Activation of oncogenic pathways in classical Hodgkin lymphoma by decitabine: A rationale for combination with small molecular weight inhibitors
- Authors:
- Published online on: December 30, 2016 https://doi.org/10.3892/ijo.2016.3827
- Pages: 555-566
Abstract
Introduction
Classical Hodgkin lymphoma (cHL) predominantly is a B-cell malignancy with unique features. Only ~1–5% of the whole tumor mass is represented by Hodgkin and Reed Sternberg (HRS) cells, the malignant component of cHL. The major part of the tumor mass is composed of an inflammatory infiltrate that provides a protective and supportive microenvironment for the tumor cells (1). Despite the 5 year overall survival of 81%, cured patients often suffer from treatment-related complications like pulmonary fibrosis, sterility, and cardiovascular disorders (2). Moreover, they may develop secondary tumors such as acute leukemia and myelodysplastic syndrome (MDS) (2). Thus, a substantial percentage of treatment failures and the high frequency of adverse effects of the chemotherapy warrants the search for novel therapeutic approaches.
Although the HRS cells are derived from germinal or post germinal center B-cells, they have lost most of their B-cell phenotype and express surface markers of various other lineages of the immune system (3). We and others have shown that epigenetic silencing contributes to the extinguishing of the B-cell program in cHL (4–6). In particular, promoter CpG island hyper-methylation was identified as a major cause of silencing of PU.1/SPI1, BOB.1/OBF.1/POU2AF1 and other important regulators of the B-cell program (6). Of note, PU.1 has been shown to act as a tumor suppressor in cHL (7). Additionally, known tumor suppressor genes like p16 and p18INK4c are also epigenetically silenced in cHL (5,7–10).
Epigenetic processes are known to contribute to the oncogenic program in virtually all tumor types by activation of proto-oncogenes or by silencing of tumor suppressor genes (11,12). Unlike the genomic aberrations, epigenetic modifications including CpG dinucleotide methylation and histone deacetylation are reversible by inhibitors of DNA methylation and of histone deacetylases (HDAC), respectively. Currently, the constantly growing list of epigenetic modifiers makes epigenetic therapy one of the most quickly emerging branches of targeted cancer therapy. For some tumors epigenetic therapy is already established as an efficient and less harmful than classical chemotherapy approach to cancer treatment (13). HDAC inhibitors were successfully studied for treatment of cHL. Combination of the pan-HDAC inhibitor vorinostat with mammalian target of rapamycin (mTOR) inhibitor sirolimus induced complete regression of primary refractory cHL (14). Another pan-HDAC inhibitor panobinostat reduced tumor mass in 74% of patients with relapsed cHL including 23% partial and 4% complete remission (15). HDAC inhibitor entinostat (SNDX-275) has been shown to induce apoptosis in cHL cell lines and entered clinical trials (16).
The DNA methyltransferase (DNMT) inhibitors, in particular decitabine (5-aza-2′-deoxycytidine/5-Aza-dC), is used for treatment of acute myeloid leukemia (AML) (17) and is already approved for treatment of patients with MDS (18). To our knowledge DNMT inhibitors are not specifically tested for use in patients with cHL. However, complete regression of relapsed metastatic cHL was described as a fortunate side-effect in a MDS patient treated with the 5-Aza-dC related demethylating agent 5-azacytidine (19). Both inhibitors have similar function and demonstrated similar efficacy against MDS and AML (20). 5-Aza-dC has often been used by us and others to demonstrate epigenetic mechanisms of gene silencing in cHL cell lines, but assessment of its cytotoxic effects was neglected (4,6,21).
In this study we focused on the possible mechanisms of the antitumor effect of demethylating agents in cHL. Using GEP we could show that along with the reactivation of tumor suppressor genes 5-Aza-dC also induced several oncogenic pathways such as MEK/ERK, JAK-STAT and NF-κB. Here we demonstrate that pharmacological inactivation of some of these pro-survival pathways significantly increases the anti-tumor effect of 5-Aza-dC against cHL.
