Advertisement
Therapeutics, Targets, and Chemical Biology

Proteasomal Inhibition by Ixazomib Induces CHK1 and MYC-Dependent Cell Death in T-cell and Hodgkin Lymphoma

Dashnamoorthy Ravi, Afshin Beheshti, Nasséra Abermil, Frank Passero, Jaya Sharma, Michael Coyle, Athena Kritharis, Irawati Kandela, Lynn Hlatky, Michail V. Sitkovsky, Andrew Mazar, Ronald B. Gartenhaus and Andrew M. Evens
DOI: 10.1158/0008-5472.CAN-15-2477 Published June 2016

Abstract

Proteasome-regulated NF-κB has been shown to be important for cell survival in T-cell lymphoma and Hodgkin lymphoma models. Several new small-molecule proteasome inhibitors are under various stages of active preclinical and clinical development. We completed a comprehensive preclinical examination of the efficacy and associated biologic effects of a second-generation proteasome inhibitor, ixazomib, in T-cell lymphoma and Hodgkin lymphoma cells and in vivo SCID mouse models. We demonstrated that ixazomib induced potent cell death in all cell lines at clinically achievable concentrations. In addition, it significantly inhibited tumor growth and improved survival in T-cell lymphoma and Hodgkin lymphoma human lymphoma xenograft models. Through global transcriptome analyses, proteasomal inhibition showed conserved overlap in downregulation of cell cycle, chromatin modification, and DNA repair processes in ixazomib-sensitive lymphoma cells. The predicted activity for tumor suppressors and oncogenes, the impact on “hallmarks of cancer,” and the analysis of key significant genes from global transcriptome analysis for ixazomib strongly favored tumor inhibition via downregulation of MYC and CHK1, its target genes. Furthermore, in ixazomib-treated lymphoma cells, we identified that CHK1 was involved in the regulation of MYC expression through chromatin modification involving histone H3 acetylation via chromatin immunoprecipitation. Finally, using pharmacologic and RNA silencing of CHK1 or the associated MYC-related mechanism, we demonstrated synergistic cell death in combination with antiproteasome therapy. Altogether, ixazomib significantly downregulates MYC and induces potent cell death in T-cell lymphoma and Hodgkin lymphoma, and we identified that combinatorial therapy with anti-CHK1 treatment represents a rational and novel therapeutic approach. Cancer Res; 76(11); 3319–31. ©2016 AACR.

Introduction

Understanding the pertinent and functional biologic oncogenic pathways of inhibition and mechanisms of resistance is critical to optimally integrate novel therapeutics into cancer treatment paradigms. Increased proteasomal activity is a frequently observed phenomenon in malignant cells; hence, proteasome inhibition may potentially block cell proliferation and result in the inhibition of tumor progression (1). Bortezomib (Velcade) was the first in class proteasomal targeted drug that is currently FDA approved for the treatment of newly diagnosed and relapsed/refractory multiple myeloma and mantle cell lymphoma (2). Next-generation proteasome inhibitors, such as ixazomib, are currently under preclinical and clinical investigations. These novel agents were developed with an objective of enhancing efficacy and improving the tolerability of antiproteasomal therapeutics (3–5). Ixazomib is an investigational proteasome inhibitor currently in clinical trials in hematologic malignancies and early reports indicate promising clinical activities in follicular and T-cell lymphoma (6); however, its biologic activity in T-cell lymphoma and Hodgkin lymphoma are largely unknown and the biologic mechanisms are not well defined.

T-cell lymphomas represent a heterogeneous group of aggressive non-Hodgkin lymphomas with overall poor prognosis (7). Further discovery of its tumor biology is needed and additional novel targeted therapeutic agents are desired. Hodgkin lymphoma is generally a curable malignancy by conventional chemotherapy; however, there continues to be a subset of patients with refractory disease or relapse that succumbs to this disease. In addition, there remains an unmet need to identify targeted, less toxic therapy for the treatment of Hodgkin lymphoma to decrease the continued acute and long-term toxicities associated with cytotoxic chemotherapy and radiation (7–9). Moreover, multiple preclinical studies strongly indicated that proteasome-dependent NF-κB may be a ‘master switch’ of Hodgkin Reed Sternberg (HRS) cells and it has been shown to be critical for cell survival in HRS and also T-cell lymphoma models (10–15). Although proteasome is a rationale therapeutic target for the treatment of T-cell lymphoma and Hodgkin lymphoma, clinical studies in patients with these malignancies treated with bortezomib were associated with modest clinical benefit (16, 17). With the development of ixazomib as second-generation proteasomal inhibitor with superior pharmacodynamic, pharmacokinetic, and tumor inhibitory properties in lymphoma compared with bortezomib (18, 19), interest in the treatment of T-cell lymphoma and Hodgkin lymphoma is renewed.

We utilized in vitro and in vivo tumor models to understand the biologic mechanisms of action and antitumor activity of ixazomib in T-cell lymphoma and Hodgkin lymphoma, at clinically relevant concentrations. Through global transcriptome and network analysis, we describe the impact of ixazomib on biologic pathways and tumor progression in T-cell lymphoma and Hodgkin lymphoma cells. Furthermore, our investigation outlines mechanisms of CHK1-dependent, MYC-regulated cell death occurring via ixazomib and the associated critical implications impacting cell signaling and drug sensitivity. The impact of ixazomib on CHK1 and MYC is significant in the context of other previous studies indicating an existence of cooperative relationship between MYC and CHK1 as an important factor in driving lymphomagenesis (20). Further sensitivity to CHK1 inhibition has also been reported in lymphoma cells with MYC overexpression (21). Thus, with the ability to impact MYC and CHK1 as key driving mechanisms of tumorigenesis in lymphoma, ixazomib is a potential appealing antilymphoma agent.

Materials and Methods

Cell culture, reagents, and transfections

Hodgkin lymphoma cell lines L540 and L428 and, T-cell lymphoma cell lines HH, Hut78, and Jurkat were grown in RPMI-1640 consisting of 10% heat-inactivated FBS and penicillin/streptomycin (Mediatech) under 5% CO2 and 37°C. Cell lines were authenticated using short tandem repeat (STR) profiling service provided by ATCC. Ixazomib was kindly provided by Takeda Pharmaceuticals, Inc. Belinostat, JQ1, and the CHK1 inhibitor, AZD7762, were purchased from Selleck Chemicals. Nontargeting or MYC siRNAs were obtained from GE Healthcare, and transfection was performed using Nucleofector device and reagent kit L (Lonza).

MTT and apoptosis

MTT assay and Annexin V apoptosis detection were performed as described previously (22). IC50 values and combination indices for drug treatment were derived using Calcusyn Version 2.1 Software (Biosoft).

Lymphoma xenografts

For examination of the in vivo effect of ixazomib, human lymphoma xenografts derived from Jurkat (T-cell lymphoma) or L540 (Hodgkin lymphoma) grown in SCID mouse models described previously (22) were treated with either saline (control) or ixazomib (0.36 or 0.72 mg/kg) by intraperitoneal (i.p.) injections daily for 5 days for 3 weeks consisting 8 mice per group. Animals observation, tumor, and body weight measurements, and statistical analysis using GraphPad Prism 5.0, (GraphPad Software, Inc.), were performed as described previously (22). To quantify tumor growth, we used nonlinear regression to fit the tumor growth phase data with curves of the form V = bect, where V is tumor volume and t is time (23). Here, c is interpreted as the tumor growth rate once the tumor starts to grow more or less exponentially; b is interpreted as the extrapolated ‘effective’ volume at the implant time, t = 0.

