Chinese Medical Journal 2012;125(12):2137-2143
Association of polymorphisms of cytosine arabinoside- metabolizing enzyme gene with therapeutic efficacy for acute myeloid leukemia
Correspondence to:CHEN Bao-an,Department of Hematology, Zhongda Hospital and Faculty of Oncology, Medical School, Southeast University, Nanjing, Jiangsu 210009, China (Tel: 86-25-83272006. Fax:86-25-83272011. E-mail:email@example.com)
deoxycytidine kinase; cytidine deaminase; single nucleotide polymorphisms; acute myeloid leukemia
Background The cytosine arabinoside (Ara-C)-based chemotherapy is the major remedial measure for acute myeloid leukemia (AML). Deoxycytidine kinase (DCK) and cytidine deaminase (CDA) are the key enzymes in the metabolism of Ara-C. Many single nucleotide polymorphisms (SNPs) and haplotypes of DCK and CDA, which contribute to susceptibility to Ara-C, have been identified in Africans and Europeans. However, there has been no report about the relation among three SNPs in DCK (rs115543896, rs72552079, and rs111454937) and two SNPs in CDA (rs2072671 and rs60369023), and their clinical response to Ara-C for a Chinese population. In this study, we aimed to investigate whether these five SNPs are associated with the therapeutic outcomes of Ara-C-based chemotherapy regimens in patients with AML.
Methods A total of 151 Chinese patients with AML were enrolled in our study. SNPs genotyping were performed using the MassARRAY system by means of the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) method.
Results The results illustrated that DCKrs111454937 AA genotype was more frequent in patients with higher platelet count, and A allele frequency was significantly higher in the group £40 years, lower white blood cell (WBC) count patients group and the group with platelet counts >60´109/L. Meanwhile, both DCKrs72552079 TC (OR=1.225, 95% CI=1.225–9.851, P=0.0192) and CDArs60369023 GA (OR=9.851, 95% CI=1.31–77.93, P=0.0263) significantly improved Ara-C-based chemotherapy response. While DCKrs11554389 AA (OR=0.147, 95% CI=0.027–0.801, P=0.0267) was associated with the decrease of Ara-C-based chemotherapy response.Conclusion It is evident that the DCK and CDA polymorphisms might be the important markers for the AML patients’ therapy outcomes in a Chinese population.
Acute myeloid leukemia (AML) is the commonest type of leukemia that threatens the human health and causes the death of the patients.1 According to the latest statistics, there are 4 000 000 patients with leukemia in China and the number is increasing by 30 000–40 000 per year.2 The cytosine arabinoside (Ara-C) based chemotherapeutics are the most common regimens for AML, such as DA (daunorubicin + Ara-C) regimen, HA (homoharringtonine + Ara-C) regimen.3,4 Nevertheless, patients in the same stage usually display different responses or varied prognoses,5 and the longer these patients wait for medical treatment, the less likely they are to recover. So the individualized chemotherapy based on pharmacogenomics and pharmacogenetics has demonstrated a potentially predictive or prognostic role to reach the preferable outcome for patients with AML.6
Single nucleotide polymorphism (SNP) is a DNA point mutation that is carried by some individuals of a population.7 The study of pharmacogenetics indicated that such small changes in the genome sequence can significantly influence the individual treatment response, toxicity, and survival for the cancer patients. Additionally, SNP has greater clinical significance in terms of its ease of clinical application, rather than its mRNA, which present some clinical difficulties in terms of obtaining marrow tissue samples from AML patients.
Deoxycytidine kinase (DCK) catalyzes the rate-limiting step in the phosphorylation of pharmacologically important anticancer and antiviral drugs such as Ara-C.8 Cytidine deaminase (CDA) is another enzyme involving in the metabolism of Ara-C by converting Ara-C to an inactive product (Ara-U).9 Some studies have shown an association between expression of CDA or DCK and sensitivity to Ara-C.10-12 However, the true contribution of genetic variation of these candidate genes to susceptibility to Ara-C remains inconclusive.
