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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Blood Rev. Author manuscript; available in PMC 2016 July 1.
Published in final edited form as:
PMCID: PMC4494870
NIHMSID: NIHMS654998

Pharmacogenetics predictive of response and toxicity in acute lymphoblastic leukemia therapy

Abstract

Acute lymphoblastic leukemia (ALL) is a relatively rare disease in adults accounting for no more than 20% of all cases of acute leukemia. By contrast with the pediatric population, in whom significant improvements in long term survival and even cure have been achieved over the last 30 years, adult ALL remains a significant challenge. Overall survival in this group remains a relatively poor 20–40%. Modern research has focused on improved pharmacokinetics, novel pharmacogenetics and personalized principles to optimize the efficacy of the treatment while reducing toxicity. Here we review the pharmacogenetics of medications used in the management of patients with ALL, including L-asparaginase, glucocorticoids, 6-mercaptopruine, methotrexate, vincristine and tyrosine kinase inhibitors. Incorporating recent pharmacogenetic data, mainly from pediatric ALL, will provide novel perspective of predicting response and toxicity in both pediatric and adult ALL therapy.

Keywords: Acute lymphoblastic leukemia, Pharmacogenetics, L-asparaginase, Glucocorticoids, 6-Mercaptopruine, Methotrexate, Vincristine, Tyrosine kinase inhibitors

Introduction

Acute lymphoblastic leukemia (ALL) is a malignancy of immature lymphoid progenitors which has historically been classified into precursor T cell leukemia, precursor B cell leukemia and mature (Burkitt) leukemia [1, 2]. According to National Cancer Institute Surveillance, Epidemiology, and End Results Program, 6,070 new cases were diagnosed in the United States in 2013. Childhood ALL accounts for the majority of these cases, responsible for almost a third of all childhood cancer in children aged from 0 to 14 years [3]. In the past 20 years, the 5-year survival rate of childhood ALL has increased from less than 40% in the mid-1960s to 91% in the mid-2000s [3]. This result was achieved by optimal use of existing anti-leukemic drugs, combinations with newly developed tyrosine kinase inhibitors and improvements in supportive care. Unfortunately, the long-term survival rate for older patients remains poor. Long term remission are achieved in 50%–60% of patients between aged 15–45, about 30% of patients aged 45–54 and in older adults the five year survival is rarely better than 15% in older adults [46].

The typical treatment course for patients diagnosed with precursor-type ALL lasts 2–3 years, and includes remission-induction therapy, consolidation therapy and maintenance. Induction generally includes glucocorticoids, vincristine, and L-asparaginase, with or without an anthracycline [7]. Consolidation therapy is given after induction therapy to eradicate minimal residual leukemia cells. High dose methotrexate (MTX) with 6-mercaptopurine (6-MP) are commonly used, accompanied by frequent pulses of vincristine, glucocorticoids and L-asparaginase for 20–30 weeks. Maintenance therapy generally lasts for 2 years and is comprised of 6-MP and weekly MTX with or without pulsed doses of vincristine and dexamethasone [7]. The frequent and multiple therapies required for the treatment of ALL result in significant toxicity which can contribute both to early morbidity and mortality as well as significant long term sequelae [8]. Many factors have the potential to contribute to the occurrence of serious side effects. Specific genetic polymorphisms have recently been identified as crucial variables in the toxicity and efficacy of drug therapy for management of ALL.

A large scale genome-wide analysis including 2,534 children with ALL found that genomic variation in Native American ancestry was independently associated with higher risk of relapse, suggesting a crucial role for pharmacogenetic effects in ALL [9]. In this review, we will summarize recent progress in pharmacogenetic research and how these achievements will potentially contribute to patient specific tailoring of ALL treatment regimens (Table 1.).

Table 1
Summary of pharmacogenomic studies of ALL treatment.

L-Asparaginase

L-asparaginase is a common component in the initial treatment of ALL, particularly in intensive induction therapy. Three asparaginase preparations were available: one derived from Escherichia coli (E.Coli asparaginase, recently removed from the market), the former’s pegylated form (PEG-asparaginase) and the third is a product isolated from Erwinia caratovora (Erwinia asparaginase) [1012]. Treatment with asparaginase has been associated with serious adverse effects, including allergy, pancreatitis and cerebrovascular accidents. Hypersensitivity responses, more commonly observed with native E.coli asparaginase [13], occur in up to 35% of patients and 10% of those reactions are life-threatening anaphylaxis [10, 14]. PEG-asparaginase demonstrates a prolonged half-life and decreased renal excretion relative to the parent compound [15]. In addition, the pegylated formulation increases efficacy and reduces the possibility of antibody generation by preventing reticuloendothelial uptake [16, 17]. The newly developed Erwinia asparaginase produced a lower rate of allergic reaction and has been demonstrated to produce effective asparaginase activity even in patients who had previously experienced an allergy to PEG-asparaginase [18]. Four different pharmacogenetic targets have been identified to have a relationship to asparaginase toxicity.

