Med Oncol (2014) 31:279 DOI 10.1007/s12032-014-0279-y

ORIGINAL PAPER

ABCB1 haplotypes but not individual SNPs predict for optimal response/failure in Egyptian patients with chronic-phase chronic myeloid leukemia receiving imatinib mesylate Mohamed A. M. Ali • Walaa Ali Elsalakawy

Received: 15 September 2014 / Accepted: 30 September 2014 / Published online: 11 October 2014 Ó Springer Science+Business Media New York 2014

Abstract Imatinib mesylate (IM) has so far been the standard of care for treating chronic myeloid leukemia (CML), but the initial striking efficacy of this drug has been overshadowed by the development of clinical resistance, which may in part be caused by pharmacogenetic variability. The ATP-binding cassette, subfamily B, member 1 (ABCB1) gene codes for P-glycoprotein (P-gp), a membrane-bound efflux transporter known to affect the pharmacokinetics of many drugs. IM is a substrate of the P-gp-mediated efflux. ABCB1 single nucleotide polymorphisms (SNPs) have been reported as modulators of ABCB1-mediated transport, affecting IM’s bioavailability and consequently the treatment outcome of IM therapy. We aimed to examine the association between ABCB1 SNPs and the likelihood of achieving optimal response in IMtreated CML patients. Three ABCB1 SNPs (C1236T, G2677T, and C3435T) were genotyped in 100 Egyptian patients with CML undergoing IM therapy using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) assay. The optimal response rate did not differ significantly between C1236T, G2677T, or C3435T genotypes (P [ 0.05). Optimal response rate was significantly different among patients with the CGC, TTT, TGC, CGT, TGT, CTC, CTT, and TTC haplotypes (P = 0.023). The 1236T-2677G-3435T haplotype was significantly associated with lower probability of achieving M. A. M. Ali (&) Department of Biochemistry, Faculty of Science, Ain Shams University, Abbassia, Cairo 11566, Egypt e-mail: [email protected] W. A. Elsalakawy Clinical Hematology and Bone Marrow Transplant Unit, Internal Medicine Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt

optimal response (P = 0.001). ABCB1 SNPs haplotype analysis should be taken into account in an attempt to get clearer insights into who is likely to respond optimally to IM for identifying CML patients who may not respond optimally to standard-dose IM therapy and potentially need an individualized therapeutic approach. Keywords Chronic myeloid leukemia  Imatinib mesylate  Optimal response  ATP-binding cassette, subfamily B, member 1 (ABCB1)  Single nucleotide polymorphisms

Introduction Chronic myeloid leukemia (CML) is a neoplastic disorder of a pluripotent hematopoietic stem cell, characterized by a reciprocal chromosomal translocation t (9; 22) (q34; q11) that results in a shortened chromosome 22 called the Philadelphia (Ph0 ) chromosome with the breakpoint cluster region–abelson oncogene 1 (BCR-ABL1) oncogenic fusion gene, which encodes the constitutively active BCR-ABL1 fusion tyrosine kinase that mediates cellular transformation and leukemogenic effects [1]. Imatinib mesylate (IM) is a selective inhibitor of the BCR-ABL1 tyrosine kinase. Because of its excellent safety and important therapeutic benefit for patients with CML, IM was approved by the Food and Drug Administration for the treatment of CML and has become the standard of care for the treatment of CML [2]. However, despite high rates of hematologic and cytogenetic responses, primary refractoriness or acquired resistance after initial response to IM is observed in a significant proportion of patients [3]. Research in CML has since focused on finding biological predictors of response allowing for treatment