In this study, we focused on the relation among three SNPs in DCK (rs115543896, rs72552079, and rs111454937) and two SNPs in CDA (rs2072671 and rs60369023), and their clinical response to Ara-C in patients with AML. Many SNPs of DCK and CDA, which contribute to susceptibility to Ara-C, have been identified in Africans, Europeans, and Chinese, such as DCKrs2306744, DCKrs67437265, and CDArs1091682.13-15 However, there has been no report about the associations of these five SNPs analysis for a Chinese population. Hence, in this study, we aimed to investigate whether these five SNPs are associated with the therapeutic outcomes of Ara-C-based chemotherapy regimens in patients with AML.
From August 2008 to January 2011, 151 patients diagnosed with AML according to French–American–Britain (FAB) criteria in six large hospitals in Jiangsu province were enrolled in the study. Patients who were diagnosed with any other cancer or other hematological malignancies were excluded from this study. All patients enrolled in our study provided informed consent for genetic analysis according to the Declaration of Helsinki and appreciated the existence of other treatment options according to the Ethics Committee of Southeast University, in compliance with Chinese guidelines for blood donation.
Among these patients with AML, six patients were diagnosed with minimally differentiated AML (M0); nine patients for AML without maturation (M1); 77 patients, AML with maturation (M2); 22 patients, acute myelomonocytic leukemia (M4); 28 patients, acute monocytic leukemia (M5); seen patients, erythroleukemia (M6); and two patients, acute megakaryoblastic leukemia (M7). The characteristics of the patients are shown in Table 1. Note that acute promyelocytic leukemia (M3) was removed in this report because of different treatment regimens. Cytogenetic risk groups were defined as follows: unfavorable, –7/del(7q), –5/del(5q), abn3q, abn9q, abn11q, abn-17p; complex aberrations (³3 independent aberrations), t(6;9), and t(9;22); favorable, t(15;17), inv(16)/t(16;16)/del(16q), and t(8;21); intermediate risk, all other karyotypic aberrations or a normal karyotype.16 Meanwhile, patients were divided into two groups respectively according to each of the following: hemoglobin level, number of white blood cells (WBC) and platelet count. Before the administration of chemotherapy regimens, a complete clinical examination and history, as well as a bone marrow biopsy, serum biochemical, and a complete blood count were performed to confirm the diagnosis of patients.
Evaluation of chemotherapy regimens and therapeutic response
Among 151 patients with AML treated with standard Ara-C based chemotherapy regimens, 70 patients received intravenous daunorubicin (DNR) 45 mg×m-2×d-1 for 1–3 days and Ara-C 100 mg×m-2×d-1 for 1–7 days (DA induction chemotherapy regimen); 36 patients received homoharringtonine (HHT) 3–4 mg×m-2×d-1 for 5–7 days and Ara-C 100 mg×m-2×d-1 for 1–7 days (HA induction chemotherapy regimen); and 45 patients received mitoxantrone 4 mg×m-2×d-1 for 1–5 days and Ara-C 100 mg×m-2×d-1 for 1–7 days (MA induction chemotherapy regimen). Complete response (CR) was defined as follows: absolute values of granular leukocytes and platelets in peripheral blood are not more than 1.5´109/L and 100´109/L respectively; blast cell count in the bone marrow was less than 5% for at least 4 weeks and symptoms and signs of leukemia disappear; and granulopoiesis and megakaryocytopoiesis after chemotherapy with normalized peripheral blood counts persisting for at least 4 weeks, without intervening chemotherapy. Partial remission (PR) was defined as at least one of the following not meeting the standard criteria for CR: clinical manifestation, blood analysis, and bone marrow biopsy, in addition to <20% blast cells and promyelocytic cells in the bone marrow. Non-remission (NR) was defined as all three of the clinical manifestation, the blood analysis, and the bone marrow biopsy not meeting the standard criteria for CR, as well as >20% promyelocytic cells in the bone marrow. Early death was defined as death within 8 weeks from the start of the first induction therapy course. For data analysis, CR and PR were combined as good response, and NR and early death were grouped as poor response.17
DNA collection and polymorphism genotyping
Blood samples of patients were collected by vacutainer and transferred to ethylenediaminetetraacetic acid (EDTA) tubes, and genomic DNA was isolated from the blood samples using TIANGEN DNA mini Kit (TIANGEN, China) and stored at −20°C until being used. SNP genotyping was performed by the Mass ARRAY system (Sequenom, USA) with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS) method according to the manufacturer’s instructions. Completed genotyping reactions were spotted onto a 384-well spectro CHIP (Sequenom) using a Mass ARRAY Nanodispenser (Sequenom) and determined by MALDI-TOF-MS.