Asparagines synthetase (ASNS) catalyzes the transfer of an amino group to aspartic acid to form asparagines. Leukemic blasts are devoid of ASNS, explaining the utility of the different L-asparaginases. Early research has unraveled that ASNS activity was an indicator of L-asparaginase resistance in vitro [19, 20] and in clinical studies. The single-nucleotide polymorphisms (SNPs) of the basic leucine zipper activating transcription factor 5 (ATF5), inducing increased ASNS activity, were associated with reduced event-free survival (EFS) [21]. Similarly, Pastorczak et al. recently reported that polymorphism of a 14-bp tandem repeat sequence in the ASNS gene itself leads to higher expression of the gene, which was associated with worse response and increased risk for relapse [22]. These retrospective and single-center studies have provided intriguing evidence for a significant pharmacogenomics contribution to therapeutic efficacy, although some of these results remain controversial and require confirmation through prospective clinical trials.

Chen et al. studied more than 500,000 SNPs in 485 children with ALL. Five SNPs with an identical relationship to different alleles of the glutamate α-amino-3-hydroxy-5-methyl-4-isocazolepropionic acid (AMPA) receptor subunit 1 gene (GRIA1) were associated with hypersensitivity to asparaginase [23]. GRIA1 gene encodes a subunit of glutamate receptor 1, which is a predominant excitatory neurotransmitter receptor in the brain. In addition, glutamate has recently been recognized as an immune modulator [24].

Furthermore, recent report demonstrated an association between HLA-DRB1*0701 with asparaginase allergy due to amino acid variants within the binding pocket of HLA-DRB1 that conferred higher binding affinity [25]. Highlighting the potential importance of such genetic variability to predict adverse drug effect the Food and Drug Administration (FDA) recently approved testing for HLA-B*5701 prior to the administration of abacavir, to patients with human immunodeficiency virus (HIV) as a mean of avoiding drug toxicity [26, 27]. Identification of genetic polymorphisms which predict drug toxicity provides a new paradigm for the incorporation of pharmacogenetics into routine clinical practice, although additional prospective evidence proving these associations may be required.

Glucocorticoids

Glucocorticoids are the keystone of ALL therapy. They exert their activity by reducing cell proliferation and promoting apoptosis or cell arrest by binding to intracytoplasmic glucocorticoid receptors. In tumor cells, up-regulation of P-glycoprotein, encoded by the ATP-binding cassette sub-family B1 (ABCB1) gene, is responsible for glucocorticoid resistance. C3435T [28], G2677T/A [29] and T129C [30] have been identified as polymorphisms associated with possible glucocorticoid resistance based on in vitro studies. Better responses to glucocorticoids therapies have been observed in patients with the A1082G SNP in the promoter region of the interleukin-10 (IL-10) gene [31]. The SNP results in up-regulated IL-10 expression and increases the binding of glucocorticoids to monocytes. Likewise, deletion of the glutathione-S-transferase (GSTs) type M1 gene has been associated with initial responsiveness to glucocorticoids as well as the severity of infectious complication by decreasing glucocorticoid metabolism [32, 33]. In B-cell ALL, Pottier et al. showed that mutations in three subunits of the nucleosome-remodeling complex correlate with in vitro glucocorticoid resistance using a panel of 177 primary pediatric ALL samples [34]. Further, Real et al. demonstrated that the NOTCH pathway is a pivotal determinant of glucocorticoid sensitivity in T-cell ALL. Combination therapy with a gamma-secretase inhibitor (inhibitor of NOTCH1) and glucocorticoids could restore the anti-leukemic effect of glucocorticoids in glucocorticoid-resistant T-cell ALL [35]. In addition, gene expression profiles of carbohydrate metabolism have revealed that increased glucose metabolism can induce prednisolone resistance [36]. Inhibition of molecules in the glycolytic pathway, for example glyceraldehydes-3-phosphate dehydrogenase (GAPDH) and 2-deoxy-D-glucose (2-DG), reverse glucocorticoid resistance in both cell lines and primary ALL samples [36]. Similarly, overexpression of the X-linked inhibition of apoptosis protein (XIAP) has been shown to predict chemotherapy resistance. In childhood with T-cell ALL, poor prednisone response was associated with increased XIAP expression, and glucocorticoid resistance could be reversed by XIAP inhibition [37]. Recent reports from Jones et al. have shown that reduced expression of Transducin Beta-Like 1 X-linked Receptor 1 (TBL1XR1) induces glucocorticoid resistance in a B-cell ALL cell line by decreasing glucocorticoid receptor affinity [38]. More recently, gene expression microarray studies performed on samples from 256 primary pediatric B-cell ALL patients have identified overexpression of epithelial membrane protein 1 (EMP1) as a novel poor prognostic factor and possible drug target important for the regulation of in vitro prednisolone resistance [39].

