European Journal of Haematology 92 (283–288)
ORIGINAL ARTICLE
OCT1 genetic variants are associated with long term outcomes in imatinib treated chronic myeloid leukemia patients Maya Koren-Michowitz1,2, Zehavit Buzaglo1, Elena Ribakovsky1, Michaela Schwarz3, Ilias Pessach1, Avichai Shimoni1,2, Katia Beider1, Ninette Amariglio1, Philipp le Coutre3, Arnon Nagler1,2 1
Division of Hematology, Chaim Sheba Medical Center, Tel Hashomer; 2Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; , Berlin, Germany Campus Virchow Klinikum Charite
3
Abstract Objectives: One third of CML patients treated with first line imatinib have suboptimal responses or treatment failures with increased risk for disease progression. Imatinib is actively transported into cells by the SLC22A1 transporter (hOCT1) and its genetic variants may affect intracellular drug import. We studied the effect of SLC22A1 genetic variants on long-term outcomes of imatinib treated patients. Methods: A total of 167 patients, 94% in chronic phase, were analyzed for rs41267797, rs683369, rs12208357, and rs628031 variants using the Sequenom MassARRAY platform. Results: Rates of CHR, MCyR, CCyR, and MMolR were not significantly different according to allelic variants. However, patients with AA or GA rs628031 genotypes had a higher incidence of poor response to imatinib compared to the GG genotype (47% compared to 29%, P = 0.06), and a higher rate of KD mutation discovery (8/16 vs. 5/27, P = 0.04), suggesting that secondary resistance was more common in these genotypes. Median EFS was shorter for rs628031 genotype AA/AG compared with the GG genotype (61 months and not reached, respectively, P = 0.05), and 5 yr OS rates were lower for patients with the rs628031 genotypes AA/AG compared with the GG genotype (88% and 97%, respectively, P = 0.03). Patients with AA/GA rs628031 and additional rare genotypes had worse EFS and OS compared to patients with only AA/GA rs628031 (P = 0.02 for EFS and 0.01 for OS). There was no difference in pretreatment SLC22A1 mRNA expression levels in patients with rs628031 genotypes GG/AA or GA. Conclusions: Studying SLC22A1 genetic variants prior to TKI initiation could influence treatment decisions. Key words CML; tyrosine kinase inhibitor; hOCT1; resistance; kinase domain mutations *Correspondence Maya Koren-Michowitz, Division of Hematology, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel 52621. Tel: 972 3 5302342; Fax: 972 3 5305343; e-mail: [email protected] There are no financial disclosures for any author.This study was supported (in part) by a generous grant from the Naor family (A.N.) and a Sarousy Foundation grant (A.N). Accepted for publication 6 November 2013
Treatment with the tyrosine kinase inhibitor (TKI) imatinib has become the cornerstone of CML therapy and has markedly changed the outcome of this disease (1). Although second generation TKI including nilotinib (2, 3) and dasatinib (4) are being introduced into the first line therapy arsenal, imatinib is still the most commonly used TKI for the upfront treatment of CML worldwide. While most patients in early chronic phase analyzed in the IRIS trial with first line
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
doi:10.1111/ejh.12235
imatinib achieved major responses (82% achieving CCyR at the last, 6-yr follow-up report), only 63% of patients remaining on study at 6 yr were still in a CCyR (5). Cytogenetic and, recently, molecular responses at early time points during therapy with imatinib are predictive of event free survival and survival without progression to an accelerated phase (AP) or blast crisis (BC) (6, 7). Imatinib plasma levels during therapy can also predict response to therapy (8), and are a
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good measure of drug adherence; however these tests are cumbersome and not available on a routine basis. Currently, the only pre-treatment predictive features for treatment response are disease associated clinical scores including the Sokal (5) and the recently introduced EUTOS scores (9). The human solute carrier family 22, member 1 (SLC22A1), also known as the organic cation transporter 1 (OCT1) effectively mediates the active transport of imatinib into cells (influx pump), and its inhibition decreases the intracellular concentration of imatinib (10, 11). Genetic variability can account for a large proportion of variability in drug disposition and effects (12), and certain single nucleotide polymorphisms (SNP) in SLC22A1 were previously reported to predict response and resistance to imatinib therapy (13, 14).Whether SLC22A1 genetic variants are associated with long term outcomes in CML is unclear. We studied a cohort of 167 CML patients treated with imatinib with a median follow up of 80 months. In order to assess the effect of genetic variants on survival, our cohort was enriched for patients with imatinib resistance that were transferred to therapy with a second generation TKI. Patients and methods
A total of 167 CML patients who received imatinib in two medical centers, the Sheba Medical Center, Israel and Campus Virchow Klinikum Charite, Germany were included. Patients had to have an available DNA or peripheral blood mononuclear cells (PBMC) sample in order to be included in the study. Patients were treated with imatinib 400 mg/d (Israel) or 400–600 mg/d (Germany). Baseline characteristics and imatinib response data were extracted from the patients’ medical records. The study was approved by the local IRB committees according to the declaration of Helsinki. Genotyping of SLC22A1 variants
Candidate SNPs in the SLC22A1 gene were selected from the Entrez SNP database and were all non-synonymous nucleotide changes with a minor allele frequency ≥0.005 (http://www.ncbi.nlm.nih.gov/sites/entrez). Genotyping was done using the Sequenom MassARRAY platform (Sequenom, San Diego, CA, USA), as previously described (15, 16). SNP specific primers were designed using the MassARRAYâ assay design software. The detection of SNPs was done by the analysis of primer extension products generated from previously amplified genomic DNA using a Sequenom chip-based matrix-assisted laser desorption/ionization timeof-flight (MALDI-TOF) mass spectrometer. SLC22A1 gene expression
