Gene expression analysis of B-lymphoma cells resistant and sensitive to bortezomib*

Authors

  • Reshma Shringarpure,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
    3. Amylin Pharmaceuticals Inc., San Diego, CAUSA
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    • These authors contributed equally.

  • Laurence Catley,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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    • These authors contributed equally.

  • Deepak Bhole,

    1. Department of Medicine, Harvard Medical School, Boston, MA, USA
    2. Department of Anesthesia, Brigham and Women's Hospital, Boston, MA, USA
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  • Renate Burger,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Klaus Podar,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Yu-Tzu Tai,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Benedikt Kessler,

    1. Department of Pathology, Harvard Medical School, Boston, MA, USA
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  • Paul Galardy,

    1. Department of Pathology, Harvard Medical School, Boston, MA, USA
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  • Hidde Ploegh,

    1. Department of Pathology, Harvard Medical School, Boston, MA, USA
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  • Pierfrancesco Tassone,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Teru Hideshima,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Constantine Mitsiades,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Nikhil C. Munshi,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Dharminder Chauhan,

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • Kenneth C. Anderson

    1. Department of Medical Oncology, Dana – Farber Cancer Institute, Boston, MA, USA
    2. Department of Medicine, Harvard Medical School, Boston, MA, USA
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  • *

    Supported by a Fellow's Award (R.S.) and Senior Research Awards (B.K. and K.P.) from the Multiple Myeloma Research Foundation, National Institutes of Health grants P50 CA100707 and PO-1 78378, and the Doris Duke Distinguished Clinical Research Scientist Award (K.C.A.).

Kenneth C. Anderson, MD, Jerome-Lipper Multiple Myeloma Center, Department of Medical Oncology, Dana-Farber Cancer Institute, 44 Binney street, Mayer 557, Boston, MA-02115, USA. E-mail: kenneth_anderson@dfci.harvard.edu

Summary

The proteasome inhibitor bortezomib has shown impressive clinical activity alone and in combination with conventional and other novel agents for the treatment of multiple myeloma (MM). Although bortezomib is known to be a selective proteasome inhibitor, the downstream mechanisms of cytotoxicity and drug resistance are poorly understood. However, resistance to bortezomib as a single agent develops in the majority of patients, and activity in other malignancies has been less impressive. To elucidate mechanisms of bortezomib resistance, we compared differential gene expression profiles of bortezomib-resistant SUDHL-4 and bortezomib-sensitive SUDHL-6 diffuse large B-cell lymphoma lines in response to bortezomib. At concentrations that effectively inhibited proteasome activity, bortezomib induced apoptosis in SUDHL-6 cells, but not in SUDHL-4 cells. We showed that overexpression of activating transcription factor 3 (ATF3), ATF4, ATF5, c-Jun, JunD and caspase-3 is associated with sensitivity to bortezomib-induced apoptosis, whereas overexpression of heat shock protein (HSP)27, HSP70, HSP90 and T-cell factor 4 is associated with bortezomib resistance.

Bortezomib/PS-341 (Velcade4), a selective proteasome inhibitor, was approved by the Food and Drug Administration, in May 2003, for treatment of patients with relapsed, refractory multiple myeloma (MM). This rapid approval was based on preclinical studies (Hideshima et al, 2001; LeBlanc et al, 2002) as well as a phase II clinical trial demonstrating that this agent can overcome resistance to conventional therapy (Richardson et al, 2003). However, some patients either fail to respond or become refractory to bortezomib after an initial response. Moreover, despite the essential role of proteasomes in cell proliferation, not all tumour cell types respond equally well to bortezomib treatment (Aghajanian et al, 2002; Orlowski et al, 2002; Richardson et al, 2003; Davis et al, 2004). Therefore, elucidating the mechanisms of resistance to bortezomib has important clinical implications.

The proteasome is a large multi-catalytic, multi-subunit protease, which regulates the turnover of a number of key regulatory proteins and is required for progression through the cell cycle (Coux et al, 1996). The ability of proteasome inhibitors to disrupt cell cycle progression has made this class of small molecule inhibitors attractive chemotherapeutic agents. However, the direct mechanistic link between proteasome inhibition and induction of apoptosis is not yet well established. Proteasome inhibition results in the stabilisation of key apoptotic proteins (e.g. p53), as well as inhibitors of cell cycle progression (p27 and p21), possibly contributing to induction of apoptosis (Adams et al, 1999; Adams, 2002). Nevertheless, previous studies have shown that bortezomib kills tumour cells independent of p53 status (An et al, 2000), and efficiently kills the drug resistant MM cell line RPMI 8226 that harbours mutant p53 (Hideshima et al, 2001). Prior studies in MM cells (Hideshima et al, 2001, 2003, Mitsiades et al, 2002) and in nonsmall cell lung cancer cells (Yang et al, 2004) have identified signalling pathways that mediate bortezomib-induced apoptosis including activation of the stress-activated protein kinase/c-Jun amino terminal kinase (SAPK/JNK) pathway. However, the basis of sensitivity versus resistance to bortezomib remains undefined.

