Abstract
Background
Imatinib has so far been the first-choice treatment in chronic myeloid leukemia (CML) with excellent results. However, only a proportion of patients achieve major molecular response. Hence, the need to find whether there are some factors that affect the response to treatment is essential. This study aimed to investigate the allele and genotype frequencies of single nucleotide polymorphisms (SNPs) of SLCO1B3 (T334G) and CYP3A5*3 in CML patients undergoing imatinib treatment and to determine whether SNPs of these two genes could predict the response of imatinib therapy in CML patients.
Subjects and methods
We investigated SLCO1B3 (T334G) and CYP3A5*3 polymorphisms by Polymerase Chain Reaction-restriction fragment length polymorphism in 86 Philadelphia positive newly diagnosed Egyptian CML patients (78 patients in chronic phase and 8 patients in accelerated phase). All patients received imatinib therapy and were followed for at least one and half years. The response to imatinib therapy was evaluated by recording the hematological response, cytogenetic response, and molecular response according to the European Leukemia Net criteria.
Results
This study included 86 Philadelphia positive newly diagnosed CML patients, 78 in the early chronic phase and 8 in the accelerated phase. In the chronic phase patients, no association between SLCO1B3 (T334G) exon 3 polymorphism and response to imatinib therapy was detected (P = 0.938) while CYP3A5*3 gene polymorphism was associated with inferior outcome (P < 0.001). In the group of accelerated phase patients, the SLCO1B3 polymorphic variants (TG) and (GG) were detected equally with none of the patients in this group having the homozygous wild form (TT). The homozygous state for the CYP3A5*3 allele was the most frequent (50%) and the homozygous state for the CYP3A5*1 allele was the least frequent (12.5%) in this group.
Conclusion
CYP3A5*3 polymorphism was associated with imatinib efficacy while the SNP SLCO1B3 (T334G) was not associated with the response to imatinib treatment in Egyptian patients with CML in chronic phase. These results prompt us to explore the effect of CYP3A5*3 in CML patients taking imatinib in a larger scale study.
Introduction
Chronic myeloid leukemia (CML), a myeloproliferative neoplasm, comprises 14% of all leukemias. The synthetic tyrosine kinase inhibitor imatinib mesylate, also known as Glivec or Gleevec, has been well documented as first line treatment for CML.Citation1
Despite the excellent efficacy of imatinib, cases of treatment failure or suboptimal response have been reported. Previous studies identified cellular mechanisms of resistance to imatinib such as gene mutations in the kinase domain of BCR-ABL1, BCR-ABL1 gene amplification, over expression of Src-related kinases, drug efflux mediated by the P-glycoprotein which is encoded by the MDR1 gene.Citation2
Another hypothesis to explain variable responses to imatinib therapy lies in pharmacokinetic variability. Imatinib is well absorbed after oral administration with a bioavailability exceeding 90%. It is extensively metabolized by the hepatic cytochrome P450 enzyme system. There is evidence that CYP3A accounts for most of the metabolism of imatinib to the active metabolite CGP74588.Citation3
Polymorphisms or nucleotide diversity occurring in the genes encoding drug metabolizing enzymes, transporters and target molecules may affect the pharmacokinetic and pharmacodynamics of respective drugs.Citation4
Organic anion-transporting polypeptides (OATPs) encoded by SLCO (organic anion transporters of solute carrier family) genes, mediate the uptake of transport proteins with broad substrate specificity. OATP/SLCO1B3 (formerly termed OATP8) is expressed in the liver. Hepatocellular uptake of a large number of organic anions from the blood in humans is mediated by OATP/SLCO1B1, OATP/SLCO2B1, and OATP/SLCO1B3 in the basolateral membrane.Citation5
Hepatocellular uptake transporters are involved in the hepatobiliary elimination of endogenous and xenobiotic substances. Mutations in genes encoding these uptake transporters may be key determinants of inter-individual variability in hepatobiliary elimination and drug disposition.Citation6
SLCO1B3 (solute carrier organic anion transporter family member 1B3, organic anion transporting polypeptide 1B3, OATP1B3) is responsible for the uptake of imatinib into hepatocytes.Citation7 Although it was not assayed in leucocytes, SLCO1B3 has an impact on the intracellular concentration of imatinib inside leucocytes.Citation8 SLCO1B3 has two major single nucleotide polymorphisms (SNPs) in exon 3 (334T > G) and exon 6 (699 G > A), which are in complete linkage disequilibrium, resulting in a serine to alanine change at amino acid 112 (S112A), and methionine to isoleucine change at amino acid 233 (M233I), respectively.Citation9
CYP3A5 is a member of the CYP3A gene family which metabolizes 50% of therapeutic drugs and steroid hormones and is one of the main imatinib-metabolizing enzymes into a still active metabolite.Citation10,Citation11 CYP3A5*3 exhibit inter-individual differences in CYP3A5 expression. CYP3A5*3 polymorphic variant in the intron 3 of the CYP3A5 gene can reduce the expression of CYP3A5 to less than 1/1000 of that found in carriers of the wild type allele (CYP3A5*1) through creation of a cryptic splice site and encoding an abnormally spliced mRNA with a premature stop codon.Citation12
This study aimed to investigate the allele and genotype frequencies of SNPs SLCO1B3 (T334G) and CYP3A5*3 in newly diagnosed CML patients undergoing imatinib treatment and to determine whether SNPs of these two genes could predict the response of imatinib therapy in CML patients. We evaluated its efficacy by recording the response to imatinib therapy (hematological response, cytogenetic response (CyR), and molecular response).