SLC22A1 mRNA levels were studied with real-time quantitative PCR (RT-qPCR) on the StepOnePlusTM Real-Time PCR
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System (Applied Biosystems, Foster City, CA, USA). RNA was extracted from archived pretreatment CP CML bone marrow or peripheral blood mononuclear cells (MNC), reverse transcribed and subjected to RT-qPCR with SLC22A1 specific primers, b2 microglubulin as the normalizing gene and KCL22 cDNA as a reference. Relative SLC22A1 expression levels were calculated using the ΔΔCt method. Statistical analysis
Genotype distribution was tested with the Hardy–Weinberg equilibrium (HWE). Response criteria including complete hematological response (CHR), complete cytogenetic response (CCyR) and major molecular response (MMolR) were defined according to the ELN guidelines (17). Patient characteristics and the rates of responses were compared for each SNP genotype between the major and minor (homozygous + heterozygous state) alleles, and between the heterozygous and homozygous alleles for the most informative SNP, rs628031 using the chi2 test. An event was defined as disease progression to an advanced phase, the loss of a previously achieved CCyR or a CHR or death. The probabilities of an event free survival (EFS) and overall survival (OS) were calculated using log-rank test and the Kaplan–Meier method. Comparison of SLC22A1 expression level was done using one-way ANOVA and student’s t-tests. Results
A total of 167 patients were included in this study, their baseline features are shown in Table 1. The majority of Table 1 Characteristics of the study patients N = 167 Median age at diagnosis (range) Disease status at diagnosis Chronic Accelerated Blast Unknown Disease status at imatinib initiation Early chronic Late chronic1 Accelerated Blast Unknown Response to imatinib (%) (N evaluable) CHR CCyR MMolR Additional CML directed therapies N (%) Interferon a Allogeneic SCT Second generation TKI
55 (18–80) 157 2 2 6 82 35 5 1 44 93 (123) 74 (111) 56 (110) 47 (36) 21 (18) 61 (48)
1
Late chronic defined as more than 12 months since diagnosis.
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
Koren-Michowitz et al.
hOCT1 variants predict CML outcomes
patients were diagnosed (94%) and treated (74%) with imatinib in CP. Allele frequency of the studied SNPs in our cohort is shown in Table 2. The minor allele frequency of rs41267797 was low (4/167 patients with the GA, none with the AA genotype), and was therefore not included in further analyses of the individual genetic variants; however, it was included in combined analysis for the rare variants. A deviation from the HWE was observed for rs683369 and rs12208357. Correlation between SLC22A1 genotype and clinical parameters
Overall, 93%, 74% and 56% of evaluable patients achieved CHR, CCyR, and MMolR, respectively, during treatment with imatinib. Treatment response according to genetic variants is shown in Table 3. There was no difference between the response rates when comparing between the different allele variants for each of the SNP studied. The achievement of a CCyR after 12 months of imatinib treatment in CP is considered an optimal response; therefore, we compared the proportion of CP patients with this landmark response between the different genetic variants. There was no difference in the 12 months rate of CCyR when comparing the rare and common genetic variants for each of the studied SNPs.
Table 2 Allele frequency of hOCT1 SNPs SNP
Ancestral allele
Minor allele
N with genotype (Allele frequency)
rs683369
C
G
rs628031
G
A
rs12208357
C
T
rs41267797
G
A
CC 117 (0.7) CG 49 (0.29) GG 1 (0.006) GG 99 (0.59) GA 41 (0.245) AA 27 (0.16) CC 150 (0.898) CT 17 (0.1) CC 0 GG 163 (0.976) GA 3 (0.018) AA 1 (0.006)
Therapy with a second-generation TKI was commenced in 61 patients in the study cohort (48% of evaluable patients); nilotinib in 46 and dasatinib in 17. The reason for therapy change was imatinib intolerance and resistance in 12 and 49 patients, respectively. Patients with AA or GA rs628031 genotypes had a higher incidence of poor response to imatinib (the combination of suboptimal response, primary and secondary failure) compared to the GG genotype (47% compared to 29%, P = 0.06). Sixty-six patients (40%) were studied for the presence of kinase domain mutation (KD) resulting in the discovery of KD mutations in 15 (23%). Patients with the rs628031 AA or GA genotypes had a higher frequency of KD mutations compared to the GG genotype (8/16 vs. 5/27, P = 0.04). There was no difference in the response rates to second generation TKI between the different allele variants. Correlation between SLC22A1 genotypes and outcome
With a median follow up of 80 months, the median EFS was 109 months and median OS was not reached for the entire cohort (Fig. 1). Only CP patients were included in further analysis for allele associations with outcome. Median EFS was shorter in patients with the rare genetic variants for all studied SNPs, but only reached statistical significance for rs628031 genotype AA/AG compared with the GG genotype (EFS 61 months and not reached, respectively, P = 0.05). Similarly, OS rates were significantly
Table 3 Responses to imatinib in CP CML according to specific genetic variants Achieved response (%) CHR PCyR CCyR MMolR
rs683369
rs628031
rs12208357
C
G/CG
G
A/AG
C
T/CT
91 76 79 49
95 70 77 55
90 79 80 55
94 67 75 44
93 74 78 51
50 50 75 50
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
Figure 1 EFS and OS of study cohort patients. Kaplan–Meier curves showing EFS and OS of the entire study cohort at a median of 80month follow-up.
