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. Author manuscript; available in PMC: 2015 Apr 22.
Published in final edited form as: Br J Haematol. 2013 Nov 17;164(3):352–365. doi: 10.1111/bjh.12633

AT-101 downregulates BCL2 and MCL1 and potentiates the cytotoxic effects of lenalidomide and dexamethasone in preclinical models of multiple myeloma and Waldenström macroglobulinaemia

Aneel Paulus 1,#, Kasyapa Chitta 1,#, Sharoon Akhtar 1, David Personett 1, Kena C Miller 2, Kevin J Thompson 1, Jennifer Carr 1, Shaji Kumar 3, Vivek Roy 2, Stephen M Ansell 3, Joseph R Mikhael 4, Angela Dispenzieri 3, Craig B Reeder 4, Candido E Rivera 2, James Foran 2, Asher Chanan-Khan 2,*
PMCID: PMC4406280  NIHMSID: NIHMS671952  PMID: 24236538

Summary

Multiple myeloma, the second most common haematological malignancy in the U.S., is currently incurable. Disruption of the intrinsic apoptotic pathway by BCL2 and MCL1 upregulation is observed in >80% of myeloma cases and is associated with an aggressive clinical course. Remarkably, there is no approved drug with the ability to target BCL2 or MCL1. Thus, we investigated the anti-tumour effects of a pan-BCL2 inhibitor, AT-101, which has high binding specificity for BCL2 and MCL1 in preclinical models of plasma cell cancers (Multiple myeloma and Waldenström macroglobulinaemia). Gene expression and immunoblot analysis of six plasma cell cancer models showed upregulation of BCL2 family members. AT-101 was able to downregulate BCL2 and MCL1 in all plasma cell cancer models and induced apoptotic cell death in a caspase-dependent manner by altering mitochondrial membrane permeability. This cytotoxic effect and BCL2 downregulation were further potentiated when AT-101 was combined with lenalidomide/dexamethasone (LDA). NanoString nCounter mRNA quantification and Ingenuity Pathways Analysis revealed differential changes in the CCNA2, FRZB, FYN, IRF1, PTPN11 genes in LDA-treated cells. In summary, we describe for the first time the cellular and molecular events associated with the use of AT-101 in combination with lenalidomide/dexamethasone in preclinical models of plasma cell malignancy.

Keywords: BCL-2, multiple myeloma, Waldenström macroglobulinaemia, lenalidomide, AT-101

Multiple myeloma (MM) is the second most common haematological malignancy in the United States and results in approximately 10 000 deaths annually (Siegel et al, 2013). MM typically presents at a median age of 70 years with bone marrow infiltration by malignant immunoglobulin-producing plasma cells that cause anaemia, lytic bone lesions, and immunosuppression (Anderson et al, 2011). Symptoms result from progressive marrow and immune failure, and patients require treatment for disease control. Typically, the clinical course is punctuated with frequent relapses and remissions that ultimately deteriorate into a resistant and fatal disease. Several drugs are now approved for the treatment of relapsed MM (including bortezomib, lenalidomide, pegylated liposomal doxorubicin, carfilzomib and pomalidomide), but none are curative (Mahindra et al, 2012). More effective regimens that can induce deeper responses are needed to improve clinical outcome in this disease. Thus, an enhanced understanding of the biological processes engaged in MM cell survival is of paramount importance to find appropriate therapies (Chanan-Khan & Giralt, 2010).

Over the past decade, appreciation of the biological processes that are critical to MM cell survival have paved the way for the development of several drugs and identified new therapeutic opportunities (Kumar et al, 2008; Borrello, 2012). Among these, disruption of the intrinsic apoptotic pathway through BCL2 (B-cell Lymphoma/Leukemia-2) upregulation serves as a vital survival mechanism employed by the MM cells. The significance of this observation can be appreciated from its high incidence (≥80%) of expression in MM cases (Tian et al, 1996; Gazitt et al, 1998; Feinman et al, 1999; Iyer et al, 2003; Sampath et al, 2012). BCL2 overexpression is associated with an aggressive clinical course, early relapses, and drug resistance. (Pettersson et al, 1992; Hu & Gazitt, 1996; Iyer et al, 2003) Several investigators have reported that perhaps in the resistant MM state, the anti-apoptotic BCL2 family member, MCL1 (Myeloid cell factor-1) may drive the aggressive disease biology (Derenne et al, 2002; Zhang et al, 2002). MCL1 is upregulated by interleukin 6 (IL6) (Puthier et al, 1999; Jourdan et al, 2003), and is expressed at high levels in 52% of previously untreated and 81% of relapsed MM patients (Wuilleme-Toumi et al, 2005). Given their biological importance in extending survival advantage to MM cells, BCL2 and MCL1 may be regarded as important therapeutic targets in MM. However, there is currently no approved drug with the ability to effectively target BCL2 or MCL1.

AT-101 (Chemical name: R-(-)-1,1′, 6,6′,7,7′-hexahydroxy-3,3′-dimethyl-5,5′-bis (1-methylethyl) [2,2′-Binapthalene]-8, 8′-dicarboxaldehyde acetic acid) is an oral BH3 mimetic agent. It is the levorotatory enantiomer of racemic gossypol (isolated from cotton plant) and is developed by Ascenta Pharmaceuticals Inc. Malvern, PA. It inhibits the anti-apoptotic proteins (BCL2, BCL2L1 [BCL-XL], MCL1 and BCL2L2 [BCL-W]) and MCL1) and is a strong inducer of the pro-apoptotic potentiator proteins (PMAIP1 [NOXA] and BBC3 [PUMA]). AT-101 binds within the BH3 binding pocket of the BCL2 anti-apoptotic proteins and prevents their interaction with the related proapoptotic proteins, thereby promoting apoptosis (Oliver et al, 2004; Mohammad et al, 2005a,b; Loberg et al, 2007). Thus, we investigated its anti-tumour efficacy in plasma cell preclinical models of MM and Waldenström macroglobulinaemia (WM).