Genotype calling was performed in real time with Mass ARRAY RT software version 126.96.36.199 (Sequenom), and analyzed using the Mass ARRAY Typer software version 3.4 (Sequenom). PCR primers and single base extension primers were designed by Primer Premier 6.0 software, and sequences of them are shown in Table 2.
Deviations from Hardy–Weinberg equilibrium (HWE) for genotypes were assessed by Pearson’s χ2-test using SHEsis. Demographic and clinical information was compared to genotype, using Pearson’s χ2-test or Fisher’s exact test (when the expected number in any cell was less than five). The significant difference of genotypes in different responders was calculated using Pearson’s χ2 test. P values lower than 0.05 were considered statistically significant. We estimated the relative risk of responding to treatment with the genotypes as odds ratio (ORs) and 95% confidence intervals (CIs). The OR and 95% CI were calculated by Logistic regression analysis with adjustment for patient gender, age at diagnosis, tumor histology, and chemotherapy regimens to quantify the association between polymorphisms and treatment of patients with AML. All statistical tests for this analysis were performed using SPSS 17.0 software (SPSS Inc., USA).
Characteristics of patients and genotypes
The main study of the characteristics from patients and relevant clinical data are presented in Table 1. Patients with AML included 65 males and 86 females, with the ages ranging from 15 to 81 years (mean age: 46.20 years). The evaluation standard of these patients was divided into: age group including <40 years, 40–60 years and >60 years; WBC count group of >50´109/L vs. £50´109/L; hemoglobin group of >100 g/L vs. £100 g/L; platelet count group of >60´109/L vs. £60´109/L. The results showed the significant differences among three genotypes of DCKrs115543896 as shown in Table 1. The frequency of the CC genotype in the FAB group was significantly higher than that in the other two genotypes. However, for the AC genotype, the frequency in the FAB group was significantly lower (P=0.015). For DCKrs111454937, a statistically significant association was found among the platelet count groups (P=0.048). However, there were no other significant differences in both WBC and hemoglobin groups (P >0.05).
Table 1. Patients’ characteristics according to the DCKrs111454937 and the DCKrs115543896
Genotype frequencies for the polymorphism are presented in Table 1. Genotype frequencies for the polymorphisms were found to be in HWE. Among these polymorphisms, the DCKrs111454937 A allele frequency showed significantly higher in the group £40 years, the group with WBC<50´109/L (P=0.034) and in the group with platelet count >60´109/L (P=0.043). Distribution of the two alleles among cytogenetic risk groups showed a significant difference (P=0.04). However, no significant differences of genotype were detected among gender, FAB classification, laboratory diagnosis, and chemotherapy regimen groups.
Genetic polymorphisms and treatment response
All patients received Ara-C-based standard induction chemotherapy regimens, and the treatment effects were evaluated after the second cycles of chemotherapy regimen. Figure 1 and Table 3 showed the frequencies of genotypes in different treatment response to patients with AML, and the association of genotypes with the treatment response. Seventy-eight cases (51.66%) achieved CR after standard induction chemotherapy regimen. Also, 28 cases (18.54%) achieved PR, 38 cases (25.17%) achieved NR, and seven cases (4.63%) were early death after standard induction chemotherapy regimens. The results indicated: (1) When outcomes were analyzed according to CR response, PR+NR response, and early death, analysis showed that the frequency of the TT genotype in the CR response group was significantly higher than in the other groups, and similarly TC genotype in the PR+NR response group (P=0.002, Figure 1); (2) Genotype influences the treatment response (Table 3 and Figure 2). Patients carrying at least one variant allele (DCKrs72552079TC and CDArs60369023 GA) were more likely to be better response compared with those without the variant allele. After adjusting for patient gender, age at diagnosis, tumor histology, and chemotherapy regimens, the OR (95% CI) for response were 1.225 (1.225–9.851, P=0.0192), 9.851 (1.313–77.93, P=0.0263) respectively. Meanwhile, DCKrs11554389 AA was associated with the decreased Ara-C-based chemotherapy response (OR (95% CI)=0.147 (0.027–0.801), P=0.0267). For other SNPs, the genotypes were not substantially different among the groups.