Glucocorticoids have a number of long-term adverse effects, including hypertension, diabetes, infection, osteoporosis and avascular necrosis (AVN). Kamden et al. determined the genotypes for 203 candidate SNPs in pediatric ALL, which were previously linked to hypertension or metabolism of anti-leukemic agents. This study identified eight genes associated with steroid-induced hypertension [40]. Furthermore, Jones et al. have shown that corticotrophin-releasing hormone receptor 1 (CRHR1) polymorphisms may impact the risk of bone mineral density loss in a study of 309 long-term ALL survivors [41]. A total of 10–15% of children develop AVN after receiving ALL treatment, and this complication can be directly attributable to the prolonged use of high-dose glucocorticoids [42, 43]. A previous case report suggested variants of thymidylate synthase (TYMS) were associated with a higher risk for developing AVN [44]; however, these results were not confirmed in subsequent studies [45]. Instead, prospective evaluation identified a SNP of plasminogen activator inhibitor-1 (PAI-1) as a candidate for the prediction of osteonecrosis [45]. Genome-wide association studies unraveled polymorphisms of acid phosphatase 1 (ACP1), which regulates lipid levels and osteoblast differentiation, as a potential predictor of osteonecrosis risk [46]. Three genes (alpha-2-HS-glycoprotein, IL-6, polymerase delta interacting protein 3) were significantly associated with dexamethasone-induced sleep disturbance [47]. In summary, it is clear that the adverse effects of glucocorticoids are linked to differential rates of clearance mediated by population variant as well as interaction with other cytokines. Prospective validation for the predictive value of such SNPs may in the future allow better prediction of severe side effects from glucocorticoids.

6-Mercaptopurine (6-MP)

6-MP is an antimetabolite used for more than 40 years. Combined with weekly MTX, daily 6-MP is the backbone of maintenance therapy for ALL, with or without pulses of vincristine and dexamethasone. After being metabolized to 6-thioguanine nucleotides (6-TG), it inhibits de-novo purine synthesis. Bhatia et al. reported that absolute 6-MP or 6-TG levels were not helpful for prognosticating relapse risk in a study including 744 pediatric patients who had achieved remission. Instead, high intra-individual variability in 6-TG levels contributed to relapse risk in this population, which reinforce the need to minimize the fluctuation of 6-MP [48].

The enzyme, thiopurine methyltransferase (TPMT) catalyzes the S-methylation of thiopurine to an inactive metabolite. These genes are co-dominantly inherited, containing nonsynonymous SNPs, leading to significant differences in enzyme activity and important clinical consequences [49]. Patients with TPMT SNPs associated with lower enzymatic activity, either heterozygous or homozygous can cause moderate to severe myelosuppression when treated with conventional doses of 6-MP [50]. Similarly, homozygosity for the TPMT deficient SNP can result in greater risk for radiation-induced brain tumors and chemotherapy-induced acute myeloid leukemia [51], although these patients tend to have a lower rate of relapse rate [52]. Since 3–14% of patients are heterozygous for TPMT associated with lower enzyme activity, routine pre-treatment testing is suggested and once identified, these patients should start with a dose reduction in the 6-MP level by 30–70% [53]. Notably, the FDA now recommends testing for the most commonly identified inactive SNP genotype, which can prospectively predict patients at higher risk of developing 6-MP-induced hematopoietic toxicity [16, 49, 50]. It is most useful in ALL protocols containing high doses 6-MP (>50 mg/m2/day) [5]. At St Jude Children’s Research Hospital, TPMT gene is evaluated in all patients at the diagnosis of ALL. It has been shown that in the ALL protocol using 6-MP at 75 mg/m2/day, prospective adjustment of 6-MP based on TPMT status allowed successful treatment at reduced dose with comparable toxicity and efficacy to those patients with wild-type TPMT [49, 54, 55].