The present study compared bortezomib-resistant and bortezomib-sensitive cells and identified molecular markers that correlated with sensitivity versus resistance to bortezomib treatment. First, cell lines from various B-cell malignancies were compared for their response to bortezomib. We then focused on two diffuse large B-cell lymphoma cell lines (SUDHL-4 and SUDHL-6) with differential sensitivity to bortezomib. Cascades mediating bortezomib-induced apoptosis in MM cells (Mitsiades et al, 2002; Hideshima et al, 2003) were active in sensitive SUDHL-6 cells, but not in resistant SUDHL-4 cells. Global gene expression patterns in SUDHL-4 and SUDHL-6 cells identified molecular pathways associated with bortezomib resistance, which therefore represent potential targets to enhance sensitivity or overcome resistance to bortezomib therapy.

Materials and methods

Cell culture and reagents

Diffuse large B-cell lymphoma cell lines SUDHL-4 and SUDHL-6 were a kind gift from Dr Margaret Shipp, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. Cells were maintained in RPMI 1640 medium (Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum. The proteasome inhibitor bortezomib (PS-341) was provided by Millennium Pharmaceuticals, Cambridge, MA, USA. The proteasome inhibitor YU-102 (Ac-Gly-Pro-Phe-Leu-epoxyketone) was purchased from Affiniti Research Products, Exeter, UK.

Cell proliferation and survival

Cell proliferation in the presence of increasing concentrations of bortezomib was assessed by measuring DNA synthesis using [3H]-thymidine (Amersham Biosciences, Piscataway, NJ, USA) uptake as described previously (Hideshima et al, 2001). Briefly, lymphoma cells (1 × 104 cells/well) were incubated in 96-well culture plates (Costar, Cambridge, MA, USA) in the presence of media alone or various concentrations of bortezomib for 48 h at 37°C. Cells were pulsed with [3H]-thymidine (18·5 kBq/well) during the last 6 h of 48 h cultures. All experiments were performed in triplicate. Cell survival was examined using the MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4- sulphophenyl)-2H-tetrazolium, inner salt] assay (Promega, Madison, WI, USA), according to the manufacturer's instructions. Cells (3 × 104) were plated in 96-well plates and then treated with indicated concentrations of bortezomib. At the end of each treatment, MTS reagent was added to each well for 3 h at 37°C. Absorbance was measured at 490 nm using a spectrophotometer (Molecular Devices Corp., Sunnyvale, CA, USA). Cell viability was estimated as a percentage of the value of untreated controls. All experiments were repeated at least two times, and each experimental condition was repeated in triplicate wells in each experiment.

Cell cycle analysis

For cell cycle analysis, 2 × 106 cells were incubated with or without 20 nmol/l bortezomib for 48 h. Cells were washed with phosphate-buffered saline, fixed with 70% ethanol, treated with 10 mg/ml RNase A (Roche Diagnostics Corp., Indianapolis, IN, USA), stained with 5 mg/ml propidium iodide (PI; Sigma, St Louis, MO, USA), and the cell cycle profile was then determined using the program M software on an Epics flow cytometer (Coulter Immunology, Hialeah, FL, USA). Data were analysed using MultiCycle for Windows software (Phoenix FlowSystems, San Diego, CA, USA) to determine the percentage of apoptotic sub-G1 cells.

Proteasome activity assays

20S proteasome activity was measured in freshly prepared cell lysates, as described previously (Ullrich et al, 1999). Briefly, treated or untreated cells were lysed in 1 mmol/l dithiothreitol (DTT), and the lysates were cleared by centrifugation. Lysates (50 Bg protein) were incubated with fluorogenic peptide substrate succinyl Leucine–Leucine–Valine–Tyrosine-7 amido 4-methyl coumarin (Suc-LLVY-AMC, 100 BM) in a buffer containing 50 mmol/l Tris-HCl (pH 7·8), 20 mmol/l KCl, 5 mmol/l MgOAc, and 0·5 mmol/l DTT for 2 h at 37°C. The proteolysis reaction was terminated by addition of an equal volume of ice-cold ethanol and 10 volumes of 0·1 mol/l sodium borate (pH 9·0). Release of 7-amido-4-methyl coumaric acid (AMC) was monitored by measuring fluorescence at an emission wavelength of 450 nm (excitation 360 nm) in a microplate fluorometer (SpectraMax Gemini XS; Molecular Devices Corp.).