Western blot analysis

Preparation of protein lysates and Western blot analysis was performed, as described previously (22). Primary antibodies against MYC, total or phospho CHK1 (Ser 345), total or acetylated histone H3, β-actin, HDAC3, p62, Cathepsin D total and cleaved caspase-3, 8, 9, PARP, and β-actin were purchased from Cell Signaling Technology.

Transcriptome analyses

Jurkat, L540, and L428 cells were treated in triplicates with 25 nmol/L ixazomib for 24 hours, RNA was isolated using RNeasy Minikit (Qiagen), and microarray experiment was performed using Affymetrix Human Gene Chip 2.0 (Jurkat and L540), or Human HT 12 Genechip Illumina (L428). The raw expression data from these experiments are available at NCBI Gene Expression Omnibus (GEO) database, with following identifiers GSE66417 (Jurkat/L540) and GSE66415 (L428). Data for Jurkat and L540 cell lines were background adjusted and quantile normalized using RMAExpress (24). Statistically relevant genes were determined by applying LIMMA (25) with an false discovery rate (FDR) < 0.05. Data for the L428 cell line (part of a larger dataset that was not used in this manuscript) was corrected through normalization of the housekeeping genes, quantile normalized, and then statistically relevant genes were determined with one-way ANOVA analysis with FDR < 0.05. Details on the pathway analysis, networks, and the unbiased method to determine the key significant genes are previously published in refs. 23, 26, 27.

Chromatin immunoprecipitation and PCR assay

Sample preparation was performed using Pierce Agarose ChIP Kit, Thermo Scientific, qRT-PCR was performed using primer set (#PPH00100B) from SABiosciences, designed to amplify human MYC promoter region proximal to transcription start site with SYBR Green Mastermix (Roche), and using Roche LightCycler I. For chromatin immunoprecipitation (ChIP), ChIP grade antibodies, Acetyl histone H3 K9 (#17-658) were purchased from EMD Millipore, anti-RNA polymerase II and normal rabbit IgG were supplied in Pierce Agarose ChIP kit and used as positive and negative control, respectively.

Results

In vitro and in vivo efficacy with therapy

Cell viability following exposure to ixazomib (12.5–1,000 nmol/L) for 72 hours in T-cell lymphoma cell lines (Jurkat, Hut78, HH) and Hodgkin lymphoma cell lines (L428, L540) resulted in a dose-dependent decrease in cell viability in all cell lines (Fig. 1A and B). L540 cells were observed to be most sensitive with associated 50% inhibitory effective dose (ED) concentration ED50 of 25 nmol/L compared with HH (41 nmol/L), Hut78 (52 nmol/L), Jurkat (38 nmol/L), and L428 (117 nmol/L). Treatment with ixazomib resulted in accumulation of ubiquitinylated protein as would be expected with proteosomal inhibition (Fig. 1C). In addition, there was induction of apoptosis in all lymphoma cell lines as detected by Western blot analysis of caspase-3, -7, -8, and -9, and PARP cleavage, except in L428 (Fig. 1C); this was confirmed with ixazomib-treated lymphoma cells using Annexin/PI staining and flow cytometry (Fig. 1D).

Figure 1.
Figure 1.

Proteasomal inhibition induces potent in vitro cell death and inhibits in vivo tumor growth in human lymphoma xenografts. A and B, dose-dependent increase in cytotoxicity with ixazomib in T-cell lymphoma and Hodgkin lymphoma lymphoma cell lines by MTT assay at 72 hours. C, Western blot analysis of ixazomib-treated T-cell lymphoma or Hodgkin lymphoma cell lines show accumulation of ubiquitinylated protein and activation of apoptotic markers at 24 hours. D, bar graph shows dose-dependent significant increase in Annexin-V–positive apoptotic cells in ixazomib-treated lymphoma cells. *, P < 0.05; **, P < 0.0001. Tumor-bearing SCID mice treated with ixazomib (0.72 mg/kg) showed significant reduction in the tumor volume (represented as line graph, P < 0.001, two-way repeated ANOVA), and Kaplan–Meier analysis showed significant increase in survival compared with controls (P < 0.001) in the experiments performed with Jurkat (E and F) or L540 (G and H)-derived tumor xenografts. I, tumor growth rate plot showing the effect of ixazomib treatment on tumor progression over the entire duration of assessment, with significant decrease in growth rate (P < 0.001) in L540, while in Jurkat, lag in tumor growth was noted.

The in vivo efficacy of ixazomib was investigated using tumor xenografts derived using either Jurkat or L540 cell lines. Results from Jurkat-derived xenograft experiments showed that after 4 weeks of ixazomib administration, there was a significant reduction in the average approximate size of the tumor (1,094 ± 76 mm3) with 0.36 mg/kg or (582 ± 45 mm3) with 0.72 mg/kg compared with the average size of tumor (1,465 ± 224 mm3) in the vehicle-treated control group (P < 0.0001; Fig. 1E). Kaplan–Meier survival analysis showed a significant improved survival in SCID mice consisting Jurkat xenograft treated with ixazomib compared with control group (P < 0.0001; Fig. 1F). Treatment with ixazomib in L540 xenograft tumor-bearing SCID mice also resulted in a significant reduction in the average size of the tumor (821 ± 54 mm3) with 0.36 mg/kg or (290 ± 5 mm3) with 0.72 mg/kg compared with vehicle-administered control group (1,128 ± 162 mm3), at the end of 4 weeks (P = <0.001; Fig. 1G). Kaplan–Meier survival analysis showed a significant increase in survival with ixazomib treatment compared with control groups (P < 0.0001; Fig. 1H).

We also analyzed detailed tumor growth kinetics by comparing tumor volumes measured before, during, and at the completion of treatment. Ixazomib resulted in decreased average tumor growth rate, 0.045 ± 0.0060 with 0.36 mg/kg and significantly (P = 0.002; 0.017 ± 0.0060 with 0.72 mg/kg), compared with the growth rate 0.049 ± 0.0045 in the vehicle-administered control group (Fig. 1I) consistent with inhibition of tumor progression in L540. This indicates there will be steady decrease in tumor growth with increasing doses of ixazomib. The kinetics of tumor growth in the Jurkat xenograft, however, showed no significant differences in growth rate (0.076 ± 0.012 with 0.36 mg/kg and 0.056 ± 0.015 with 0.72 mg.kg) compared with the growth rate of 0.052 ± 0.006 vehicle-administered control group, suggesting that ixazomib is causing a lag time delay in the tumor growth rather than any significant change in the growth rate. It should be noted that this prediction is obscured by large variances in the growth rates of tumor observed in the ixazomib-treated cohorts (Fig. 1I). Although ixazomib treatment appeared to affect the kinetics of the tumor growth by causing a lag time delay in the Jurkat-derived xenografts, comparison of average tumor size resulted in overall reduction in the tumor burden and improved survival benefit (Fig. 1E and H), indicating antitumor activity of ixazomib in this model. The results from in vitro and in vivo experiments demonstrate that proteasomal inhibition via ixazomib is associated with strong activity against T-cell lymphoma and Hodgkin lymphoma.

