Multidrug resistance gene expression and ABCB1 SNPs in plasma cell myeloma

Leukemia Research 35 (2011) 1457–1463

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Multidrug resistance gene expression and ABCB1 SNPs in plasma cell myeloma Stephen Drain a,b,∗ , Louise Flannely a,b , Mary B. Drake a , Paul Kettle a , Nick Orr c , Anthony J. Bjourson b , Mark A. Catherwood a,b , H. Denis Alexander a,b a b c

Haemato-Oncology Laboratory, Belfast HSC Trust, Belfast City Hospital, Northern Ireland, UK Biomedical Sciences Research Institute, University of Ulster, Coleraine, Northern Ireland, UK The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK

a r t i c l e

i n f o

Article history: Received 20 February 2011 Received in revised form 19 April 2011 Accepted 26 May 2011 Available online 25 June 2011 Keywords: Plasma cell myeloma Multidrug resistance ABC transporters Gene expression Haplotype Overall survival

a b s t r a c t Multi-drug resistance (MDR) leads to impaired treatment efficacy in all forms of malignancy. The main forms of MDR are thought to be mediated by the substrate transporting actions of certain adenosine triphosphate binding cassette (ABC) transport proteins. The genes ABCB1, ABCB4, ABCC1, ABCG2 and LRP1 have been identified as the most prominent contributors to clinically significant MDR. To date, no study has investigated the expression of these genes in plasma cell myeloma (PCM), or attempted to relate their expression to the incidence of relapse and/or stage at presentation. Here, we show that ABCB4 may be a prominent mediator of tumour cell MDR within PCM. Additionally, there are three SNPs (rs1045642, rs2032582 and rs1128503) within the most widely studied of these genes, ABCB1, which have been suggested to have a potential impact on OS in PCM and which may form a haplotype in ABCB1. rs1045642 in ABCB1 appears to be the only SNP affecting OS within the PCM patients studied, with minimal linkage disequilibrium demonstrated between it and rs2032582 and rs1128503. © 2011 Elsevier Ltd. All rights reserved.

1. Introduction Multi-drug resistance (MDR) can lead to impaired treatment efficacy in all forms of malignancy [1]. Although many mechanisms of resistance have been identified, the most prominent forms of MDR seem to be either mediated by, or connected to, the substrate transporting actions of certain adenosine triphosphate binding cassette (ABC) transport proteins [2–4]. Active ABC transporters are present in a variety of tissues, with the greatest expression demonstrated in the intestine, liver and blood brain barrier [5–8]. Some expression has also been noted in normal bone marrow cells [9]. ABC proteins have clearly defined roles in dietary metabolism and in the formation of xenobiotic substrate barriers. Previous studies in acute leukaemia and chronic lymphoproliferative disorders (CLPD) have demonstrated that increased expression in patient tumour cells of the most promiscuous transporter, P-glycoprotein (P-gp), predicts poor clinical outcome and increased likelihood of relapse following treatment [10–13]. Studies in plasma cell myeloma (PCM) have shown that the amount of P-gp expressed at relapse correlates with the amount of chemotherapy given [10],

∗ Corresponding author at: Haemato-Oncology Laboratory, Department of Haematology, C Floor, Belfast HSC Trust, Belfast City Hospital, Northern Ireland BT97AB, UK. Tel.: +44 02890601129; fax: +44 02890263870. E-mail address: [email protected] (S. Drain). 0145-2126/$ – see front matter © 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.leukres.2011.05.033