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Figure 2 EFS and OS of chronic phase patients according to rs628031 allelic variants. (A) EFS (upper panel) and OS (lower panel) of patients with rs628031 AA/GA genotypes compared to the GG genotype. (B) EFS (upper panel) and OS (lower panel) of rs628031 AA/GA with and without additional rare SLC22A1 variants.
lower for patients with the rs628031 genotypes AA/AG compared with the GG genotype (5 yr OS 88% and 97%, respectively, P = 0.03) (Fig. 2). Since the rs628031 rare genotypes (AA/GA) were associated with worse median EFS and OS, we assessed whether additional SLC22A1 variants had a modifying effect on these outcomes. Patients with AA/GA rs628031 and additional rare genotypes had worse EFS and OS compared to patients with only AA/ GA rs628031 (P = 0.02 for EFS and 0.01 for OS) (Fig. 2). Correlations between SLC22A1 expression level and SLC22A1 genotypes
To study further the mechanism underling the relation of SLC22A1 allelic variation with CML associated outcomes we studied SLC22A1 expression level in CML patients’ samples. SLC22A1 relative expression levels were variable ranging between 0.9 and 7.2. Mean expression level in rs628031 GA, AA, and GG genotypes was 2.2, 3.2, and 2.0, respectively, P = 0.45; and it was 2.4 and 2.9 in isolated rs628031 GA/AA and GA/AA genotype and additional rare genotypes, respectively, P = 0.7 (Fig. 3). Discussion
Imatinib is actively imported into cells by hOCT1, the transporter coded by SLC22A1. Decreased hOCT1 activity could result in lower intracellular imatinib level, less potent inhibition of BCR-ABL, and worse response outcomes. Indeed, White et al. showed that low hOCT1 activity was associated with suboptimal responses to imatinib, and that higher doses of imatinib could achieve better responses in patients with
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Figure 3 SLC22A1 expression levels. Pretreatment SLC22A1 relative expression in (A) patients with rs628031 GG, GA, and GA genotypes and (B) patients with rs628031 AA/GA with and without additional rare SLC22A1 variants.
low hOCT1 activity (18). Several groups have previously shown the importance of SLC22A1 in cellular based handling of imatinib in CML cells. We studied the correlation between SLC22A1 genetic variants and clinical outcomes of imatinib treated CML patients. The rs628031 genotype was the most informative SNP in our cohort with frequencies of 0.59, 0.245, and 0.16 for the GG, GA, and AA genotypes, respectively. Although not associated with the rates of response achievement, GA and AA genotypes were associated with lower EFS and OS rates at a median follow up of 80 months. Furthermore, a higher rate of imatinib failures
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
Koren-Michowitz et al.
and a higher incidence of ABL-KD development were seen in patients with either GA or AA genotypes, supporting a contributory effect of these genotypes on the development of secondary resistance to imatinib therapy. Previous studies on SLC22A1 in imatinib treated CML patients have looked at SLC22A1 functional activity, SLC22A1 genetic variants or SLC22A1 expression levels. SLC22A1 activity in MNC from untreated CP-CML patients was shown to correlate with cytogenetic and molecular responses to imatinib (18, 19), as well as 5 yr outcomes including overall, event-free, and transformation-free survival (18). Lower activity of SLC22A1 in CD34+ CML cells was suggested to contribute to the relative resistance of CML primitive cells to imatinib therapy (20), although the lack of correlation between CD34+ and mature MNC SLC22A1 activities from the same patient suggests that CD34+ SLC22A1 activity is not a major determinant of imatinib response achievement (21). Several studies have investigated the association between the SLC22A1 genetic variants and response to imatinib treatment. Kim et al. studied the correlation of 5 SLC22A1 genetic variants and CML clinical outcomes in a cohort of 229 CML patients (203-CP) treated with imatinib (13). Similar to our results, none of the studied variants correlated with response rates. rs683369 was associated with the risk for treatment failure or loss of response to imatinib. The lack of associations between rs628031 found significant in our study and clinical outcomes in that study may be explained by the shorter median follow up of 43 compared to 80 months in our cohort. Interestingly, Kim et al. found strong linkage disequilibrium (LD) between rs683369 and rs628031 (13), suggesting that either genetic variant may be informative. Indeed, in our trial both genetic variants were associated with EFS; however, association with rs628031 was more statistically significant. Furthermore, in a multivariate analysis including all 3 informative SLC22A1 SNPs, rs628031 was the only independent variable associated with outcomes. Interestingly, we found that having a combination of SLC22A1 rare genetic variants was worse than having only the rs628031 rare alleles. These results are supported by a recent publication that found a significant association between a combination of SLC22A1 SNPs and rates of response achievement (22). SLC22A1 SNPs studied in this trial are all associated with amino acid changes and in theory could affect SLC22A1 carrier activity by interfering with function or proper localization. However, in vitro studies in non-leukemic cells (23), as well as in CML patients samples (24) did not show a decrease in SLC22A1 activity with the Met408Val variant associated with rs628031. We, therefore, hypothesized that SLC22A1 genetic variants may affect SLC22A1 expression level. Indeed, SLC22A1 mRNA levels were previously reported to correlate with imatinib responses in CML (11, 25), although other studies did not find such correlations