Western blotting and immunoprecipitaion

SUDHL-4 and SUDHL-6 cells were cultured in the presence or absence of various concentrations of bortezomib. Cells were harvested and lysed in RIPA buffer (Boston Bioproducts, Worcester, MA, USA) supplemented with 1 mmol/l sodium fluoride, 1 mmol/l sodium vanadate, 1 mmol/l phenylmethylsulphonyl fluoride (PMSF), 10 Bg/ml leupeptin, and protease inhibitor cocktail (Roche Molecular Biochemicals, Mannheim, Germany). Equal amounts of protein from cell lysates were separated by 12% sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) and subjected to Western blotting as described previously (Podar et al, 2001). Antibodies detecting the following proteins were used: ubiquitin (Chemicon Inc., San Diego, CA, USA); β-catenin and ATF-2 (Santa Cruz Biotechnology, Santa Cruz, CA, USA); T-cell factor (TCF)-4, phospho-c-Jun and c-Jun (Upstate Biotechnology, Lake Placid, NY, USA); caspase-3 and Poly(ADP-Ribose) Polymerase (PARP) (BD Pharmingen, San Diego, CA, USA); phospho-JNK1 and JNK1 (Cell Signaling, Beverly, MA, USA); and tubulin (Sigma).

Caspase-3 activity assays

Activation of caspase-3 was monitored by Western blotting to detect the cleaved (active) 18 kDa fragment, as well as by measuring the ability of cell lysates to degrade the fluorogenic caspase-3 substrate Ac-DEVD-AFC (Asp-Glu-Val-Asp-7-amino-4-trifluoromethylcoumarin). The activity assay was carried out with a caspase-3 activity assay kit (Calbiochem, San Diego, CA, USA), according to manufacturer's instructions. Lysates from an equal number of treated or untreated cells were used, and increase in activity was shown as relative fluorescence units (RFUs) in comparison with untreated cells.

RNA isolation and hybridisation

SUDHL-4 and SUDHL-6 Cells (10 × 107) were treated in duplicate with 20 nmol/l bortezomib or medium alone for 6 h and then resuspended in 0·75 ml Trizol (Invitrogen). RNA isolation was performed according to manufacturer's instructions, and hybridisation was performed at the Microarray core facility, Dana-Farber Cancer Institute. Briefly, first strand cDNA was synthesised using a T7 promoter-tailed oligo-dT primer followed by synthesis of the second strand. cDNA was purified with phase lock gel (PLG) tubes. In vitro transcription (IVT) was catalysed by T7 polymerase and contained biotinylated CTP, UTP and four unmodified ribonucleotides. The biotinylated cRNA was purified using the RNeasy system (Qiagen, Valencia, CA, USA), fragmented, added to a hybridisation solution containing several biotinylated control oligonucleotides, and hybridised to human U133A microarray chips (Affymetrix, Santa Clara, CA, USA) overnight at 45°C. The chips were washed in a GeneChip fluidics Station 400 (Affymetrix). Phycoerythrin-conjugated streptavidin (SAPE) was bound to the hybridised (biotinylated) cRNA, followed by addition of more fluorophores using biotinylated anti-streptavidin antibody and SAPE. Each cRNA bound to its complementary oligonucleotide was excited using a confocal laser scanner, and the positions and intensities of the fluorescent emissions were captured. These measurements provided the basis of subsequent biostatistical analysis.

Microarray analysis

Scanned image output files were normalised for overall chip brightness with d-chip software using the invariant set method. A model based Expression Index was calculated using the ‘perfect match only’ model. Data were analysed using d-chip 1.3 (Li & Wong, 2001). Analysis using the ‘compare samples’ function identified signals varying by 1·5-fold or greater with 90% confidence.

Real time-polymerase chain reaction

Total RNA was extracted from untreated or bortezomib-treated cells using TRIzol reagent (Invitrogen), according to the manufacturer's instructions. RNA was treated with RNase free DNase using the MessageClean kit (Genhunter Corp., Nashville, TN, USA), phenol-chloroform extracted, and ethanol precipitated. cDNA was synthesised at 0·05 Bg/Bl with random primers using the Reverse Transcription System (Promega), and quantitative real time-polymerase chain reaction (RT-PCR) was performed using an iCycler detection system (Biorad, Hercules, CA, USA). cDNAs were amplified in 25 μl reactions containing iQ SYBRGreen supermix (Biorad), 50 ng of cDNA and 0·2 mol/l of each primer. Amplification was done with an initial soak at 95°C for 2 min, followed by 95°C for 30 s, 60°C for 30 s, and 72°C for 30 s for a total of 40 cycles. The following gene-specific primers were used:

HSP 70 A1b, forward 5′-aggaggcggagaagtacaaag-3′ and reverse 5′-cttcatgttgaaggcgtaggac-3′; TCF-4, forward 5′-tcttcacagtagtgccatggag-3′ and reverse 5′-cttgctgatggagcatagactg-3′; cyclin D1, forward 5′-gcgtgtagctatggaagttgc-3′ and reverse 5′-agagtcctacaggtacaacgcc-3′; c-myc, forward 5′-gtctccacacatcagcacaact-3′ and reverse 5′-acactgtccaacttgaccctct-3′; caspase-3, forward 5′-gtttgagcctgagcagagacat-3′ and reverse 5′-gtatggagaaatgggctgtagg-3′; and actin, forward 5′-ggtggcttttaggatggcaag-3′ and reverse 5′-actggaacggtgaaggtgacag-3′; c-Jun, forward 5′-agacagacagacacagccagc-3′ and reverse 5′-gggcagttagagagaaggtgaa-3′; ATF-3 forward 5′-agaagaaggagaagacggagtg-3′ and reverse 5′-accctcttcttcagagaaaccc-3′.