Materials and methods

AT-101 was provided as a gift from Ascenta Therapeutics Inc, Malvern, PA; lenalidomide was purchased from Sellekhem, Houston TX, and dexamethasone was purchased from Sigma-Aldrich (St. Louis, MO). Lenalidomide and AT-101 were dissolved in dimethyl sulfoxide (10 mmol/l) and dexamethasone was dissolved in ethanol (10 mmol/l). RPMI-1640 medium, penicillin, streptomycin, tetramethylrhodamine methyl ester (TMRM) and fetal bovine serum (FBS) were purchased from Life Technologies (Carlsbad, CA). Antibodies for BCL2, MCL1 and BCL2L1 (BCL-XL) were purchased from Santa Cruz Biotechnology (Dallas, TX). Antibodies for caspases 9, 3 and PARP1 were obtained from Cell Signaling Technology (Danvers, MA). Annexin V/propidium iodide (PI) apoptosis staining kit was purchased from BD Biosciences (San Jose, CA).

Cell culture

Human plasma cell cancer cell lines and their corresponding bortezomib-resistant (BR) clones, which were developed in our laboratory, were used in experiments. All cell lines were cultured in RPMI-1640 medium containing 10% FBS and penicillin (100 μ/ml) and streptomycin (100 μg/ml). Culture medium was replaced every 3 d. Cell viability was always maintained at >90% and was measured by trypan blue exclusion assay using a ViCell-XR viability counter.

RNA preparation

Total RNA from four MM cell lines (U266, U266-BR, KMS11, KMS11-BR) and two WM cell lines (BCWM1 and BCWM1-BR) were prepared using the TRizol Reagent (Invitrogen, Carlsbad, CA) following the manufacturer's instructions. After elution, RNA samples were concentrated by ethanol precipitation at −20°C overnight and resuspended in nuclease-free water. Before labelling, RNA samples were quantitated using a ND-1000 spectrophotometer (NanoDrop, Thermo Scientific, Wilmington, DE) and evaluated for degradation using a 2100 Bioanalyser (Agilent Technologies, Santa Clara, CA). By Illumina (Illumina Inc., San Diego, CA) criteria, samples were required to have a RNA Integrity Number >7, an optical density (OD) 260:280 of 1·9–2·0, an OD 260/230 >1·8 and >1·5 28S:18S ratio of the ribosomal bands for gene expression array analysis.

Gene expression assays

For determination of baseline BCL2 family member mRNA status, expression profiling was performed using the HumanHT-12 v3 whole-genome gene expression direct hybridization assay (Illumina). Briefly, 500 ng of total RNA was converted to cDNA, followed by an in vitro transcription step to generate labelled cRNA using the Ambion Illumina TotalPrep RNA Amplification Kit (Ambion, Austin, TX) according to the manufacturer's instructions. 750 ng of the labelled probes were subsequently mixed with hybridization reagents and hybridized overnight to the HumanHT-12 v3 BeadChips. Following washing and staining, the BeadChips were imaged using the Illumina BeadArray Reader to measure fluorescence intensity at each probe. The quantity of mRNA present in each original sample respectively corresponds to the signal intensity emitted at each probe.

Gene expression profiling (GEP) using NanoString nCounter technology

The NanoString nCounter (NanoString, Seattle, WA) assay was performed for mRNA quantification and expression in MM and WM cells that were treated with either AT-101 (A), lenalidomide plus dexamethasone (LD) or AT-101 plus lenalidomide and dexamethasone (LDA). A description and analysis of the NanoString nCounter assay has been thoroughly described elsewhere (Geiss et al, 2008). Briefly, a library is constructed with two sequence-specific probes for the gene of interest. Unique pairs of 3′ reporter and 5′ capture probes are developed to distinguish transcripts for the gene of interest using a colour-based barcoding system. The capture probe contains a base pair sequence that is complementary to the target mRNA and linked to a biotin affinity tag, which binds the mRNA of interest. The reporter probe is also designed to be complementary to the target mRNA, contains a base sequence that is linked to an RNA-based colour-coded molecular tag that provides a signal for detection. Using this method, a distinct colour code is digitally generated for each gene of interest. In our experiments, all probes were mixed together with total RNA (100 ng from each sample) in a single hybridization reaction for 12 h at 65°C in solution. Using the nCounter Prep Station, each probe-mRNA complex was captured post-hybridization onto a streptavidin coated surface, aligned and imaged. Each sample was scanned for 600 fields of view on the nCounter Digital Analyser. As each target mRNA is designated by its unique colour code, the level of expression was quantified by counting the number of codes for each molecule. Subsequent normalization of the raw data to internal controls provided by the manufacturer was performed using the nSolver Analysis software v1.1. Data was extracted using the nCounter Reporter Code Count (RCC) Collector; based on the positive and negative controls, a cutoff of 20 was used to filter out transcript signals that registered at levels of background noise.

Data analysis

Illumina-based BeadChip data files were analysed with Illumina's GenomeStudio gene expression module and R-based Bioconductor package to determine gene expression signal levels. Briefly, BeadScan was utilized to extract and scan the raw intensity signals from the Illumina Human HT-12 v3.0 gene expression array with subsequent data correction by background subtraction in GenomeStudio module (V1.9.0). Twenty-six members of the BCL2 family were log2 transformed and analysed for differential expression using Welch's T-test at an alpha of 0·05, for the six cell lines and their respective replicates. Nine genes were found to be differentially expressed and annotated according to the current literature for the their pro/anti-apoptotic behaviour within the current system model. These data are presented as an annotated heatmap, using the Bioconductor package Heatplus. Using only the probe values for BCL2, MCL1 and BCL2L1 (BCL-XL), a whisker and box plot was made depicting the overall log-transformed signal intensities indicative of differential expression of the aforementioned genes across all the human plasma cell cancer models tested. Briefly, the central plot contains the interquartile (25–75%) range, representing 50% of the probe values. The line within the box represents the median value of all probe signals consistent with their respective gene. Whiskers outlying the top and bottom of the box signify the maximum and minimum probe values, respectively.