indicating that it may be part of an intrinsic pathway activated in response to treatment. P-gp is the most widely studied MDR protein in malignancy [14]. Recent evidence has suggested that other ABC proteins may exert a more prominent role in MDR than P-gp [15–17]. The five main contributors to clinically significant MDR have been identified as P-gp (ABCB1), MDR3 (ABCB4) [18], multidrug resistance protein (ABCC1), lung resistance protein (LRP1), and breast cancer associated protein (ABCG2) [16]. It is thought that up-regulation of ABC proteins at relapse may be contingent upon basal levels being present in tumour cells at diagnosis [19]. It is conceivable that an interactive effect between multiple MDR proteins and drug resistance may exist, perhaps where they are highly expressed in the same cells, although this remains unproven. Mutations and single nucleotide polymorphisms (SNP) within the germline sequence of MDR genes have been shown to reduce the expression and activity of the protein produced [20–23]. This decreased protein activity may lead to improved clinical outcome, enhanced drug response and overall survival in a subset of patients. rs1045642 is one such SNP that may alter the activity of P-gp either alone or in combination with one of two other SNPs, rs2032582 and rs1128503, alleles of which define a common haplotype in this gene [24]. Indeed, the linkage disequilibrium (LD) between these SNPs has made it difficult to elucidate the primary contributor to MDR [24,25]. Two retrospective studies in PCM have demonstrated an association with OS and rs1045642 and in a further study with rs2032582 [26–28].

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Table 1 Product information for Taqman pre-designed primer-probe reagent from applied biosystems. Gene nomenclature

Product number

ABCB1 ABCB4 LRP1 ABCG2 ABCC1 GUSB

Hs00184491 Hs00240956 Hs00911183 Hs01053790 Hs01561499 Hs03929099

m1 m1 m1 m1 m1 m1

against the expression of a selected housekeeper gene (GUSB) assayed within the same sample and also against the target gene expression within non-clonal (normal) plasma cell RNA samples. Patient RNA samples were analysed in duplicate with positive standards and negative controls included to fully validate the results on the individual patients. 2.6. Genotyping of common ABCB1 SNPs

This study was designed to assess the mRNA expression of the ABC transporter genes ABCB1, ABCB4, ABCC1, LRP1 and ABCG2 in plasma cell dyscrasias (PCD) at both diagnostic stages (MGUS and PCM) and at relapse in PCM. A further aim was to investigate the impact of the three SNPs (rs1045642, rs2032582 and rs1182503) on ABCB1 gene expression and OS in PCM. 2. Materials and methods 2.1. Patient recruitment Levels of MDR gene expression were measured in 89 patients with a confirmed PCD at various stages of disease (MGUS, PCM and relapse), 35 of which were also genotyped for the ABCB1 SNPs. A further 134 PCM patients, on 69 of whom we reported previously [27], were investigated to determine the impact of the ABCB1 SNPs, individually, on OS in PCM and to determine the LD between these SNPs. This study has full ethical approval from the Office for Research Ethics Committees Northern Ireland (ORECNI). Informed consent was obtained prior to sample collection, in accordance with the Declaration of Helsinki. 2.2. CD138+ cell selection To obtain a purified sample of patient tumour cells, PCD patient BM aspirates were separated by density gradient centrifugation using Ficoll-PaqueTM (Amersham Pharmacia Biotech, UK), with the mononuclear cell (MNC) layer harvested for CD138+ cell selection using anti-CD138 magnetic microbeads and an autoMACS instrument (Miltenyi Biotech, Germany). Tumour specific RNA was then extracted from these CD138+ cells using the Trizol method (Invitrogen, UK). 2.3. Generation of cDNA from patient RNA PCD patient RNA (concentration assessed using a Nanodrop ND 1000 spectrophotometer and adjusted to 100 ng) was set up for a standard reverse transcription PCR reaction with a two step PCR protocol using the random primers method (Invitrogen, UK). cDNA generation was performed using a Thermocycler model gene amp 2700 instrument (Applied Biosystems, UK). 2.4. Selection of housekeeper gene A selection of patient samples (n = 10) and the normal plasma cell samples were assayed using Taqman probes as outlined below with GUSB, TATA and PGK-1 genes chosen as potential candidates and the CT values used for comparison. GUSB demonstrated the lowest inter and intra patient variability and its expression was deemed sufficient to serve as a good housekeeper gene (CT = 26). 2.5. Relative quantification of mRNA Expression of each gene was determined by qRTPCR using a Roche Lightcycler 1.2 instrument and validated Taqman assays (Table 1). The PCR cycle was recorded when sample amplification, and therefore the fluorescence intensity of the FAM probe, crossed the detectable threshold during the exponential phase of the PCR reaction (CT). Once determined, this CT value was quantified against serially diluted cDNA standards generated from a cell line with high levels of each gene expression, placing expression for all samples on a linear scale. mRNA expression could then be reported for each patient as a relative fold change from normal, standardised

