas prostate lines were most resistant (Fig. 1B). This spectrum of antitumor responses was replicated using NaBu, a member of the short-chain fatty acid subclass of HDACi (Fig. 1C and D). Differential sensitivity to HDACi was not due to differences in the extent of HDAC inhibition, as histone H3 acetylation was similarly increased by vorinostat in representative sensitive and resistant lines (Supplementary Fig. S1).

Figure 1.

A, Apoptotic sensitivity of 50 cancer cell lines to vorinostat. Cells were treated with drug for 72 hours and apoptosis determined by propidium-iodide (PI) staining and FACS analysis. Cell lines within each tumor type are ordered by increasing sensitivity. Values shown are mean ± SEM from two independent experiments, each performed in triplicate. B, Separation of the 50 cell lines into solid vs. hematologic cancer cell lines. C, Apoptotic sensitivity of 50 cell lines to sodium-butyrate (5 mmol/L, NaBu). Apoptosis was assessed as for vorinostat. D, Pearson's correlation of vorinostat and NaBu-induced apoptosis across the 50 cell lines.

Figure 1.

A, Apoptotic sensitivity of 50 cancer cell lines to vorinostat. Cells were treated with drug for 72 hours and apoptosis determined by propidium-iodide (PI) staining and FACS analysis. Cell lines within each tumor type are ordered by increasing sensitivity. Values shown are mean ± SEM from two independent experiments, each performed in triplicate. B, Separation of the 50 cell lines into solid vs. hematologic cancer cell lines. C, Apoptotic sensitivity of 50 cell lines to sodium-butyrate (5 mmol/L, NaBu). Apoptosis was assessed as for vorinostat. D, Pearson's correlation of vorinostat and NaBu-induced apoptosis across the 50 cell lines.

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HDACis induce sustained IE gene expression in multiple tumor cell types and in CTCL patients in vivo

Using our comprehensive profile of HDACi-induced apoptosis, we next investigated the mechanisms likely to underpin HDACi response across multiple cancers. Based on our prior findings in colon cancer cells (24), we investigated whether the induction of the IE genes FOS, JUN, ATF3, EGR1, EGR3, and GADD45B is a general consequence of HDACi treatment, independent of tumor type. Using eight HDACi-sensitive cell lines representing solid and hematologic cancers, we found that vorinostat robustly induced these genes by 2- to 10-fold within 2 hours, and sustained their expression over 48 hours (Fig. 2A). Dose-dependent induction of these genes was confirmed in SK-MEL-28 (melanoma) and MCF7 (breast) cells (Fig. 2B), and corresponding increase in protein expression of c-FOS, c-JUN, and ATF3 was confirmed in 5 sensitive cell lines (Fig. 2C). Induction of this transcriptional response was independent of HDACi chemical subclass as FOS, JUN, ATF3, EGR1, EGR3, and GADD45B were also induced in the HH CTCL cell line treated with panobinostat, belinostat, depsipeptide, entinostat, and valproic acid (Supplementary Fig. S2).

Figure 2.

A, Effect of vorinostat on FOS, JUN, ATF3, EGR1, EGR3, and GADD45B mRNA expression in 8 HDACi-sensitive cell lines. Cells were treated with 5 μmol/L vorinostat for 2 to 48 hours and gene expression determined by quantitative real-time PCR. Values shown are average Log2 fold induction from three biological experiments represented in a heat map. B, Effect of vorinostat dose escalation on FOS, JUN, ATF3, EGR1, EGR3, and GADD45B mRNA expression in 2 representative HDACi-sensitive cell lines (SK-MEL-28 and MCF7). Values shown are average Log2 fold induction from a representative experiment performed in triplicate. C, Effect of vorinostat (Vorino 5 μmol/L) treatment on FOS, JUN, and ATF3 protein expression in 5 representative HDACi-sensitive cell lines. D, Effect of panobinostat on FOS, JUN, ATF3, EGR1, EGR3, and GADD45B mRNA expression in PBMCs isolated from 2 CTCL patients. Samples were collected before and 4 hours after panobinostat treatment. Values shown are mean ± SEM of the Log2 fold change in post- versus pretreated samples analyzed in triplicate. E, Correlation of the magnitude of change in expression of FOS, JUN, ATF3, EGR1, EGR3, and GADD45B with apoptosis following vorinostat (5 μmol/L) treatment across the 50 cell lines. The magnitude of gene induction was determined in each cell line 24 hours after HDACi treatment by qRT-PCR.

Figure 2.