Results

Differential sensitivity of SUDHL-4 and SUDHL-6 cells to bortezomib

Cells were incubated in the presence of increasing concentrations of bortezomib for 48 h, and proliferation was assessed by [3H] thymidine uptake (Fig 1A). SUDHL-6 cell proliferation was almost completely inhibited by 5 nmol/l bortezomib (left panel). In contrast, proliferation of SUDHL-4 cells was still 71% of control despite treatment with 20 nmol/l bortezomib (right panel). The effect of proteasome inhibitors bortezomib and YU-102 on cell survival was assessed by an MTS assay (Fig 1B). SUDHL-6 cells were sensitive to bortezomib treatment (IC50 ∼ 2 nmol/l at 48 h), whereas SUDHL-4 cells were relatively resistant (IC50 ∼ 48 nmol/l at 48 h) (left panel). Bortezomib primarily inhibits chymotrypsin-like activity of the proteasome (Lightcap et al, 2000). We therefore tested the sensitivity of both cell lines to YU-102, which predominantly inhibits the postglutamyl peptide hydrolyzing (PGPH) activity of the proteasome (Myung et al, 2001) (right panel). Both cell lines showed differential sensitivity to YU-102, indicating that SUDHL-4 cells were also resistant to inhibition of other proteasomal functions (right panel). To further confirm the resistance of SUDHL-4 cells to bortezomib, we performed cell cycle analysis (Fig 1C). Bortezomib (20 nmol/l) led to an increase in the sub-G1 population (62·6% vs. 26% in control) in sensitive SUDHL-6 cells (left panel) at 48 h. In contrast, resistant SUDHL-4 cells treated with 20 nnmol bortezomib for 48 h had virtually no effect on the sub-G1 population (right panel).

Figure 1.

 Differential sensitivity of SUDHL-6 and SUDHL-4 cells to bortezomib. (A) The effect of bortezomib on the proliferation of SUDHL-6 (left) and SUDHL-4 (right) cells was measured by 3H-thymidine uptake in the presence of indicated concentrations of bortezomib for 48 h. Values represent the mean [3H] thymidine incorporation (counts per minute, cpm) of triplicate cultures (error bars, SD). (B) Cell survival in the presence of increasing concentrations of the proteasome inhibitor, bortezomib (left) or YU-102 (right) was assessed with an MTS assay in SUDHL-6 (bsl00001) and SUDHL-4 (bsl00043) cells. Error bars represent mean ± SD of triplicates in one representative experiment. (C) Cell cycle profile of SUDHL-6 (left) and SUDHL-4 (right) cells incubated in absence or presence of bortezomib (20 nmol/l) for 48 h was assessed using propidium iodide. There was an increase from 26% to 63% in the sub-G1 fraction of SUDHL-6 cells treated with bortezomib, representing apoptosis. There was no significant increase in the Sub-G1 population of SUDHL-4 cells (0·9–2·1%) treated for 48 h with 20 nmol/l bortezomib (grey fill), and the profile of treated cells was identical to that of untreated cells.

Bortezomib inhibits chymotrypsin-like proteasome activity in both sensitive and resistant cells

In order to ensure that bortezomib efficiently reached its intended target in both cell lines, we measured proteasome inhibition in response to bortezomib. As seen in Fig 2A, the predominant chymotrypsin-like activity of the proteasome was inhibited within 6 h in a dose-dependent fashion in both SUDHL-6 and SUDHL-4 cells. Moreover, over 80% inhibition of chymotrypsin-like activity was maintained for at least 48 h after bortezomib (20 nmol/l) treatment in SUDHL-4 cells (Fig 2B), excluding the possibility of more rapid drug metabolism. Although bortezomib primarily inhibits the chymotrypsin-like activity of the 20S proteasome (Lightcap et al, 2000), we also measured the effect of bortezomib on trypsin-like and PGPH activities. Consistent with prior reports(Lightcap et al, 2000), bortezomib did not inhibit trypsin-like activity of the proteasome, and moderately inhibited PGPH activity (data not shown) at high drug concentrations (50 nmol/l) in both cell lines. Proteasome inhibition in both cell lines was further confirmed by intracellular accumulation of high-molecular weight ubiquitin conjugates (Fig 2C). These data show that proteasome inhibition is effective even in resistant SUDHL-4 cells, and that type or extent of proteasome inhibition does not account for differential drug sensitivity.