Genotyping for all three SNPs was performed using real time PCR and melting curve analysis on the LightCycler 1.2 instrument (Roche Diagnostics, UK), with fluorescence resonance energy transfer (FRET) hybridisation probe and primer sets for rs1045642, rs1128503 and rs2032582 detection (TIB MOLBIOL, Germany). PCR was performed using a 10 ␮l reaction volume in LightCycler capillaries (Roche Diagnostics, UK) with primers and probes at the concentrations shown in Table 2 and approximately 40 ng of genomic DNA. Two microlitres of Faststart DNA Masterplus Hybprobe buffer (Roche Diagnostics, UK) were added to the reaction mix with PCR grade water to make the volume up to 10 ␮l. The PCR protocol utilised a preliminary denaturation at 95 ◦ C for 10 min, followed by a number of cycles of denaturation, annealing and extension (Table 2). Melting curve analysis directly followed the amplification with a denaturation step at 95 ◦ C for 0 s and annealing (Table 2) for 2 min using a 10 ◦ C/s ramp rate. The temperature was then increased to 75 ◦ C at 0.1 ◦ C/s with fluorescence monitored continuously on the FL-2 channel. Genotype discrimination was determined as the difference in melting temperatures of the sensor probe from the target strand with peaks at distinct temperatures demonstrating the C-T, G-T-A and C-T alleles (Table 2). Melting curve analysis was validated using anonymous DNA samples (4 from each genotype) which were previously confirmed by sequencing. 2.7. Statistical analysis Mean expression of the MDR genes, presented as a fold change from normal, was demonstrated using bar graphs, to highlight the expression of each gene in the various stages and forms of PCD. Differences in mRNA expression by genotype were assessed using analysis of variance (ANOVA). The correlation coefficient r2 was computed as a measure of linkage disequilibium. The impact of each SNP on OS was estimated using Cox regression with covariates for age, gender and immunoglobulin heavy and light chain classes. All statistical analysis was conducted in R.

3. Results 3.1. MDR gene expression in PCM Expression of all five genes of interest (ABCB1, ABCB4, ABCC1, ABCG2, LRP1) was corrected against housekeeper gene (GUSB) expression and reported as a fold change from expression in normal plasma cells. Information on existing diagnostic and prognostic markers in PCM (beta-2 microglobulin (B2M), albumin, paraprotein type and light chain restriction) was also available on most patients in this group (Table 3). Mean gene expression for the five genes of interest (ABCB1, ABCB4, ABCC1, ABCG2 and LRP1) in MGUS, PCM and PCM at relapse is presented in Table 4 and Fig. 1. All genes apart from ABCB4 are generally expressed at low levels in tumour cell samples with the lowest expression seen for ABCB1. ABCB4 on the other hand was shown to have a mean 20 fold increase in expression in patients diagnosed as PCM and interestingly a mean 34 fold increase in patients diagnosed as MGUS. It should be noted, however, that expression of all genes with the exception of ABCB1 demonstrated a high degree of variability between individuals and all genes, with the exception of ABCB1, demonstrated lower expression in unpaired relapsed patients (Table 4). When PCM patients were grouped according to ISS staging criteria there was increased expression of ABCB4 expression in stage 3 patients compared to

Table 2 PCR conditions and melting temperatures for ABCB1 SNP determination. Genotype

rs1045642 rs1128503 rs2032582

PCR protocol (◦ C) (s)

Primer/probe concentrations (␮mol/l)

Melting temperatures (◦ C)

F. primer

R. primer

Sensor

Anchor

Cycles

Denature

Annealing

Extension

C

G

T

A

0.3 0.8 0.25

0.3 0.2 0.25

0.2 0.2 0.05

0.2 0.2 0.1

45 55 45

95 (0) 95 (0) 95 (0)

58 (4) 58 (4) 58 (10)

72 (4) 72 (4) 72 (15)