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
hOCT1 variants predict CML outcomes
(18). Nevertheless, SLC22A1 expression in our samples was quite variable and was not significantly different between the specific rs628031 genotypes. Possibly, this is due to the relative small sample size studied for expression level. Finally, due to the retrospective nature of our study we were not able to include imatinib plasma level in the model to predict response to imatinib. A combination of SLC22A1 genetic variants and imatinib plasma level could have a better predictive value than either one alone. In conclusion, we show that SLC22A1 genetic variants, in particular the rs628031 minor genotypes GA and AA, have an impact on secondary resistance to imatinib and on long term outcomes of imatinib treated CML patients. Furthermore, we found an additional additive effect for SLC22A1 SNP combinations, supporting the recently published data of Angelini et al. (22). With generic imatinib soon to enter the market, analysis of SLC22A1 genetic variants could be introduced into pretreatment predictors of treatment outcomes. Acknowledgements
The study done as partial fulfillment for a MA degree at the Bar-Ilan University, Israel (Z.B). References 1. O’Brien SG, Guilhot F, Larson RA, et al. Imatinib compared with interferon and low-dose cytarabine for newly diagnosed chronic-phase chronic myeloid leukemia. N Engl J Med 2003;348:994–1004. 2. Larson RA, Hochhaus A, Hughes TP, et al. Nilotinib vs imatinib in patients with newly diagnosed Philadelphia chromosome-positive chronic myeloid leukemia in chronic phase: ENESTnd 3-year follow-up. Leukemia 2012;26:2197–203. 3. Koren-Michowitz M, le Coutre P, Duyster J, Scheid C, Panayiotidis P, Prejzner W, Rowe JM, Schwarz M, Goldschmidt N, Nagler A. Activity and tolerability of nilotinib: a retrospective multicenter analysis of chronic myeloid leukemia patients who are imatinib resistant or intolerant. Cancer 2010;116:4564–72. 4. Kantarjian HM, Shah NP, Cortes JE, et al. Dasatinib or imatinib in newly diagnosed chronic-phase chronic myeloid leukemia: 2-year follow-up from a randomized phase 3 trial (DASISION). Blood 2012;119:1123–9. 5. Hochhaus A, O’Brien SG, Guilhot F, et al. Six-year followup of patients receiving imatinib for the first-line treatment of chronic myeloid leukemia. Leukemia 2009;23:1054–61. 6. Hanfstein B, Muller MC, Hehlmann R, et al. Early molecular and cytogenetic response is predictive for long-term progression-free and overall survival in chronic myeloid leukemia (CML). Leukemia 2012;26:2096–102. 7. Hughes TP, Hochhaus A, Branford S, et al. Long-term prognostic significance of early molecular response to imatinib in newly diagnosed chronic myeloid leukemia: an analysis from
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the International Randomized Study of Interferon and STI571 (IRIS). Blood 2010;116:3758–65. 8. Koren-Michowitz M, Volchek Y, Naparstek E, Gavish I, Levi I, Rowe JM, Shimoni A, Nagler A. Imatinib plasma trough levels in chronic myeloid leukaemia: results of a multicentre study CSTI571AIL11TGLIVEC. Hematol Oncol 2012;30:200–5. 9. Hasford J, Baccarani M, Hoffmann V, et al. Predicting complete cytogenetic response and subsequent progression-free survival in 2060 patients with CML on imatinib treatment: the EUTOS score. Blood 2011;118:686–92. 10. Thomas J, Wang L, Clark RE, Pirmohamed M. Active transport of imatinib into and out of cells: implications for drug resistance. Blood 2004;104:3739–45. 11. Crossman LC, Druker BJ, Deininger MW, Pirmohamed M, Wang L, Clark RE. hOCT 1 and resistance to imatinib. Blood. 2005; 106: 1133–4; author reply 4. 12. Kalow W, Endrenyi L, Tang B. Repeat administration of drugs as a means to assess the genetic component in pharmacological variability. Pharmacology 1999;58:281–4. 13. Kim DH, Sriharsha L, Xu W, Kamel-Reid S, Liu X, Siminovitch K, Messner HA, Lipton JH. Clinical relevance of a pharmacogenetic approach using multiple candidate genes to predict response and resistance to imatinib therapy in chronic myeloid leukemia. Clin Cancer Res 2009;15:4750–8. 14. Bazeos A, Marin D, Reid AG, et al. hOCT1 transcript levels and single nucleotide polymorphisms as predictive factors for response to imatinib in chronic myeloid leukemia. Leukemia 2010;24:1243–5. 15. Koren-Michowitz M, Shimoni A, Vivante A, Trakhtenbrot L, Rechavi G, Amariglio N, Loewenthal R, Nagler A, Cohen Y. A new MALDI-TOF-based assay for monitoring JAK2 V617F mutation level in patients undergoing allogeneic stem cell transplantation (allo SCT) for classic myeloproliferative disorders (MPD). Leuk Res 2008;32:421–7. 16. Vivante A, Amariglio N, Koren-Michowitz M, Ashur-Fabian O, Nagler A, Rechavi G, Cohen Y. High-throughput, sensitive and quantitative assay for the detection of BCR-ABL kinase domain mutations. Leukemia 2007;21:1318–21. 17. Baccarani M, Cortes J, Pane F, et al. Chronic myeloid leukemia: an update of concepts and management recommenda-
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18.