Materials and methods
Antibodies and inhibitors
The primary monoclonal mouse antibodies against BCL2 (#sc-509) and ACTB (#sc-130300), as well as the primary polyclonal rabbit antibody against p65 (#sc-372), and the secondary goat anti-rabbit (#sc-2004) and anti-mouse (#sc-2005) antibodies were purchased from Santa Cruz Biotechnology, Inc. (Dallas, TX, USA). The primary monoclonal mouse antibodies against CDKN1A (#556431) and GAGE (#611746) were acquired from BD Bioscience (Heidelberg, Germany). The primary monoclonal rabbit antibodies against BCL2L1 (#2764), and p44/42 MAPK (ERK1/2) (#4695), as well as the primary polyclonal rabbit antibody against phospho-p44/42 MAPK (pERK1/2) (#9101) were purchased from Cell Signaling Technology (Leiden, The Netherlands). The primary monoclonal mouse anti-SSX antibody (#OP196) was acquired from Oncogene Research Products (Boston, MA, USA) and the primary polyclonal rabbit anti-TUBB antibody (#ab6046) from Abcam (Cambridge, UK).
JQ1 was kindly provided by J.E. Bradner (Division of Hematologic Neoplasia, Dana-Faber Cancer Institute, Boston, MA, USA). 5-aza-2′-deoxycytidine (5-Aza-dC) was purchased from Calbiochem (Darmstadt, Germany) and KP372-1 from MoBiTec GmbH (Göttingen, Germany). ABT263, fedratinib, QNZ (EVP4593) and SH-4-54 were acquired from Selleckchem (Munich, Germany). UO126 was purchased from Cell Signaling Technology.
Cell lines and short tandem repeat (STR) analysis
The cHL cell lines L428, and L1236 were cultured in complete RPMI-1640 medium as described earlier (6). The cell lines were obtained from DSMZ (Braunschweig, Germany). The authenticity of the cell lines was proved by STR DNA typing using GenomeLab GexP™ Genetic Analysis System (Sciex, Darmstadt, Germany) and GenomeLabHuman STR primer set (Beckman Coulter, Krefeld, Germany) as described in user's manual. The obtained STR profiles were compared with comprehensive DSMZ database of STR cell line profiles using 'Online STR Analysis' (www.dsmz.de, 13.08.2015). 5-Aza-dC, if not mentioned differently, was used at a concentration of 1 µM. The cells were seeded at a density of 0.5×106/ml and incubated with 5-Aza-dC for 24 h mimicking clinical relevant bolus dose and time schedule. After complete exchange of medium the cells were incubated for another 3 days before harvesting. The cells were counted by a haemocytometer.
Gene expression profiling (GEP)
L428, and L1236 cell lines were seeded at a density of 0.5×106/ml and incubated with 5-Aza-dC at a concentration of 1 µM for 24 h mimicking clinical relevant bolus dose and time schedule. After complete change of medium the cells were incubated for another 3 days before harvesting. Isolation of the RNA was performed using the RNeasy mini kit (Qiagen, Hilden, Germany) according to the user's manual. Two biological replicates were analyzed for each cell line. Labeling of RNA (cRNA synthesis) was performed by The Microarray Facility, University of Tübingen (Tübingen, Germany) according to a standard Affymetrix® procedure (One-Cycle Target Labeling kit; Affymetrix UK Ltd., High Wycombe, UK). The biotinylated complementary RNA (cRNA) was cleaned and fragmented by a 35 min incubation at 95°C. GeneChip® Human genome U133 Plus 2.0 array (spotted with 1,300,000 oligonucleotides informative for 47,000 transcripts originated from 39,000 genes, Affymetrix UK Ltd.) was used as described in user's manual. We used GeneSifter software for data processing and analysis (www.genesifter.net; 28.09.2015; PerkinElmer, Waltham, MA, USA). Global background correction, across array normalization, and log2 transformation of PM values were done by robust multi-array average (RMA) method. The 3623 probe sets, modulated by 5-Aza-dC at least >3-fold in one of the cell lines, were filtered (threshold X3, Benjamini and Hochberg correction, adjusted P<0.05). The microarray data were deposited in the Gene Expression Omnibus (GEO) database under accession number GSE86068.