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optimization. Several determinants were known to be associated with the pharmacokinetics of IM, affecting the systemic levels or intracellular concentrations of IM [4]. The human adenosine triphosphate (ATP)-binding cassette, subfamily B, member 1 (ABCB1) gene codes for P-glycoprotein (P-gp), a membrane-bound ATP-dependent efflux transporter protein. The level of protein expression and the functional integrity of P-gp affect its pharmacokinetic interaction with therapeutically administered drugs. Therefore, it has a significant impact on therapeutic efficacy and toxicity of drug treatment. IM has been reported to be a substrate of the P-gp-mediated efflux. Accordingly, P-gp was suggested as a potential determinant of intracellular concentration of IM through ATP-driven efflux pathway [5]. ABCB1 is a highly polymorphic gene with 66 single nucleotide polymorphisms (SNPs) have been identified in the coding sequence so far [6]. Among these SNPs, the most widely investigated for their clinical implications are the 1236C[T, 2677G[T/A, and 3435C[T SNPs located in exons 12, 21, and 26, respectively [7, 8]. Observed inter-patient pharmacokinetic variability may be due to patients’ genetics. ABCB1 SNPs that have the potential to alter ABCB1 gene expression as well as P-gp expression and function would be predicted to be associated with changes in both the pharmacokinetics and pharmacodynamics of several P-gp drug substrates [9–11]. Therefore, ABCB1 SNPs could affect IM’s bioavailability and consequently the treatment outcome of IM therapy which might explain at least in part variable responses to IM [12, 13]. Furthermore, differences in the frequency of ABCB1 alleles have been described among various ethnic populations, suggesting that there may be ethnic differences in the disposition and pharmacologic effects of the drugs that are substrates for P-gp [14]. To date, despite numerous groups attempting to demonstrate the impact of ABCB1 variants on IM efficacy in CML patients, the results remain inconsistent rather than conclusive [15–23]. In an attempt to decrease the uncertainty of the pharmacogenomic effect of ABCB1 genetic variants on response to IM and to provide more conclusive evidence regarding the clinical relevance of this pharmacogenomic association, we explored whether SNPs in the ABCB1 are associated with the optimal response or primary failure to IM in Egyptian patients with CML.

Patients and methods

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Hematology unit, Faculty of Medicine, Ain Shams University, Cairo, Egypt, were retrospectively enrolled in this pharmacogenetic study. Inclusion criteria included morphologic and cytogenetic evidence of Ph?-CML in early CP (defined as \12 months from diagnosis), CP-CML was defined as the presence of \15 % blasts and \30 % blasts plus promyelocytes in peripheral blood or bone marrow,\20 % basophils in peripheral blood, with no extramedullary involvement. Exclusion criteria included previous treatment for CML (busulfan, hydroxyurea, IFN-a, or Ara-C). Patients received standard dose (400 mg) of IM orally once a day. CML therapies other than IM were prohibited on-study. The study protocol was approved by the scientific ethical committee of Faculty of Medicine, Ain Shams University. A written informed consent was obtained from all the enrolled patients prior to inclusion into the study in accordance with the Declaration of Helsinki. Definition of response criteria The response to IM was defined as ‘‘optimal’’ or ‘‘failure’’. Failures were distinguished as either primary (failure to achieve a given response at a given time) or secondary (loss of response) [24]. Molecular response (MR) was defined according to the International Scale (IS) as the ratio of BCR-ABL1 transcripts to ABL1 transcripts, and it was expressed and reported as BCRABL1 % on a log scale, where 10, 1, 0.1, 0.01, 0.0032, and 0.001 % correspond to a decrease of 1, 2, 3, 4, 4.5, and 5 logs, respectively, below a standardized baseline [25]. MR was categorized as major molecular response (MMR; MR3.0 = detectable disease with B0.1 % BCR-ABL1 IS); MR4.0 = detectable disease with\0.01 % BCR-ABL1 IS; MR4.5 = detectable disease with\0.0032 % BCR-ABL1 IS; MR5 = detectable disease with \0.001 % BCR-ABL1 IS [26]. Optimal response was defined as BCR-ABL1 transcript levels B10 % at 3 months, \1 % at 6 months, and B0.1 % from 12 months onward, whereas failure was defined as [10 % at 6 months and [1 % from 12 months onward [24]. Evaluation of response to IM Monitoring the response to IM was performed using a standardized real-time quantitative polymerase chain reaction (RQ-PCR) for the assessment of BCR-ABL1 transcript levels every 3 months until a MMR or better is achieved, then every 3–6 months according to the recommendations of the European LeukemiaNet [24].