A, Effect of vorinostat on FOS, JUN, ATF3, EGR1, EGR3, and GADD45B mRNA expression in 8 HDACi-sensitive cell lines. Cells were treated with 5 μmol/L vorinostat for 2 to 48 hours and gene expression determined by quantitative real-time PCR. Values shown are average Log2 fold induction from three biological experiments represented in a heat map. B, Effect of vorinostat dose escalation on FOS, JUN, ATF3, EGR1, EGR3, and GADD45B mRNA expression in 2 representative HDACi-sensitive cell lines (SK-MEL-28 and MCF7). Values shown are average Log2 fold induction from a representative experiment performed in triplicate. C, Effect of vorinostat (Vorino 5 μmol/L) treatment on FOS, JUN, and ATF3 protein expression in 5 representative HDACi-sensitive cell lines. D, Effect of panobinostat on FOS, JUN, ATF3, EGR1, EGR3, and GADD45B mRNA expression in PBMCs isolated from 2 CTCL patients. Samples were collected before and 4 hours after panobinostat treatment. Values shown are mean ± SEM of the Log2 fold change in post- versus pretreated samples analyzed in triplicate. E, Correlation of the magnitude of change in expression of FOS, JUN, ATF3, EGR1, EGR3, and GADD45B with apoptosis following vorinostat (5 μmol/L) treatment across the 50 cell lines. The magnitude of gene induction was determined in each cell line 24 hours after HDACi treatment by qRT-PCR.

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To determine if HDACis induce IE genes in a clinical context, we assessed their expression before and after 4-hour panobinostat treatment in 2 patients with CTCL enrolled in an institutional phase II panobinostat trial (Clinicaltrials.gov identifier: NCT01658241). Both patients had >70% tumor load in their PBMCs and received 30 mg panobinostat orally. As in cell lines, panobinostat robustly induced IE genes in PBMCs in both patients establishing induction of this transcriptional response as a clinically detectable consequence of HDACi therapy (Fig. 2D).

HDACi-induced apoptosis correlates with the magnitude of IE gene induction independent of tumor type

We next examined if HDACi-induced apoptosis was coupled to the magnitude of IE gene induction by assessing HDACi induction of this transcriptional response in all 50 cell lines. Vorinostat-induced apoptosis across the 50 cell lines correlated significantly with the corresponding magnitude of FOS, JUN, and ATF3 induction, but not EGR1, EGR3, or GADD45B (Fig. 2E). Similar results were observed following treatment of the 50 cell lines with NaBu (Supplementary Fig. S3A). The preferential induction of FOS, JUN, and ATF3 in HDACi-sensitive cell lines was confirmed at the protein level in 2 representative sensitive and resistant cell lines, derived from different tumor types (Supplementary Fig. S3B).

FOS, JUN, and ATF3 encode members of the AP-1 family of transcription factors, which control transcription when bound to specific DNA sequences as homo- or heterodimers (30). To determine if induction of these genes by HDACi causes AP-1 activation and if the magnitude of AP-1 activation is associated with apoptotic sensitivity, AP-1 reporter gene assays were performed on 5 representative HDACi-sensitive and -resistant cell lines derived from multiple tumor types. Consistent with the preferential induction of FOS, JUN, and ATF3 in sensitive lines, HDACi induction of AP-1 reporter activity was significantly higher in the sensitive cell lines (Supplementary Fig. S3C).

Finally, we have previously demonstrated that the Sp1 and Sp3 transcription factors are required for HDACi induction of IE gene expression, and that HDACis preferentially induce Sp1/Sp3 reporter activity in HDACi-sensitive colon cancer cell lines (24). To determine if the differential induction of IE genes is linked to differential activation of Sp1/Sp3 transcription factors independent of tumor type, the 5 HDACi-sensitive and -resistant cell lines derived from different tumor types were transfected with an Sp1/Sp3 reporter construct and treated with vorinostat for 24 hours. Consistent with the findings in colon cancer cells, HDACi induction of Sp1/Sp3 reporter activity was significantly higher in sensitive cell lines, suggesting preferential activation of these transcription factors mediates IE gene induction independent of tumor type (Supplementary Fig. S3D).