62 57 –

– – 48

55 63 42

– – 52

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Table 3 Clinicopathological features of 89 PCD patients included in gene expression study. Clinical feature

n

Age at diagnosis 40-49 50-59 60-69 70+ Gender Male Female Stage at diagnosis MGUS I II III Unknown Ig class IgA IgG FLC Unknown Light chain restriction Kappa Lambda Unknown Beta-2-microglobulin <3.5 mg 3.5–5.4 mg ≥5.5 mg Unknown Albumin >3.5 g/dl ≤3.5 g/dl Unknown

3 (3%) 12 (14%) 25 (28%) 49 (55%) 52 (58%) 37 (42%) 16 (18%) 15 (17%) 9 (10%) 7 (8%) 42 (47%) 18 (20%) 42 (47%) 11 (12%) 18 (20%)

Fig. 1. mRNA levels of five candidate MDR genes at different treatment related stages of PCD. Gene expression is represented as mean fold changes from expression in normal plasma cells.

50 (56%) 35 (39%) 4 (4%) 26 (29%) 20 (22%) 19 (21%) 24 (27%) 49 (55%) 19 (21%) 21 (24%)

stage 1 and 2 patients (Fig. 2). However, these findings were not statistically significant (p > 0.05). No significant correlations were observed between the expression levels of any of the MDR genes and either B2M or albumin levels at diagnosis. Paraprotein parameters were also not significantly associated with MDR gene expression in PCM. rs1045642, rs2032582 and rs1128503 were not significantly associated with ABCB1 gene expression in this study (Fig. 3).

albumin levels at diagnosis, and immunoglobulin heavy and light chain class, were available for most patients in this study (Table 5). Table 6 shows the pairwise estimates of LD between the three SNPs in this study. There was only modest LD between each SNP, with the weakest correlations observed between rs1045642 and the other two SNPs. Cox regression analysis including existing prognostic covariates demonstrated no significant associations between rs2032582 or rs1128503 and OS in PCM (Fig. 4). As reported previously [27], rs1045642 remains significantly associated with OS (p = 0.01) (Fig. 4). However, correcting for multiple testing shows this association to be of borderline significance. Additionally, although almost all cytotoxic drugs used in PCM are now considered substrates of P-gp, there was no association between any treatment regimen and genotype at rs1045642, rs2032582 or rs1128503.

3.2. Linkage disequilibrium within ABCB1 common SNPs and associations with overall survival in PCM One hundred and thirty four PCM patients were genotyped for rs1045642, rs2032582 and rs1182503, with overall survival data spanning over 10 years from the first diagnosis. B2M and Table 4 Gene expression for plasma cell dyscrasia patients staged as MGUS, PCM or relapsed PCM. Gene

Stage

n

Mean FC

Std dev

std error

ABCB1

MGUS PCM RELAPSE MGUS PCM RELAPSE MGUS PCM RELAPSE MGUS PCM RELAPSE MGUS PCM RELAPSE

17 53 10 15 53 9 19 56 10 18 52 10 20 58 11

0.42 0.16 2.8 34.80 20.39 9.50 2.7 1.6 0.67 3.05 1.74 1.84 0.97 4.30 0.47

0.93 0.32 8.96 104.65 66.98 19.43 3.51 1.46 0.40 5.40 3.40 2.92 0.92 26.21 0.37

0.23 0.44 2.83 27.02 9.20 6.48 0.81 0.19 0.13 1.27 0.47 0.92 0.21 3.44 0.11

ABCB4

LRP1

ABCG2

ABCC1

Fig. 2. mRNA levels of five candidate MDR genes at each stage of PCM as determined by ISS staging criteria. Gene expression is represented as mean fold changes from expression in normal plasma cells. Although an association appears to exist between ABCB4 expression and ISS staging, no significant associations were seen between stage and expression for ABCB1 (p = 0.70) ABCB4 (p = 0.21) LRP1 (p = 0.16) ABCG2 (p = 0.25) or ABCC1 (p = 0.40).

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Fig. 3. ABCB1 gene expression is not significantly associated with genotype at (a) rs1045642 (b) rs2032582 or (c) rs1128503. Gene expression was measured as a fold change from expression in normal plasma cells corrected against housekeeper gene expression.