Transcriptome analyses of the impact of proteasomal inhibition on biologic pathways and “hallmarks of cancer”

Global transcriptome analyses following ixazomib exposure showed significant gene changes with a 1.2 fold change for Jurkat (508 genes), L540 (4765 genes), and L428 (423 genes; Fig. 2A) with an FDR < 0.05. L540 with the highest significantly differential expressed genes was the most ixazomib-sensitive Hodgkin lymphoma line (Fig. 1A) with significant inhibition of tumor growth (Fig. 1I). Gene expression with ixazomib compared with untreated control showed a total of 40 overlapping genes with a 1.2 fold change difference in Jurkat, L540, and L428 cells, with 326 overlapping genes in Jurkat and L540, and 212 overlapping gene sets in L428 and L540 Hodgkin lymphoma cells (Fig. 2B). The overlap based on common significantly regulated genes in Jurkat, L540, and L428 cells treated with ixazomib showed conserved upregulation of ubiquitin proteasome components PSMB3, PSMB6, PSMC4, PSMD6, UBE2H, UBFD1, and lysosome-associated factors ATG4A, CD68, PSAP, and SQSTM1 (also known as p62; Fig. 2C; ref. 9), and these gene expression changes were confirmed by qRT-PCR–based assay (Supplementary Fig. S1).

Figure 2.
Figure 2.

Gene expression profiling identifies critical genes, signaling pathways, and regulators affected by antiproteasomal therapy. A, average signal log2 fold-change comparing Ixazomib 24 hours versus control for 25 nmol/L ixazomib treatment in Jurkat, L540, and L428 cells. Whiskers show the range of the outliers, with max and min values as O and the 1 and 99th percentile outliers as X. Individual data points are shown on the left of box plots as filled circles. Dotted red lines show the 1.2 fold-change cutoff. B, Venn diagrams of the genes with 1.2 up- and downregulated fold changes for comparisons between ixazomib 24 hours versus control for Jurkat, L540, and L428 cells. C, scatter plot of average signal log2 fold-change comparing common significantly regulated genes between ixazomib 24 hours versus control for 25 nmol/L ixazomib treatment in Jurkat, L540, and L428 cells. Dotted red lines show the 1.2 fold-change cutoff.

Upstream regulator analysis performed using Ingenuity Pathway Analysis (IPA) and in conjunction with published data reporting impact on tumor progression, (Fig. 3; Supplementary Table S1) summarized the effects of ixazomib on tumor dynamics. Ixazomib treatment in Jurkat and L540 appeared to have shifted the balance of upstream regulators associated with tumor promotion and tumor suppression in favor of tumor inhibition (Fig. 3A), supporting the tumor-inhibitory effects of ixazomib observed with tumor xenografts (Fig. 1I). Conversely, the responses in L428 with ixazomib appeared to favor tumor progression (Fig. 3). Next, the status of upstream regulators was mapped on their functional contextual relationship to classical “hallmarks of cancer” (28, 29). Results from this evaluation show that ixazomib overwhelmingly impacts 9 of 12 “hallmarks of cancer,” (Fig. 4A), providing clues to tumor-inhibitory functions of ixazomib in L540 (Fig. 3A). In contrast, ixazomib treatment in L428 appears to promote the “self-sufficiency in growth signal” favoring tumor progression (Fig. 4B). Although additional experiments for a functional validation of these predictions are required, it must be noted that there was an apparent lack of apoptotic activity in L428 cells despite proteasomal inhibition with ixazomib (as detected as accumulation of ubiquitinylated protein; Fig. 1C). In fact, these cells demonstrated the lowest sensitivity to ixazomib compared with other cell lines tested (Fig. 1A and B). Interestingly, MYC inhibition represented among several “hallmarks of cancer” present in L540 is notably absent in L428 with ixazomib treatment (Fig. 4) and further validated by qRT-PCR–based assay (Supplementary Fig. S1). MYC is functionally associated with several oncogenic mechanisms associated with tumor progression (30), and inhibition of MYC with ixazomib treatment could be an important event in the antitumor activity of ixazomib.

Figure 3.
Figure 3.

Common upstream regulators determined by IPA software from the significant genes with antiproteasomal treatment. A, a schematic of the activation states of the upstream regulators illustrating the balance between the tumor promoters (text in yellow) and tumor suppressors (text in white and underlined) with a predicted activation (circled in orange) or predicted inhibition (circled in blue). B, scatter plot of the common significant upstream regulators (with activation z-scores > 2 or < −2) between ixazomib 24 hours treatment versus controls for Jurkat, L540, and L428 cells. Nonsignificant genes for L428 are also shown as gray dots. Dotted red lines show the cutoff for significantly regulated upstream regulators.

Figure 4.
Figure 4.

Effects of antiproteasomal treatment on the “hallmarks of cancer.” A and B, a schematic of the “hallmarks of cancer” overlaid with activation states of the upstream regulators illustrating the balance between the tumor promoters (text in red or blue) and tumor suppressors (text in red or blue, and underlined) with a predicted activation (text in red) or predicted inhibition (text in blue), showing the effect on “hallmarks of cancer” inhibition (shaded in dark/light green) or activation (shaded in red/orange) in the ixazomib treatment versus controls for L540 and L428 cells.

Gene set enrichment analysis (GSEA) revealed conserved upregulation of biologic pathways representing protein localization, proteasome, vesicle transport, apoptosis, oxidative stress, NF-κB, and catabolic processes with ixazomib in both L540 and L428 cells (Fig. 5A and Supplementary Fig. S2; Supplementary Tables S2 and S3). This included conservation of biologic pathways with gene expression analysis using different and higher doses of ixazomib in L428 and L540 (data not shown). Although biologic pathways associated with DNA repair, mitotic cell cycle, and microtubule organization oppositely regulated between L540 and L428 Hodgkin lymphoma cells, such patterns of biologic responses to ixazomib were consistently observed with GSEA performed using multiple reference databases (KEGG, Reactome and Biocarta; Supplementary Fig. S2; Supplementary Tables S2 and S3). In addition, GSEA predicted overall downregulation of MYC pathway with ixazomib in L540 or Jurkat (Supplementary Fig. S1C) as validated by qRT-PCR–based assay (Supplementary Fig. S1).

Figure 5.
Figure 5.

GSEA of transcriptomic network and the significant key genes in responses to antiproteasomal treatment. A, network representation of GSEA for GO C5 gene sets for ixazomib 24 hours versus control for Jurkat, L540, and L428 cells, with L540 overlaid with either Jurkat or L428. Leading edge analysis with a FDR < 0.05 determined significant gene sets enriched for each group. The size of each node reflects the amount of molecules involved for each gene set. The edge thickness (green lines for L540 and blue lines for either Jurkat or L428) represents the number of genes associated with the overlap of two gene sets (or nodes) that the edge connects. Clusters in each grouping were named according to common function. Upregulated gene sets, red; downregulated gene sets, blue. B, common significant key genes with the lymphoma cells treated with ixazomib. The interactions of the common key significant genes with symbols representing the biologic function and colors denoting up or downregulation in gene expression are described in the inserted legend. C, schematic of the activation states of the common significant key genes illustrating the balance between the tumor promoters (text in blue) and tumor suppressors (text in black and underlined) with the status of up (circled in red) or downregulation (circled in green) in the gene expression experiment with ixazomib.

Sixteen common key significant genes were determined for Jurkat and L540 cells treated with ixazomib, and these were nonoverlapping with L428 (Supplementary Table S4). These key genes are considered as “core responsive genes” and were determined by comparing common genes involved in the predicted upstream regulator analysis and biofunction analysis through IPA with the genes involved in the GSEA analysis (Fig. 5B). Surprisingly, the majority of these genes also have existing known interactions (Fig. 5B). Analysis of these 16 key genes (shown in Fig. 5B) using DAVID functional annotation and classification tool (31) identified 22 functional clusters that included mitotic cell cycle, apoptosis, proteolysis, metabolism, and lysosomal activity as key biologic responses affected by ixazomib in Jurkat and L540 (Supplementary Table S5).