ATF3 is required for HDACi-induced apoptosis

To define the contributions of c-FOS, c-JUN, and ATF3 to HDACi-induced apoptosis, expression of each of these AP-1 proteins was knocked down in three HDACi-sensitive cell lines. We found that only ATF3 depletion was sufficient to attenuate HDACi-induced apoptosis (Fig. 3A and B). These effects were confirmed using multiple ATF3-targeting siRNAs (Supplementary Fig. S4). To test the role of ATF3 in HDACi-induced apoptosis in a different model, mouse embryonic fibroblasts (MEF) derived from wild-type and Atf3 knockout mice were treated with HDACi. As expected, vorinostat induced ATF3 mRNA only in wild-type MEFs (Fig. 3C). Atf3−/− MEFs were significantly less responsive to vorinostat and NaBu-induced apoptosis than wild-type cells (Fig. 3D and E), collectively implicating ATF3 as a key mediator of HDACi-induced apoptosis in multiple cell types.

Figure 3.

Effect of FOS, JUN, and ATF3 knockdown on HDACi-induced apoptosis. HDACi-sensitive cell lines (A549, AGS, and HCT116) were transiently transfected with a nontargeting siRNA or FOS, JUN, or ATF3-targeting siRNAs, and treated with vorinostat (5 μmol/L) for 24 hours. A, Knockdown efficiency of FOS, JUN, and ATF3 protein; B, corresponding apoptotic responses determined by PI staining and FACS analysis. Values shown are mean ± SD from a representative experiment performed in triplicate. C, Induction of Atf3 mRNA following 24-hour vorinostat (5 μmol/L) treatment of WT and Atf3−/− MEFs. D and E, Corresponding apoptotic response to 72-hour (D) vorinostat and (E) sodium-butyrate treatment. Values shown are mean ± SEM from three biological experiments performed in triplicate. *, P < 0.05, unpaired t tests.

Figure 3.

Effect of FOS, JUN, and ATF3 knockdown on HDACi-induced apoptosis. HDACi-sensitive cell lines (A549, AGS, and HCT116) were transiently transfected with a nontargeting siRNA or FOS, JUN, or ATF3-targeting siRNAs, and treated with vorinostat (5 μmol/L) for 24 hours. A, Knockdown efficiency of FOS, JUN, and ATF3 protein; B, corresponding apoptotic responses determined by PI staining and FACS analysis. Values shown are mean ± SD from a representative experiment performed in triplicate. C, Induction of Atf3 mRNA following 24-hour vorinostat (5 μmol/L) treatment of WT and Atf3−/− MEFs. D and E, Corresponding apoptotic response to 72-hour (D) vorinostat and (E) sodium-butyrate treatment. Values shown are mean ± SEM from three biological experiments performed in triplicate. *, P < 0.05, unpaired t tests.

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HDACi-induced ATF3 represses the prosurvival factor BCL-XL

HDACi-induced apoptosis has been linked with altered expression of regulators of both the intrinsic and extrinsic apoptotic pathways; however, the majority of studies indicate a dominant role for the intrinsic (mitochondrial) pathway (2, 31, 32). To determine if ATF3 induction plays a role in altering expression of the key regulators of this pathway, we first determined the effect of HDACi treatment on expression of all known components of the intrinsic apoptotic pathway in 15 cell lines spanning a range of tumor types and HDACi sensitivities. HDACi significantly induced expression of BIM, BIK, BMF, and NOXA (PMAIP1) and downregulated expression of BCL-w (BCL2L2) in all cell lines, independent of apoptotic response (Supplementary Fig. S5). We next investigated if altered expression of any components of the intrinsic apoptotic pathway correlated with the magnitude of HDACi-induced apoptosis and the magnitude of HDACi induction of ATF3. This analysis identified BCL-XL (BCL2L1) as a candidate ATF3-repressed gene, whose expression was inversely correlated with both the magnitude of HDACi-induced apoptosis and HDACi induction of ATF3 (Fig. 4A and B). Consistent with changes in its transcript levels, BCL-XL protein was also preferentially repressed by HDACi in sensitive cell lines (Supplementary Fig. S6).

Figure 4.