4. Discussion The capacity of tumour cells to evade the cytotoxicity of drugs remains a major cause of treatment failure in haematological malignancies. As most PCM patients eventually relapse, mechanisms such as those moderated by the ABC transporters, which generate this MDR phenotype, are of particular interest. 4.1. MDR gene expression in PCM In the current study, the mRNA expression of the genes ABCB1, ABCB4, LRP1, ABCC1 and ABCG2 was determined for 89 patients, with Table 5 Clinicopathological features of 134 PCM patients included in ABCB1 SNPs study. Clinical feature Age at diagnosis 30-39 40-49 50-59 60-69 70+ Gender Male Female Ig class IgA IgG FLC Light chain restriction Kappa Lambda Beta-2-microglobulin <3.5 mg 3.5–5.4 mg ≥5.5 mg Unknown Albumin >3.5 g/dl ≤3.5 g/dl Unknown

n 4 (3%) 17 (13%) 33 (25%) 33 (25%) 47 (35%) 79 (59%) 55 (41%) 28 (21%) 80 (60%) 26 (19%) 87 (65%) 47 (35%) 43 (32%) 17 (12%) 16 (11%) 58 (43%) 62 (46%) 27 (20%) 45 (34%)

results standardised against the same housekeeper gene (GUSB) and expressed as a fold change from expression in normal plasma cell samples. Using this approach we have demonstrated that ABCB4 (MDR3) may be a prominent contributor to MDR in PCM since this gene appears to be substantially overexpressed relative to the four other genes investigated (Fig. 1). We hypothesise that MDR3 protein expression may better correlate with initial treatment failure and mediate reduced OS in PCM via direct tumour cell efflux. However, the unexpected finding that mean expression of ABCB4 was reduced, albeit not significantly, in treated and/or relapsed PCM patients would suggest that this gene may be down regulated following treatment and therefore MDR3 may not play as important a role in subsequent treatment failure following relapse in PCM. ABCB1 was expressed at a very low level in both diagnostic and relapsed samples (Fig. 1). Given earlier evidence implicating P-gp expression as a factor affecting MDR in PCM [10,26] there are several possible explanations for this finding. One is that Pgp protein expression is mediated by post translational factors as previously reported in K562 leukemic cells [29] and that low mRNA levels may be detected despite potentially increased levels of protein expression. Unfortunately P-gp protein expression could not be determined retrospectively on this patient cohort. Another possibility is that the contribution of P-gp to MDR is primarily due to the natural intestinal expression previously documented for Pgp [7,30]. In this scenario, increased intestinal expression would ultimately reduce the bioavailability of orally administered therapeutics, resulting in a lesser cytotoxic effect on the tumour cells. This would lead to a similar systemic effect to that which has been attributed previously to tumour cell P-gp expression. Thus, Table 6 Matrix of correlation for the ABCB1 SNPs rs1045642, rs2032582 and rs1128503.

rs1045642 rs2032582 rs1128503

rs1045642

rs2032582

rs1128503

1.0 0.503609467496 0.309221819062

1.0 0.627991415051

1.0

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Fig. 4. (a) rs1045642 is the only SNP within the ABCB1 common haplotype which demonstrates an association with OS in PCM after correction for multiple testing (p = 0.01). (b) rs2032582 and (c) rs1128503 are not significantly associated with OS in PCM.

individuals with higher P-gp protein expression and/or activity would have a poorer outcome [11,13,26,27]. We noted a large degree of intra-patient variability in MDR gene expression, with some individuals demonstrating up to 400 fold increases in expression for one or more of the genes studied (data not shown). This would suggest that the clinical contribution of ABC proteins to the MDR phenotype in PCM may be considered an individualised phenomenon with considerable potential differences in individual patients throughout the course of their disease. Strategies for the detection of ABC proteins, and indeed the activity of these proteins, in patient samples would therefore be essential when using our knowledge of MDR to inform patient treatment strategies, especially as the individual ABC proteins can have an affinity for the transport of different substrates [22]. Our analysis of MDR gene expression has demonstrated no significant correlations between the five genes analysed and other prognostic factors in PCM. The generally low levels of ABCB1 mRNA detected in PCM patients may explain this. P-gp protein expression may yet demonstrate higher levels of expression and could correlate more significantly with other prognostic factors in PCM [31–33]. We also wished to determine if ABCB1 SNPs generated a post transcriptional effect, altering the mRNA levels of ABCB1 in PCM patients. rs1045642, rs2032582 and rs1128503 were not significantly associated with ABCB1 gene expression in this study (Fig. 3).