Figure 1. Number of DCK and CDA polymorphism genotypes influencing response to induction therapy. CR: complete response. PR: partial remission. NR: non-remission.
Figure 2. Genotype of CDArs60369023, DCKrs115543896, DCKrs72552079, and response to chemotherapy among AML patients (n=151). CR: complete response. PR: partial remission.
The numbers of patients with AML are the most maximum in leukemia patients, and the clinical chemotherapy has been the main method for AML therapy. At present, more than 50% of adult patients with AML achieve a CR undergoing the induction of therapy with Ara-C-based chemotherapy.18 Unfortunately, the occurrence of resistance to chemotherapy influenced the therapeutic effect of the patients and confused hematologists. And the resistance to Ara-C is one of the most important reasons for treatment failure among patients with AML.19-23 Hereditary factors are one of the determinants of drug efficacy and side effects. The implementation of individual therapies, including genotype-based recommendations for risk assessment and treatment decision making, will be a challenge in the future for physicians.
Ara-C is a kind of deoxycytidine analogue that is a standard agent for treatment of AML. DCK and CDA are the key enzymes in the metabolism of Ara-C. Several mutants of DCK similar to rs2306744 were reported in acute lymphocytic leukemia (ALL), AML, unclassified myeloproliferative syndrome (MPS), down syndrome, and unclassifiable myeloproliferative syndrome.13,14,24 The SNPs at the 3¢ untranslated region of DCK gene (DCKrs72552097 and rs2306744) post-transcriptionally regulates mRNA copy level and translation efficiency in which DCK rs72552097G/rs2306744T alleles expresses higher levels of DCK mRNA.24 AML patients with DCK rs72552097CC/rs2306744CC genotype had a significantly inferior response to therapy as compared to the other genotypes. It was reported that these two SNPs were in perfect linkage-disequilibrium (LD).13 Previously, the functional variations of CDArs60369023 and rs2072671 have been described among ALL patients, and rs2072671 alters the enzymatic function and might affect the treatment response of Ara-C.25 Other study from Gilbert’s group found that the CDArs60369023A and rs2072671C alleles have reduced activity compared to wild type alleles in vitro studies in American population.26
The majority studies about the association between SNPs and AML were mainly related to the susceptibility. It has been noted that the same doses of standard therapy have caused considerable heterogeneity in the efficacy across human populations, and this heterogeneity can lead to unpredictable life-threatening or even lethal adverse effects in small groups of patients.27,28 Five SNPs were selected for our study, which might play a role in regulatory processes during the metabolism of Ara-C. The CDArs60369023 is located at nucleotide 208 within the 5¢ precusor peptide sequence that causes an amino acid substitution of alanine to threonine at codon 70 (Ala70Thr). The CDArs2072671 also causes the substitution of a single amino acid from lysine to glutamine (Lys27Gln). The SNP DCK rs111454937 has been identified at nucleotide 359 within the 5¢ precusor peptide sequence that causes an amino acid substitution of glutamine to glycine at codon 120 (Glu120Gly). DCKrs115543896 is located in the exon 1. The DCKrs72552079 polymorphisms are located in the 3¢-UTR region, which may affect miRNA expression and its potential targets. This study indicated the association between the chemotherapy outcomes and DCKrs111454937/rs115543896 in the AML patients for the first time. Moreover, in this retrospective study, the Ara-C-based standard chemotherapeutic regimens had been used to treat the AML patients, so the predictive role of DCK and CDA would have been more credible. The DCKrs111454937 AA genotype was more frequent in patients with higher platelet count, and A allele frequency was significantly higher in patients with higher WBC and platelet counts. The rs115543896 AA genotype was more frequent in patients with acute myelomonocytic leukemia (M4) and good therapy response, and CDArs60369023 GG genotype was also higher in patients with the good therapy response group. Thus, the polymorphic status of DCKrs11554389, DCKrs72552079, and CDArs60369023 might be used to predict treatment response of AML patients. However, the polymorphism of other SNPs was not significantly associated with AML. Our study was performed in a Chinese population, so it is possible that the results may be different from other populations, which may be influenced by the sample sizes and study groups as well as other factors.