Gene set enrichment analysis (GSEA)
We used the Broad Institute's Molecular Signatures Database gene set collections 'C2-curated gene sets', and 'C6-oncogenic signatures' for GSEA (http://www.broadinstitute.org/gsea/index.jsp,02.10.2015) (22,23).
Immunoblot
Cells (1×106) were lysed in 100 µl Laemmli buffer containing 6 M urea. Then 25 µl of the protein extracts were separated on 10% polyacrylamide gels by SDS page using the Mini-PROTEAN® Tetra vertical Electrophoresis (Bio-Rad Laboratories, Munich, Germany) and blotted to a nitrocellulose membrane using the Mini-Electrophoretic Blotting system (CBS Scientific, Del Mar, CA, USA). The membranes were blocked with 5% dry milk in PBS and then incubated with the primary antibodies at 4°C overnight. After several washing steps the membranes were incubated for 1 h with the secondary antibody. Signals were detected with the Super Signal West Dura Extended Duration Substrate (Thermo Scientific, Rockford, IL, USA). The representative immunoblots were quantified with help of ImageJ software (imagej.net; 14.01.2016).
Cell viability assay
For measurement of cell viability 50 µl medium containing decreasing concentrations of the specific inhibitors were pipetted in triplicate into flat bottomed 96-well plates creating serial dilutions. Cells/well (2×104) were seeded and cultured for 6 days. Then 25 µl 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) solution from Sigma-Aldrich (Darmstadt, Germany) (5 mg/ml in PBS) per well were added and incubated for 2 h. After dissolving the formazan crystals with MTT-lysis-buffer the absorbance was detected with the Microplate Reader SpectraMax 190 (Molecular Devices, Biberach, Germany) at a wavelength of 570 nm. All experiments were repeated at least two times. The IC50 values were generated by using the software CompuSyn (http://www.combosyn.com/, 16.03.2016) with IC50 being the concentration where 50% of the maximum possible inhibition was reached (24,25).
Combination plot
5-Aza-dC was combined with the different inhibitors using decreasing concentrations of the two drugs at a ratio of IC50 (5-Aza-dC)/IC50 (inhibitor). The drugs were added simultaneously to the cells. The experiment was performed as described in 'Cell viability assay'. The data were analyzed applying the combination index (CI) theorem and plot of Chou and Talalay (24,25) using the CompuSyn software (http://www.combosyn.com/16.03.2016).
Dual luciferase reporter assay and electrophoretic mobility shift assay (EMSA)
Nuclear extraction and EMSA were performed as described earlier (26). The experiment was performed twice. For the reporter assay 1×107 cells were transfected by electroporation with the reporter vectors containing binding sides either for STAT3 (Panomics; Gentaur Molecular Products, Aachen, Germany), STAT6 (27) or NF-κB (28) using the Bio-Rad GenePulser II (Bio-Rad Laboratories). The luciferase activity was normalized by cotransfection of the ubi-Renilla vector. After 24 h of incubation the luciferase activity was measured with help of the Dual Luciferase Reporter assay system (Promega, Mannheim, Germany) using a luminometer (Berthold Technologies, Bad Wildbach, Germany). This experiment was performed in duplicate and repeated three times.
Statistical analysis
The values of the Dual Luciferase reporter assay and the measurement of cell number are shown as means ± SD. For the statistical analysis the unpaired two-tailed Student's t-test was used. P<0.05 were considered statistically significant. The data were analyzed with help of GraphPad Prism 5 (GraphPad Software, San Diego, CA, USA).
Results
5-Aza-dC is toxic for cHL cell lines and reactivates epigenetically silenced genes at clinically achievable concentrations
In the present study we used a 5-Aza-dC incubation schedule aimed to obtain optimal reactivation of epigenetically silenced genes as we described earlier for cHL (6) and for Burkitt lymphoma (28). Maximal demethylation induced by 5-Aza-dC is achieved after 72 h (29). We incubated the cells for only 24 h with 5-Aza-dC and after complete change of the medium incubated the cells for additional 72 h without drug, to minimize direct toxicity. Using this experimental setting, 5-Aza-dC strongly reduced cell numbers of L428 (Fig. 1A) and L1236 (Fig. 1B) cHL cell lines. Even concentrations 4–5-fold lower than peak plasma concentration in patients [0.93–2.01 µM (30)] showed significant antitumor effects.