This would be in concordance with earlier evidence showing that rs1045642 is involved in the co-translational folding of P-gp [22,25] and would therefore not be expected to have an impact on the transcriptional activity of ABCB1. 4.2. Linkage disequilibrium analysis of common ABCB1 SNPs and associations with overall survival in PCM Following our previous study of the impact of rs1045642 on OS in PCM [27], we investigated two further SNPs within ABCB1 which are thought to form a common haplotype and may also demonstrate similar associations with OS. Correlation analysis demonstrated low levels of LD between rs1045642, rs2032582 and rs1128503, with the weakest association seen between rs1045642 and the other SNPs. This data is in contrast to previous studies where higher r2 coefficients were demonstrated for these SNPs [25,28]. However, it is acknowledged that this lack of LD may reflect the patient cohorts studied. Cox regression analysis demonstrated no associations between rs2032582 and rs1128503, and only a borderline association with rs1045642, and OS in PCM. As rs1045642 now seems to be fairly commonly accepted as a retrospective model of P-gp functionality [34], we can reasonably conclude that alterations to P-gp function in different patients may be an independent factor affecting outcomes in PCM. We may also hypothesise that, as rs1045642 is the only

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SNP to demonstrate an association with OS, it is indeed the main contributor to reductions in P-gp function as previously reported [25]. However, it is also acknowledged that the potential effects of these SNPs on P-gp function are as yet undetermined in PCM and that larger patient cohorts need to be studied for a more statistically robust analysis of associations with survival. Based on our current and previous findings [18,27], and those by other groups [25,35], future studies of these MDR proteins should include additional parameters. Although gene expression as determined in previous studies is a potentially useful measure of MDR, protein expression and indeed functionality for each of these proteins should be investigated as this represents their functional biological contribution to MDR within the human model. Although we have confirmed that the clinical effects of SNPs within the ABCB1 common haplotype seem to be mediated primarily by rs1045642 [25], there are many more SNPs within this gene, as yet not widely studied. Indeed it is possible that a more prominent contributor to P-gp function and hence OS may yet exist within ABCB1 that could even demonstrate a degree of LD with the SNPs investigated within this study. A total analysis of the genomic instability at 7q21 and its effect on OS would therefore be important in order to elucidate the full clinical contribution of ABCB1 SNPs in MDR. To the best of our knowledge this is the first study to investigate gene expression for these five most prominent candidate MDR proteins in PCM and also the first study to consider the clinical impact of these three SNPs in PCM. In this study, we highlight that ABCB4 may mediate a prominent contribution to MDR in PCM. We have also elucidated that rs1045642 is the only contributor of the SNPs studied to OS in PCM, and may therefore be solely responsible for the reductions in P-gp function demonstrated previously. A further study is also warranted to determine if any SNPs within ABCB4 can alter the activity of the protein and if these SNPs can ultimately affect the clinical outcome of PCM patients.

Role of the funding source This work was supported by the N Ireland Department of Education and Learning (DELNI) and the Belfast City Hospital Haematology Research Trust Fund.

Conflicts of interest The authors confirm no conflicts of interest with this study. Acknowledgements Sincere thanks are given to the patients included in this study and to the clinical staff involved in the bone marrow aspiration. Contributions. The study design was conceived and designed by the authors H.D.A., M.A.C. and S.D. S.D. also performed the data acquisition, and interpretation with contributions from L.F., M.B.D. and P.J.K. Data analysis was performed by N.O. This manuscript was drafted by S.D. and was critically reviewed by A.J.B., M.A.C. and H.D.A. before final approval was obtained from all authors. References [1] Sanford S, Deborshi R, Schindler M. Cell biological mechanisms of multidrug resistance in tumors. Proc Natl Acad Sci 1994;91:3497–504. [2] Fletcher JI, Haber M, Henderson MJ, Norris MD. ABC transporters in cancer: more than just drug efflux pumps. Nat Rev Cancer 2010;10(February (2)):147–56.

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