Study cohort and treatment protocol ABCB1 genotyping A total of 100 newly diagnosed Egyptian patients with Philadelphia chromosome-positive (Ph?) chronic-phase (CP)CML who were referred to the outpatient clinics of the

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Three SNPs in the ABCB1 gene (National center for biotechnology information reference sequence gene; NCBI

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Table 1 Primer sequences and restriction endonucleases used for the analysis of ABCB1 SNPs by PCR-RFLP assay SNP

Position

ref SNP ID

Amino acid change

Primer sequence (50 ? 30 )

PCR Product length (bp)

Restriction enzyme

Fragments length (bp)

1236C[T

Exon 12

rs1128503

Synonymous (Gly412Gly)

FP: TATCCTGTGTCTGTGAATTGCC

366

HaeIII

CC: 35, 62, 269

RP: CCTGACTCACCACACCAATG

TT: 97, 269 CT: 35, 62, 97, 269

2677G[T

3435C[T

Exon 21

Exon 26

rs2032582

rs1045642

Non-synonymous (Ala893Ser)

Synonymous (Ile1145Ile)

FP: TGCAGGCTATAGGTTCCAGG

224

BanI

GG: 26, 198

RP: TTTAGTTTGACTCACCTTCCCG

TT: 224

FP: CAAAGAAATAAAGCGACTGAATG

GT: 26, 198, 224 CC: 63, 138

198

DpnII

RP: TTATTAGGCAGTGACTCGATGAA

TT: 201 CT: 63, 138, 201

SNP single nucleotide polymorphism, FP forward primer, RP reverse primer, PCR polymerase chain reaction, bp base pair

RefSeq gene: NG_011513.1) at nucleotides 1236C[T, 2677G[T, and 3435C[T were genotyped using polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP) assay. The primer sequences used for the amplification of the DNA fragments containing the ABCB1 polymorphic sites, restriction endonucleases, and RFLP fragment sizes were adapted from previously published articles (1236C[T and 2677G[T [27]; 3435C[T [28]; Table 1). Briefly, venous blood samples were collected in ethylenediaminetetraacetic acid (EDTA)—vacutainer tubes by venipuncture. Genomic DNA was extracted from peripheral blood leukocytes using the QIAampÒ DNA Blood Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. PCRs were carried out in a total volume of 25 lL, containing 15 mM Tris– HCl?50 mM KCl (Gene Amp 10X PCR Gold Buffer), 1.5 mM MgCl2 (Gene Amp 25 mM MgCl2), 400 lM of each dNTP (Gene Amp 10 mM dNTP Blend), 1 U Taq DNA polymerase (AmpliTaq Gold 5 U/lL DNA polymerase; Applied Biosystems, Foster City, CA, USA), 0.5 lM of each of the primers (Sigma-Aldrich, St. Louis, MO, USA), and 100 ng of genomic DNA. The thermal cycling conditions were as follows: initial denaturation at 94 °C for 5 min followed by 35 amplification cycles of denaturation at 94 °C for 30 s, annealing at 60 °C (1236C[T and 2677G[T), 58 °C (3435C[T) for 30 s, and extension at 72 °C for 30 s followed by terminal extension at 72 °C for 10 min. The PCR products were purified using QIAquick PCR Purification Kit (Qiagen, Hilden, Germany). The purified PCR products were digested with the corresponding restriction enzyme (New England Biolabs, Ipswich, MA, USA) at 37 °C for 1 h according to the

manufacturer’s protocol. HaeIII, BanI, and DpnII were used to analyze 1236C[T, 2677G[T, and 3435C[T, respectively. DNA fragments generated after restriction enzyme digestion were electrophoresed on a 10 % polyacrylamide gel (Bio-Rad Laboratories, Hercules, CA, USA) using GeneRuler Ultra Low Range DNA Ladder (Thermo Scientific, Waltham, MA, USA) as a size marker, visualized by staining the gels with ethidium bromide, followed by destaining with water, and finally photographed under ultraviolet illumination using a digital camera. Statistical analyses Continuous variables were expressed as mean ± standard deviation (SD) and compared using independent Student’s t test. Categorical variables were expressed as the numbers of patients and percentages in parentheses and compared using the Pearson chi-square test. For all statistical tests, P values were two-sided, and a P value of \0.05 was considered statistically significant. Data statistical analyses were conducted using the statistical package for the social sciences (SPSS software 20; SPSS Inc., Chicago, IL, USA) [29]. Genotype, allele, and haplotype frequencies were estimated and tested for correlation with the rates of optimal response. Genotype frequencies at each ABCB1 gene locus were compared with the frequencies expected by the Hardy–Weinberg equilibrium (HWE) using a chi-square goodness of fit test [30]. Pairwise linkage disequilibrium (LD) between the three ABCB1 gene loci was assessed by estimating the coefficients of LD (D0 , standardized disequilibrium; r2, square of the correlation coefficient) [31].