Materials and methods
Patients
This is a prospective study. Our patients presented to the Hematology Department, Medical Research Institute, Alexandria University, with CML from June 2009 to August 2012.
Eighty-six Philadelphia (Ph) chromosome positive newly diagnosed CML patients undergoing imatinib treatment were enrolled in this study. Whole blood samples were obtained. Informed consent was obtained from all subjects. Seventy-eight patients were in early chronic phase of the disease and eight patients were in the accelerated phase of the disease. They were treated with standard dose imatinib (400 mg/day) for early chronic phase and (600 mg/day) for accelerated phase, respectively. Patients were followed up for a minimum of 18 months.
The treatment for CML aims to obtain a hematological response followed by cytogenetic and molecular responses. Before commencing imatinib therapy, in addition to routine history taking and physical examination, all patients had a complete blood cell count as well as routine biochemical analyses. Baseline tests also included bone marrow evaluation for morphology, fluorescent in situ hybridization studies (FISH) and quantitative real-time polymerase chain reaction (RQ-PCR) for BCR-ABL1 mRNA.
Patients were regularly monitored on an outpatient basis: biweekly physical examinations, blood counts, and biochemistry were obtained during the first month of imatinib therapy and then monthly until a CyR was achieved, and then every 3 months thereafter. Until a complete CyR was confirmed, bone marrow evaluation and FISH studies were performed every 3 months. The quantification of peripheral blood BCR-ABL1 fusion gene transcripts was repeated every 3 months regardless of CyR using RQ-PCR.
They were followed for a minimum of 18 months. Patients who stopped imatinib therapy due to intolerance were excluded from the study. Hematological response, CyR, and molecular response to imatinib therapy were defined and the attained overall response of each patient was categorized into optimal response, suboptimal response, or treatment failure according to the criteria of the European Leukemia Net.Citation13,Citation14
BCR-ABL1 real-time quantitative PCR
RNA was extracted from peripheral blood leucocytes using RNeasy Mini Kit (Qiagen, Valencia, CA) according to the manufacturer's instructions. Reverse transcription, which was performed on 1 µg of total RNA using random hexamers and RevertAid Premium Reverse Transcriptase (Thermoscientific, Middletown, VA), as recommended by the manufacturer. The resulting cDNA was subjected to real-time PCR by Step One real-time PCR system (Applied Biosystems, Foster City, CA) using IS-MMR Kit (Ipsogen, USA) according to the manufacturer instructions. The BCR-ABL1 transcripts copy number (CN) was normalized for the housekeeping gene (ABL1) transcripts CN giving the normalized copy number (NCN). The included international scale (IS) of the assay kit was used to harmonize the results to the IS giving the IS-normalized copy number (IS-NCN). The results of follow-up assays were evaluated for molecular response where IS-NCN ≤0.05 represents major molecular remission, IS-NCN ≥0.15 represents failure to achieve major molecular response and IS-NCN between 0.05 and 0.15 represents inconclusive result.
Genotyping
Blood was collected into EDTA vacutainer tubes and DNA was extracted using genomic DNA purification kit (Fermentas, Hanover, MD).