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tions of European LeukemiaNet. J Clin Oncol 2009;27: 6041–51. White DL, Saunders VA, Dang P, Engler J, Venables A, Zrim S, Zannettino A, Lynch K, Manley PW, Hughes T. Most CML patients who have a suboptimal response to imatinib have low OCT-1 activity: higher doses of imatinib may overcome the negative impact of low OCT-1 activity. Blood 2007;110:4064–72. White DL, Saunders VA, Dang P, Engler J, Zannettino ACW, Cambareri AC, Quinn SR, Manley PW, Hughes TP. OCT-1– mediated influx is a key determinant of the intracellular uptake of imatinib but not nilotinib (AMN107): reduced OCT-1 activity is the cause of low in vitro sensitivity to imatinib. Blood 2006;108:697–704. Engler JR, Frede A, Saunders VA, Zannettino ACW, Hughes TP, White DL. Chronic myeloid leukemia CD34+ cells have reduced uptake of imatinib due to low OCT-1 activity. Leukemia 2010;24:765–70. Engler JR, Frede A, Saunders V, Zannettino A, White DL, Hughes TP. The poor response to imatinib observed in CML patients with low OCT-1 activity is not attributable to lower uptake of imatinib into their CD34+ cells. Blood 2010;116:2776–8. Angelini S, Soverini S, Ravegnini G, et al. Association between imatinib transporters and metabolizing enzymes genotype and response in newly diagnosed chronic myeloid leukemia patients receiving imatinib therapy. Haematologica 2013;98:193–200. Kerb R, Brinkmann U, Chatskaia N, Gorbunov D, Gorboulev V, Mornhinweg E, Keil A, Eichelbaum M, Koepsell H. Identification of genetic variations of the human organic cation transporter hOCT1 and their functional consequences. Pharmacogenetics 2002;12:591–5. White DL, Saunders VA, Dang P, Engler J, Hughes TP. OCT-1 activity measurement provides a superior imatinib response predictor than screening for single-nucleotide polymorphisms of OCT-1. Leukemia 2010;24:1962–5. Wang L, Giannoudis A, Lane S, Williamson P, Pirmohamed M, Clark RE. Expression of the uptake drug transporter hOCT1 is an important clinical determinant of the response to imatinib in chronic myeloid leukemia. Clin Pharmacol Ther 2007;83:258–64.
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
ORIGINAL ARTICLE
OCT1 genetic variants are associated with long term outcomes in imatinib treated chronic myeloid leukemia patients Maya Koren-Michowitz1,2, Zehavit Buzaglo1, Elena Ribakovsky1, Michaela Schwarz3, Ilias Pessach1, Avichai Shimoni1,2, Katia Beider1, Ninette Amariglio1, Philipp le Coutre3, Arnon Nagler1,2 1
Division of Hematology, Chaim Sheba Medical Center, Tel Hashomer; 2Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; , Berlin, Germany Campus Virchow Klinikum Charite
3
Abstract Objectives: One third of CML patients treated with first line imatinib have suboptimal responses or treatment failures with increased risk for disease progression. Imatinib is actively transported into cells by the SLC22A1 transporter (hOCT1) and its genetic variants may affect intracellular drug import. We studied the effect of SLC22A1 genetic variants on long-term outcomes of imatinib treated patients. Methods: A total of 167 patients, 94% in chronic phase, were analyzed for rs41267797, rs683369, rs12208357, and rs628031 variants using the Sequenom MassARRAY platform. Results: Rates of CHR, MCyR, CCyR, and MMolR were not significantly different according to allelic variants. However, patients with AA or GA rs628031 genotypes had a higher incidence of poor response to imatinib compared to the GG genotype (47% compared to 29%, P = 0.06), and a higher rate of KD mutation discovery (8/16 vs. 5/27, P = 0.04), suggesting that secondary resistance was more common in these genotypes. Median EFS was shorter for rs628031 genotype AA/AG compared with the GG genotype (61 months and not reached, respectively, P = 0.05), and 5 yr OS rates were lower for patients with the rs628031 genotypes AA/AG compared with the GG genotype (88% and 97%, respectively, P = 0.03). Patients with AA/GA rs628031 and additional rare genotypes had worse EFS and OS compared to patients with only AA/GA rs628031 (P = 0.02 for EFS and 0.01 for OS). There was no difference in pretreatment SLC22A1 mRNA expression levels in patients with rs628031 genotypes GG/AA or GA. Conclusions: Studying SLC22A1 genetic variants prior to TKI initiation could influence treatment decisions. Key words CML; tyrosine kinase inhibitor; hOCT1; resistance; kinase domain mutations *Correspondence Maya Koren-Michowitz, Division of Hematology, The Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel 52621. Tel: 972 3 5302342; Fax: 972 3 5305343; e-mail: [email protected] There are no financial disclosures for any author.This study was supported (in part) by a generous grant from the Naor family (A.N.) and a Sarousy Foundation grant (A.N). Accepted for publication 6 November 2013
Treatment with the tyrosine kinase inhibitor (TKI) imatinib has become the cornerstone of CML therapy and has markedly changed the outcome of this disease (1). Although second generation TKI including nilotinib (2, 3) and dasatinib (4) are being introduced into the first line therapy arsenal, imatinib is still the most commonly used TKI for the upfront treatment of CML worldwide. While most patients in early chronic phase analyzed in the IRIS trial with first line
© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd
doi:10.1111/ejh.12235
imatinib achieved major responses (82% achieving CCyR at the last, 6-yr follow-up report), only 63% of patients remaining on study at 6 yr were still in a CCyR (5). Cytogenetic and, recently, molecular responses at early time points during therapy with imatinib are predictive of event free survival and survival without progression to an accelerated phase (AP) or blast crisis (BC) (6, 7). Imatinib plasma levels during therapy can also predict response to therapy (8), and are a
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hOCT1 variants predict CML outcomes
good measure of drug adherence; however these tests are cumbersome and not available on a routine basis. Currently, the only pre-treatment predictive features for treatment response are disease associated clinical scores including the Sokal (5) and the recently introduced EUTOS scores (9). The human solute carrier family 22, member 1 (SLC22A1), also known as the organic cation transporter 1 (OCT1) effectively mediates the active transport of imatinib into cells (influx pump), and its inhibition decreases the intracellular concentration of imatinib (10, 11). Genetic variability can account for a large proportion of variability in drug disposition and effects (12), and certain single nucleotide polymorphisms (SNP) in SLC22A1 were previously reported to predict response and resistance to imatinib therapy (13, 14).Whether SLC22A1 genetic variants are associated with long term outcomes in CML is unclear. We studied a cohort of 167 CML patients treated with imatinib with a median follow up of 80 months. In order to assess the effect of genetic variants on survival, our cohort was enriched for patients with imatinib resistance that were transferred to therapy with a second generation TKI. Patients and methods
A total of 167 CML patients who received imatinib in two medical centers, the Sheba Medical Center, Israel and Campus Virchow Klinikum Charite, Germany were included. Patients had to have an available DNA or peripheral blood mononuclear cells (PBMC) sample in order to be included in the study. Patients were treated with imatinib 400 mg/d (Israel) or 400–600 mg/d (Germany). Baseline characteristics and imatinib response data were extracted from the patients’ medical records. The study was approved by the local IRB committees according to the declaration of Helsinki. Genotyping of SLC22A1 variants
Candidate SNPs in the SLC22A1 gene were selected from the Entrez SNP database and were all non-synonymous nucleotide changes with a minor allele frequency ≥0.005 (http://www.ncbi.nlm.nih.gov/sites/entrez). Genotyping was done using the Sequenom MassARRAY platform (Sequenom, San Diego, CA, USA), as previously described (15, 16). SNP specific primers were designed using the MassARRAYâ assay design software. The detection of SNPs was done by the analysis of primer extension products generated from previously amplified genomic DNA using a Sequenom chip-based matrix-assisted laser desorption/ionization timeof-flight (MALDI-TOF) mass spectrometer. SLC22A1 gene expression
SLC22A1 mRNA levels were studied with real-time quantitative PCR (RT-qPCR) on the StepOnePlusTM Real-Time PCR
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System (Applied Biosystems, Foster City, CA, USA). RNA was extracted from archived pretreatment CP CML bone marrow or peripheral blood mononuclear cells (MNC), reverse transcribed and subjected to RT-qPCR with SLC22A1 specific primers, b2 microglubulin as the normalizing gene and KCL22 cDNA as a reference. Relative SLC22A1 expression levels were calculated using the ΔΔCt method. Statistical analysis
Genotype distribution was tested with the Hardy–Weinberg equilibrium (HWE). Response criteria including complete hematological response (CHR), complete cytogenetic response (CCyR) and major molecular response (MMolR) were defined according to the ELN guidelines (17). Patient characteristics and the rates of responses were compared for each SNP genotype between the major and minor (homozygous + heterozygous state) alleles, and between the heterozygous and homozygous alleles for the most informative SNP, rs628031 using the chi2 test. An event was defined as disease progression to an advanced phase, the loss of a previously achieved CCyR or a CHR or death. The probabilities of an event free survival (EFS) and overall survival (OS) were calculated using log-rank test and the Kaplan–Meier method. Comparison of SLC22A1 expression level was done using one-way ANOVA and student’s t-tests. Results
A total of 167 patients were included in this study, their baseline features are shown in Table 1. The majority of Table 1 Characteristics of the study patients N = 167 Median age at diagnosis (range) Disease status at diagnosis Chronic Accelerated Blast Unknown Disease status at imatinib initiation Early chronic Late chronic1 Accelerated Blast Unknown Response to imatinib (%) (N evaluable) CHR CCyR MMolR Additional CML directed therapies N (%) Interferon a Allogeneic SCT Second generation TKI
55 (18–80) 157 2 2 6 82 35 5 1 44 93 (123) 74 (111) 56 (110) 47 (36) 21 (18) 61 (48)
1
Late chronic defined as more than 12 months since diagnosis.