123

0.940

0.332

32.22 32.5 T allele

32.73

25.56

67.78 67.27 C allele

31.82 29

67.5

T allele

32.22

74.44

36.36

71

68.18

34.5 T allele

G allele

67.78 63.64 C allele

65.5

Primary failure (n = 45) Optimal response (n = 55) Patients (n = 100)

The study cohort consisted of a total of 100 patients with CML, of which 49 % were male and 51 % were female, with a mean age at clinical diagnosis of 43.56 ± 10.74 years (range 23–71 years). Patients were classified according to MR criteria into two groups: optimal response (55 patients) and primary failure (45 patients). Among those 55 patients who had optimal response, 24 (43.64 %) were male and 31 (56.36 %) were female, with a mean age at diagnosis of 42.49 ± 11.46 years. On the other hand, of the 45 patients with primary failure, 25 patients (55.56 %) were male and 20 patients (44.44 %) were female, with a mean age at diagnosis of 44.87 ± 9.79 years. Patients of both optimal response and primary failure groups showed no significant difference regarding gender (P = 0.236) and age at diagnosis (P = 0.273).

0.505 4/55 (7.27 %) 9 (9 %)

5/45 (11.11 %)

0.387 28/55 (50.91 %) 47 (47 %)

19/45 (42.22 %)

0.627 23/55 (41.82 %) 44 (44 %)

21/45 (46.67 %)

0.904

0.15 5/55 (9.1 %) 6 (6 %)

1/45 (2.22 %)

25/55 (45.45 %) 46 (46 %)

21/45 (46.67 %)

0.573 25/55 (45.45 %) 48 (48 %)

23/45 (51.11 %)

0.732 0.657

0.55 19/45 (42.22 %) 20/55 (36.36 %)

30/55 (54.55 %) 5/55 (9.09 %)

39 (39 %)

53 (53 %) 8 (8 %)

T/T

C/T

C/C 3435C[T

T/T

G/T

G/G

C/C 1236C[T

2677G[T

Primary failure (n = 45) Optimal response (n = 55) Patients (n = 100)

23/45 (51.11 %) 3/45 (6.67 %)

P value

The distribution of the genotypes and alleles of ABCB1 SNPs is summarized in Table 2, which showed that the genotype and allele frequencies of C1236T, G2677T, or C3435T SNPs were not significantly different between patients with or without optimal response. The results of the PCR-RFLP assay are shown in Fig. 1, revealing the DNA fragments pattern generated after restriction enzymes digestion for each SNP on ethidium bromide-stained 10 % polyacrylamide gel. The three ABCB1 variants (1236C[T, 2677G[T, and 3435C[T) were organized in eight haplotypes (CGC, TTT, TGC, CGT, TGT, CTC, CTT, and TTC) in our cohort. The frequency of the CGC, TTT, TGC, CGT, CTC, CTT, and TTC haplotypes did not differ significantly between patients with or without optimal response (P [ 0.05). Unexpectedly, the frequency of the TGT haplotype was significantly higher in patients with primary failure (8.89 %) than in those with optimal response (0 %; P = 0.001; Table 3). Effect of ABCB1 genotypes and haplotypes on optimal response to IM

C/T T/T

Allele frequency (%) Allele

Baseline demographic characteristics of the patients

Outcome of IM therapy according to ABCB1 genotypes

Genotype

Genotype distribution n (%)

All genetic analyses were performed using Haploview version 3.32 (Broad Institute, Cambridge, MA, USA) [32].

Results

Locus

Table 2 Genotype distribution and allele frequency of ABCB1 SNPs in IM-treated CP-CML patients of both optimal response and primary failure groups

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0.540

P value

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The influence of ABCB1 genotypes and haplotypes on optimal response rate is presented in Table 4. The optimal response rate did not differ significantly between patients with 1236CC, 1236CT, or 1236TT genotypes (CC vs CT; P = 0.613, CC vs TT; P = 0.562, CT vs TT; P = 0.753).

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(P [ 0.05). Interestingly, 1236C[T, 2677G[T, and 3435C[T SNPs showed a significant LD to each other.