Downregulation of MYC via proteosomal inhibition

Analysis of upstream regulators and GSEA with ixazomib transcriptome predicted MYC inhibition in L540 and Jurkat cells, but notably absent in L428 (Figs. 3 and 4) and validated by qRT-PCR–based assay (Supplementary Fig. S1). MYC is an important regulator of cell cycle, DNA repair, and replication, chromatin modification, inflammatory responses, lysosomal autophagy, metabolism, and oxidative stress (32, 33), and these pathways are also enriched with ixazomib treatment (Supplementary Fig. S2). Therefore, we next investigated the biologic responses of these enriched pathways using ixazomib-treated panel of lymphoma cells. Results from our experiments showed that MYC protein levels decreased with increasing concentrations of ixazomib in all lymphoma cells, except in the relatively less sensitive L428 cell line (Fig. 6A) consistent with transcriptional downregulation of MYC expression, as determined by qRT-PCR–based assay (Supplementary Fig. S1). A dose-dependent increase in lysosomal activity-associated Cathepsin D cleavage was observed in most of the cell lines, with L428 showing increase in lysosomal autophagy-related p62. Lysosomal activation could be relevant to MYC downregulation with ixazomib as previous data showed that MYC was a substrate in Cathepsin D–dependent proteolysis (34); presumably the activation of lysosomal proteolysis by ixazomib could be relevant to downregulation of MYC protein levels.

Figure 6.
Figure 6.

MYC downregulation by ixazomib. A, Western blot analysis show the dose-dependent effects of ixazomib on MYC protein and the events associated with lysosomal activity, cell cycle, and chromatin modification responses. B, electron microscopic findings with ixazomib treatment show presence of vacuolar structures with light to dense amorphous granulations, representing lysosomal bodies (arrows), localized predominantly in the cytoplasm and occasionally present in the perinuclear or nuclear region. C, cytoplasm; N, nucleus. C, inhibition of lysosomal proteases with E64/Pepstatin potentiates downregulation of MYC and acetylation of histone H3, and increases caspase-3 and PARP cleavage, detected by Western blot analysis. D, box plot based on average signal log2 fold-change comparing ixazomib 24 hours versus control for 25 nmol/L ixazomib treatment in Jurkat, L540, and L428 cells. Dotted red lines show the 1.2 fold-change cutoff for the differentially expressed MYC- and CHK1-related genes. E, bar graph shows representation in percentages of MYC- or CHK1-regulated differentially expressed genes within the entire set of MYC- or CHK1-regulated genes among the entire transcriptome and overlap between these differentially expressed gene sets in ixazomib-treated Jurkat, L540, and L428 cells.

Proteasomal inhibition has been previously shown to inhibit DNA damage response to IR via inhibition of CHK1 phosphorylation (35) and our results from GSEA show downregulation of genes associated with DNA damage, DNA repair and cell-cycle progression with ixazomib (Fig. 5 and Supplementary Fig. S2; Supplementary Tables S2 and S3). We examined inhibition of CHK1 phosphorylation as a marker for these responses (36) and observed inhibition of CHK1 phosphorylation in all cell lines with ixazomib treatment except in L428 (Fig. 6A). Histone H3 acetylation, a marker of chromatin modification, which is regulated by CHK1 (37) and affects MYC expression (38), was also decreased with increasing concentrations of ixazomib in Jurkat, HH, and Hut78 and L540 cells, without significant effect in L428 cells (Fig. 6A). Collectively, these results suggest that biologic responses of MYC, lysosome, cell cycle, and chromatin modification correlate with each other and are conserved in ixazomib T-cell lymphoma and Hodgkin lymphoma cell lines, while such conservation was lacking in L428 cells, exactly as predicted from GSEA (Fig. 5) and DAVID analysis (Supplementary Table S5)

Lysosomal activity represents as alternate means for protein degradation and therefore, excess protein accumulation resulting from proteasomal inhibition is expected to trigger lysosomal function (39). Because MYC is also a substrate for lysosomal proteolysis (34), we subsequently investigated the role of lysosomal activity and its relation to MYC. Analysis via electron microscopy revealed characteristic features representing lysosomal maturation in ixazomib-treated cells (Fig. 6B); however, subsequent Western blot analysis did not show evidence of autophagy as determined on the basis of mTOR and Beclin phosphorylation, and LC3A cleavage (data not shown). Further inhibition of lysosomal protease with E64d/Pepstatin CHK1 did not result in MYC accumulation but rather led to accelerated reduction in MYC protein and histone H3 acetylation, and enhanced apoptosis, detected as cleaved caspase-3 and PARP in ixazomib-treated Jurkat and L428 cells (Fig. 6C). There was no corresponding HDAC accumulation with decreased histone H3 acetylation with lysosomal inhibition (Fig. 6C), suggesting HDAC-independent reduction of histone H3 acetylation with ixazomib. Taken together, inhibition of proteasomal and lysosomal proteolysis, instead of resulting in MYC accumulation resulted in further loss of MYC protein, indicating a possible role for transcriptional regulation of MYC expression with ixazomib treatment.

Next, we focused our investigation on the cell-cycle regulatory CHK1 in the context of MYC function, because MYC and CHK1 interaction is a known oncogenic mechanism in lymphomagenesis (20), the role of CHK1 in transcriptional regulation via histone H3 acetylation is known (37), and histone H3 acetylation is required for MYC transcription (33). We examined genes regulated by MYC and CHK1 in ixazomib-treated cells and observed strong overlap in the target gene sets regulated by MYC and CHK1. There was overall downregulation of MYC-associated genes in both L540 (53%) and Jurkat (5%) and upregulation of MYC-associated genes in L428 (6%; Fig. 6D and E). Similarly, there was overall downregulation of CHK1-associated genes in both L540 (47%) and Jurkat (11%) and upregulation of CHK1-associated genes in L428 (7%; Fig. 6D and E). By comparing MYC and CHK1-regulated genes, we noted the presence of overlapping gene sets in L540 (20%), Jurkat (7%), and L428 (33%). Considering the strong overlap and the pattern of differentially expressed gene sets representing both MYC and CHK1, we narrowed our investigation to determine the biologic relationship between these oncogenes.

MYC promoter binding and importance of CHK1

We investigated the effect of CHK1 inhibition on histone H3 acetylation and MYC in L428 cells treated with ixazomib. We observed that CHK1 inhibitor (AZD7762) alone, or in combination with ixazomib, strongly downregulated histone H3 acetylation, phosphorylation of CHK1-dependent Threonine 11 (37), on histone H3, and MYC protein (Fig. 7A). Furthermore, inhibition of histone acetyl transferase (HAT) by C646 also resulted in downregulation of MYC (Supplementary Fig. S3), indicating that CHK1 and histone H3 acetylation are upstream in the regulation of MYC expression. Therefore, we performed ChIP using anti-acetylated histone H3 and PCR assay for its binding on the MYC promoter region. We observed that ixazomib treatment resulted in decreased MYC amplification relative to untreated Jurkat control cells (Fig. 7B), indicating reduced MYC promoter occupancy by acetylated histone H3 as a possible mechanism for ixazomib-dependent downregulation of MYC expression in the Jurkat cells. In contrast, we noted increased PCR amplification of MYC in L428 cells, indicating higher promoter occupancy by acetyl histone H3, suggesting an active transcription process with ixazomib (Fig. 7B). Our conclusions based on the results from the ChIP experiment showed decreased and increased promoter occupancy in Jurkat and L428 (Fig. 7B), respectively, which are consistent with the patterns of MYC-dependent gene expression observed in these cells (Fig. 6A and D), indicate that MYC function is regulated at the level of transcription with ixazomib treatment. Because we observed that ixazomib treatment resulted in downregulation of MYC and CHK1 phosphorylation in all lymphoma cells, except in L428 cells, we chose to examine the consequences of blocking CHK1 on MYC expression in L428 cells. Previous analyses demonstrated a direct role for CHK1 kinase activity in histone H3 phosphorylation (Threonine 11) and stabilization of histone H3 acetylation to facilitate transcription via retention of relaxed chromatin confirmation (37). Therefore, we performed ChIP PCR assay for MYC, in the presence of AZD7762 (CHK1 inhibitor) to determine whether CHK1-dependent histone modification affects MYC expression. The results from our experiments show decreased MYC promoter occupancy by acetylated-Histone compared with untreated control, or in the presence of ixazomib in L428 cells (Fig. 7C). Taken together, these results demonstrated that CHK1 inhibition leading to decreased histone H3 acetylation and MYC expression (Fig. 7A) is associated with decreased promoter occupancy on MYC gene (Fig. 7C), suggesting that CHK1 is actively involved in the transcriptional control of MYC in the ixazomib-treated lymphoma cells.