Statistical interpretation of NanoString nCounter assay

Statistical interpretation and data visualization (heatmap) was conducted using Multi Experiment Viewer (MeV) from The Institute for Genomic Research (TIGR) (Saeed et al, 2003, 2006). Using the normalized data that was exported from nCounter RCC Collector, an average of mRNA transcript probe values was taken for each cell line across controls and treated samples, a tab-delimited text file was generated in Microsoft Excel and uploaded into MeV. Genes were log-2 transformed and mean centred. Bi-dimensional, average-linkage, unsupervised hierarchical clustering analysis was applied to find the relationships between samples and genes using the Pearson correlation coefficient.

Immunoblot analysis

Total protein extracts were prepared using radioimmunoprecipitation assay (RIPA) lysis buffer (50 mmol/l Tris containing 150 mmol/l NaCl, 0·1% sodium dodecyl sulfate [SDS], 1% TritonX-100, 1% sodium deoxycholate, pH 7·2) with 0·2% protease and phosphatase inhibitor cocktail (Sigma-Aldrich, MO) on ice for 40 min, vortexing for 5 s every 10 min. Following centrifugation at 18 400 gfor 20 min, the supernatant was collected and used for Western blot analyses. Protein content in the extracts was measured by bicinchoninic acid protein assay reagent. Aliquots of 30 μg of total protein were boiled in Laemmli sample buffer, loaded onto 10% SDS polyacrylamide gel electrophoresis (SDS-PAGE) gels and transferred onto a nitrocellulose membrane. Membranes were blocked for 1 h in Tris-buffered saline (TBS)/Tween 20 [TTBS] containing 1% nonfat dried milk and 1% bovine serum albumin. Incubation with primary antibodies was done overnight at 4°C, followed by washing 3× with TTBS and incubation for 1 h with horseradish peroxidase-conjugated secondary antibody. The blots were developed using chemiluminescence (Thermo Scientific).

Apoptosis assay

Apoptosis was measured using the Annexin V binding assay kit from BD Biosciences (San Diego, CA) according to the manufacturer's instructions. Briefly, at the end of the treatment, cells were washed with PBS and 1 × 106 cells were re-suspended in 100 μl of binding buffer. Fluorescein isothiocyanate (FITC)-labelled Annexin V (5 μl) and PI (10 μl) were added to each sample and incubated in the dark for 15 min at room temperature. The cells were subsequently analysed by flow cytometry using BD Accuri, the C6 flow cytometer and its software. Data from 10 000 events per sample were collected and analysed.

Determination of mitochondrial outer membrane permeability (MOMP)

Cells were treated with different agents for 48 h and assessed for MOMP using TMRM, which was directly added to the cell cultures at 100 nmol/l concentrations and incubated at 37°C in the dark for 15 min. At the end of the incubation, cells were washed twice with cold PBS containing 2% FBS and analysed. The cells were washed for fluorescence (FL2) and analysed by BD Accuri, the C6 flow cytometer and its software. Data from at least 20 000 events per sample was collected and analysed. TMRM-negative (%) cells were calculated to determine % MOMP.

Results

BCL2 profiling of human MM and WM cell lines

It is reported that levels of pro-survival BCL2 proteins may impact response to anti-BCL2 agents (Placzek et al, 2010). Therefore, we first determined the mRNA expression pattern of BCL2 family members that are known targets of AT-101 in our preclinical models of human malignant plasma cell cancer. GEP of four MM (KMS11, KMS11BR, U266, U266BR) and two WM (BCWM1 and BCWM1BR) cell lines was conducted with a subsequent interrogation focused on all known BCL2-related genes (26 genes total). Of the pro-survival subset of BCL2 family members, BCL2, MCL1and BCL2L1 are the best characterized; as such we first investigated their gene expression in our preclinical models. As depicted by whisker and box plot in Fig 1A, we noted upregulation of all three pro-survival genes across the six cell lines tested. Next, we examined the differential expression of pro- and anti-apoptotic BCL2 family members in each of the cell lines. Upon unsupervised hierarchical analysis, we observed clustering of BCL2 family genes in relation to the malignant plasma cell lines with consistent overexpression of BCL2 family members (P < 0·05) (Fig 1B). An increase in the transcription of BCL7C and the chemo resistance promoting BCL11Bgene (Grabarczyk et al, 2010) was also apparent in a subset of the cell lines. As anticipated, the overall BCL2 family expression profile varied to some degree among the different plasma cell tumour models. This variation in the expression profile of BCL2 and its members may suggest differential reliance of survival on BCL2 versus other anti-apoptotic members that could be cell-line specific.

Figure 1.

Figure 1

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Gene expression profiling of BCL2 family members in preclinical models of human plasma cell cancer. (A) Whisker and box plot shows the overall log-transformed signal intensity of spotted probes for the BCL2, BCL2L1 and MCL1 genes present in multiple myeloma and Waldenström macroglobulinaemia cell lines (n = 6, with respective replicates). The line inside the box represents the median value of the signal. Further analysis in which all 26 BCL2 family members were examined for differential expression shows clustering of pro- and anti-apoptotic BCL2 genes with some variation among the cell lines. Unsupervised hierarchical clustering analysis (B) shows that all cell lines consistently expressed BCL2 and the anti-apoptotic BCL2 family members, MCL1 andBCL2L1.

BCL2 and MCL1 expression changes with resistance to bortezomib, however BR cells remain sensitive to therapeutic BCL2 downregulation

Though centrally engaged in the intrinsic apoptotic pathway, BCL2 (and its family members) shift their expression pattern (and possibly their functional engagement) in response to cellular stress induced by treatment. How this modulation is organized remains unknown, but it may be effectively sequenced to maintain survival benefit in favour of the tumour cell. MM patients are exposed to several lines of therapy, and this can affect BCL2 biology in the relapsed state. Based on findings from the GEP analysis, we investigated alterations in BCL2 behaviour in our BR models (Chitta et al, 2009). Bortezomib is a potent proteasome inhibitor whose mechanism of action in MM is independent of BCL2, and therefore this serves as an important biological model to interrogate the changing behaviour of BCL2 under drug induced stress. Although GEP did not showBCL2 mRNA overexpression in the bortezomib resistant cell lines, we observed significant upregulation of BCL2 and MCL1 at the protein level (Fig 2A), suggesting post-translational and feedback mechanisms that regulate bioavailability of the anti-apoptotic proteins. Being a pan BCL2 inhibitor, we predicted that this shift in the BCL2 and MCL1 expression pattern should not alter the tumour cells sensitivity to AT-101. As anticipated, treatment of these bortezomib resistant cell lines (n = 3) with AT-101 at a 5-μmol/l concentration for 24 h resulted in a significant decrease in viability and induction of apoptosis that was comparable to their parental bortezomib-sensitive (Wild type) cell lines (Fig 2B).