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hOCT1 variants predict CML outcomes
patients were diagnosed (94%) and treated (74%) with imatinib in CP. Allele frequency of the studied SNPs in our cohort is shown in Table 2. The minor allele frequency of rs41267797 was low (4/167 patients with the GA, none with the AA genotype), and was therefore not included in further analyses of the individual genetic variants; however, it was included in combined analysis for the rare variants. A deviation from the HWE was observed for rs683369 and rs12208357. Correlation between SLC22A1 genotype and clinical parameters
Overall, 93%, 74% and 56% of evaluable patients achieved CHR, CCyR, and MMolR, respectively, during treatment with imatinib. Treatment response according to genetic variants is shown in Table 3. There was no difference between the response rates when comparing between the different allele variants for each of the SNP studied. The achievement of a CCyR after 12 months of imatinib treatment in CP is considered an optimal response; therefore, we compared the proportion of CP patients with this landmark response between the different genetic variants. There was no difference in the 12 months rate of CCyR when comparing the rare and common genetic variants for each of the studied SNPs.
Table 2 Allele frequency of hOCT1 SNPs SNP
Ancestral allele
Minor allele
N with genotype (Allele frequency)
rs683369
C
G
rs628031
G
A
rs12208357
C
T
rs41267797
G
A
CC 117 (0.7) CG 49 (0.29) GG 1 (0.006) GG 99 (0.59) GA 41 (0.245) AA 27 (0.16) CC 150 (0.898) CT 17 (0.1) CC 0 GG 163 (0.976) GA 3 (0.018) AA 1 (0.006)
Therapy with a second-generation TKI was commenced in 61 patients in the study cohort (48% of evaluable patients); nilotinib in 46 and dasatinib in 17. The reason for therapy change was imatinib intolerance and resistance in 12 and 49 patients, respectively. Patients with AA or GA rs628031 genotypes had a higher incidence of poor response to imatinib (the combination of suboptimal response, primary and secondary failure) compared to the GG genotype (47% compared to 29%, P = 0.06). Sixty-six patients (40%) were studied for the presence of kinase domain mutation (KD) resulting in the discovery of KD mutations in 15 (23%). Patients with the rs628031 AA or GA genotypes had a higher frequency of KD mutations compared to the GG genotype (8/16 vs. 5/27, P = 0.04). There was no difference in the response rates to second generation TKI between the different allele variants. Correlation between SLC22A1 genotypes and outcome
With a median follow up of 80 months, the median EFS was 109 months and median OS was not reached for the entire cohort (Fig. 1). Only CP patients were included in further analysis for allele associations with outcome. Median EFS was shorter in patients with the rare genetic variants for all studied SNPs, but only reached statistical significance for rs628031 genotype AA/AG compared with the GG genotype (EFS 61 months and not reached, respectively, P = 0.05). Similarly, OS rates were significantly
Table 3 Responses to imatinib in CP CML according to specific genetic variants Achieved response (%) CHR PCyR CCyR MMolR
rs683369
rs628031
rs12208357
C
G/CG
G
A/AG
C
T/CT
91 76 79 49
95 70 77 55
90 79 80 55
94 67 75 44
93 74 78 51
50 50 75 50
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Figure 1 EFS and OS of study cohort patients. Kaplan–Meier curves showing EFS and OS of the entire study cohort at a median of 80month follow-up.
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Figure 2 EFS and OS of chronic phase patients according to rs628031 allelic variants. (A) EFS (upper panel) and OS (lower panel) of patients with rs628031 AA/GA genotypes compared to the GG genotype. (B) EFS (upper panel) and OS (lower panel) of rs628031 AA/GA with and without additional rare SLC22A1 variants.