Figure 7.
Figure 7.

CHK1 and histone H3 acetylation-dependent MYC response to ixazomib. A, inhibition of CHK1 potentiates downregulation acetylation and phosphorylation of histone H3, and MYC protein with ixazomib. B, ChIP with anti-acetylated histone H3 and PCR for MYC promoter normalized with input DNA, show decreased promoter occupancy in Jurkat, and increased promoter occupancy in L428 cells with ixazomib treatment. C, ChIP with anti-acetylated histone H3 and PCR for MYC promoter normalized with input DNA, show that AZD7762 (i.e., CHK1 inhibitor) decreased acetylated histone H3 promoter occupancy in L428 cells, with ixazomib treatment. D–F, bar graphs show significant increase in Annexin V positivity (P < 0.001) in ixazomib-treated L428 cells in the presence of AZD7762 compared with all doses of ixazomib alone. Western blot analysis show treatment with JQ1 (i.e., bromodomain inhibitor) downregulates MYC and increases caspsase-3 and PARP cleavage with ixazomib in Jurkat and L428 cells as well as via with MYC or CHK1 RNAi silencing results in increased PARP cleavage. G–J, treatment of ixazomib in combination with AZD7762 or JQ1 for 72 hours, in L428 and the analysis of results from MTT assay show synergistic effect (CI < 1), represented as median dose effect curve and combination indices graph, determined using Calcusyn software.

CHK1 or MYC inhibition synergizes with antiproteasomal therapy

Considering that CHK1 phosphorylation and MYC expression were not affected by ixazomib treatment in L428 (Fig. 6A and D), and L428 showed least sensitivity to ixazomib (by MTT and Apoptosis; Fig. 1B and C) compared with other lymphoma cells, we predicted that a combination CHK1 inhibitor and ixazomib is likely to downregulate MYC and restore ixazomib sensitivity in the L428 Hodgkin lymphoma cells. Therefore, we treated L428 cells with increasing doses of ixazomib alone and in presence of CHK1 inhibitor, AZD7762, and observed a significant increase in Annexin—positive apoptosis (P < 0.001) in the combination of ixazomib with AZD7762 compared with controls (Fig. 7D). Next considering that MYC downregulation is predicted as a prominent mechanism in ixazomib sensitivity, and we used JQ1 (bromodomain inhibitor, blocks MYC transcription) to inhibit MYC expression and observed potentiation of apoptosis, detected as cleaved PARP, both in Jurkat (T-cell lymphoma) and L428 Hodgkin lymphoma cells in the presence of ixazomib (Fig. 7E). Furthermore, these results were independently confirmed using RNAi-mediated silencing of MYC or CHK1 (Fig. 7F). Considering that MYC downregulation and cotargeting of MYC could be clinically relevant for ixazomib-based treatments, we finally investigated to determine whether such targeted drug combinations would be synergistic. Our results based on MTT assays show that targeting CHK1 with AZD7762 (ED50 1.1 μmol/L) in the presence of ixazomib was synergistic (CI < 1) in L428 Hodgkin lymphoma cells (Fig. 7G and H) and similarly, combination of JQ1 (ED50 5.5 μmol/L) with ixazomib also resulted in synergistic effect (CI < 1) in L428 (Fig. 7I and J), suggesting that AZD7762 or JQ1-dependent MYC downregulation will lead to synergistic cell death in ixazomib-refractory L428 cells, with dominant MYC function.

Discussion

The prominent substrates regulated by proteasome-dependent turnover includes key proteins involved in the regulation of replication, transcription, translation, cell cycle, tumor suppression, signal transduction, apoptosis, metabolism among others (40). NF-κB has been shown to be constitutively active in Hodgkin lymphoma cell lines and also critical for HRS cell survival in xenograft studies (10, 11). Furthermore, NF-κB has been shown to be highly overexpressed and responsible for tumorigenesis in both HRS and T-cell lymphoma models (14, 15). Despite these promising preclinical data, proteosomal inhibition with bortezomib had only modest clinical activity in Hodgkin lymphoma (16, 17), while more encouraging clinical activity has been reported in T-cell lymphoma (41, 42). To exploit the strong and functional presence of NF-κB in Hodgkin lymphoma and T-cell lymphoma, which is regulated by the proteasome, we examined the effects of the novel second-generation orally bioactive proteasome inhibitor, ixazomib, which has superior pharmacokinetics/pharmacodynamics compared with bortezomib (18). Considering also that early reports from ixazomib lymphoma clinical studies have been encouraging (6), the results from our analyses provide the biologic basis and the mechanisms of activity of ixazomib activity.

Results herein demonstrated that ixazomib induced potent cell death and inhibited tumor growth in T-cell lymphoma and Hodgkin lymphoma cells at clinically achievable nanomolar concentrations. Transcriptome analysis showed conserved and consistent biologic responses with ixazomib in both T-cell lymphoma and Hodgkin lymphoma cells. Furthermore, the activation status of tumor suppressors and inhibition of oncogenes indicated strong potential for the inhibition of tumor progression with ixazomib in T-cell lymphoma and Hodgkin lymphoma and substantial impact were predicted on overall global “hallmarks of cancer.” Although we observed conserved biologic regulations with ixazomib treatment in Jurkat and L540 cells, we also noted that a lack of conservation with biologic responses, associated with minimal impact on the ‘hallmarks of cancer’ was related to poor sensitivity to ixazomib in L428 cells.

We postulated that examining the biologic differences in response to ixazomib in the differentially sensitive lymphoma cells could provide clues to determine the associated biologic mechanisms of actions to ixazomib treatment. Constitutive expression of NF-κB has been commonly observed in Hodgkin lymphoma cells including L428 (43). Furthermore, we observed induction of NF-κB genes with ixazomib treatment in both ixazomib-sensitive L540 and -resistant L428 Hodgkin lymphoma cells (Fig. 5A), and we subsequently verified that NF-κB activation occurs in ixazomib-treated multiple T-cell lymphoma and Hodgkin lymphoma cells as shown by Western blot assays (data not shown) thus ruling out a significant role for NF-κB in resistance to ixazomib. Among the significant upstream regulators affected with ixazomib, inactivation of MYC, which was predicted in Jurkat and L540 cells, were absent in L428. MYC is central to major regulatory pathways including cell cycle, DNA repair, replication, transcription and translation, and metabolism (44) with global impact on major “hallmarks of cancer” progression (30). MYC is transcriptionally regulated by cell-cycle regulatory proteins (p21, CHK1, CDC2) through chromatin modification via histone acetylation (37) and BRCA1 pathways (45).