Figure 2.

Figure 2

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Bortezomib resistance induces changes in the expression profile of BCL2 family proteins, however bortezomib-resistant cells are sensitive to BCL2 inhibition by AT-101. Human myeloma cell lines (n = 3) were continuously treated with bortezomib until resistance (inhibitory concentration [IC50] >1000 nmol/l) was established. (A) Expression of BCL2 proteins was analysed by Western blot analysis in wild type (IC50 6 nmol/l) versus bortezomib-resistant OPM2 cells. BCL2, MCL1, BID and PMAIP1 (NOXA) were overexpressed in bortezomib-resistant cells compared to the parent wild type OPM2 cells. (B) Wild type (WT) and bortezomib-resistant (BR) cells were treated with AT-101 (5 μmol/l) for 24 h and apoptosis determined by flow cytometry after staining with annexin V. AT-101 treatment resulted in programmed cell death that was comparable in both bortezomib-sensitive and resistant cells. Data from two representative cell lines (OPM2-WT and OPM2-BR variant) are shown.

AT-101 downregulates BCL2 and MCL1 expression, which is associated with changes in the mitochondrial membrane potential (MOMP)

To validate if AT-101 treatment results in downregulation of its intended targets, e.g., BCL2 and MCL1, we treated KMS11, OPM2, and BCWM1 cells with varying concentrations of AT-101 in vitrofor 24 h. We observed a dose-dependent decrease in both BCL2 and MCL1 proteins. Importantly, and consistent with the reported binding potential of AT-101 to BCL2 versus MCL1, the inhibitory effect was more pronounced on BCL2 compared to MCL1. Data from one representative cell line, KMS11, is shown (Fig 3A). The BCL2 anti-apoptotic members act to dampen the pro-apoptotic signal delivered to the cell. Their central role is to stabilize the outer mitochondrial membrane and prevent pore formation through which cytochrome C (an activator of apoptosis) can be released into the cytoplasm (Kuwana & Newmeyer, 2003; Reed, 2008). Thus downregulation of BCL2 and MCL1 is expected to compromise MOMP, leading to the release of both cytochrome-C and Smac/Diablo; thus effectively activating the intrinsic apoptotic cascade. We therefore investigated if treatment with AT-101 does in fact impact MOMP. MM cells were treated in vitro with various doses of AT-101 for 24 h and MOMP was analysed by flow cytometry. AT-101 significantly increased MOMP in a dose-dependent manner (Fig 3B), validating that the anti-neoplastic effect of AT-101 in plasma cell cancers is mediated through the mitochondria.

Figure 3.

Figure 3

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AT-101 downregulates BCL2 and MCL1, inducing changes in the mitochondrial membrane permeability (MOMP) in multiple myeloma and Waldenström macroglobulinaemia cells. (A) KMS11, OPM2 and BCWM1 cells were treated in vitro with increasing concentrations of AT-101 for 24 h. Protein extracts were probed for BCL2 and MCL1 by immunoblot analysis. Treatment with AT-101 resulted in a dose-dependent decrease of BCL2 and MCL1 proteins (data from one representative cell line, KMS11 is shown here). ACTB (β-actin) was used as control. (B) For MOMP determination, KMS11, OMP2 and BCWM1 cells were incubated with AT-101 at various concentrations (x-axis) for 24 h. Cells were incubated with 20 nmol/l tetramethylrhodamine methyl ester for 15 min and MOMP analysed by flow cytometry. MOMP was most activated at an AT-101 concentration of 10 μmol/l. The data shown represents the average values taken from the aforementioned three cell lines.

AT-101 treatment of MM & WM cells induces apoptosis in a caspase-dependent manner

MOMP activation also suggests restoration of the intrinsic apoptotic pathway. Therefore we subsequently investigated if this event was catastrophic and induced apoptosis in malignant MM and WM models. We observed in several human plasma cell cancer models (n = 3) that in vitrotreatment with AT-101 at different concentrations (24-h incubation) resulted in apoptosis induction as determined by annexin V/PI staining followed by flow cytometry (Fig 4A; data represents average values taken from KMS11, OPM2, BCWM1 cells). Furthermore, PARP1 cleavage and activation of caspase 9 and 3 was also observed, which was reversed by concurrent treatment with the pan-caspase inhibitor Z-VAD.fmk (used at a 20 μmol/l concentration for 6 h), thus confirming that tumour cell death induced by AT-101 is largely caspase-mediated and acts through the intrinsic apoptotic pathway (Fig 4B). Notably, these effects of AT-101 were observed independent of the tumour cells acquired resistance to bortezomib.

Figure 4.

Figure 4

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AT-101-induced apoptosis in malignant plasma cells is caspase-dependent: (A) multiple myeloma (KMS11, OMP2) and Waldenström macroglobulinaemia cells (BCWM1) were treated with AT-101 at various concentrations for 24 h and stained with annexin V and propidium iodide. AT-101 demonstrated a dose dependent increase in apoptosis as determined by flow cytometry. Data represents average values taken from 3 treated cell lines. (B) BCWM1 cells (Wild type [WT] and bortezomib-resistant [BR]) were treated with 10 μmol/l AT-101 for 24 h with or without Z-VAD.fmk (20 μmol/l for 6 h). Western blot analysis demonstrates cleavage of PARP1, caspase-9 and caspase-3 in the presence of AT-101; this was observed in both the WT and BR cells. Concurrent treatment with Z-VAD.fmk (pan-caspase inhibitor) prevented this effect and confirmed that AT-101 mediated tumour cell death is carried out in a caspase-dependent manner through the intrinsic apoptotic pathway.