To control the efficacy of the demethylating activity of 5-Aza-dC we analyzed the expression of cancer/testis (CT) antigens SSX and GAGE, a class of genes epigenetically silenced by promoter hypermethylation in differentiated cells, which can be reactivated by 5-Aza-dC in cHL cell lines (31). 5-Aza-dC induced expression of SSX and GAGE in L428 (Fig. 1C) and L1236 (Fig. 1D) cell lines at all concentrations used.
Thus, 5-Aza-dC shows antitumor effects against cHL cell lines when used at clinically relevant concentrations.
5-Aza-dC activates main oncogenic pathways of cHL
To characterize the molecular mechanisms involved in the 5-Aza-dC antitumor effect, we used GEP. With help of Genesifter software we filtered out 3623 probe sets modulated more than 3-fold in at least one of the two cell lines. To identify modulated pathways we first used Gene Set Enrichment Analysis (GSEA) (Table I). Among the significantly enriched signatures (FDR<0.25; nominal P<0.05) were P53_DN.V1_UP (Fig. 2A and Table I), comprising 194 genes upregulated in cell lines with mutated TP53, KRAS.KIDNEY_UP.V1_DN (Fig. 2B and Table I), containing 142 genes induced in epithelial kidney cancer cells by overexpression of KRAS, and RELA_DN.V1_DN (Fig. 2C and Table I), consisting of 141 genes upregulated in kidney fibroblasts with mutated RELA. Applying the utility 'Gene function' of the Genesifter software we showed that among the genes of the TP53 signature X57348 (SFN), a TP53 stabilizer and a negative regulator of cell cycling, was on top of the list (Fig. 3A) (32). The TP53 associated gene list also included CDKN1A, GADD45A and GADD45B, as well as apoptosis-associated TP53 target gene TP53I3 (Fig. 3A) (33). Another potential tumor suppressor gene in TP53 annotation was thrombospondin 1 (THBS1), that facilitates RAS-induced senescence by repressing ERK signaling (Fig. 3A) (34). Surprisingly, among the upregulated genes we also found repression targets of TP53 including genes that support cell cycle progression (CCND1, CCND2 and CDK6). Among the upregulated genes of KRAS signature were also the positive regulator of transcription BRDT (35) and protooncogene SRC. Moreover, we found that signatures of the gene sets REACTOME_TRANSCRIPTION (Fig. 2D and Table I) and MIKKELSEN_MEF_WITH_H3_UNMETHYLATED (Fig. 2E and Table I) were significantly enriched, suggesting that 5-Aza-dC not only demethylates epigenetically silenced genes, but raises global transcription levels in cHL cell lines.
 | Table ISelected significantly correlated gene sets out of the Curated Gene Sets (C2) and Oncogenic signatures (C6) gene set collections. |
We further applied Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis to identify additional significantly upregulated signatures (Table II). Two of the pathways with highest enrichment scores were 'JAK-STAT signaling pathway' (z-score, 3.93) (Fig. 3B and Table II), and 'Cytokine-cytokine receptor interaction' (z-score, 5.18) (Fig. 3C and Table II). Among upregulated genes of 'Cytokine-cytokine receptor interaction' signature were CXCL10, IL-6, IL-6R and IL-13, that provide growth and survival signals to the HRS cells (Fig. 3C) (36,37). In addition, among the upregulated genes of JAK-STAT signature were positive regulators of cell cycling CCND1 and CCND2 and critical for cHL survival anti-apoptotic gene BCL2L1 (Fig. 3B). The NF-κB target gene STAT5A, which is constitutively active in cHL (38), was upregulated as well (Fig. 3B). Then we applied the utility 'Gene function' of the Genesifter software to identify other pro-survival genes using the ontologies 'ERK1 and ERK2 cascade' (Fig. 3D), 'NF-κB/IκB signaling' (Fig. 3E) and 'negative regulation of apoptosis' (Fig. 3F). This helped us to identify several other important upregulated proto-oncogenes including BCL2.
| Table IISignificantly enriched pathways of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. |
We suggested that, although 5-Aza-dC has antitumor effect in cHL cell lines, it may be hampered by activation of pro-survival pathways including JAK-STAT, NF-κB and KRAS.