A, Pearson's correlation of the magnitude of repression of BCL-XL versus induction of apoptosis following HDACi treatment across 15 cell lines. B, Pearson's correlation showing the inverse relationship between the magnitude of induction of ATF3 and the repression of BCL-XL mRNA following HDACi treatment across 15 cell lines. C, BCL-XL promoter reporter constructs used including location of putative AP-1– and CREB-binding sites and regions (R) amplified in chromatin immunoprecipitation (ChIP) analyses. UPS (upstream). D, HCT116 cells were transiently transfected with a series of BCL-XL promoter reporter constructs and treated with vorinostat (Vor) or panobinostat (Pan) for 24 hours. Luciferase activity was corrected for total cellular protein. E, Effect of ATF3 knockdown on HDACi-mediated repression of the BCL-XL P1281 promoter activity. Cells were transiently transfected with nontargeting or ATF3-targeting siRNAs overnight and treated with vorinostat for 24 hours. F, Effect of ATF3 overexpression on BCL-XL promoter activity. HCT116 cells were transiently transfected with BCL-XL luciferase reporter constructs of varying lengths and an ATF3 expression vector (pcDNA-ATF3) or empty vector control (pcDNA-EV) and luciferase activity assessed after 24 hours. All cells were also transfected with TK-Renilla as a control for transfection efficiency. Values shown are mean ± SD from three biological experiments performed in triplicate. **, P < 0.01; ***, P < 0.005, unpaired t tests. G, HCT116 cells were treated with vorinostat (5 μmol/L) for 24 hours and ATF3 binding to sequential regions of the BCL-XL promoter determined by ChIP. H, Effect of ATF3 knockdown on HDACi-induced BCL-XL repression. The HDACi-sensitive cell lines A549, AGS, and HCT116 were transiently transfected with ATF3-targeting siRNAs and treated with vorinostat for 24 hours. ATF3 knockdown efficiency is shown in Fig. 5. Note that the HCT116 β-Tubulin control in H is the same HCT116 β-Tubulin control in Fig. 3A because it was the loading control for both samples, which were run in parallel.

Figure 4.

A, Pearson's correlation of the magnitude of repression of BCL-XL versus induction of apoptosis following HDACi treatment across 15 cell lines. B, Pearson's correlation showing the inverse relationship between the magnitude of induction of ATF3 and the repression of BCL-XL mRNA following HDACi treatment across 15 cell lines. C, BCL-XL promoter reporter constructs used including location of putative AP-1– and CREB-binding sites and regions (R) amplified in chromatin immunoprecipitation (ChIP) analyses. UPS (upstream). D, HCT116 cells were transiently transfected with a series of BCL-XL promoter reporter constructs and treated with vorinostat (Vor) or panobinostat (Pan) for 24 hours. Luciferase activity was corrected for total cellular protein. E, Effect of ATF3 knockdown on HDACi-mediated repression of the BCL-XL P1281 promoter activity. Cells were transiently transfected with nontargeting or ATF3-targeting siRNAs overnight and treated with vorinostat for 24 hours. F, Effect of ATF3 overexpression on BCL-XL promoter activity. HCT116 cells were transiently transfected with BCL-XL luciferase reporter constructs of varying lengths and an ATF3 expression vector (pcDNA-ATF3) or empty vector control (pcDNA-EV) and luciferase activity assessed after 24 hours. All cells were also transfected with TK-Renilla as a control for transfection efficiency. Values shown are mean ± SD from three biological experiments performed in triplicate. **, P < 0.01; ***, P < 0.005, unpaired t tests. G, HCT116 cells were treated with vorinostat (5 μmol/L) for 24 hours and ATF3 binding to sequential regions of the BCL-XL promoter determined by ChIP. H, Effect of ATF3 knockdown on HDACi-induced BCL-XL repression. The HDACi-sensitive cell lines A549, AGS, and HCT116 were transiently transfected with ATF3-targeting siRNAs and treated with vorinostat for 24 hours. ATF3 knockdown efficiency is shown in Fig. 5. Note that the HCT116 β-Tubulin control in H is the same HCT116 β-Tubulin control in Fig. 3A because it was the loading control for both samples, which were run in parallel.

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To directly determine if ATF3 is required for HDACi-mediated repression of BCL-XL, we examined the effect of HDACi on BCL-XL promoter activity using a series of BCL-XL promoter reporter constructs (Fig. 4C; ref. 29). Vorinostat and panobinostat maximally repressed activity of the P1281 reporter (–664 downstream to +617 of the transcription start site) and also repressed the P828 and P1692 reporters (Fig. 4D). Conversely, minimal effect was observed on the P621 reporter, implicating key cis-acting sequences located between −4 and −664 bp upstream of the transcription start site that are required for HDACi-mediated repression of BCL-XL promoter activity (Fig. 4D). Vorinostat also significantly repressed activity of the BCL-XL P1281 reporter in two additional HDACi-sensitive cell lines, A549 and AGS (Supplementary Fig. S7). To determine if these effects were mediated through ATF3, experiments were repeated following ATF3 knockdown, which resulted in significant attenuation of HDACi-induced BCL-XL promoter repression (Fig. 4E).