Genotyping of SLC01B3 polymorphisms
Polymorphisms of T334G in exon 3 were determined by the PCR-restriction fragment length polymorphism (PCR-RFLP) using a set of primers: forward primer 5′-GAA GGT ACA ATG TCT TGG GC-3′ and reverse primer 5′-CTC TCA AAA GGT AAC TGC CC-3′. PCR was carried out in 50 µl volumes containing 0.1 µg of genomic DNA, 0.25 µM of each of the primer set, 10x PCR buffer, 1.5 mM MgCl2, 200 µM each dNTP and 1.25 U of Taq DNA polymerase (Fermentas). PCR amplification was performed as follows: initial denaturation step at 94°C for 5 minutes, followed by 35 cycles of denaturation at 94°C for 1 minute, annealing at 50–60°C for 30 seconds, extension at 72°C for 2 minutes, and final extension at 72°C for 5 minutes.
RFLP analysis was conducted with Alu I (Fermentas, USA) according to the manufacturer instructions then electrophoresis was conducted with 1.5% agarose gel, in which ethidium bromide was incorporated. The wild-type allele gives a major fragment of 253 bp and the variant-type allele gives a major fragment of 213 bp.Citation15
Genotyping of CYP3A5*3 polymorphisms
The genotypes of each individual at the CYP3A5*3 alleles were determined using PCR– (RFLP) analysis using forward primer 5′-gtt gtacgc cac aca gca cc-3′ and Reverse 5′-ctc ttt aaa gag ctc ttt tgt ctc tca-3′ to get 155 bp PCR product. After PCR amplification, 5 µl of PCR product was digested for a minimum of 2 hours at 37°C with 5units of DdeI before electrophoresis using a 3% agarose gel. CYP3A5*1 (wild allele) was identified by the presence of two fragments of size 121, 34 bp whereas CYP3A5*3 (mutant allele) by fragments of sizes 97, 34,and 24 bps. The heterozygote is identified by the presences of 121, 97, 34 & 24 bp fragments.Citation12
PCR reactions were carried out in 25 µl of solution consisting of 2.5 µl of 10X PCR buffer, 0.2 mM of each dNTP, 0.4 M of each primer, 90 ng of genomic DNA as a template, and 1 unit of Taq DNA polymerase (Fermentas, USA). After initial denaturation at 95°C for 10 minutes, amplification was performed using 37 cycles of 94°C for 30 seconds, 56°C for 30 seconds, and 72°C for 30 seconds, followed by 72°C for 5 minutes for final extension.Citation16
FISH assay
Bone marrow samples were subjected to hypotonic treatment with KCl (0.075 mol/l) at 37°C for 20 minutes followed by several washes with fixative (methanol/acetic acid 3:1) then slides were prepared. Ten microliters of Poseidon™ BCR-ABL1 t(9;22) dual-color translocation, dual fusion probe (kreatech Diagnostics, Amsterdam, Netherlands) was then applied to each slide, which was cover-slipped and sealed with fixogum. The BCR-ABL1 probe is designed to detect both rearranged chromosomes by two co-localized red/green (yellow) fusion signals (F). Single color red (R) and green (G) signals will identify the normal chromosomes 9 and 22. This probe has been optimized to also detect cryptic insertion of ABL in the BCR gene region or BCR into the ABL region.
Hybridization was performed by denaturating sample and probe for 10 minutes at 72°C then for 16 hours at 37°C in the thermobrite. Post-hybridization washes consisted of two rinses in wash II for 2 minutes at room temperature and wash I for 2 minutes at 72°C. Dehydrate in 70%, 85%, and 100% ethanol for 1 minute each. Finally, nuclei were counter stained with DAPI. Cells were analyzed under a fluorescence microscopes equipped with Metaclass software (Microptic, Barcelona).
Statistical methods data were fed to the computer using the Predictive Analytics Software (PASW Statistics 18). Qualitative data were described using number and percent. Association between categorical variables was tested using χ2 test. When more than 20% of the cells have expected count less than 5, correction for χ2 was conducted using Fisher's Exact test or Monte Carlo correction.
Quantitative data were described using minimum and maximum as well as mean and standard deviation. The distributions of quantitative variables were tested for normality using Kolmogorov-Smirnov test, Shapiro-Wilk test. D'Agstino test was used if there was a conflict between the two previous tests. If it reveals normal data distribution, parametric tests were applied. If the data were abnormally distributed, non-parametric tests were used. For normally distributed data, comparison between two independent population were done using independent t-test while more than two population were analyzed F-test (analysis of variance) to be used. Significance test results are quoted as two-tailed probabilities. Significance of the obtained results was judged at the 5% level.