In addition to TPMT, inosine triphosphate pyrophosphatase (ITPA) is another candidate enzyme involved in 6-MP metabolism. ITPA catalyzes the hydrolysis of inosine triphosphate (ITP) to inosine monophasphate (IMP) [53]. Studies performed by Stocco et al. demonstrated that non-functional ITPA was associated with higher concentrations of methylated nucleotide metabolites of 6-MP in patients’ leukemia cells adjusted for TPMT genotype [55, 56]. A recent report replicated this observation, showing that methylated 6-MP concentrations are higher in wild-type TPMT/variant ITPA patients [57]. Two SNPs associated with defective ITPA gene function, rs1127354 (Pro32Thr) and IVS2+21A>C, were identified in approximately 10% of Caucasians, leading to a higher risk for 6-MP induced toxicity [58, 59]. Therefore, identification of variant ITPA SNPs may be the next pharmacogenomics test adopted into clinical practice.

Methotrexate (MTX)

MTX is a folate inhibitor introduced into clinical practice in the 1950s and remains a major component of approach to ALL therapy. MTX suppresses DNA synthesis by competitively inhibiting the enzyme dihydrofolate reductase (DHFR) thus interrupting thymidine biosynthesis. Multiple transporters and enzymes participate in the metabolism of folate, and many of these demonstrate genetic polymorphisms which may impact the metabolism and activity of MTX [60].

MTX enters cells via a transporter, called reduced folate carrier 1 (RFC-1) or solute carrier family 19 member 1 (SLC19A1) [61]. Impaired function of this transporter has been recognized as a major mechanisms for MTX resistance [62]. A common variant of RFC-1, G80A is associated with decreased inward MTX transportation [63]. Furthermore, Laverdiere et al. demonstrated that pediatric ALL patients with the G80A variant of RFC-1 had worse prognosis manifested by increased relapse rate and decreased EFS, than those carrying the GG genotype [64]. In contrast with these results, other studies failed to reveal a relationship between disease outcome and RFC-1 polymorphisms. These data may be explained by differences in the doses of MTX used in the two studies. At higher dose (5 g/m2 body surface area), MTX can enter cells via passive diffusion, and thus polymorphisms resulting in decreased transporter mediated influx may be less significant [65, 66].

Solute carrier organic anion transporter 1B1 (SLCO1B1) is another MTX carrier mainly located on human hepatocytes. Two SNPs in SLCO1B1, rs11045879 and rs4149081 have been linked to MTX clearance across regimens and with severe gastrointestinal toxicity during consolidation therapy [67]. Subsequent studies from other research groups have validated these SNPs as contributing to clinical outcome [68, 69]. A recent report from Radtke et al. demonstrated that the SLCO1B1 rs4149056 variant was significantly associated with MTX kinetics. MTX area under the concentration time curve (AUC)0–48h increased by 26% in the presence of rs4149056 [65]. From deep re-sequencing of SLCO1B1 exons in 699 children, four common SLCO1B1 haplotypes were associated with the lowest MTX clearance. Differences in this gene can account for 10.7% of the population variability in MTX clearance [70]. Therefore, SLCO1B1 SNPs are significant determinants for MTX toxicity, especially stomatitis and mucositis during consolidation therapy.

Methylenetetrahydrofolate reductase (MTHFR) is the most extensively studied gene in MTX metabolism. It catalyzes the conversion of 5,10-methylene-tetrahydrofolate to 5-methyl-tetrahydrofolate, which serves as a methyl donor to convert homocysteine to methionine [71]. Two SNPs, C677T (rs1901133) resulting in substitution of alanine with valine at codon 222 (Ala222Val) [72] and A1298C (rs1801131) resulting in substitution of alanine for glutamic acid at codon 429 (Glu429Ala) [73] have been related to reduced activity of MTHFR and increased MTX level. Some case reports demonstrated that the C677T (rs1901133) variant induced neurotoxicity [74] and liver toxicity [75], whereas, other publications failed to confirm this relationship [76, 77]. A study that recruited 520 children with ALL demonstrated that the C677T variant allele was significantly associated with relapse without increased risk of toxicity or infection [77]. In the ALL- Berlin-Münster-Frankfurt (BFM) 2000 study population, MTHFR A1298C (rs1801131) was associated with minimal residual disease and shorter EFS, with a hazard ratio of 7.3 [65]. However, Chiusolo et al. reported that the C677T (rs1901133) and A1298C (rs1801131) alleles were not significant in predictors of relapse free survival or EFS in Thai pediatric ALL patients (n=76), but were associated with increased susceptibility to hematopoietic and hepatotoxicity doses ranging from 15–30 mg/m2 [78]. These different results make it difficult to draw any strong conclusions about the role of MTHFR SNPs in predicting MTX toxicity and response. Variability may stem from differences in the treatment protocols across the different studies with inconsistent doses of MTX, small number of patients and other confounding factors, like other SNPs or ethnic heterogeneity between Asian and Northern European patient populations.