AT-101 in combination with lenalidomide and dexamethasone (LD) significantly compromises the viability of MM and WM cells

LD is a standard and US Food and Drug Administration (FDA) approved therapy for patients with MM, both in the frontline and relapsed setting (Weber et al, 2007; Rajkumar et al, 2010). However, it is not curative, and the incidence of complete remission remains low. Furthermore, high BCL2 undermines the effectiveness of dexamethasone (Ailawadhi et al, 2012). We asked whether down regulation of BCL2 and MCL1 could enhance the efficacy of a currently used anti-MM therapeutic regimen. We previously demonstrated in primary chronic lymphocytic leukaemia (CLL) cells that downregulation of BCL2 enhances the antitumour effect of lenalidomide. The cooperation of AT-101 with lenalidomide was both direct, as well as indirect, with the latter through enhancement of the cytotoxic potential of lenalidomide-activated immune effector cells (Masood et al, 2011). In MM, lenalidomide is noted to have a direct cytotoxic effect by down regulation of the PI3K/AKT1 (PI3/Akt) pathway (Hayashi et al, 2005). We first tested in vitro the effect of each drug on MM cell proliferation either alone or in combination at pharmacological doses. Cells were treated with AT-101 (1 μmol/l), lenalidomide (1 μmol/l), dexamethasone, (10 μmol/l) or in combinations with one another (LD, LDA) for 48 h followed by cell viability analysis using the trypan blue exclusion assay. Figure 5 shows data from two representative cell lines (high BCL2/MCL1 versus low BCL2/MCL1), intentionally selected based on BCL2 and MCL1 expression profile. A significant decrease in MM cell proliferation was observed with the LD combination that was further potentiated with the addition of AT-101. Although AT-101 by itself was also able to inhibit MM cell proliferation, the triple combination had the most potent effect. It is important to note that in all drug combination experiments, AT-101 was used at a 1-μmol/l concentration.

Figure 5.

Figure 5

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The triple combination of AT-101 plus lenalidomide/dexamethasone significantly decreases the viability of malignant plasma cells. Multiple myeloma and Waldenström macroglobulinaemia cells were treated with AT-101 (A; 1 μmol/l), lenalidomide (L; 1 μmol/l), dexamethasone, (D; 10 μmol/l) or in combination (LD, LDA) for 48 h and cell viability analysed by trypan blue exclusion assay. Both AT-101 and LD treatment resulted in loss of cell viability, however a maximum decrease in viability was observed when all three drugs were combined (LDA combination). Importantly, this effect of AT-101 on tumour cell viability was noted with a significantly lower dose (1 μmol/l). Data from two representative cell lines is shown, one with high BCL2/MCL1 protein expression (KMS11) and one with low BCL2/MCL1 protein expression (BCWM1).

AT-101 potentiates the cytotoxicity of lenalidomide and dexamethasone therapy in MM and WM

To inspect if this decrease in viability was due to induction of death, as would be expected, we checked for apoptosis induction with the triple combination. Human MM and WM cell lines (n = 6 total) were treated with each drug (L, D or A) alone or in different combinations at similar concentrations as used for viability measurements for 48 h. Figure 6A, B depicts the results from two representative cell lines where the triple drug combination demonstrated significantly increased apoptosis versus either of the drugs alone or in LD permutation (P < 0·05). Further validation of apoptosis was confirmed by cleavage of PARP1, which was most significantly noted with the triple combination (Fig 6C). This effect of AT-101 on apoptosis was independent of the BCL2/MCL1 expression levels of the cell line. Interestingly, these effects were demonstrated at a significantly lower dose. The dose of AT-101 required to induce comparable apoptotic effects in the triple combination was significantly lower (1 μmol/l) as compared to the dose needed when used in single agent form (5 μmol/l, Fig 4A).

Figure 6.

Figure 6

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AT-101 enhances the cytotoxicity of lenalidomide/dexamethasone (LD) in multiple myeloma (MM) and Waldenström macroglobulinaemia (WM) cells. MM and WM cell lines (n = 6) were treated in vitro with AT-101 (A; 1 μmol/l), lenalidomide (L; 1 μmol/l), dexamethasone (D; 10 μmol/l) or a combination (LD, LDA) for 48 h, and cell death was assessed by annexin-V staining. Data from two representative cell lines (BCWM1 and KMS11) with variable BCL2 and MCL1 protein profiles is shown. When combined with LD, AT-101 significantly increased apoptosis (LDA versus A alone or LD) in (A) a low BCL2/low MCL1 expressing as well as in (B) a high BCL2/high MCL1 expressing cell line. Cleavage of PARP1 as assessed by western blot at 48 h post treatment, confirmed activation of the intrinsic apoptotic pathway (C). To demonstrate the potent effect of the LDA combination a low dose of AT-101 (1 μmol/l) was used in these experiments.

BCL2 downregulation is enhanced when AT-101 is combined with LD

We then examined how the enhanced anti-MM effect of the triple combination is delivered. Western blot analysis revealed that lenalidomide did not downregulate BCL2 but, as anticipated, AT-101 did. Interestingly, the triple combination had significantly more inhibitory effect on BCL2 expression (Fig 7A). Furthermore, we investigated the effect on MOMP induction with the triple combination in context with single agent AT-101 or LD. As noted in Fig 7B, the most potent induction of MOMP was seen with the triple combination (LDA), and this seemed to be primarily driven by AT-101 (compare lane 3 versus lane 6 in Fig 7A). In these experiments, tumour cells were treated with lenalidomide (1 μmol/l), dexamethasone (10 μmol/l) and AT-101 m (1 μmol/l) for 48 h.

Figure 7.