To determine if ATF3 can directly repress BCL-XL promoter activity, we first assessed the effect of ATF3 overexpression alone on BCL-XL promoter activity. Similar to the effects of HDACi, ATF3 overexpression repressed activity of the P828, P1281, and P1692 reporters but not the P621 reporter (Fig. 4F). Analysis of the promoter sequence −4 to −664 bp downstream of the transcription start site identified the presence of an AP-1 site and three CREB sites, which are putative ATF3-binding motifs (Fig. 4C). To directly establish ATF3 binding to this region in response to HDACi treatment, we performed ATF3 chromatin immunoprecipitation (ChIP) experiments which sequentially interrogated ATF3 binding along the BCL-XL promoter. The most robust enrichment of ATF3 binding following vorinostat treatment was observed at regions R2 and R3 (Fig. 4G), overlapping the key regulatory region (−4 to −664) identified in the promoter reporter assays. Notably, HDACi and ATF3 overexpressions were able to repress the P828 promoter despite the lack of ATF3 binding to this region, suggesting that ATF3 may also indirectly repress BCL-XL promoter activity.

Finally, to establish the requirement of ATF3 induction for HDACi-mediated repression of BCL-XL at the endogenous level, ATF3 knockdown was performed in three sensitive cell lines prior to HDACi treatment. In each case, ATF3 knockdown markedly attenuated BCL-XL repression in response to HDACi treatment (Fig. 4H), establishing ATF3 induction as a critical requirement for HDACi-mediated BCL-XL repression.

BCL-XL inhibition overcomes inherent resistance to HDACi-induced apoptosis

We next examined the importance of BCL-XL repression in HDACi-induced apoptosis. Knockdown of BCL-XL in HDACi-refractory PANC1, U87, and PC3 cells significantly enhanced HDACi-induced apoptosis, implicating BCL-XL repression as a key determinant of HDACi response (Fig. 5A). Conversely, BCL-XL overexpression in FLAG-tagged hBCL-XL MEFs conferred resistance to vorinostat-induced apoptosis compared with WT MEFs (Fig. 5B), collectively establishing BCL-XL repression as a key determinant of HDACi-induced apoptosis.

Figure 5.

A, Effect of BCL-XL knockdown on HDACi-induced apoptosis in HDACi-resistant cell lines. Cells were transiently transfected with a nontargeting or BCL-XLtargeting siRNA and treated with vorinostat (5 μmol/L) for 24 hours. (Top plots) Knockdown efficiency of BCL-XL protein assessed by Western blot. (Bottom plot) Corresponding apoptotic response following treatment with vorinostat (5 μmol/L) for 72 hours. Values shown are mean ± SD from three biological experiments performed in triplicate. *, P < 0.05; **, P < 0.005, unpaired t test. B, BCL-XL overexpression (O/E) protects MEFs from HDACi-induced apoptosis. (Top plot) Validation of overexpression of flag-tagged BCL-XL in MEFs by Western blot (Endog: Endogenous BCL-XL). (Bottom plot) Effect of 72-hour vorinostat treatment (20 μmol/L) on apoptosis. Values shown are mean ± SD from a representative experiment performed in triplicate. *, P < 0.05; **, P < 0.005, unpaired t test. C and D, Apoptotic response of HDACi-resistant cell lines to combination treatment with vorinostat (5 μmol/L) and the BH3 mimetic (C) ABT-263 (10 μmol/L) or the (D) BCL-XL–specific inhibitor A1331852 (10 μmol/L). E and F, Apoptotic response of the HDACi-sensitive cell line HCT116 to combination treatment with vorinostat (2.5 μmol/L) and (E) ABT-263 (0.1 μmol/L) or (F) A1331852 (1 μmol/L). All cell lines were treated with either drug alone or in combination for 72 hours and apoptotic response determined by PI staining and FACS analysis. Values shown are mean ± SD (n = 3). *, P < 0.05; **, P < 0.01; and ***, P < 0.005, unpaired t tests.

Figure 5.