We demonstrated that ixazomib affected many of the aforementioned MYC-related biologic pathways and expression of MYC protein (Fig. 6A). Overexpression of MYC occurs in 30% of all human cancers and frequently predicts for aggressive biologic behavior, advanced stage of disease, increased likelihood of relapse, and poor clinical outcome (46, 47). Studies in transgenic mouse models showed that even brief MYC inactivation is sufficient to induce tumor regressions (48) and that targeting MYC may destabilize apoptosis regulatory network and induce cell death in lymphoma (49). In multiple myeloma, a correlation between MYC overexpression (50) and poor response to treatment with bortezomib has been reported, and in mantle cell lymphoma, cotargeting MYC with (CPI203) was shown to overcome bortezomib resistance (51). Although these studies show a correlation between MYC and resistance to proteasome inhibition, results from our experiments demonstrated the biologic mechanism for MYC-dependent resistance to proteasome inhibition, and moreover, how to circumvent these mechanisms to improve therapeutic response.

In L428 cells, poor sensitivity to ixazomib correlated with lack of MYC regulation and histone H3 acetylation. Both histone acetylation and MYC affect similar downstream biologic processes including, chromatin modification, gene expression, DNA replication and repair, cell cycle, cytoskeletal function, and protein trafficking (52). Chromatin modification involving histone acetylation is mediated by a family of HATs and HDACs with opposing enzymatic activities, and histone acetylation is an important mechanism in the regulation of MYC gene expression (52). Furthermore, the cell-cycle regulatory CHK1 is known to regulate histone acetylation via histone H3 phosphorylation (37), which leads to HDAC3 disassociation favoring MYC transcription (38). Thus, in our experiments, CHK1 inhibition alone or in the presence of ixazomib, decreased MYC promoter occupancy (by acetylated histone H3) and reduced MYC protein in L428 (Fig. 7A and D). Furthermore, by using pharmacologic inhibitors and RNAi for CHK1 and MYC, we demonstrated that MYC downregulation was required for inducing cell death with ixazomib. In addition, CHK1 inhibition has been reported to enhance cytotoxicity with lenalidomide selectively in MYC-dependent lymphoma (53), supporting the role for CHK1 dependency in MYC-driven tumors. Altogether, results from our analyses showed that ixazomib alone or in combination with CHK1 inhibition has the potential to significantly downregulate MYC and induce potent cell death in T-cell lymphoma and Hodgkin lymphoma models, and it represents a novel combinatorial therapeutic platform for the treatment of these cancers.

Disclosure of Potential Conflicts of Interest

A.M. Evens has received speakers bureau honoraria from and is a consultant/advisory board member for Millennium. No potential conflicts of interest were disclosed by the other authors.

Authors' Contributions

Conception and design: D. Ravi, M.V. Sitkovsky, A.P. Mazar, A.M. Evens

Development of methodology: D. Ravi, A. Beheshti, I. Kandela, L. Hlatky, A.M. Evens

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): D. Ravi, A. Beheshti, N. Abermil, F. Passero, J. Sharma, M. Coyle, I. Kandela

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): D. Ravi, A. Beheshti, F. Passero, J. Sharma, I. Kandela, R.B. Gartenhaus, A.M. Evens

Writing, review, and/or revision of the manuscript: D. Ravi, A. Beheshti, N. Abermil, M. Coyle, A. Kritharis, R.B. Gartenhaus, A.M. Evens

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D. Ravi, A.P. Mazar, A.M. Evens

Study supervision: D. Ravi, A. Beheshti, L. Hlatky, A.M. Evens

Other (discussions of the need to focus on the manipulation of the mechanisms of cell death to improve the immunogenicity of lymphomas): M.V. Sitkovsky

Grant Support

Research funding and ixazomib drug were provided by Takeda Pharmaceutical Inc. (A.M. Evens) and NIH grant R01 CA164311 (A.M. Evens and R.G. Gartenhaus).

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.

Footnotes

  • Note: Supplementary data for this article are available at Cancer Research Online (http://cancerres.aacrjournals.org/).

  • Received September 4, 2015.
  • Revision received January 27, 2016.
  • Accepted February 29, 2016.