Blood MTX levels have not been demonstrated to reliably predict disease outcome [64]. Accumulation of the active metabolites of MTX, however, such as MTX polyglutamates (MTXPGs), have been associated with anti-leukemic activity [7, 11, 71]. MTX and MTXPG inhibit TYMS and subsequently suppress DNA synthesis. Double or triple tandem repeats of TYMS gene participate in enhancing TYMS expression and activity and thus have been postulated to result in MTX resistance. Krajinovic et al. studied 205 children with ALL who were treated with MTX and showed that individuals who were homozygous for triple repeats (3R) had worse outcome when compared with children with other genotypes [79]. A subsequent study extended to 259 children with ALL confirmed the finding that 3R increased the risk of relapse and fatal outcome [80]. By contrast, results from Lauten et al. did not demonstrate a relationship between TYMS 3R polymorphism and ALL relapse, making this association ambiguous [81]. To date, the association between the TYMS gene polymorphisms and ALL outcomes remains uncertain.

Although most of the studies in the literature have focused exclusively on coding genes, corresponding to only 1.5% of the entire genome, emerging data has supported the importance of microRNAs (miRNAs), small non-coding RNAs that regulate gene expression in a post-transcriptional manner in ALL. miRNAs can regulate genes involved in drug transportation, metabolism and targeting. Consequently, studies of variant miRNAs in patients may shed further light on new aspects of drug-resistance. For example, SNP 829C>T, near the miR-24 binding site of DHFR, causes elevation of DHFR expression [82]. The ATP-binding cassette sub-family C (ABCC), which are efflux MTX transporters, is down-regulated by miRNA SNPs, leading to increased MTX levels. Similarly, up-regulation of miR-453 decreases the activity of ABCC1, ABCB1, ABCC2 and ABCC4 genes, leading to increased MTX levels and toxicity [83]. Presence of the SNP of rs639174 in DROSHA gene, which encodes the enzyme RNAse III processing miRNA, was related to gastrointestinal toxicity induced by MTX in pediatric B-cell ALL patients. This study was the first to demonstrate a potential role for polymorphisms in miRNA processing genes to predict for toxicity in ALL management [84]. Further studies of miRNA, epigenetics and genome-wide screening will better elucidate the individual variability in MTX efficacy and toxicity.

Vincristine

Vincristine binds to tubulin dimers, interfering with microtubule formation and thereby mitotic spindle dynamics, and resulting in mitotic arrest and leukemic cell death in metaphase. Vincristine-induced neurotoxicity, characterized by constipation and motorsensory dysfunction remains a serious and largely unpredictable problem for patients with ALL. The cytochrome P450 enzyme (CYP) 3A5 is responsible for 55–59% of total vincristine metabolism [85]. An early study revealing variable grades of neurotoxicity between Caucasians (34.8%) and African-Americans (4.8%) suggested a role for polymorphisms in CYP3A5 in vincristine-induced toxicities [86]. Another study involving 616 pediatric ALL patients did not find an association between EFS and CYP3A5 polymorphisms in ALL patients [87]. However, a sub-group evaluation from this study demonstrated that in T-cell ALL patients the CYP3A5*36986A>G allele, which leads to low expression of CYP3A5, had an eight times higher relapse rate, indicating a specific role for CYP3A5 in T-cell ALL [87]. In pre-B ALL, expression of CYP3A5 was associated with less vincristine-induced peripheral neuropathy compared to non-expressors [88]. This effect may be achieved by a lower ratio of vincristine to its’ primary metabolite (M1) [88]. Despite these intriguing results, two other studies, which enrolled a total of 86 patients, and evaluated the presence of CYP3A5*3, CYP3A5*6 and ABCB1 SNPs failed to confirm a significant association with the occurrence of vincristine-induced side effects [8991]. These studies are limited due to the small number of patients included. In a recent abstract, investigators performed genome-wide SNP analysis in 321 pediatric ALL patients and demonstrated that variants of rs924607 localized to chromosome 5 within the promoter region of centrosomal protein of 72 kDa (CEP72), were linked to altered risks of vincristine-induced neuropathy [92]. Larger scale prospective studies, including a wider range of genotypic variants, are needed to address which SNPs best predict vincristine-induced neurotoxicity in ALL patients.