A, Effect of BCL-XL knockdown on HDACi-induced apoptosis in HDACi-resistant cell lines. Cells were transiently transfected with a nontargeting or BCL-XLtargeting siRNA and treated with vorinostat (5 μmol/L) for 24 hours. (Top plots) Knockdown efficiency of BCL-XL protein assessed by Western blot. (Bottom plot) Corresponding apoptotic response following treatment with vorinostat (5 μmol/L) for 72 hours. Values shown are mean ± SD from three biological experiments performed in triplicate. *, P < 0.05; **, P < 0.005, unpaired t test. B, BCL-XL overexpression (O/E) protects MEFs from HDACi-induced apoptosis. (Top plot) Validation of overexpression of flag-tagged BCL-XL in MEFs by Western blot (Endog: Endogenous BCL-XL). (Bottom plot) Effect of 72-hour vorinostat treatment (20 μmol/L) on apoptosis. Values shown are mean ± SD from a representative experiment performed in triplicate. *, P < 0.05; **, P < 0.005, unpaired t test. C and D, Apoptotic response of HDACi-resistant cell lines to combination treatment with vorinostat (5 μmol/L) and the BH3 mimetic (C) ABT-263 (10 μmol/L) or the (D) BCL-XL–specific inhibitor A1331852 (10 μmol/L). E and F, Apoptotic response of the HDACi-sensitive cell line HCT116 to combination treatment with vorinostat (2.5 μmol/L) and (E) ABT-263 (0.1 μmol/L) or (F) A1331852 (1 μmol/L). All cell lines were treated with either drug alone or in combination for 72 hours and apoptotic response determined by PI staining and FACS analysis. Values shown are mean ± SD (n = 3). *, P < 0.05; **, P < 0.01; and ***, P < 0.005, unpaired t tests.

Close modal

These findings suggested that therapeutic targeting of BCL-XL may have similar effects. To test this, the HDACi-resistant cell lines PANC1, PC3, and U87 were treated with vorinostat alone and in combination with the BH3 mimetics ABT-263 (navitoclax), which inhibits BCL-2, BCL-XL, and BCL-w. Combination treatment significantly enhanced apoptosis compared with either agent alone in each cell line (Fig. 5C). Similar effects were obtained using its precursor compound, ABT-737 (Supplementary Fig. S8A). To directly determine the role of BCL-XL, we next examined the effects of combining HDACi with the novel BCL-XL–specific inhibitor, A-1331852 (33). Combination treatment significantly enhanced apoptosis in all 3 cell lines compared with either agent alone (Fig. 5D). In contrast, combination treatment with the BCL-2–specific inhibitor ABT-199 (venetoclax) resulted in modest to no enhancement of HDACi-induced apoptosis (Supplementary Fig. S8B). We next determined whether this combination could also be utilized in HDACi-sensitive cell lines, by enabling each drug to be used at significantly lower concentrations. Treatment of the HDACi-sensitive cell line HCT116 with a 2-fold lower concentration of vorinostat (2.5 μmol/L) and a 100-fold lower concentration of ABT-263 (0.1 μmol/L), or a 10-fold lower concentration of A-1331852 (1 μmol/L) to that used in resistant cells was still sufficient to induce >60% apoptosis (Fig. 5E and F).

As A-1331852 is not suitable for use in vivo, we next tested the effect of combination treatment with vorinostat and ABT-263 on growth of HDACi-refractory U87 xenografts in vivo. Daily treatment with the combination significantly inhibited tumor growth compared with control or either agent alone (Fig. 6A–C). Importantly, no differences in body weight were observed in either the single agent or combination treatment arms compared with control (Fig. 6D).

Figure 6.

Effect of vorinostat and ABT-263 treatment alone and in combination on tumor growth in vivo. HDACi-refractory U87 cells were injected into the right and left flanks of BALB/c nu/nu mice (day 0). On day 4, mice were randomized to receive vehicle, vorinostat (50 mg/kg), ABT-263 (25 mg/kg), or the combination. Mice were treated daily for 5 days followed by 2-day break for a total of 19 days. A, Tumor volume was monitored over time by caliper measurement. B, Representative resected tumors at study completion (day 19) and (C) weight of resected tumors. D, Body weight of mice relative to weight at day 0. Data represented are mean ± SEM. *, P < 0.05 and **, P < 0.005, unpaired t tests.

Figure 6.

Effect of vorinostat and ABT-263 treatment alone and in combination on tumor growth in vivo. HDACi-refractory U87 cells were injected into the right and left flanks of BALB/c nu/nu mice (day 0). On day 4, mice were randomized to receive vehicle, vorinostat (50 mg/kg), ABT-263 (25 mg/kg), or the combination. Mice were treated daily for 5 days followed by 2-day break for a total of 19 days. A, Tumor volume was monitored over time by caliper measurement. B, Representative resected tumors at study completion (day 19) and (C) weight of resected tumors. D, Body weight of mice relative to weight at day 0. Data represented are mean ± SEM. *, P < 0.05 and **, P < 0.005, unpaired t tests.