Discussion

Fig. 1 PCR-RFLP assay for the detection of the ABCB1 SNPs. DNA fragments generated after restriction enzymes digestion were separated on ethidium bromide-stained 10 % polyacrylamide gel and sized using GeneRuler ultra low range: 10–300 bp DNA marker (M). 1236C[T SNP genotypes: lane 1 = CC: 35, 62, 269 bp; lane 2 = CT: 35, 62, 97, 269 bp; lane 3 = TT: 97, 269 bp. 2677G[T SNP genotypes: lane 4 = GG: 26, 198 bp; lane 5 = GT: 26, 198, 224 bp; lane 6 = TT: 224 bp. 3435C[T SNP genotypes: lane 7 = CC: 63, 138 bp; lane 8 = CT: 63, 138, 201 bp; lane 9 = TT: 201 bp

In addition, the optimal response rate was slightly but not significantly higher in patients with 2677TT genotype than in those with 2677GT or 2677GG genotype (GG vs TT; P = 0.146, GT vs TT; P = 0.176). On the other hand, the optimal response rate did not differ significantly between patients with 2677GG and 2677GT genotypes (P = 0.826). Moreover, the optimal response rate did not differ significantly between patients with 3435CC, 3435CT, or 3435TT genotypes (CC vs CT; P = 0.483, CC vs TT; P = 0.669, CT vs TT; P = 0.401). We further investigated whether the haplotypes derived from the tested ABCB1 polymorphisms were associated with optimal response to IM. The optimal response rate was significantly different among patients with the CGC, TTT, TGC, CGT, TGT, CTC, CTT, and TTC haplotypes (P = 0.023). Surprisingly, the optimal response rate was significantly lower in patients with the TGT haplotype than in those with the other haplotypes (P = 0.001), indicating that the TGT haplotype was significantly associated with lower probability of achieving optimal response (Table 4). As shown in Table 5, the distribution of the observed genotypes for 1236C[T, 2677G[T, and 3435C[T SNPs was not significantly different from the expected distribution according to HWE, indicating that the genotypic distribution of these SNPs did not deviate significantly from HWE expectations

The spectrum of therapeutic options for CML patients has recently been enriched by second-generation tyrosine kinase inhibitors (TKIs) that are more potent and/or more selective than IM in BCR-ABL1 inhibition. Chemically optimized second-generation TKIs, such as dasatinib and nilotinib, have been approved in case of resistance or intolerance to IM [33, 34] as well as alternative treatment options instead of IM in newly diagnosed CML patients [35–38]. Paradoxically, the availability of multiple therapeutic options is not paralleled by the availability of biological predictors of outcome enabling identification, at the time of diagnosis, of those patients who are more likely to benefit from nilotinib or dasatinib rather than from IM—hence, there is still a need for CML treatment optimization. Therefore, a refined stratification of patients in terms of likelihood of achieving optimal response would be the necessary starting point. Pharmacogenetics has proven to be a potential source of biomarkers given the known influence of polymorphisms in key genes encoding drug transporters on intracellular drug delivery and, therefore, on the effectiveness of the drugs. It is well known that SNPs in the ABCB1 gene might alter P-gp expression and activity toward specific drugs, thereby influencing their therapeutic efficacy. In the current study, we have demonstrated that the optimal response rate to IM did not differ significantly between C1236T, G2677T, or C3435T genotypes. Our findings indicated that ABCB1 SNPs do not predict for optimal response/primary failure in patients with CP-CML receiving IM. Several pharmacogenetic association studies have focused on the effect of ABCB1 SNPs on the therapeutic efficacy of IM in CML patients, but they are not totally comparable since they all suffered from the limitation of being conducted in heterogeneous populations including patients at different phases of disease, not all treated with IM first line, having limited sample sizes and of having different therapeutic end points as well as different response criteria definitions [15–23]. In particular, the role of three variants—C1236T, C3435T, and G2677T/A—has been extensively studied, with strikingly contrasting results. Dulucq et al. [15] have investigated the association of ABCB1 SNPs at positions 1236, 2677, and 3435 with MMR after 12 months of standard-dose IM therapy in CML French patients and observed that patients with the homozygous T allele at position 1236 were reported to have higher MMR rates

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279 Page 6 of 10 Table 3 Haplotype frequency of ABCB1 SNPs in IM-treated CP-CML patients of both optimal response and primary failure groups

* A statistical significant difference

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Haplotype

1236C[T

2677G[T 3435C[T

Patients (n = 100)

Optimal response (n = 55)

P value Primary failure (n = 45)