Results
The present study included 86 Philadelphia positive newly diagnosed CML patients, 78 in the early chronic phase and 8 in the accelerated phase.
Early chronic phase patients: Early chronic phase patients’ age ranged from 18 to 78 years with a median age of 53 years. Male patients were 61.5% and female patients were 38.5%. With regard to SLCO1B3 polymorphism, heterozygous (TG) form was the most frequent (44.9%) while the homozygous wild form (TT) was the least frequent (14.1%) with an allele frequency of 0.36 for the (T) allele and 0.63 for the (G) allele. The CYP3A5 1/3 heterozygous state was the most frequent (41%) while the homozygous wild form was the least frequent (26.9%) with a frequency of the 3 allele 0.53. Sixty patients of this group (76.9%) achieved optimal response to imatininb, 13 patients (16.7%) achieved suboptimal response while 5 patients (6.4%) failed to respond to imatinib ().
Table 1. Characteristics of the studied CML patients
In this group of patients, no association between SLCO1B3 (T334G) exon 3 polymorphism and response to imatinib therapy was detected (P = 0.938). With regard to CYP3A5*3 gene polymorphism, all patients with 1/1 genotype and 30 patients of the 32 patients with 1/3 genotype had optimal response whereas 3/3 genotype was detected in all patients who had treatment failure (P < 0.001) ().
Table 2. SLCO1B3 and CYP3A5 polymorphic variants in early chronic phase chronic myeloid leukemia patients in relation to the response to imatinib therapy
Accelerated Phase patients: Accelerated phase patients age ranged from 34 to 62 years with a median age of 49.5 years. Five patients were male and three were female. The SLCO1B3 polymorphic variants (TG) and (GG) were detected equally in these patients with none of the patients in this group having the homozygous wild form (TT). The (G) allele frequency in this group was 0.75. With regard to the CYP3A5 polymorphic variants, the homozygous state for the three alleles was the most frequent (50%) and the homozygous state for the one allele was the least frequent (12.5%) with an allele frequency of 0.69 for the three alleles. Half the number of the patients in this group failed to respond to imatinib while only one patient achieved optimal response ().
Discussion
The molecular basis for inter-individual variations in the response to imatinib is still unclear. While a number of factors may contribute to inter-individual variability, the genotype of a patient is increasingly implicated in influencing drug disposition and activity.Citation17
Our 78 early chronic phase Egyptian CML patients carried the heterozygous state of SLCO1B3 (T334G) exon 3 polymorphism as the most frequent genotype, while the TT homozygous state was the least frequent. In concordance with these results, the studies of Nambu et al.Citation8 and Yamakawa et al.Citation18 stated that the TT genotype was the least frequent. However, in those two studies, the GG genotype was the most frequent in chronic phase CML patients. This can be attributed to the smaller number of cases enrolled in these studies when compared with ours and/or the ethnic differences. Nevertheless, studies on a larger scale are needed to accurately evaluate these frequencies in chronic phase CML patients of different ethnic origins.
In this study, 21 of 78 (26.9%) of the CML patients in early chronic phase had CYP3A5*1/*1 genotype whereas 32 of 78 (41%) had CYP3A5*1/*3, and 25 of 78 (32.1%) patients carried the CYP3A5*3/*3 genotype, respectively. In agreement with this, Liu et al.Citation19 and Prachi et al.Citation20 reported that the CYP3A5*1/*1 genotype was the least frequent among their chronic phase CML patients. Certainly, the evaluation of these results will be through the conduction of large scale case–control studies on persons from different ethnic origins. Up to our knowledge, this is the first study evaluating SLCO1B3 and CYP3A5*3 polymorphisms in Egyptian CML patients.
The response to imatinib among our early chronic phase CML Egyptian patients was not associated with SLCO1B3 T334G polymorphism. In concordance with our results, Takahashi et al.Citation21, who investigated 67 Japanese chronic phase CML patients, found no associations between SLCO1B3 polymorphism and the response to imatinib or even between this polymorphism and plasma trough imatinib concentration.
However, the impact of SLCO1B3 polymorphism on the intracellular imatinib concentration was demonstrated by Nambu et al.Citation8 who found that the intracellular concentration imatinib appeared to be higher in patients with the SLCO1B3 TT genotype than in patients with the TG and GG genotypes. Knowing that this polymorphism involves the transmembrane domain of this transporter protein, thus this finding might suggest an impact of the tested polymorphism on the transporting specificity.Citation22 However, the intracellular concentration of a drug is not the only determinant of the response to it. Drug metabolizing machinery and the kinetics and functional properties of the drug metabolites can govern the response.