Figure 2.

 Bortezomib inhibits proteasome chymotrypsin-like activity in both sensitive and resistant cells. Cells were treated for 6 h with the indicated concentrations of bortezomib (A) or (B) with 20 nmol/l bortezomib for the indicated time points. Chymotrypsin-like activity of the 20S proteasome was measured in total lysates of SUDHL-6 (bsl00001) and SUDHL-4 (bsl00043) cells by monitoring the degradation of fluorogenic peptide substrate Suc-LLVY-MCA. (C) SUDHL-4 (lanes 1,2) and SUDHL-6 cells (lanes 3,4) were treated with vehicle alone (lanes 1,3) or 20 nmol/l bortezomib (lanes 2,4) for 6 h. Cell lysates were resolved by 12% sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and probed with an anti-ubiquitin antibody.

Reduced caspase-3 induction in resistant SUDHL-4 cells

To characterise the apoptotic response to bortezomib, we examined the effect of bortezomib on the expression and activation of caspase-3 in SUDHL-4 and SUDHL-6 cells. The baseline expression of caspase-3 mRNA in sensitive SUDHL-6 cells was only 1·7-fold higher than that of resistant SUDHL-4 cells; however, treatment with 20 nmol/l bortezomib for 24 h resulted in a 9·4-fold induction in sensitive SUDHL-6 cells (Fig 3A) when compared with a modest 2·9-fold induction of caspase-3 mRNA in resistant SUDHL-4 cells. Furthermore, cleavage of procaspase-3 was observed as early as 6 h after treatment with 20 nmol/l bortezomib in sensitive SUDHL-6 cells, but not in resistant SUDHL-4 cells even after 24 h of bortezomib treatment (Fig 3B). Activation of caspase-3 only in sensitive SUDHL-6 cells was further confirmed by proteolytic cleavage of Ac-DEVD-AFC, a fluorogenic peptide substrate of caspase-3 (Fig 3C and D), and by cleavage of the cellular caspase-3 substrate PARP (Fig 3E), in response to treatment with bortezomib.

Figure 3.

 Reduced induction of caspase-3 in resistant SUDHL-4 cells. (A) Caspase-3 mRNA levels were measured by RT-PCR and normalised to expression of actin. The relative increase in mRNA with respect to baseline mRNA in untreated SUDHL-4 cells (1·0) is indicated. (B) Western blot analysis confirmed caspase-3 cleavage. Caspase-3 activity with increasing concentrations of bortezomib at 6 h (C) or with 20 nmol/l bortezomib treatment over time (D) was measured by degradation of the fluorogenic caspase-3 substrate Ac-DEVD-AFC. (E) Activation of caspase-3 was further confirmed by PARP cleavage at 24 h in SUDHL-6 but not SUDHL-4, cells.

Gene expression analysis of SUDHL-4 and SUDHL-6 cells

To further explore the molecular mechanisms of differential drug sensitivity, we performed gene microarray profiling of SUDHL-6 and SUDHL-4 cells. A genome wide analysis of expressed gene transcripts in both cell lines was carried out using Affymetrix U133A chips (Fig 4A). The ‘compare samples’ function identified genes that were differentially expressed in a statistically significant manner. We used this function to identify genes that were differentially expressed in untreated SUDHL-4 and SUDHL-6 cells, with emphasis on (i) heat shock protein genes; (ii) genes for multi-drug resistance and drug metabolism; (iii) genes of the ubiquitin-proteasome pathway; and (iv) transcription factors involved in cell growth and differentiation. In all, 149 genes were overexpressed (twofold or higher) in SUDHL-4 cells relative to SUDHL-6 cells, whereas 159 genes were underexpressed in SUDHL-4 cells compared with SUDHL-6 cells.

Figure 4.

 Gene expression analysis of SUDHL-4 and SUDHL-6 cells (A) Hierarchical clustering of differentially expressed genes. SUDHL-4 and SUDHL-6 cells were treated in duplicate with 20 nmol/l Bortezomib for 6 h, followed by isolation of total RNA. RNA was then hybridised to U133A affymetrix chips. Data were analysed using dchip 1.3 software; hierarchical clustering of all genes is shown. (B) Hierarchical clustering of heat shock protein and chaperone genes. Rows represent individual genes, and columns represent individual samples in duplicate. Colour scale for relative changes in gene expression is shown below each cluster, with red indicating higher expression and blue indicating lower expression. The absolute fold changes for each gene are listed in Table SI. (C) Fold difference in expression of HSP70 1A mRNA in resistant SUDHL-4 cells compared with SUDHL-6 cells as seen by microarray data (open bars) and subsequently confirmed by RT-PCR (solid bars).