CGC

C

G

C

55.5

51.8

60

0.247

TTT

T

T

T

21

22.7

18.9

0.507

TGC CGT

T C

G G

C T

6.5 4.5

9.1 5.5

3.3 3.3

0.1 0.472

TGT

T

G

T

4

0

8.9

0.001*

CTC

C

T

C

3.5

3.6

3.3

0.908

CTT

C

T

T

2.5

3.6

1.1

0.255

TTC

T

T

C

2.5

3.6

1.1

0.255

than those with CC and CT genotypes. Also, patients with 2677TT/TA genotype responded significantly better regarding MMR than those with 2677GG/GT/GA. Contrary to expectations, in a subsequent study, however, Dulucq et al. [16] could not confirm these results in a larger patient cohort of French patients with CML. For C1236T, G2677T/A, and C3435T SNPs, no significant difference was observed in genotype frequencies between patients with or without MMR at 12 months in IM-treated CML patients. Such results highlight the importance of studying a large cohort of homogeneous CML patients in order to draw conclusions on the real impact of ABCB1 genotypes on IM response. Similarly, Kim et al. [17] failed to identify an association between the ABCB1 genotype and cytogenetic/molecular response to IM in Canadian patients with CML. Likewise, Takahashi et al. [18] could not identify an association between any of the ABCB1 gene polymorphisms (C1236T, C3435T, and G2677T/A) and MMR achievement in Japanese patients with CP-CML. On the contrary, a report by Deenik et al. [19] in a cohort of Dutch patients with early CP-CML receiving high-dose IM found that the incidence of MMR and complete molecular response (CMR) was higher in patients with 1236CC genotype than in those with 1236CT/TT genotype. Also, patients homozygous for 3435T and 2677T showed lower probabilities to obtain MMR and CMR. Additionally, Ni et al. [20] reported that the distribution of ABCB1 1236, 2677, or 3435 genotypes was significantly different between CP-CML Chinese patients with or without response to IM. They suggested that the resistance rate was higher in patients homozygous for the 1236T allele when compared to those with CT/CC genotype. A higher complete cytogenetic response (CCyR) rate was observed in patients with 2677AG/AT/AA genotype when compared to those with 2677TT/GT/GG genotype. Also, patients with 2677GT genotype revealed a higher CCyR rate when compared to those with 2677TT/AT/AA/AG/GG genotype. Moreover, patients with 3435TT/CT genotype

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Haplotype frequency (%)

showed a higher resistance rate in comparison to patients with 3435CC genotype. Furthermore, Maffioli et al. [21] have found in IM-treated Caucasian patients with CP-CML that the presence of the T allele at the 2677 locus (GT/TT) was found to confer protection from primary failure to IM, whereas the 3435CC genotype was significantly associated with higher probability of primary failure. A recent study by Angelini et al. [22] has observed nearly significant associations between the presence of 3435CC genotype and CMR achievement in a cohort (Caucasian, Asian and nonwhite, and non-Asian) of CML patients receiving IM. In a more recent study, Vine et al. [23] reported that ABCB1 genotypes at position 2677 and 3435 did not predict treatment failure and that IM trough levels, but not the ABCB1 SNPs could determine IM failure in IM-treated CML Caucasian patients. Data of the present study are quite consistent with those of Dulucq et al. [16], Kim et al. [17], Takahashi et al. [18], and Vine et al. [23] who did not find significant association between ABCB1 SNPs and response to IM in CML patients. On the other hand, our findings differ from those of Dulucq et al. [15], Deenik et al. [19], Ni et al. [20], Maffioli et al. [21], and Angelini et al. [22] who suggested that ABCB1 polymorphisms might be associated with response and/or resistance in IM-treated CML patients. These discrepancies could be explained, at least in some cases, by different study sample size, disease phase, treatment protocols, IM dosage, and response criteria. Alternatively, the limited number of studies investigated the effect of variants and/or the existence of other unknown variants with a pharmacogenomic effect that are in LD with the examined ones. Another possibility is that the results are not always supported by the expected functional effect of a given polymorphism. It therefore seems plausible that pharmacokinetic resistance due to a variety of mechanisms affecting IM plasma levels rather than tumor cell resistance due to P-gp activity may be suggested as an alternative explanation for our results.