In this study, an association between CYP3A5*3/3 genotype, which leads to a poorly functioning CYP3A5 enzyme, and inferior response to imatinib was found despite the expectation to have a better response to a drug when the metabolizing enzyme is poorly functioning. However, the same observation was noted in the studies of Liu et al.Citation19 and kim et al.Citation23
In concordance with the above mentioned results, Green and his colleaguesCitation24 reported that patients who achieved complete molecular response showed significantly higher in vivo CYP3A activity. The explanation may be through the observation of Qiang and Anthony who reported that polymorphisms of a single gene encoding a drug-metabolizing enzyme responsible for the metabolism and disposition of a substrate drug caused aberrant response to the drug.Citation25 Moreover, CGP74588 (the main metabolite of imatinib) is pharmacologically active and has a potency and selectivity similar to those of imatinib.Citation26 CGP74588 has a longer terminal half-life (85–95 hours) than imatinib indicating that it might reach steady state and contribute to the clinical effects at a later time point during therapy.Citation27 In addition, CGP74588 may be active against sequence variations of the BCR-ABL1 which are not affected by imatinib.Citation24
On the other hand, Takahashi et al. did not find an association between CYP3A5*3 and dose-adjusted imatinib trough concentration or clinical response.Citation21 Hence, further evaluation is still needed to reach a final conclusion regarding the impact of this polymorphism on imatinib response.
The eight patients in accelerated phase in this study had the SLCO1B3 GG genotype in 50% and CYP3A5*3/3 genotype in 50%. Although the number of patients in this group is small, and the data in literature concerning the studied parameters in this phase of CML are deficient, yet an explanation pointing to the role of CYP3A enzyme in metabolizing genotoxic substances could presume that when CYP3A activity is diminished in those who have the CYP3A5*3 genotype can lead to increased exposure to genotoxic substances which can result in additional genetic abnormalities in CML patients pushing them into a more advanced phase of the disease.
References
- Hochhaus A. Chronic myelogenous leukemia (CML) resistance to tyrosine kinase inhibitors. Ann Oncol. 2006;17:274–9.
- Walz C, Sattler M. Novel targeted therapies to overcome imatinib mesylate resistance in chronic myeloid leukemia (CML). Crit Rev Oncol Hematol. 2006;57:145–64.
- Peng B, Lloyd P, Schran H. Clinical pharmacokinetics of imatinib. Clin Pharmacokinet. 2005;44:879–94.
- Anthony Au, Ravindran A, Ai Sim G, Fadilah S, Abdul W, Abdul Aziz B. Influence of ABCB1 C3435T and ABCG2 C421A gene polymorphisms in response to imatinib mesylate in chronic myeloid leukemia patients. International Conference on Clean and Green Energy IPCBE (2012), vol. 27. Singapore: IACSIT Press.
- Konig J, Seithel A, Gradhand U, Fromm MF. Pharmacogenomics of human OATP transporters. Naunyn-Schmiedeberg's Arch Pharmacol. 2006;372:432–43.
- Katrin L, Dietrich K, Jörg K. Mutations in the SLCO1B3 gene affecting the substrate specificity of the hepatocellular uptake transporter OATP1B3 (OATP8). Pharmacogenetics. 2004;14(7):441–52.
- Franke RM, Sparreboom A. Inhibition of imatinib transport by uremic toxins during renal failure. J Clin Oncol. 2008;26:4226–7.
- Nambu T, Hamada A, Nakashima R, Yuki M, Kawaguchi T, Mitsuya H, et al. Association of SLCO1B3 polymorphism with intracellular accumulation of imatinib in leukocytes in patients with chronic myeloid leukemia. Biol Pharm Bull. 2011;34(1):114–9.
- Smith NF, Marsh S, Scott-Horton TJ, Hamada A, Mielke S, Mross K, et al. Variants in the SLCO1B3 gene: interethnic distribution and association with paclitaxel pharmacokinetics. Clin Pharmacol Ther. 2007;81:76–82.
- Paulussen A, Lavrijsen K, Bohets H, Hendrickx J, Verhasselt P, Luyten W, et al. Two linked mutations in transcriptional regulatory elements of the CYP3A5 gene constitute the major genetic determinant of polymorphic activity in humans. Pharmacogenetics. 2000;10:415–24.