Close modal

HDACis are an established treatment for hematologic malignancies (CTCL, multiple myeloma) and continue to be tested, mostly in combination, for activity in other tumor types (1). Comparatively, the activity of these agents in solid tumors is more limited. The goal of this study was to define the mechanisms of HDACi action in tumor cells in order to provide a framework for the rational design of drug combinations involving their use, and the identification of molecular determinants of sensitivity.

We previously demonstrated that HDACi-induced apoptosis in colon cancer cells is associated with a specific transcriptional response involving the induction of multiple IE response genes, including 3 members of the AP-1 transcription factor family, FOS, JUN and ATF3. We now demonstrate that this transcriptional response provides a robust and early readout of HDACi-induced apoptosis which transcends tumor cell type.

Although HDACi treatment preferentially induces expression of three AP-1 family members in sensitive cell lines, we found that only ATF3 is required for HDACi-driven apoptosis. The proapoptotic role for ATF3 identified herein is consistent with ATF3 overexpression alone being sufficient to induce apoptosis in prostate (34) and ovarian cancer cells (35), and the resistance of Atf3 knockout MEFs to UV-induced apoptosis (36). Furthermore, ATF3 is required for apoptosis induced by ER stress (37), anoxia (38), and the chemotherapeutic agents 5FU, etoposide, and cisplatin (39–41). Finally, ATF3 is required for apoptotic sensitization to HDACi combination therapy with cisplatin and agonistic anti-DR5 antibodies (41, 42) and for HDACi-induced apoptosis in bladder cancer cells (43). However, the subsequent mechanisms of apoptosis induction have not been investigated.

Prior studies have linked HDACi-induced apoptosis with altered expression of a number of pro- and antiapoptotic genes, particularly components of the intrinsic apoptotic pathway (43). However, these effects have not been investigated in the context of sensitivity across tumor cell type, and the mechanisms which underpin altered expression of these genes have not been systematically addressed. The current study identifies a uniform mechanism that determines HDACi-induced apoptosis, involving ATF3-mediated repression of BCL-XL, which transcends tumor cell type. The role of ATF3 as a transcriptional repressor is consistent with prior reports (44), and our ChIP and reporter gene analysis indicate that repression of BCL-XL in HDACi-treated tumor cells involves direct binding of ATF3 to the BCL-XL promoter. Furthermore, we demonstrate that repression of BCL-XL is central in HDACi-induced apoptosis, as both molecular and pharmacologic inhibition of this prosurvival factor markedly enhanced HDACi-induced apoptosis in vitro and in vivo, and BCL-XL overexpression protects cells from HDAC-induced apoptosis, consistent with previous studies (18, 45).

However, we note that the molecular or pharmacologic inhibition of BCL-XL alone did not induce apoptosis to the same extent as when BCL-XL was inhibited in the presence of HDACi, suggesting the requirement for additional HDACi-induced molecular changes to drive apoptosis. In this regard, we did identify consistent induction of the proapoptotic BH3-only genes BIM, BIK, BMF, and NOXA in response to HDACi treatment, several of which has been shown to be required for HDACi-induced apoptosis (32, 46). Notably however, induction of these genes occurred uniformly across the cell lines, independent of apoptotic sensitivity, implying their altered expression is not the basis for differential HDACi response. We therefore propose a model whereby HDACi-induced apoptosis involves both the induction of proapoptotic factors such as BIM, BIK, BMF, and NOXA and the ATF3-dependent repression of the prosurvival factor BCL-XL, of which the magnitude of induction of ATF3 and subsequent repression of BCL-XL determines apoptotic response.

Delineating BCL-XL repression as a key determinant for HDACi-induced apoptosis has significant implications for the rational design of strategies to enhance HDACi antitumor activity. We exploited this using navitoclax (ABT-263), a BH3-mimetic drug (that inhibits BCL-2, BCL-w, and BCL-XL), and the BCL-XL–specific inhibitor A-1331852, which significantly enhanced HDACi-induced apoptosis in tumor cells inherently refractory to HDACi. These findings have the potential to enhance the range of tumors amenable to HDACi treatment by overcoming inherent resistance and to potentially reduce toxicities in sensitive cells by enabling HDACi to be used at lower concentrations.