* A statistical significant difference

51.4

5/8 (62.5 %)

T/T (n = 8)

Optimal response (n = 55)

30/53 (56.6 %)

C/T (n = 53)

CGC

20/39 (51.28 %)

C/C (n = 39)

1236C[T

Haplotype

Optimal response (n = 55)

Locus

59.5

TTT 76.9

TGC 66.7

CGT 0

TGT

GG versus GT: 0.826

57.1

CTC

GT versus TT: 0.176

5/6 (83.33 %)

T/T (n = 6)

CT versus TT: 0.753

25/46 (54.35 %)

G/T (n = 46)

P value

GG versus TT: 0.146

25/48 (52.08 %)

G/G (n = 48)

2677G[T

CC versus TT: 0.562

CC versus CT: 0.613

P value

Table 4 Influence of ABCB1 genotypes and haplotypes on optimal response to IM in 100 CP-CML patients

80

CTT

23/44 (52.27 %)

C/C (n = 44)

3435C[T

80

TTC

28/47 (59.57 %)

C/T (n = 47)

CT versus TT: 0.401

CC versus TT: 0.669

CC versus CT: 0.483

TTC versus others: 0.255

CTT versus others: 0.255

CTC versus others: 0.908

TGT versus others: 0.001*

CGT versus others: 0.472

TGC versus others: 0.1

TTT versus others: 0.507

CGC versus others: 0.247

P value

4/9 (44.44 %)

T/T (n = 9)

P value

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Table 5 Hardy–Weinberg equilibrium and pairwise linkage disequilibrium for ABCB1 SNPs in 100 IM-treated CP-CML patients Locus

Genotype

Observed frequency (%)

Expected frequency (%)

P value

1236C[T

C/C

39

42.9

0.141

C/T

53

45.2

2677G[T

3435C[T

Locus 1

T/T

8

11.9

G/G

48

50.41

G/T

46

41.18

T/T

6

8.41

C/C C/T

44 47

45.56 43.88

T/T

9

10.56

Locus 2

D0

r2

0.38

0.669

P value

1236C[T

2677G[T

0.695

0.375

\0.001

1236C[T

3435C[T

0.685

0.429

\0.001

2677G[T

3435C[T

0.715

0.434

\0.001

Here, we reported that the optimal response rate was significantly different among patients with the different haplotypes. The key finding of the current study is that the optimal response rate was significantly lower in patients with the TGT haplotype than in those with the other haplotypes, indicating that patients who carried the TGT haplotype were more likely to develop primary failure as compared to carriers of the other haplotypes. Thus, lack of significant association in the ABCB1 genotypes analysis does not totally exclude a role, albeit minor, for ABCB1 genetic variants in the response to IM. This observation suggested that haplotype analysis of ABCB1 SNPs in CML patients treated with IM may be used as a basis for studies on the relationship between ABCB1 genotypes and IM efficacy and may provide some insight into who is likely to respond optimally to standarddose IM. Previously, Dulucq et al. [15] found that the 1236C2677G-3435C haplotype was significantly linked to less frequent MMR. In addition, Maffioli et al. [21] have observed a significant association between the 1236T2677G-3435C haplotype and primary failure. Furthermore, Angelini et al. [22] have recently suggested that ABCB1 haplotypes were not associated with IM response. We studied only three SNPs in the coding region of the ABCB1 gene. However, genotype and/or haplotype variants not only in the coding region but also in the promoter region of the ABCB1 gene may be important for interindividual differences in P-gp expression. Furthermore, several reports have shown different pharmacokinetic and pharmacodynamic profiles associated with ethnic origin,

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genotypic and allelic frequencies, of several drugs operating as P-gp substrates [39]. In conclusion, an approach targeting other SNPs of the ABCB1 gene besides those already analyzed in large pharmacogenomic studies will be necessary to more comprehensively estimate the effect from the analysis of both individual SNPs and haplotypes in order to provide more conclusive evidence on the role of this genetic marker in the response to IM. The results of these studies could be useful for early identification of CML patients who may not respond optimally to standard-dose IM therapy and need an individualized therapeutic approach. Therefore, haplotype analysis should be taken into account in an attempt to get clearer insights into how IM treatment can be tailored to each patient’s genetics, with the aim of enhancing efficacy in terms of achievement of optimal response. Focusing on studying the genes whose products are essential for IM levels and action may identify potential pharmacokinetic and/or pharmacodynamic markers of IM response. These markers, complementing existing ones such as drug plasma concentrations, could allow the prediction, for each individual, of a lack of efficacy, leading first to pharmacogenetically guided prospective clinical trials and ultimately to personalized treatment. Conflict of interest of interest.

The authors declare that they have no conflict

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