References

  1. 1.↵
    1. Edwards CM,
    2. Lwin ST,
    3. Fowler JA,
    4. Oyajobi BO,
    5. Zhuang J,
    6. Bates AL,
    7. et al.
    Myeloma cells exhibit an increase in proteasome activity and an enhanced response to proteasome inhibition in the bone marrow microenvironment in vivo . Am J Hematol 2009;84:268–72.
    OpenUrlCrossRefPubMed
  2. 2.↵
    1. Esseltine DL,
    2. Mulligan G
    . An historic perspective of proteasome inhibition. Semin Hematol 2012;49:196–206.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Chen D,
    2. Frezza M,
    3. Schmitt S,
    4. Kanwar J,
    5. Dou QP
    . Bortezomib as the first proteasome inhibitor anticancer drug: current status and future perspectives. Curr Cancer Drug Targets 2011;11:239–53.
    OpenUrlCrossRefPubMed
  4. 4.↵
    1. Kirk CJ
    . Discovery and development of second-generation proteasome inhibitors. Semin Hematol 2012;49:207–14.
    OpenUrlCrossRefPubMed
  5. 5.↵
    1. Moreau P,
    2. Richardson PG,
    3. Cavo M,
    4. Orlowski RZ,
    5. San Miguel JF,
    6. Palumbo A,
    7. et al.
    Proteasome inhibitors in multiple myeloma: 10 years later. Blood 2012;120:947–59.
    OpenUrlAbstract/FREE Full Text
  6. 6.↵
    1. Assouline SE,
    2. Chang J,
    3. Cheson BD,
    4. Rifkin R,
    5. Hamburg S,
    6. Reyes R,
    7. et al.
    Phase 1 dose-escalation study of IV ixazomib, an investigational proteasome inhibitor, in patients with relapsed/refractory lymphoma. Blood Cancer J 2014;4:e251.
    OpenUrlCrossRefPubMed
  7. 7.↵
    1. Coiffier B,
    2. Federico M,
    3. Caballero D,
    4. Dearden C,
    5. Morschhauser F,
    6. Jager U,
    7. et al.
    Therapeutic options in relapsed or refractory peripheral T-cell lymphoma. Cancer Treat Rev 2014;40:1080–8.
    OpenUrlCrossRefPubMed
  8. 8.↵
    1. Evens AM,
    2. Hutchings M,
    3. Diehl V
    . Treatment of Hodgkin lymphoma: the past, present, and future. Nat Clin Pract Oncol 2008;5:543–56.
    OpenUrlCrossRefPubMed
  9. 9.↵
    1. Rogov V,
    2. Dotsch V,
    3. Johansen T,
    4. Kirkin V
    . Interactions between autophagy receptors and ubiquitin-like proteins form the molecular basis for selective autophagy. Mol Cell 2014;53:167–78.
    OpenUrlCrossRefPubMed
  10. 10.↵
    1. Bargou RC,
    2. Emmerich F,
    3. Krappmann D,
    4. Bommert K,
    5. Mapara MY,
    6. Arnold W,
    7. et al.
    Constitutive nuclear factor-kappaB-RelA activation is required for proliferation and survival of Hodgkin's disease tumor cells. J Clin Invest 1997;100:2961–9.
    OpenUrlCrossRefPubMed
  11. 11.↵
    1. Bargou RC,
    2. Leng C,
    3. Krappmann D,
    4. Emmerich F,
    5. Mapara MY,
    6. Bommert K,
    7. et al.
    High-level nuclear NF-kappa B and Oct-2 is a common feature of cultured Hodgkin/Reed-Sternberg cells. Blood 1996;87:4340–7.
    OpenUrlAbstract/FREE Full Text
  12. 12.↵
    1. Kuppers R
    . Molecular biology of Hodgkin lymphoma. Hematology Am Soc Hematol Educ Program 2009;1:491–6.
    OpenUrl
  13. 13.↵
    1. Hinz M,
    2. Loser P,
    3. Mathas S,
    4. Krappmann D,
    5. Dorken B,
    6. Scheidereit C
    . Constitutive NF-kappaB maintains high expression of a characteristic gene network, including CD40, CD86, and a set of antiapoptotic genes in Hodgkin/Reed-Sternberg cells. Blood 2001;97:2798–807.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. Saitoh Y,
    2. Yamamoto N,
    3. Dewan MZ,
    4. Sugimoto H,
    5. Martinez Bruyn VJ,
    6. Iwasaki Y,
    7. et al.
    Overexpressed NF-kappaB-inducing kinase contributes to the tumorigenesis of adult T-cell leukemia and Hodgkin Reed-Sternberg cells. Blood 2008;111:5118–29.
    OpenUrlAbstract/FREE Full Text
  15. 15.↵
    1. Mathas S,
    2. Johrens K,
    3. Joos S,
    4. Lietz A,
    5. Hummel F,
    6. Janz M,
    7. et al.
    Elevated NF-kappaB p50 complex formation and Bcl-3 expression in classical Hodgkin, anaplastic large-cell, and other peripheral T-cell lymphomas. Blood 2005;106:4287–93.
    OpenUrlAbstract/FREE Full Text
  16. 16.↵
    1. Blum KA,
    2. Johnson JL,
    3. Niedzwiecki D,
    4. Canellos GP,
    5. Cheson BD,
    6. Bartlett NL
    . Single agent bortezomib in the treatment of relapsed and refractory Hodgkin lymphoma: cancer and leukemia Group B protocol 50206. Leuk Lymphoma 2007;48:1313–9.
    OpenUrlCrossRefPubMed
  17. 17.↵
    1. Ishitsuka K,
    2. Utsunomiya A,
    3. Katsuya H,
    4. Takeuchi S,
    5. Takatsuka Y,
    6. Hidaka M,
    7. et al.
    A phase II study of bortezomib in patients with relapsed or refractory aggressive adult T-cell leukemia/lymphoma. Cancer Sci 2015;106:1219–23.
    OpenUrlCrossRefPubMed
  18. 18.↵
    1. Kupperman E,
    2. Lee EC,
    3. Cao Y,
    4. Bannerman B,
    5. Fitzgerald M,
    6. Berger A,
    7. et al.
    Evaluation of the proteasome inhibitor MLN9708 in preclinical models of human cancer. Cancer Res 2010;70:1970–80.
    OpenUrlAbstract/FREE Full Text
  19. 19.↵
    1. Lee EC,
    2. Fitzgerald M,
    3. Bannerman B,
    4. Donelan J,
    5. Bano K,
    6. Terkelsen J,
    7. et al.
    Antitumor activity of the investigational proteasome inhibitor MLN9708 in mouse models of B-cell and plasma cell malignancies. Clin Cancer Res 2011;17:7313–23.
    OpenUrlAbstract/FREE Full Text
  20. 20.↵
    1. Hoglund A,
    2. Nilsson LM,
    3. Muralidharan SV,
    4. Hasvold LA,
    5. Merta P,
    6. Rudelius M,
    7. et al.
    Therapeutic implications for the induced levels of Chk1 in Myc-expressing cancer cells. Clin Cancer Res 2011;17:7067–79.
    OpenUrlAbstract/FREE Full Text
  21. 21.↵
    1. Li X,
    2. Zhang XA,
    3. Xie W,
    4. Li X,
    5. Huang S
    . MYC-mediated synthetic lethality for treatment of hematological malignancies. Curr Cancer Drug Targets 2015;15:53–70.
    OpenUrlCrossRefPubMed
  22. 22.↵
    1. Ravi D,
    2. Bhalla S,
    3. Gartenhaus RB,
    4. Crombie J,
    5. Sharma J,
    6. Kandela IK,
    7. et al.
    The novel organic arsenical darinaparsin induces MAPK-mediated and SHP1-dependent cell death in T-cell lymphoma and Hodgkin lymphoma cells and human xenograft models. Clin Cancer Res 2014;20:6023–33.
    OpenUrlAbstract/FREE Full Text
  23. 23.↵
    1. Beheshti A,
    2. Sachs RK,
    3. Peluso M,
    4. Rietman E,
    5. Hahnfeldt P,
    6. Hlatky L
    . Age and space irradiation modulate tumor progression: implications for carcinogenesis risk. Radiat Res 2013;179:208–20.
    OpenUrlCrossRefPubMed
  24. 24.↵
    1. Bolstad BM,
    2. Irizarry RA,
    3. Astrand M,
    4. Speed TP
    . A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 2003;19:185–93.
    OpenUrlAbstract/FREE Full Text
  25. 25.↵
    1. Smyth GK,
    2. Michaud J,
    3. Scott HS
    . Use of within-array replicate spots for assessing differential expression in microarray experiments. Bioinformatics 2005;21:2067–75.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. Beheshti A,
    2. Benzekry S,
    3. McDonald JT,
    4. Ma L,
    5. Peluso M,
    6. Hahnfeldt P,
    7. et al.
    Host age is a systemic regulator of gene expression impacting cancer progression. Cancer Res 2015;75:1134–43.
    OpenUrlAbstract/FREE Full Text
  27. 27.↵
    1. Beheshti A,
    2. Neuberg D,