Figure 7

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Decrease in BCL2 expression is noted when AT-101 is combined with lenalidomide/dexamethasone (LD). Multiple myeloma (MM) and Waldenström macroglobulinaemia (WM) cell lines (n = 6) were treated in vitro with AT-101 (A; 1 μmol/l), lenalidomide (L; 1 μmol/l), dexamethasone, (D; 10 μmol/l), LD or LDA for 48 h. Representative data from BCWM1 and KMS11 cells is shown. (A) BCL2 downregulation was examined by Western blot analysis. AT-101 combined with LD markedly decreased BCL2 (versus A alone or LD) in both low BCL2/low MCL1 expressing (BCWM1) and high BCL2/high MCL1 expressing (KMS11) cell lines. The effect on BCL2 was more pronounced in low BCL2/low MCL1 expressing BCWM1 cells. (B) The effect of AT-101 on MOMP was determined by flow cytometry after incubating tumour cells with tetramethylrhodamine methyl ester (TMRM). AT-101 significantly increased mitochondrial membrane permeability (MOMP) in MM and WM cells particularly when used in combination with LD (LDA) (P < 0·05). Consistent with observations in (A), an increase in MOMP was more pronounced in the low BCL2/low MCL1 expressing (BCWM1) cell model. It is important to note that AT-101 was used at a 1 μmol/l concentration to demonstrate its potency at low doses when used in the LDA combination. This may account for variation in BCL2 downregulation and MOMP activation in the high BCL2/high MCL1 expressing (KMS11) cell line.

Molecular sequelae of treatment with LDA combination

Our data demonstrated that targeting BCL2 and its family members with AT-101 improves the lethality of LD. BCL2 and its family members directly and indirectly influence several molecular pathways. Furthermore, lenalidomide and dexamethasone also have specific molecular targets, and these are linked to alternative intracellular pathways that can regulate tumour cell survival. Thus, to further enhance our understanding of the various cellular mechanisms that are influenced by LDA therapy and may account for the significant antineoplastic activity of this combination, we analysed the effect of LDA on gene expression profiles of MM and WM cells using the NanoString nCounter Assay and then assessed the critical pathways affected with this regimen. Owing to its high sensitivity and capability of directly measuring mRNA abundance (as opposed to a fluorescence based value), the NanoString nCounter assay has demonstrated itself to be an equivalent alternative to quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) or Open Array real-time PCR (Prokopec et al, 2013). Between the two cell line models, a total of 62 genes (Tables S1, S2) were differentially altered in LDA treated cells and grouped according to their behavioural pattern on unsupervised hierarchical clustering analysis (Fig 8). An intersect analysis of the 62 genes revealed five genes (CCNA2, FRZB, FYN, IRF1, PTPN11) that were significantly altered (P < 0·05) in the same orientation in both MM and WM cells in the presence of LDA (Table 1). We utilized the web and knowledge-based tool, IPA to identify molecular networks and pathways that were relevant to this group of genes and those implicated as master regulators; forming other major gene networks. IPA network analysis of the five common genes uncovered a major network centred on the IRF1 gene. IRF1 is a major transcription factor and is known to interact with the tumour suppressor TP53 (p53). IPA canonical pathway analysis demonstrated TP53 signalling and the cyclins and cell cycle regulation pathways to be the most significantly activated by LDA therapy. Further inquiry into the upstream regulatory elements operational in LDA-treated cells exposed five genes that target numerous downstream genes in our dataset, including those identified on intersect analysis. These upstream regulator genes are comprised ofE2F2, NOTCH1, RB1, TP53 (encoding transcription factors), and HRAS (encoding the HRAS enzyme), all whose targets include BCL2 and its family members (Table 2). Although MM and WM are related malignancies, their cell populations are distinct from one another and, as such, a differential response in gene expression would also be expected. Our analysis revealed that the IRF1 gene was the most upregulated (4·07-fold change) and the CDH1 gene was the most downregulated (−3·7-fold change) in BCWM1 cells. In KMS11 cells, we found FYN (4·64-fold change) and CCNA2 (−2·99-fold change) to be the most up and downregulated genes in the dataset, respectively.

Figure 8.

Figure 8

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Gene expression of BCWM1 and KMS11 cells treated with lenalidomide/dexamethasone and AT-101 (LDA) using the NanoString nCounter assay. KMS11 and BCWM1 cells were treated with 1 μmol/l of lenalidomide + dexamethasone (LD), 1 μmol/l of AT-101 (A), or lenalidomide + dexamethasone + AT-101 (LDA, all at a 1 μmol/l concentration) for 24 h. Unsupervised, hierarchical, bi-dimensional clustering analysis of KMS11 (KMS) and BCWM1 (BC) cells showed differential expression and behavioural pattern of genes in response to LD, A, or LDA treatment. In comparison to untreated control cells, 17 genes were differentially expressed in LDA-exposed BCWM1 cells when a threshold of −1·5- and 1·5-fold change was applied. Using a similar cutoff value, 45 genes were differentially expressed in LDA-treated KMS cells versus control cells. Scale colour of red indicates upregulation of gene, whereas blue indicates downregulation. Intersect analysis of KMS11 and BCWM1 gene profiles revealed five common genes (CCNA2, FRZB, FYN, IRF1, PTPN11) that were significantly altered (P < 0·05) in the presence of LDA.

Table 1.

List and role of genes altered in both MM and WM cell lines in response to LDA treatment.

Gene Response to LDA Fold change Role
MM, multiple myeloma; WM, Waldenström macroglobulinaemia; LDA, lenalidomide, dexamethasone, AT-101.
CCNA2 Downregulated −1·99 to −2·99 Encodes for cyclin A2 protein, regulates cell cycle progression
FRZB Upregulated 1·53–2·23 Encodes for soluble frizzled-related-protein 3, negatively regulates WNT signalling
FYN Upregulated 1·78–4·64 Encodes for non-receptor tyrosine kinase Fyn, mediates B-cell receptor signalling
IRF1 Upregulated 2·83–4·07 Encodes for interferon regulatory transcription factor 1, facilitates apoptosis and transactivates TP53
PTPN11 Upregulated 1·53–1·89 Encodes for non-receptor protein tyrosine phosphatase Shp-2, negatively regulates JAK/STAT signalling
JUN Upregulated (KMS11) 1·49 Transcription factor that binds AP1 elements within target genes and can regulate JNK signalling. Can modulate expression of TP53
Downregulated (BCWM.1) −1·55
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Table 2.