Validation of GEP results
To validate results of the GEP we measured the expression of selected genes by immunoblot. We found that 5-Aza-dC strongly induced CDKN1A protein synthesis at a broad range of concentrations (Fig. 4A and B). One of the main functions of CDKN1A is the inhibition of CDK2, which is among other proteins responsible for cell cycle progression through S phase (39). Moreover, CDKN1A is an antiapoptotic protein that induces cell cycle arrest and downregulates pro-apoptotic genes such as procaspase-3 or caspase-8 (39). We also proved the upregulation of the antiapoptotic proteins BCL2 (Fig. 4C and D) and BCL2L1 (Fig. 4C and E).
5-Aza-dC activates MEK/ERK signaling
Since GEP and subsequent enrichment analysis indicated induction of critical oncogenic pathways in cHL, we assessed activity of MEK/ERK, JAK-STAT and NF-κB pathways. We first assessed the phosphorylation status of ERK1/2 using immunoblot. 5-Aza-dC strongly induced the phosphorylation of ERK1 in one the two cell lines and phosphorylation of ERK2 in both cell lines with no changes seen in the levels of unphosphorylated ERK1/2 protein expression (Fig. 5A). Next using EMSA we investigated NF-κB pathway activation. No significant increase but rather decrease of NF-κB binding could be detected in treated cells compared to control cells in both cell lines (Fig. 5B). In addition we analyzed NF-κB activation by 5-Aza-dC in L428 cells with help of luciferase reporter assay using a vector containing three κB binding sites. The luciferase reporter assay did also not reveal induction of NF-κB-dependent transcription (Fig. 5C). Finally we analyzed the activity of the JAK-STAT pathway in L428 cells using luciferase-expression vectors harboring STAT3 (Fig. 5D) and STAT6 (Fig. 5E) promoters. We did not see an increase of luciferase activity in L428 cells after treatment with 5-Aza-dC.
Thus, although 5-Aza-dC significantly enriched gene expression signatures of main oncogenic pathways of cHL, it did not directly facilitate nuclear translocation of STATs and NF-κB. This implies that other mechanisms, like transcription-activating chromatin modifications of STAT and NF-κB target genes, may contribute to the 5-Aza-dC induced activation of these pathways.
Inhibition of the upregulated oncogenic pathways increases the antitumor effect of 5-Aza-dC
We assumed that targeting of the activated pro-survival pathways may potentiate the anti-tumor effect of 5-Aza-dC. Given that 5-Aza-dC also induced genes activating transcription, we also included the BET inhibitor JQ1 which blocks transcriptional activation through interaction with acetylated chromatin.
First we assessed the antitumor effects of the single treatments by calculating their IC50 values (Tables III and IV). L428 and L1236 showed different sensitivity to the inhibitors. The BCL2/BCL2L1 inhibitor ABT263 had the highest cytotoxic activity in both cell lines (Tables III and IV). The least toxic were the MEK inhibitor UO126, and the STAT3/STAT5 inhibitor SH-4-54, although UO126 had somehow stronger activity in L1236 and SH-4-54 in L428 cell lines (Tables III and IV). The JAK inhibitor fedratinib had strong antitumor activity against L1236, whereas L428 cells were less sensitive (Tables III and IV). The NF-κB pathway inhibitor QNZ, AKT inhibitor KP372-1, the bromodomain and extra-terminal (BET) family proteins inhibitor JQ1 also differed in their antitumor effect towards cHL cell lines. L428 was more sensitive to KP372-1 and QNZ (Table III), whereas JQ1 showed a stronger antitumor effect in L1236 (Table IV).
To analyze the dose effect relationships of the drug combinations we applied the method of Chou and Talaly (24,25). With help of the CompuSyn Software we produced CI-Fa combination plots. The CI represents the value of the effect of the combined drugs, with CI values >1 indicating antagonism, CI values =1 additive effects, and CI values <1 synergism (24,25). The fraction affected (Fa) values represent the magnitude of the antitumor effect of the combination. Fa=0 indicates the absence of therapeutic effects, and Fa=1 the maximum achievable antitumor activity (24,25). For each Fa value the software generates a predictive CI value, which can be seen on the plots as the curves with the solid line. The experimental combination data, that were used to generate the CI-Fa combination plots, are represented as dots (24,25).