In summary, our results demonstrate that the DCK and CDA polymorphisms might be the important markers for therapy outcomes of AML patients in a Chinese population. Based on the predictive role of these SNPs, in vivo functional studies should be further performed in our future research to define their role and value in the conventional treatment setting for patients with AML.
Acknowledgment: We would like thank TONG Na (School of Public Health, Nanjing Medical University) for her assistance in data analysis.
1. Hildreth CJ, Lynm C, Glass RM. Acute myeloid leukemia. JAMA 2010; 304: 2759.
2. Chinese Red Cross Foundation (http://en.crcf.org.cn/ prozi.asp?lm=20&lm2=36).
3. Rai KR, Holland JF, Glidewell OJ, Weinberg V, Brunner K, Obrecht JP, et al. Treatment of acute myelocytic leukemia: a study by Cancer and Leukemia Group B. Blood 1981; 58: 1203-1212.
4. Han LN, Zhou J, Schuringa JJ, Vellenga E. Treatment strategies in acute myeloid leukemia. Chin Med J 2011; 124: 1409-1421.
5. Bolanos-Meade J, Guo C, Gojo I, Karp JE. A phase II study of timed sequential therapy of acute myelogenous leukemia (AML) for patients over the age of 60: two cycle timed sequential therapy with topotecan, ara-C and mitoxantrone in adults with poor-risk AML. Leuk Res 2004; 28: 571-577.
6. Kuptsova N, Kopecky KJ, Godwin J, Anderson J, Hoque A, Willman CL, et al. Polymorphisms in DNA repair genes and therapeutic outcomes of AML patients from SWOG clinical trials. Blood 2007; 109: 3936-3944.
7. Anthony B. SNP attack on complex traits. Nat Genet 1998; 20: 217-218.
8. Van Rompay AR, Johansson M, Karlsson A. Substrate specificity and phosphorylation of antiviral and anticancer nucleoside analogues by human deoxyribonucleoside kinases and ribonucleoside kinases. Pharmacol Ther 2003; 100: 119-139.
9. Hapke DM, Stegmann AP, Mitchell BS. Retroviral transfer of deoxycytidine kinase into tumor cell lines enhances nucleoside toxicity. Cancer Res 1996; 56: 2343-2347.
10. Achiwa H, Oguri T, Sato S, Maeda H, Niimi T, Ueda R. Determinants of sensitivity and resistance to gemcitabine: the roles of human equilibrative nucleoside transporter 1 and deoxycytidine kinase in non-small cell lung cancer. Cancer Sci 2004; 95: 753-757.
11. Hamada A, Kawaguchi T, Nakano M. Clinical pharmacokinetics of cytarabine formulations. Clin Pharmacokinet 2002; 41: 705-718.
12. Song JH, Kim SH, Kweon SH, Lee TH, Kim HJ, Kim HJ, et al. Defective expression of deoxycytidine kinase in cytarabine-resistant acute myeloid leukemia cells. Int J Oncol 2009; 34: 1165-1171.
13. Shi JY, Shi ZZ, Zhang SJ, Zhu YM, Gu BW, Li G, et al. Association between single nucleotide polymorphisms in deoycytidine kinase and treatment response among acute myeloid leukemia patients. Pharmacogenetics 2004; 14: 759-768.