Heat shock proteins (HSPs) and other proteins with chaperone-like functions showed higher baseline expression in resistant SUDHL-4 cells (Fig 4B and Table SI). Real-time PCR confirmed that expression of HSP70 was approximately eigtfold higher in resistant SUDHL-4 cells than in sensitive SUDHL-6 cells (Fig 4C). These data, coupled with prior observations of the role of HSP27 (Chauhan et al, 2003) and HSP90 (Mitsiades et al, 2002) in conferring resistance to proteasome inhibition, further confirm that higher expression of HSP70, HSP27, HSP90 and other chaperones is associated with resistance to bortezomib.

Among genes for multi-drug resistance and drug metabolism, only two genes were overexpressed in resistant SUDHL-4 cells (Table SI). Of these, the ATP-binding cassette (ABC), subfamily A, member 1 (ABCA1) functions as a cholesterol efflux pump in the cellular lipid removal pathway (Brooks-Wilson et al, 1999). Since treatment with low concentrations of bortezomib efficiently inhibited the chymotrypsin-like activity of the proteasome, drug elimination by efflux pumps is unlikely to contribute to bortezomib-resistance in these cells. Among the genes for drug metabolism, cytochrome P450, subfamily XXVIA, polypeptide 1, a retinoic acid-metabolising enzyme (designated P450RAI) (White et al, 1997) was overexpressed in resistant SUDHL-4 cells. However, whether P450 RAI can metabolise bortezomib is not known, and since inhibition of proteasome activity was maintained for over 48 h, rapid drug metabolism does not appear to confer drug resistance.

While genes encoding certain proteasome subunits, and other proteins of the ubiquitin-proteasome pathway were differentially expressed in the two cell lines (Table SI), no distinct pattern was recognisable. Further analysis of distinct proteasome activities and proteasome subunit composition in these two cell lines is currently under investigation in a separate study.

Bortezomib induced a significant upregulation of ATF 3, ATF 4, ATF 5, c-Jun and Jun D proto-oncogene in SUDHL-6 cells, as determined by gene expression profile (Fig 5A); this bortezomib-induced upregulation was further confirmed by RT-PCR (shown for c-Jun and ATF-3, Fig 5B). Prior studies from our laboratory have identified several signalling pathways that mediate bortezomib-induced apoptosis in MM cells, including activation of the SAPK/JNK pathway (Hideshima et al, 2001, 2003, Mitsiades et al, 2002). The SAPK/JNK pathway was also involved in bortezomib-induced apoptosis in nonsmall cell lung cancer cells (Yang et al, 2004). We therefore examined the effect of bortezomib treatment on activation of the SAPK/JNK pathway in both cell lines. Activation of JNK-1 in response to bortezomib was confirmed by an increase in phospho-JNK1 as well as increased phosphorylation of JNK substrates, c-Jun and ATF-2 in sensitive SUDHL-6 cells (Fig 5C). However, we did not observe a similar activation of JNK-1 in response to bortezomib in resistant SUDHL-4 cells, as described previously (Hideshima et al, 2005).

Figure 5.

 Bortezomib upregulates ATF-3, ATF-4, ATF-5, c-Jun, and activates the SAPK/JNK pathway in sensitive SUDHL-6 cells (A and B) Bortezomib induced a significant up-regulation of ATF 3, ATF 4, ATF 5, c-Jun and Jun D proto-oncogene, as determined by gene expression profile (A), and mRNA upregulation was confirmed by RT-PCR (shown for c-Jun and ATF-3). (C) SUDHL-6 cells were treated with 20 nmol/l bortezomib for 0, 6 or 24 h. Cell lysates were resolved by 12% SDS-PAGE and probed sequentially with antibodies to phospho-JNK-1, JNK-1, phospho c-Jun, c-Jun, phospho-ATF2, ATF-2 and tubulin. Activation of JNK-1 in response to bortezomib was confirmed by an increase in phospho-JNK1 as well as increased phosphorylation of JNK substrates c-Jun and ATF-2, in sensitive SUDHL-6 cells. Activation of JNK-1 in response to bortezomib in resistant SUDHL-4 cells was not observed (data not shown).