Similar to the single treatments, cHL cell lines varied in terms of sensitivity to the drug combinations. In general, L428 cells were more sensitive than L1236 cells. The most effective in both cell lines was the combination with the NF-κB inhibitor QNZ (Fig. 6A and Table IV). Targeting AKT, one of the downstream molecules in NF-κB signaling, with the AKT-inhibitor KP372-1, resulted in synergistic antitumor effects in both cell lines (Fig. 6B and Table IV).
Combination of 5-Aza-dC with the BCL2/BCL2L1 inhibitor ABT263 resulted in very strong synergy especially in L428 (Fig. 6C). In L1236 a synergistic effect could only be observed at low Fa values (Table IV). Targeting the JAK-STAT pathway by combining 5-Aza-dC with the STAT3/STAT5 inhibitor SH-4-54 (Fig. 6D) or JAK2 inhibitor fedratinib (Fig. 6E) showed synergistic effects in L428 at almost all concentrations. In L1236 only SH-4-54 showed a slight synergistic effect at intermediate Fa values (Table IV). Fedratinib did not increase the antitumor effect of 5-Aza-dC in L1236 (Table IV).
Among the gene sets significantly enriched by 5-Aza-dC we identified REACTOME_TRANSCRIPTION, that comprises genes involved in transcription. We applied the concept of dual epigenetic therapy to inhibit the 5-Aza-dC-induced transcription activation. The inhibitor JQ1 inhibits BRDs binding to acetylated histones (35). We observed synergism at high concentration in L428 cells (Fig. 6F) and at low concentrations in L1236 cells (Table IV).
Given the positive effect of 5-Aza-dC on ERK activation we expected to observe strong synergy with MEK inhibitors. Against our expectations, combination with the MEK inhibitor UO126 showed strong antagonistic effects in both cell lines (Tables III and IV).
Thus, inhibition of pro-survival pathways induced by 5-Aza-dC in cHL cell lines potentiates the antitumor effect.
Discussion
Here we provide experimental evidence that the demethylating agent 5-Aza-dC has antitumor effects on cHL. However, the magnitude of the effect is hampered by simultaneous induction of pro-survival pathways. The inhibition of these pathways significantly improved the antitumor activity of 5-Aza-dC.
5-Aza-dC was successfully used for treatment of a wide spectrum of tumors (40). In cHL there is only one anecdotic evidence on clinical efficacy of 5-Aza-dC (19). In addition it was suggested that 5-Aza-dC could be used for increasing immunogenicity of HRS cells and to make them a more attractive target for T-cell therapy (41). This study on antitumor effects of 5-Aza-dC at clinically relevant concentrations supports the idea on the feasibility of demethylating therapy for cHL.
At the same time we revealed a serious drawback of 5-Aza-dC treatment. We detected a significant upregulation of the pathways, that are known to contribute to the oncogenic program of cHL (MEK/ERK, NF-κB and JAK-STAT) (1). The ability of 5-Aza-dC to modulate MEK/ERK activity is cell type specific and depends on the activation status of other pathways. In ovarian cancer cell lines, 5-Aza-dC strongly activated ERK phosphorylation only in cell lines harboring activating KRAS mutations (42). In the human AML cell line NB4 and in freshly isolated AML cells, 5-Aza-dC also stimulated ERK phosphorylation (43). In other normal and malignant cell types including osteoclasts (44), acute lymphoblastic leukemia (45), and lung cancer cell lines (46) 5-Aza-dC attenuated MEK/ERK activity, inter alia by reactivating epigenetically silenced negative regulators. JAK-STAT signaling is inhibited by 5-Aza-dC, in particular by the reactivation of JAK-STAT inhibitors (47,48).