14. Joerger M, Bosch TM, Doodeman VD, Beijnen JH, Smits PH, Schellens JH. Novel deoxycytidine kinase gene polymorphisms: a population screening study in Caucasian healthy volunteers. Eur J Clin Pharmacol 2006; 62: 681-684.
15. Styczynski J. Drug resistance in childhood acute myeloid leukemia. Curr Pharm Biotechnol 2007; 8: 59-75.
16. Barragan E, Collado M, Cervera J, Martin G, Bolufer P, Roman J, et al. The GST deletions and NQO1*2 poly-morphism confers interindividual variability of response to treatment in patients with acute myeloid leukemia. Leuk Res 2007; 3: 947-953.
17. Diamond HR, Ornellas MH, Orfao A, Gomes BE, Campos MM, Fernandez TS, et al. Acute myeloid leukemia of donor origin after allogeneic stem cell transplantation from a sibling who harbors germline XPD and XRCC3 homozygous polymorphisms. J Hematol Oncol 2011; 4: 39.
18. Ravindranath Y, Chang M, Steuber CP, Becton D, Dahl G, Civin C, et al. Pediatric Oncology Group (POG) studies of acute myeloid leukemia (AML): a review of four consecutive childhood AML trials conducted between 1981 and 2000. Leukemia 2005; 19: 2101-2116.
19. Si S, Liao Q, Zhao YP, Hu Y, Zhang Q, You LL. Relationship between single nucleotide polymorphisms in the deoxycytidine kinase gene and chemosensitivity of gemcitabine in six pancreatic cancer cell lines. Chin Med J 2011; 124: 419-422.
20. Fernandez-Calotti P, Jordheim LP, Giordano M, Dumontet C, Galmarini CM. Substrate cycles and drug resistance to 1-beta-D-arabinofuranosylcytosine (Ara-C). Leuk Lymphoma 2005; 46: 335-346.
21. Galmarini CM, Thomas X, Calvo F, Rousselot P, Jafaari AE, Cros E, et al. Potential mechanisms of resistance to cytarabine in AML patients. Leuk Res 2002; 26: 621-629.
22. Cros E, Jordheim L, Dumontet C, Galmarini CM. Problems related to resistance to cytarabine in acute myeloid leukemia. Leuk Lymphoma 2004; 45: 1123-1132.
23. Deng CH, Zhang QP. Leukemia stem cells in drug resistance and metastasis. Chin Med J 2010; 123: 954-960.
24. Lamba JK, Crews K, Pounds S, Schuetz EG, Gresham J, Gandhi V, et al. Pharmacogenetics of deoxycytidine kinase: identification and charaeterization of novel genetic variants. J Pharmacol Exp Ther 2007; 323: 935-945.
25. Banklau C, Jindadamrongwech S, Sawangpanich R, Apibal S, Hongeng S, Paisooksantivatana K, et al. Effect of genetic alterations of cytarabine-metabolizing enzymes in childhood acute lymphoblastic leukemia. Hematol Oncol Stem Cell Ther 2010; 3: 103-108.
26. Gilbert JA, Salavaggione OE, Ji Y, Pelleymounter LL, Eckloff BW, Wieben ED, et al. Gemcitabine pharmacogenomics: cytidine deaminase and deoxycytidylate deaminnase gene resequencing and functional genomics. Clin Cancer Res 2006; 12: 1794-1803.
27. Fagerlund TH, Braaten O. No pain relief from codeine? An introduction to pharmacogenomics. Acta Anaesthesiol Scand 2001; 45: 140-149.
28. Dong S, Guo AL, Chen ZH, Wang Z, Zhang XC, Huang Y, et al. RRM1 single nucleotide polymorphism -37C→A correlates with progression-free survival in NSCLC patients after gemcitabine-based chemotherapy. J Hematol Oncol 2010; 3: 10.
- National Key Basic Research Program 973 of China,No. 2010CB732404;National Natural Science Funds of People’s Republic of China,No. 81170492;Key Medical Disciplines of Jiangsu Province, and the Graduate Research and Innovation Program of Jiangsu Province,No. CXLX_0150;