Elevated expression of TCF-4 and increased transcription by TCF-4/β-catenin complex in resistant SUDHL-4 cells – several transcription factors involved in cell growth/differentiation were differentially expressed in SUDHL-4 and SUDHL-6 cells (Fig 6A and Table SI). Among these, the expression of TCF-4 or transcription factor 4 was 15-fold higher in resistant SUDHL-4 cells compared with sensitive SUDHL-6 cells (Fig 6B). TCF-4 is a central player in the Wnt signalling pathway that has been implicated in cancer development, differentiation, and drug resistance (Korinek et al, 1998; Peifer & Polakis, 2000; Chen et al, 2001; Taipale & Beachy, 2001; van de Wetering et al, 2002; Hatsell et al, 2003; Qiang et al, 2003; Reya et al, 2003; Shiina et al, 2003). Differential expression of TCF-4 in SUDHL-4 and SUDHL-6 cells was confirmed by RT-PCR (Fig 6C). Potential downstream target genes of the TCF-4/β-catenin complex, cyclin D1 and c-myc, were also upregulated in SUDHL-4 cells relative to SUDHL-6 cells as demonstrated by RT-PCR (Fig 7A). Although the possibility of other systems regulating cyclin D1 and c-myc expression cannot be ruled out, this finding further supports the differential activation of the TCF-4/β-catenin complex in resistant SUDHL-4 cells.

Figure 6.

 Elevated expression of T-cell factor-4 (TCF-4). (A) Gene expression profile revealed TCF-4 upregulation in SUDHL-4, but not SUDHL-6, cells. (B) TCF-4 expression in SUDHL-4 cells was 15-fold higher than in SUDHL-6 cells. (C) Differential TCF-4 gene expression was confirmed by RT-PCR analysis. SUDHL-4 cells required fewer cycles of amplification (horisontal axis) compared with SUDHL-6 cells to attain the same level of fluorescence (vertical axis), confirming the higher level of TCF-4 expression in these cells. Levels of actin mRNA (bsl00066) in both cell lines did not show significant differences.

Figure 7.

 Increased transcription by TCF-4/β-catenin complex. (A) Expression of TCF-4/β-catenin target genes. Expression of cyclin D1 and c-myc was measured by quantitative RT-PCR using gene-specific primers, and normalised to expression of actin.

Discussion

In this study, we explored the resistance to proteasome inhibitor-induced cell death by comparing the transcriptional profile of resistant SUDHL-4 cells with that of sensitive SUDHL-6 cells. SUDHL-4 and SUDHL-6 are closely related lymphoma cell lines with remarkably different responses to bortezomib treatment. Previous gene expression profiles of diffuse large B-cell lymphoma (DLBCL) cell lines demonstrated that both cell lines display similar molecular signatures, and cluster together with a ‘germinal centre-derived’ phenotype rather than an ‘activated B-cell type’ or ‘type3’ phenotype (Rosenwald et al, 2002). Both cell lines also carry the t(14;18) translocation involving the immunoglobulin heavy chain locus and bcl-2 (Bakhshi et al, 1985; Siminovitch et al, 1986). SUDHL-4 and SUDHL-6 cell lines therefore represent a good model system to identify markers that account for their differential response to proteasome inhibition. Considerable proteasome inhibition was observed after drug treatment in both cell lines. Almost 80% of proteasome chymotrypsin-like activity was inhibited by treatment with 10 nmol/l bortezomib in both cell lines, and treatment with higher concentrations of bortezomib did not increase the extent of proteasome inhibition. Accumulation of high molecular weight ubiquitin conjugates as well as known substrates of the proteasome in both cell lines further confirmed inhibition of proteasome activity, but with strikingly different effects on cell survival, growth and apoptosis. Since bortezomib reached its intended target, as evidenced by significant proteasome inhibition in both cell lines, the presence of multi-drug resistance genes or efflux pumps is unlikely to account for bortezomib resistance in SUDHL-4 cells.

In the current studies, bortezomib-sensitive SUDHL-6 cells showed a robust induction in caspase-3 mRNA and activity in response to bortezomib, in contrast to bortezomib-resistant SUDHL-4 cells, which showed only a very weak induction of caspase-3. Cleavage of caspase-3 and PARP, hallmarks of apoptosis, were observed in SUDHL-6 cells but not SUDHL-4 cells. Bortezomib-induced apoptosis in sensitive SUDHL-6 cells involved activation of the SAPK/JNK pathway, as was shown previously in MM cells (Mitsiades et al, 2002; Hideshima et al, 2003) and in nonsmall cell lung cancer cells (Yang et al, 2004). Resistant SUDHL-4 cells contain mutant p53; however, previous studies have shown that bortezomib induces apoptosis independent of p53 status (An et al, 2000), and bortezomib efficiently killed drug resistant MM cell line RPMI8226, which has a mutant p53 (Hideshima et al, 2001). The p53 status is therefore unlikely to account for resistance to proteasome inhibition.

We have previously shown that proteasome inhibition with bortezomib triggers induction of HSPs in MM cells. The HSP90 inhibitor geldanamycin can increase sensitivity to bortezomib in MM (Mitsiades et al, 2002). Our current observations further support the view that higher expression of HSPs is associated with resistance to bortezomib. HSP27 confers resistance to bortezomib (Chauhan et al, 2003). Our microarray analysis revealed that a number of HSPs, including HSP27 and other chaperones, were expressed at a higher level in resistant SUDHL-4 cells. These data support previous evidence that HSPs can protect against proteasome inhibitor-induced apoptosis.