A further application of these findings could be in the selection of patients likely to respond to HDACi by assessment of the magnitude of FOS, JUN, and ATF3 induction following short-term HDACi treatment. The feasibility of this approach is supported by our demonstration of induction of these genes following 4-hour panobinostat treatment in 2 patients with CTCL with high circulating tumor load. This approach could potentially be extended to solid tumors where freshly isolated tumor cells in the form of biopsy material, organoids, patient-derived xenografts, or circulating tumor cells are assessed for FOS, JUN, and ATF3 induction following short-term HDACi treatment as a predictor of the likelihood of response.

Our findings also suggest a framework for identifying molecular biomarkers of HDACi response prior to drug treatment through detailed investigation of the molecular determinants of differential ATF3 induction among tumors. In this regard, our previous studies in colon cancer cells demonstrated that HDACi induction of IE genes, including ATF3, is dependent on the Sp1 and Sp3 transcription factors, and that HDACis preferentially induce Sp1/Sp3 reporter activity in HDACi-sensitive colon cancer lines (24). We now extend these findings by demonstrating that HDACis preferentially induce Sp1/Sp3 reporter activity in sensitive cell lines, independent of tumor type. A central role for Sp1 and Sp3 in regulating HDACi-induced apoptosis independent of tumor type is also plausible given their ubiquitous expression (47). However, SP1 and SP3 are not mutated in human cancers, and analyses in colon cancer cells suggest basal differences in expression are unlikely to be determinants of HDACi response (24). Notably, both SP1 and SP3 are posttranslationally modified by a number of mechanisms including acetylation, ubiquitination, and phosphorylation which can alter their activity (48). Exploration of whether such posttranslational modifications occur in response to HDACi treatment and identification of the factors regulating these changes, which may vary between sensitive and resistant cells, may provide novel insight into the basis for differential HDACi response. Notably, several other mechanisms of ATF3 induction have also been described, including induction by p53 (49), activation of JNK, ERK, and p38 signaling (50), and by ATF4 subsequent to activation of the ER stress/unfolded protein response pathway (37). In addition to modulating SP1 and SP3, HDACi can also affect these pathways which may contribute to the differential induction of ATF3 among tumors.

In summary, we have identified a specific transcriptional response associated with HDACi-induced apoptosis that transcends tumor type, involving the coordinate induction of FOS, JUN, and ATF3. We identify the induction of ATF3 and subsequent repression of BCL-XL as a central mechanism of HDACi-induced apoptosis and applied these findings to develop rational drug combinations which overcome inherent resistance and enhance the activity of HDACi in a range of tumor types.

M. Dickinson reports receiving other commercial research support from, reports receiving speakers bureau honoraria from, and is a consultant/advisory board member for Novartis. No potential conflicts of interest were disclosed by the other authors.

Conception and design: A.C. Chüeh, J.W.T. Tse, P. Ioannidis, M.R. Thompson, W.D. Fairlie, A.S. Dhillon, J.M. Mariadason

Development of methodology: A.C. Chüeh, J.W.T. Tse, P. Ioannidis, L. Togel, E. Lee, J.M. Mariadason

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): A.C. Chüeh, J.W.T. Tse, M. Dickinson, P. Ioannidis, L. Jenkins, B. Tan, I. Luk, R. Nightingale, J.M. Mariadason

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): A.C. Chüeh, J.W.T. Tse, M. Dickinson, P. Ioannidis, A.S. Dhillon, J.M. Mariadason

Writing, review, and/or revision of the manuscript: A.C. Chüeh, J.W.T. Tse, M. Dickinson, L. Togel, B.R.G. Williams, G. Lessene, E.F. Lee, W.D. Fairlie, A.S. Dhillon, J.M. Mariadason

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A.C. Chüeh, J.W.T. Tse, L. Togel, M. Davalos-Salas, J.M. Mariadason

Study supervision: A.C. Chüeh, A.S. Dhillon, J.M. Mariadason

We thank Paul G. Ekert (Murdoch Children's Research Institute), Kaye Wycherley (Walter Eliza Hall Institute for Medical Research), Andrew Wei (Alfred Hospital), and Michael H. Kershaw (Peter Mac Cancer Centre) for providing us with the leukemia and multiple myeloma cell lines used in this study.

This study was funded by the National Health and Medical Research Council (NHMRC) of Australia (1008833 and 1066665), The National Institutes of Health (NIH1RO1 CA123316), an Australian Research Council Future Fellowship (FT0992234), an NHMRC Senior Research Fellowship (1046092) to J.M. Mariadason, Ludwig Cancer Research, and the Operational Infrastructure Support Program, Victorian Government, Australia. J.W.T. Tse was supported by an Australian Postgraduate Award.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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Supplementary data