- Sailaja K, Rao DN, Rao DR, Vishnupriya S. Analysis of CYP3A5*3 and CYP3A5*6 gene polymorphisms in Indian chronic myeloid leukemia patients. Asian Pac J Cancer Prev. 2010;11:781–4.
- Kuehl P, Zhang J, Lin Y, Lamba J, Assem M, Schuetz J, et al. Sequence diversity in CYP3A promoters and characterization of the genetic basis of polymorphic CYP3A5 expression. Nat Genet. 2001;27:383–91.
- Baccarani M, Saglio G, Goldman J, Hochhaus A, Simonsson B, Appelbaum F, et al. Evolving concepts in the management of chronic myeloid leukemia: recommendations from an expert panel on behalf of the European Leukemia Net. Blood. 2006;108:1809–20.
- Baccarani M, Cortes J, Pane F, Niederwieser D, Saglio G, Apperley J, et al. Chronic myeloid leukemia: an update of concepts and management recommendations of European Leukemia Net. J Clin Oncol. 2009;27(35):6041–51.
- Tsujimoto M, Dan Y, Hirata S, Ohtani S, Sawada Y. Influence of SLCO1B3 Gene Polymorphism on the Pharmacokinetics of Digoxin in Terminal Renal Failure. Drug Metab Pharmacokinet. 2008;23(6):406–11.
- Fukuda T, Onishi S, Fukuen S, Ikenaga Y, Ohno M, Hoshino K, et al. CYP3A5 genotype did not impact on nifedipine disposition in healthy volunteers. Pharmacogenomics J. 2004;4(1):34–9.
- Sauna ZE, Kimchi-Sarfaty C, Ambudkar SV, Gottesman MM. Gottesman. Silent polymorphisms speak: how they affect pharmacogenomics and the treatment of cancer. Cancer Res. 2007;67:9609–12.
- Yamakawa Y, Hamada A, Nakashima R, Yuki M, Hirayama C, Kawaguchi T, et al. Association of genetic polymorphisms in the influx transporter SLCO1B3 and the efflux transporter ABCB1 with imatinib pharmacokinetics in patients with chronic myeloid leukemia. Ther Drug Monit. 2011;33(2):244–50.
- Liu TC, Lin SF, Chen TP, Chang JG. Polymorphism analysis of CYP3A5 in myeloid leukemia. Oncol Rep. 2002;9(2):327–9.
- Prachi B, Anil Kumar T, Deepa A. Genetic Polymorphism of CYP3A5 gene in Indian chronic myeloid leukemia patients. Mol Cell Biochem. 2010;336(1–2):49–54.
- Takahashi N, Miura M, Scott SA, Kagaya H, Kameoka Y, Tagawa H, et al. Influence of CYP3A5 and drug transporter polymorphisms on imatinib trough concentration and clinical response among patients with chronic phase chronic myeloid leukemia. J Human Genet. 2010;55(11):731–7.
- Tsujimoto M, Hirata S, Dan Y, Ohtani H, Sawada Y. Polymorphisms and Linkage Disequilibrium of the OATP8 (OATP1B3) Gene in Japanese Subjects Drug Metab. Pharmacokinetics. 2006;21(2):165–9.
- Kim DH, Sriharsha L, Xu W, Kamel-Reid S, Liu X, Siminovitch K, et al. Clinical relevance of a pharmacogenetic approach using multiple candidate genes to predict response and resistance to imatinib therapy in chronic myeloid. Clin Cancer Res. 2009;15(14):4750–8.
- Gréen H, Skoglund K, Rommel F, Mirghani RA, Lotfi K. CYP3A activity influences imatinib response in patients with chronic myeloid leukemia: a pilot study on in vivo CYP3A activity. Eur J Clin Pharmacol. 2010;66(4):383–6.
- Qiang M, Anthony YHLu. Pharmacogenetics, Pharmacogenomics, and Individualized Medicine. Pharmacol Rev. 2011;63(2):437–59.
- Cohen MH, Williams G, Johnson JR, Duan J, Gobburu J, Rahman A, et al. Approval summary for imatinib mesylate capsules in the treatment of chronic myelogenous leukemia. Clin Cancer Res. 2002;8:935–42.
- Larson RA, Druker BJ, Guilhot F, O'Brien SG, Riviere GJ, Krahnke T, et al. Imatinib pharmacokinetics and its correlation with response and safety in chronic-phase chronic myeloid leukemia: a subanalysis of the IRIS study. Blood. 2008;111:4022–8.