In our current gene expression analysis, we observed a coordinated upregulation of activating protein 1 (AP-1) and activating transcription factor (ATF) families of transcription factors in response to bortezomib only in sensitive SUDHL-6 cells. ATF 3 is a stress sensor and is a novel contributor to the apoptotic pathway (Vlug et al, 2005; Yan et al, 2005a,b). ATF 4 is an important mediator of the unfolded protein response (Rutkowski & Kaufman, 2003, 2004; Blais et al, 2004). Bortezomib-induced upregulation of AP-1 activity was observed at the level of transcription, translation, and post-translational modification in sensitive SUDHL-6 cells, whereas resistant SUDHL-4 cells did not show activation of AP-1 activity or ATFs by any of these mechanisms. These data indicate a potential role of ATFs in mediating bortezomib-induced apoptosis, and warrant further study.

Among other transcripts that were differentially expressed in the two cell lines, TCF-4, a member of the LEF/TCF family of high mobility group (HMG) transcription factors, was overexpressed in resistant SUDHL-4 cells. TCF-4 is a downstream effector of the Wnt signalling pathway, along with β-catenin (van Noort & Clevers, 2002; van de Wetering et al, 2002). Wnt signalling activation induces accumulation of β-catenin, which dimerises with TCF-4 to activate downstream target genes, such as c-myc (He et al, 1998) and cyclin D1 (Tetsu & McCormick, 1999). Conversely, in the absence of Wnt signalling, β-catenin is sequestered in a complex with GSK3β, adenomatous polyposis coli (APC) and axin. GSK3β phosphorylates β-catenin, thereby targeting it for degradation by the proteasome (Taipale & Beachy, 2001; van de Wetering et al, 2002; Qiang et al, 2003; Reya et al, 2003). Dysregulation of different components of the Wnt signalling pathway leading to constitutive (ligand-independent) activation of TCF-4/β-catenin driven transcription has been observed in a variety of human cancers (Korinek et al, 1997; Morin et al, 1997; Tetsu & McCormick, 1999; Taipale & Beachy, 2001; van Noort & Clevers, 2002; Hatsell et al, 2003; Qiang et al, 2003; Lu et al, 2004). Although most of the regulation of TCF-4/β-catenin driven transcription occurs by stabilisation of β-catenin, aberrant TCF-4 expression has also been implicated in abnormal activation of Wnt target genes (Barker et al, 1999; Brinkmeier et al, 2003; Cui et al, 2003; Kardon et al, 2003; Shiina et al, 2003; Zhao et al, 2004). Mutations in APC leading to excessive accumulation of β-catenin are most frequent in colorectal cancers (Korinek et al, 1997; Morin et al, 1997; Tetsu & McCormick, 1999). In our current studies, TCF-4 overexpression in SUDHL-4 relative to SUDHL-6 cells was observed in microarray analysis and confirmed by RT-PCR. Furthermore, for the first time, an association between TCF-4/β-catenin driven transcription and resistance to bortezomib was found, as seen by increased transcription of TCF-4 target genes cyclin D1 and c-myc in resistant SUDHL-4 cells.

Increased Wnt signalling may play a role in cancer development by inhibiting apoptosis rather than by inducing proliferation; upregulation of TCF-4/β-catenin target genes was shown to correlate inversely with levels of caspase-3 and caspase-7 transcripts (Chen et al, 2001, 2003). While the effect of TCF-4 overexpression on caspase-3 activation, if any, remains to be identified, our studies confirm the inverse correlation between the activities of TCF-4 and caspase-3. The ability of resistant SUDHL-4 cells to attenuate caspase-3 activity may account, at least in part, for drug resistance. Recent efforts to develop small molecule antagonists of TCF-4/β-catenin interaction (Lepourcelet et al, 2004), together with our present studies, suggest that these inhibitors may be useful to overcome the resistance of SUDHL-4 cells to bortezomib and possibly, to other chemotherapeutic drugs.

In conclusion, differential gene expression profiles of bortezomib-resistant SUDHL-4 and bortezomib-sensitive SUDHL-6 diffuse large B-cell lymphoma cell lines have confirmed the activation of pathways mediating bortezomib-induced apoptosis in sensitive SUDHL-6 cells, but not in resistant SUDHL-4 cells. These and future studies will provide valuable insights into the mechanisms of drug resistance to bortezomib, and identify molecular targets to overcome bortezomib resistance in haematological malignancies.

Acknowledgements

We are grateful to Dr Margaret A. Shipp, Dana-Farber Cancer Institute, Boston, MA, USA for kindly providing the diffuse large B-cell lymphoma cell lines, SUDHL-4 and SUDHL-6. We would also like to thank Dr Edward A. Fox and his staff at the Dana-Farber Cancer Institute, Boston, MA, USA, for help with microarray data analysis.

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