lower for patients with the rs628031 genotypes AA/AG compared with the GG genotype (5 yr OS 88% and 97%, respectively, P = 0.03) (Fig. 2). Since the rs628031 rare genotypes (AA/GA) were associated with worse median EFS and OS, we assessed whether additional SLC22A1 variants had a modifying effect on these outcomes. Patients with AA/GA rs628031 and additional rare genotypes had worse EFS and OS compared to patients with only AA/ GA rs628031 (P = 0.02 for EFS and 0.01 for OS) (Fig. 2). Correlations between SLC22A1 expression level and SLC22A1 genotypes
To study further the mechanism underling the relation of SLC22A1 allelic variation with CML associated outcomes we studied SLC22A1 expression level in CML patients’ samples. SLC22A1 relative expression levels were variable ranging between 0.9 and 7.2. Mean expression level in rs628031 GA, AA, and GG genotypes was 2.2, 3.2, and 2.0, respectively, P = 0.45; and it was 2.4 and 2.9 in isolated rs628031 GA/AA and GA/AA genotype and additional rare genotypes, respectively, P = 0.7 (Fig. 3). Discussion
Imatinib is actively imported into cells by hOCT1, the transporter coded by SLC22A1. Decreased hOCT1 activity could result in lower intracellular imatinib level, less potent inhibition of BCR-ABL, and worse response outcomes. Indeed, White et al. showed that low hOCT1 activity was associated with suboptimal responses to imatinib, and that higher doses of imatinib could achieve better responses in patients with
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Figure 3 SLC22A1 expression levels. Pretreatment SLC22A1 relative expression in (A) patients with rs628031 GG, GA, and GA genotypes and (B) patients with rs628031 AA/GA with and without additional rare SLC22A1 variants.
low hOCT1 activity (18). Several groups have previously shown the importance of SLC22A1 in cellular based handling of imatinib in CML cells. We studied the correlation between SLC22A1 genetic variants and clinical outcomes of imatinib treated CML patients. The rs628031 genotype was the most informative SNP in our cohort with frequencies of 0.59, 0.245, and 0.16 for the GG, GA, and AA genotypes, respectively. Although not associated with the rates of response achievement, GA and AA genotypes were associated with lower EFS and OS rates at a median follow up of 80 months. Furthermore, a higher rate of imatinib failures
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Koren-Michowitz et al.
and a higher incidence of ABL-KD development were seen in patients with either GA or AA genotypes, supporting a contributory effect of these genotypes on the development of secondary resistance to imatinib therapy. Previous studies on SLC22A1 in imatinib treated CML patients have looked at SLC22A1 functional activity, SLC22A1 genetic variants or SLC22A1 expression levels. SLC22A1 activity in MNC from untreated CP-CML patients was shown to correlate with cytogenetic and molecular responses to imatinib (18, 19), as well as 5 yr outcomes including overall, event-free, and transformation-free survival (18). Lower activity of SLC22A1 in CD34+ CML cells was suggested to contribute to the relative resistance of CML primitive cells to imatinib therapy (20), although the lack of correlation between CD34+ and mature MNC SLC22A1 activities from the same patient suggests that CD34+ SLC22A1 activity is not a major determinant of imatinib response achievement (21). Several studies have investigated the association between the SLC22A1 genetic variants and response to imatinib treatment. Kim et al. studied the correlation of 5 SLC22A1 genetic variants and CML clinical outcomes in a cohort of 229 CML patients (203-CP) treated with imatinib (13). Similar to our results, none of the studied variants correlated with response rates. rs683369 was associated with the risk for treatment failure or loss of response to imatinib. The lack of associations between rs628031 found significant in our study and clinical outcomes in that study may be explained by the shorter median follow up of 43 compared to 80 months in our cohort. Interestingly, Kim et al. found strong linkage disequilibrium (LD) between rs683369 and rs628031 (13), suggesting that either genetic variant may be informative. Indeed, in our trial both genetic variants were associated with EFS; however, association with rs628031 was more statistically significant. Furthermore, in a multivariate analysis including all 3 informative SLC22A1 SNPs, rs628031 was the only independent variable associated with outcomes. Interestingly, we found that having a combination of SLC22A1 rare genetic variants was worse than having only the rs628031 rare alleles. These results are supported by a recent publication that found a significant association between a combination of SLC22A1 SNPs and rates of response achievement (22). SLC22A1 SNPs studied in this trial are all associated with amino acid changes and in theory could affect SLC22A1 carrier activity by interfering with function or proper localization. However, in vitro studies in non-leukemic cells (23), as well as in CML patients samples (24) did not show a decrease in SLC22A1 activity with the Met408Val variant associated with rs628031. We, therefore, hypothesized that SLC22A1 genetic variants may affect SLC22A1 expression level. Indeed, SLC22A1 mRNA levels were previously reported to correlate with imatinib responses in CML (11, 25), although other studies did not find such correlations
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hOCT1 variants predict CML outcomes
(18). Nevertheless, SLC22A1 expression in our samples was quite variable and was not significantly different between the specific rs628031 genotypes. Possibly, this is due to the relative small sample size studied for expression level. Finally, due to the retrospective nature of our study we were not able to include imatinib plasma level in the model to predict response to imatinib. A combination of SLC22A1 genetic variants and imatinib plasma level could have a better predictive value than either one alone. In conclusion, we show that SLC22A1 genetic variants, in particular the rs628031 minor genotypes GA and AA, have an impact on secondary resistance to imatinib and on long term outcomes of imatinib treated CML patients. Furthermore, we found an additional additive effect for SLC22A1 SNP combinations, supporting the recently published data of Angelini et al. (22). With generic imatinib soon to enter the market, analysis of SLC22A1 genetic variants could be introduced into pretreatment predictors of treatment outcomes. Acknowledgements
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