The effect of 5-Aza-dC on NF-κB activity is cell-type dependent. 5-Aza-dC activated NF-κB signaling in Burkitt lymphoma (28) and in AML (49), but inhibited NF-κB activity in osteoclasts (44). Of note, although in our experiments we observed significant upregulation of NF-κB and STAT target genes, this was not mediated by increased nuclear translocation of these transcription factors. Most probably the increasing transcription of NF-κB and STAT targets reflects solely general stimulating effects of 5-Aza-dC on chromatin structure. It was shown that 5-Aza-dC increases global histones acetylation independent of DNA methylation (50). Thus, 5-Aza-dC not only induces activation of hypermethylated promoters but also stimulates transcriptional activity of already active genes, i.e. the genes constituting tumor survival and proliferation programs.
Consequently we have shown that repression of the activated pro-survival pathways can potentiate the antitumor effect of 5-Aza-dC. So far, 5-Aza-dC was used in combination with chemotherapeutics to prevent or reverse epigenetic silencing of genes mediating the cytotoxic effect (51). Combination of 5-Aza-dC with epidermal growth factor receptor inhibitor gefitinib has synergistic antitumor effects against colon carcinoma cells (52).
To potentiate the antitumor effect of 5-Aza-dC on cHL cell lines, we targeted JAK-STAT and NF-κB pathways. As a single treatment the small molecular weight inhibitor of JAK2 fedratinib already showed strong antitumor activity against cHL in vitro and in vivo (53). Our findings provide a rationale for combination of this inhibitor with 5-Aza-dC. Targeting NF-κB with the inhibitor QNZ also significantly increased the antitumor effect of 5-Aza-dC. Of note, other NF-κB inhibitors like the proteasome inhibitor bortezomib were considered as an attractive approach to treat cHL (54), however clinical trials did not meet the expectations (55). We hope that combination with 5-Aza-dC may be a way to improve the efficacy of NF-κB inhibitors.
We found that MEK/ERK signaling, which is constitutively active in most of the HRS cells (1), was activated by 5-Aza-dC. Unexpectedly, we revealed antagonistic interactions between 5-Aza-dC and MEK1/2 inhibitor U0126. Interestingly, Stewart et al described a decrease in the sensitivity of an ovarian cancer cell line to the ERK inhibitor trametinib by treatment with 5-Aza-dC and attributed it to 5-Aza-dC-induced ERK hyper-activation (42). It is conceivable that ERK-dependent induction of BCL2 and BCL2L1 (56) contributed to the protective effect of 5-Aza-dC. Our data on strong synergistic effects of BCL2/BCL2L1 inhibitor ABT263 with 5-Aza-dC supports this assumption. Synergism of 5-Aza-dC with BCL2 inhibitors was described earlier in ovarian cancer models (42).
We could also observe strong synergism of 5-Aza-dC with the BET inhibitor JQ1. JQ1 predominantly inhibits transcription of oncogenes highly expressed in tumor cells, including MYC, by preventing recruitment of transcription activating BET proteins to acetylated histones (57). Considering a functional connection between histone modifications and DNA methylation it is not surprising that treatment with 5-Aza-dC induces histone acetylation and activation of transcription (50). It is therefore conceivable, that JQ1 blocks this 5-Aza-dC-induced transcriptional activation. Interestingly, the synergistic interaction between JQ1 and hypomethylating drugs has been predicted earlier (58).
Due to its low toxicity 5-Aza-dC is an attractive alternative for classical chemotherapy especially in elderly patients and for palliative care (59). Combination of epigenetic therapy with matched pathway inhibition may therefore be a promising approach to treat elderly and multi-morbid patients with cHL. Further in vitro and in vivo studies will be required to fully understand the potential of the different combinations and to evaluate their toxicity profile.
Acknowledgments
We thank Anita Kick for excellent technical assistance, Harald J. Maier and Uta Manfras for their help with EMSA, Elena Kelsch and Michaela Buck (Institute of Pathology, University of Ulm, Germany) for STR analysis of the cell lines, and Beatrix Schwarz for help in preparation of the manuscript. We are thankful to J.E. Bradner (Division of Hematologic Neoplasia, Dana-Faber Cancer Institute, Boston, MA, USA) for donation of JQ1. This study was supported in part by grant 110564 from the Deutsche Krebshilfe e.V. (to T.W. and A.U.). T.S. was supported by grant 111817 from the Deutsche Krebshilfe e.V.
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