IPA-generated list of top upstream regulator genes in LDA-treated MM and WM cell lines

Upstream regulator Molecule type Activation z-score P-value of overlap Target molecules in dataset
IPA, Ingenuity Pathways Analysis; MM, multiple myeloma; WM, Waldenström macroglobulinaemia; LDA, lenalidomide, dexamethasone, AT-101.
E2F2 Transcription regulator –0·176 2·48E-17 BCL2, BIRC5, BMI1, CCNA2, CCND1, CCND3, CDKN1A, CDKN2A, CDKN2C, E2F1, E2F3, MLH1, MYB, MYBL2, MYCN, PCNA, SERPINE1, TERT, TP53
HRAS Enzyme 0·382 8·76E-16 BCL2, BCL2L1, BIRC5, CAV1, CCNA2, CCND1, CCND2, CCND3, CD44, CDH1, CDKN1A, CDKN2A, CDKN2B, CTGF, CYP1A1, E2F1, EGR1, ETS1, FAS, FGF2, GUSB, HIF1A, HRAS, IL8, ITGB1, JUN, MET, MMP3, MYCN, PCNA, PTEN, SERPINE1, SOD1, STAT3, TERT, TNF, TNFRSF10B, TP53
NOTCH1 Transcription regulator 0·666 4·25E-16 BCL2, BCL2L1, BIRC2, CCND1, CCND2, CCND3, CDH1, CDKN1A, CEBPA, CTGF, E2F1, FGF2, IGFBP3, IL8, IRF1, ITGB1, MYCL, NOTCH1, PPARG, PTEN, RB1, SERPINE1, TEK, TGFBR2, TNF, TP53
RB1 Transcription regulator 0·673 5·95E-16 BCL2, BIRC5, CCNA2, CCND1, CDH1, CDKN1A, CDKN2A, CEBPA, CTGF, E2F1, E2F3, EGR1, FAS, FGF2, HRAS, IGF1, KIT, MET, MYB, MYBL2, PCNA, PPARG, RB1, SERPINE1, TERT, TNF, TP53
TP53 Transcription regulator –0·326 1·19E-16 BCL2, BCL2A1, BCL2L1, BCL3, BIRC2, BIRC5, CAV1, CCNA2, CCND1, CCND2, CCND3, CD44, CDH1, CDKN1A, CDKN2A, CEBPA, CSF3R, CTGF, CYP1A1, DAPK1, E2F1, EGR1, ESR1, FAS, FGF2, FYN, HIF1A, HRAS, IGF1, IGFBP3, IL8, JUN, MCL1, MET, MLH1, MMP3, MYBL2, NOTCH1, NPM1, PCNA, PPARG, PTEN, RB1, SERPINE1, SOD1, STAT1, TERT, TGFBR2, TNF, TNFRSF10B, TNFRSF1B, TP53
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Discussion

B-cell cancers, including MM and WM, utilize BCL2 and MCL1 to disrupt the intrinsic apoptotic pathway, and this confers a survival advantage to the tumour cells (Hu & Gazitt, 1996; Tian et al, 1996; Gazitt et al, 1998; Feinman et al, 1999; Iyer et al, 2003; Chitta et al, 2009; Sampath et al, 2012). Induced expression of BCL2 in MM cell lines results in resistance to chemotherapy and steroids. Conversely, downregulation of BCL2 reverses this and improves sensitivity to anti- MM therapeutics. Clinically in MM patients, BCL2 upregulation is associated with an aggressive clinical course, frequent relapses, and suboptimal response to therapy, which all compromise patient survival. Despite several compounds undergoing clinical investigation, no BCL2 or MCL1 inhibitor has been approved for B-cell cancers including MM to date. In MM the initial clinical studies primarily focused on BCL2 mRNA downregulation using oblimersen (Advani et al, 2011). Phase II studies (van de Donk et al, 2004; Chanan-Khan et al, 2009) noted the clinical benefit of targeting BCL2 with oblimersen in combination with chemotherapy or thalidomide and dexamethasone, respectively. However, our phase III trial of dexamethasone with or without oblimersen in heavily pretreated MM patients did not demonstrate any survival advantage in favour of oblimersen. (Chanan-Khan et al, 2009) Although several factors were identified, the specificity of oblimersen towards only BCL2 mRNA and its lack of effect on other BCL2 family members (such as MCL1), which play an equally important role in relapsed MM (Derenne et al, 2002; Wuilleme-Toumi et al, 2005), was presented as a possible reason for the negative results observed in this study. Interestingly, oblimersen was also investigated in patients with relapsed CLL. In the phase III study of chemotherapy (fludarabine/cyclophosphamide) with or without oblimersen, we observed that addition of oblimersen did indeed result in survival advantage. Although, oblimersen could not secure FDA approval, these clinical experiences provide the proof of principle that BCL2 can be therapeutically targeted, and that this can impact an improved clinical outcome in patients (as noted in CLL) (O'Brien et al, 2007). Therefore it is important to review how the BCL2 family of proteins is engaged in regulating the intrinsic apoptotic pathway and control tumour cell survival.

Members of the BCL2 family are designed to either prevent apoptosis (BCL2, BCL2L1 [BCL-XL] MCL1, BCL2A1 [BFL/A1], BCL2L10 [BCL-B]) or promote pro-apoptotic signals (BAX, BAK1 [Bak]). The pro-apoptotic effectors are additionally facilitated by several other BCL2 family members such as BID, BAD, BCL2L11 (BIM), BIK, BMF, HRK, PMAIP1 (NOXA), and BBC3 (PUMA) (Hunter et al, 2007). The molecule of the BCL2 protein is made up of four BCL2 homology (BH) domains namely BH1, BH2, BH3, BH4 and a transmembrane domain, whereas the other family members possess ≤4 domains and variation in homology (Youle & Strasser, 2008). All BCL2 family members share the BH3 domain, which direct their functional engagement and role. Thus the anti- or pro-apoptotic effector molecules have multiple domains, and the facilitator molecules only one (BH3) domain (Zeitlin et al, 2008). Upon tertiary folding, the BH1 – three domains form a hydrophobic groove (the BH3-binding domain) that allows binding of the other family members through their respective BH3 domains, and this directs functional engagement of the effector molecules. In the mitochondria, the pro-apoptotic molecules (BAX, BAK1) generate oligomeric pores triggering the release of apoptotic signalling molecules (cytochrome C)(Skommer et al, 2007) a process that is counterbalanced by their binding to the anti-apoptotic molecules BCL2, BCL2L1 (BCL-XL, BCL2L2) and MCL1. The facilitator BH3-only proteins potentiate apoptotic activity through enhanced pore formation either by directly binding to and inhibiting the anti-apoptotic molecules, competitively binding to BAX/BAK1 and blocking access of the anti-apoptotic proteins, or directly initiating oligomerization of BAX/BAK1 (Reviewed by Zeitlin et al, 2008). Ergo, the balance of these regulatory proteins (pro- versus anti-apoptotic) determines the apoptotic threshold of the tumour cell. An important strategy in targeting the BCL2 family for cancer therapy is to tip the balance in favour of pro-apoptotic members by downregulating one or more members from the anti-apoptotic group. Maintaining the integrity of the intrinsic apoptotic pathway is critical for cancer therapeutics and preclinical models of cancer display chemotherapy resistance or sensitivity with induction or downregulation of the BCL2 protein, respectively (Miyashita & Reed, 1992; Campos et al, 1993; Walton et al, 1993). A pan BCL2 inhibitor in this regard can be highly effective, as it targets multiple members of the BCL2 family.