    3. McDonald JT,
    4. Vanderburg CR,
    5. Evens AM
    . The impact of age and sex in DLBCL: systems biology analyses identify distinct molecular changes and signaling networks. Cancer Inform 2015;14:141–8.
    OpenUrlPubMed
  28. 28.↵
    1. Hanahan D,
    2. Weinberg RA
    . Hallmarks of cancer: the next generation. Cell 2011;144:646–74.
    OpenUrlCrossRefPubMed
  29. 29.↵
    1. Sankar N,
    2. Kadeppagari RK,
    3. Thimmapaya B
    . c-Myc-induced aberrant DNA synthesis and activation of DNA damage response in p300 knockdown cells. J Biol Chem 2009;284:15193–205.
    OpenUrlAbstract/FREE Full Text
  30. 30.↵
    1. Whitfield JR,
    2. Soucek L
    . Tumor microenvironment: becoming sick of Myc. Cell Mol Life Sci 2012;69:931–4.
    OpenUrlCrossRefPubMed
  31. 31.↵
    1. Merico D,
    2. Isserlin R,
    3. Stueker O,
    4. Emili A,
    5. Bader GD
    . Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. PLoS ONE 2010;5:e13984.
    OpenUrlCrossRefPubMed
  32. 32.↵
    1. Toh PP,
    2. Luo S,
    3. Menzies FM,
    4. Rasko T,
    5. Wanker EE,
    6. Rubinsztein DC
    . Myc inhibition impairs autophagosome formation. Hum Mol Genet 2013;22:5237–48.
    OpenUrlAbstract/FREE Full Text
  33. 33.↵
    1. Baluchamy S,
    2. Rajabi HN,
    3. Thimmapaya R,
    4. Navaraj A,
    5. Thimmapaya B
    . Repression of c-Myc and inhibition of G1 exit in cells conditionally overexpressing p300 that is not dependent on its histone acetyltransferase activity. Proc Natl Acad Sci U S A 2003;100:9524–9.
    OpenUrlAbstract/FREE Full Text
  34. 34.↵
    1. Wong WJ,
    2. Qiu B,
    3. Nakazawa MS,
    4. Qing G,
    5. Simon MC
    . MYC degradation under low O2 tension promotes survival by evading hypoxia-induced cell death. Mol Cell Biol 2013;33:3494–504.
    OpenUrlAbstract/FREE Full Text
  35. 35.↵
    1. Jacquemont C,
    2. Taniguchi T
    . Proteasome function is required for DNA damage response and fanconi anemia pathway activation. Cancer Res 2007;67:7395–405.
    OpenUrlAbstract/FREE Full Text
  36. 36.↵
    1. Thanasoula M,
    2. Escandell JM,
    3. Suwaki N,
    4. Tarsounas M
    . ATM/ATR checkpoint activation downregulates CDC25C to prevent mitotic entry with uncapped telomeres. EMBO J 2012;31:3398–410.
    OpenUrlAbstract/FREE Full Text
  37. 37.↵
    1. Shimada M,
    2. Niida H,
    3. Zineldeen DH,
    4. Tagami H,
    5. Tanaka M,
    6. Saito H,
    7. et al.
    Chk1 is a histone H3 threonine 11 kinase that regulates DNA damage-induced transcriptional repression. Cell 2008;132:221–32.
    OpenUrlCrossRefPubMed
  38. 38.↵
    1. Yang W,
    2. Xia Y,
    3. Hawke D,
    4. Li X,
    5. Liang J,
    6. Xing D,
    7. et al.
    PKM2 phosphorylates histone H3 and promotes gene transcription and tumorigenesis. Cell 2012;150:685–96.
    OpenUrlCrossRefPubMed
  39. 39.↵
    1. Jia L,
    2. Gopinathan G,
    3. Sukumar JT,
    4. Gribben JG
    . Blocking autophagy prevents bortezomib-induced NF-kappaB activation by reducing I-kappaBalpha degradation in lymphoma cells. PLoS ONE 2012;7:e32584.
    OpenUrlCrossRefPubMed
  40. 40.↵
    1. Lim MS,
    2. Elenitoba-Johnson KS
    . Ubiquitin ligases in malignant lymphoma. Leuk Lymphoma 2004;45:1329–39.
    OpenUrlCrossRefPubMed
  41. 41.↵
    1. Evens AM,
    2. Rosen ST,
    3. Helenowski I,
    4. Kline J,
    5. Larsen A,
    6. Colvin J,
    7. et al.
    A phase I/II trial of bortezomib combined concurrently with gemcitabine for relapsed or refractory DLBCL and peripheral T-cell lymphomas. Br J Haematol 2013;163:55–61.
    OpenUrlCrossRefPubMed
  42. 42.↵
    1. Zinzani PL,
    2. Musuraca G,
    3. Tani M,
    4. Stefoni V,
    5. Marchi E,
    6. Fina M,
    7. et al.
    Phase II trial of proteasome inhibitor bortezomib in patients with relapsed or refractory cutaneous T-cell lymphoma. J Clin Oncol 2007;25:4293–7.
    OpenUrlAbstract/FREE Full Text
  43. 43.↵
    1. Wood KM,
    2. Roff M,
    3. Hay RT
    . Defective IkappaBalpha in Hodgkin cell lines with constitutively active NF-kappaB. Oncogene 1998;16:2131–9.
    OpenUrlCrossRefPubMed
  44. 44.↵
    1. Meyer N,
    2. Penn LZ
    . Reflecting on 25 years with MYC. Nat Rev Cancer 2008;8:976–90.
    OpenUrlCrossRefPubMed
  45. 45.↵
    1. Chen Y,
    2. Xu J,
    3. Borowicz S,
    4. Collins C,
    5. Huo D,
    6. Olopade OI
    . c-Myc activates BRCA1 gene expression through distal promoter elements in breast cancer cells. BMC Cancer 2011;11:246.
    OpenUrlCrossRefPubMed
  46. 46.↵
    1. Gamberi G,
    2. Benassi MS,
    3. Bohling T,
    4. Ragazzini P,
    5. Molendini L,
    6. Sollazzo MR,
    7. et al.
    C-myc and c-fos in human osteosarcoma: prognostic value of mRNA and protein expression. Oncology 1998;55:556–63.
    OpenUrlCrossRefPubMed
  47. 47.↵
    1. McKeown MR,
    2. Bradner JE
    . Therapeutic strategies to inhibit MYC. Cold Spring Harb Perspect Med 2014;4.
  48. 48.↵
    1. Jain M,
    2. Arvanitis C,
    3. Chu K,
    4. Dewey W,
    5. Leonhardt E,
    6. Trinh M,
    7. et al.
    Sustained loss of a neoplastic phenotype by brief inactivation of MYC. Science 2002;297:102–4.
    OpenUrlAbstract/FREE Full Text
  49. 49.↵
    1. Klapproth K,
    2. Wirth T
    . Advances in the understanding of MYC-induced lymphomagenesis. Br J Haematol 2010;149:484–97.
    OpenUrlCrossRefPubMed
  50. 50.↵
    1. Sekiguchi N,
    2. Ootsubo K,
    3. Wagatsuma M,
    4. Midorikawa K,
    5. Nagata A,
    6. Noto S,
    7. et al.
    Impact of C-Myc gene-related aberrations in newly diagnosed myeloma with bortezomib/dexamethasone therapy. Int J Hematol 2014;99:288–95.
    OpenUrlCrossRefPubMed
  51. 51.↵
    1. Moros A,
    2. Rodriguez V,
    3. Saborit-Villarroya I,
    4. Montraveta A,
    5. Balsas P,
    6. Sandy P,
    7. et al.
    Synergistic antitumor activity of lenalidomide with the BET bromodomain inhibitor CPI203 in bortezomib-resistant mantle cell lymphoma. Leukemia 2014;28:2049–59.
    OpenUrlPubMed
  52. 52.↵
    1. Hideshima T,
    2. Richardson PG,
    3. Anderson KC
    . Mechanism of action of proteasome inhibitors and deacetylase inhibitors and the biological basis of synergy in multiple myeloma. Mol Cancer Ther 2011;10:2034–42.
    OpenUrlAbstract/FREE Full Text
  53. 53.↵
    1. Murga M,
    2. Campaner S,
    3. Lopez-Contreras AJ,
    4. Toledo LI,
    5. Soria R,
    6. Montana MF,
    7. et al.
    Exploiting oncogene-induced replicative stress for the selective killing of Myc-driven tumors. Nat Struct Mol Biol 2011;18:1331–5.
    OpenUrlCrossRefPubMed
View Abstract
Back to top
Cancer Research: 76 (11)
June 2016
Volume 76, Issue 11

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Email Article
Citation Tools
Proteasomal Inhibition by Ixazomib Induces CHK1 and MYC-Dependent Cell Death in T-cell and Hodgkin Lymphoma
Dashnamoorthy Ravi, Afshin Beheshti, Nasséra Abermil, Frank Passero, Jaya Sharma, Michael Coyle, Athena Kritharis, Irawati Kandela, Lynn Hlatky, Michail V. Sitkovsky, Andrew Mazar, Ronald B. Gartenhaus and Andrew M. Evens
Cancer Res June 1 2016 (76) (11) 3319-3331; DOI: 10.1158/0008-5472.CAN-15-2477
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo

Jump to section

Advertisement