AT-101 alters the functional equilibrium between the pro- and anti-apoptotic BCL2 protein family members. This shift restores the intrinsic apoptotic pathways thereby disarming the tumour cells’ survival mechanism (Wang et al, 2000; Kitada et al, 2003; Zhang et al, 2003). Among blood cancers, AT-101 has been investigated in lymphoma and CLL (James et al, 2005; Castro et al, 2006; Kingsley et al, 2009) and, in the latter, has produced anti-leukaemic effects with a favourable toxicity profile in patients (James et al, 2006). However, a limited number of clinical responses in these malignancies restricted its development as a single agent. This is anticipated considering the biology of BCL2, where mere restoration of the intrinsic apoptotic pathways may not be sufficient to induce clinically significant tumour kill. Thus, development of BCL2 inhibitors will typically require a partnership with other agent(s). Preclinical work by James et al (2005) led to the clinical study of AT-101 in combination with rituximab (anti-CD20 monoclonal antibody), which improved the overall response rate to 38% in relapsed or refractory CLL (Castro et al, 2006). Further, our group has demonstrated preclinically that the combination of AT-101 and dexamethasone results in more programmed cell death in primary patient myeloma cells as compared to AT-101 alone (Kline et al, 2008). Collectively, these studies validate the proposition that the best strategy in the development of a BCL2 agent is through rational combination treatment design.

AT-101 has not been clinically investigated in patients with MM. LD is an established and FDA-approved regimen for patients with relapsed MM, and it has a toxicity profile that is non-overlapping with AT-101. Although each of these agents has distinct molecular targets, they appear to activate inter-related gene networks, which lead to enhanced tumour cell death (Fig 9). In our analysis, we found the majority of genes that were differentially expressed and exhibited the same behavioural pattern belonged to the TP53 signalling and cell cycle regulation cascades. The major upstream regulatory elements (mainly transcription factors such as TP53, RB1, E2F2 and NOTCH1) that govern the expression of the LDA-relevant genes were all found to act on BCL2 and its family members (Table 2). Intriguingly, a major gene network emerged on intersect analysis of MM and WM cell lines that centred on the IRF1 gene node. IRF1 is a putative tumour suppressor gene that is known to inhibit BCL2 and BCL2L1 (BCL-XL) and increase expression of executioner caspase 8. Its expression was upregulated in our LDA-treated tumour cells (2·83- to 4·7-fold change). IRF1 can be induced by a number of cytokines including STAT1 and TNF (TNFα) (Schwartz et al, 2011), which we also found to be upregulated in LDA-treated cells (Table S2). Lenalidomide has been shown to phosphorylate STAT1, and although paradoxical to its anti-TNF properties, we have previously reported the ability of lenalidomide to upregulate TNF in CLL patients; in effect producing an acute phase inflammatory reaction that is predictive of clinical response (Chanan-Khan et al, 2011). Thus, these network analyses reveal the molecular events catalysed by the LDA combination, which converge on common signalling pathways (i.e. TP53) to ensure cellular demise.

Figure 9.

Figure 9

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Schematic representation of the scientific rationale to combine AT-101 with lenalidomide and dexamethasone for the treatment of multiple myeloma.

In summary, the data presented here demonstrate that AT-101 enhances the cytotoxic effects of lenalidomide and dexamethasone. This is mediated through the restoration of the intrinsic apoptotic pathway via modulation of BCL2 and its anti-apoptotic family members, along with induction of pivotal genetic networks that operate simultaneously to promote cell death.

Supplementary Material

Supplementary Tables

Acknowledgements

The authors would like to thank Mrs. Kelly Viola and Mrs. Alison Dowdell for their editorial assistance and Ascenta Therapeutics Inc, Malvern, PA, for providing AT-101. The experiments and analysis carried out in this study were supported by funding from the Leukemia and Lymphoma Society (AC is a Leukemia and Lymphoma Scholar in Clinical Research) and the Daniel Foundation of Alabama (AC).

Footnotes

Author's contributions

AP, KC, SK, and AC were responsible for concept and design of the study. KC, SA, DP, KJT, JC, SK, SMA, and AC conducted the experiments. AP, KC, DP, SK, and AD collected the data. AP, KC, KCM, VR, JRM, CBR, JF, and AC analysed and interpreted the data. AP, KC, CBR, and AC drafted the article. AP, KC, SA, KJT, and JC generated the Figs. AP, KC, and SA collected the images. AP, KCM, VR, SMA, JRM, AD, CER, JF, and AC critically revised the article for important intellectual content. AP, SMA, KCM, JRM, AD, JF, and AC made final approval of the article.

Disclosures of conflict of interest

SK's institution received a consulting fee and honorarium from Millennium, Celgene, and Onyx for aspects of this study, and SK also receives money for consultancy from Millennium, Celgene, Array Biopharma, Onyx, Genzyme, and NIH outside of the submitted work. AD's institution receives clinical trial money from Millenium, Celgene, Pfizer, and Jansen outside of the submitted work. JF's institution received grant money from Celgene for aspects of this study. Ascenta Therapeutics Inc. provided AT-101, but no financial funding.

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