Tyrosine kinase inhibitor (TKI)

The Philadelphia chromosome (Ph) is the most common cytogenetic aberration in adult ALL. Translocation of genetic material between chromosomes 9 and 22 [t(9,22)(q34;q11)] produces a fusion gene BCR-ABL1, which result in a constitutively active tyrosine kinase [4]. Only 5% of children and those younger than 20 demonstrate Ph-chromosome positive ALL; but, the incidence increases to 33% in patients 20–40 years, 49% in those over 40 years and decreases to 35% in those over 60 years [4, 93, 94]. Combining the BCR-ABL1 inhibitor, imatinib, with conventional chemotherapy has increased the complete remission (CR) rate in these patients to 95%, and improved 3-year overall survival (OS) rate to >50%. Fielding et al. demonstrated that the inclusion of imatinib resulted in a significant improvement in long-term outcomes using a large database of clinical trials for Ph-positive ALL conducted prior to and after the development of imatinib therapy in the United Kingdom [95]. The 4-year OS was 38% in the imatinib cohort as compared with 22% in the chemotherapy only cohort [95]. Despite these results, Ph+ ALL patients exhibit heterogeneous responses to TKIs. This has been attributed to the presence of additional genetic abnormalities, for example, the Ikaros family zinic finger protein 1 (IKZF1) gene deletion [96], novel BCR-ABL1 gene mutations, or disruption of drug transportation [4].

Patients have also demonstrated wide inter-individual variability in the metabolism of imatinib which is mediated by CYP3A4/5 [97]. Although a number of polymorphisms in genes affecting drug transport and DNA repair have been associated with drug efficacy [98, 99], pharmacogenetic studies of toxicity are rare. While patients with the TT genotype of ABCB1 gene loci 1236, 2677 and 3435 demonstrated higher drug clearance rate, individuals without these SNPs also did not demonstrate any significant toxicity related to higher drug levels [100]. Several reports have shown that CYP2D6*4 [101] or ABCG2421A variant alleles [102] may contribute to increased adverse effects. However, these data are not convincing enough to be conclusive, and most of the studies were performed in patients with chronic myeloid leukemia (CML) or gastrointestinal stromal tumors, not Ph+ ALL. It is important to note that, in contrast to CML, responses to imatinib in patients with Ph+ ALL are generally short-lived with high rates of relapse. When they do so, many of leukemia cells demonstrate novel point mutations in the BCR-ABL1 kinase or adjacent domain rendering them resistance to imatinib therapy [4, 103]. Although second-generation BCR-ABL1 TKIs, such as dasatinib and nilotinib, appear to be safe and efficacious in imatinib resistant ALL patients, the emergence of T315I and other resistance conferring BCR-ABL1 mutations, lead to treatment failure [104]. More research is needed in order to better personalize TKI management in the treatment of Ph+ ALL.

Perspectives

Substantial changes have occurred in ALL therapy over the last several decades, with significant improvements in prognosis for patients with adult ALL. These successes are partially based on the progress in genetics and the incorporation of pharmacogenomics. New risk stratification, personalized regimens and therapeutic modification based upon insights into drug clearance ideally should be integrated with SNP genotypes and genetics testing to help us better predict therapy response and avoid drug toxicity. The FDA currently recommends genetic testing of TPMT for all patients who will be treated with high dose 6-MP in order to prevent hematopoietic toxicity. Despite these recommendations, the use of genetic testing to best individualize therapy is not universal. Among the barriers responsible for a failure to adopt such testing are inadequate recognition of the clinical benefits for patient care, high cost, concerns about the ethical implication of these data, and the technical challenges/availability of the tests. Additionally, pharmacogenomics alone will likely be insufficient to explain all of the variability. There may be some nihilism about the potential benefits of such testing. The application of pharmacogenomics remains a challenge; however these data support the proposition that this area warrants further research. We anticipate that in the future molecular profiles will help tailor individualized ALL therapy. Indeed, the future may be upon us since the group at St. Jude Children’s Research Hospital have developed a systemic approach and incorporated pharmacogenetics testing, including TPMT, CYP2D6, SLCO1B1 and CYP2C19, into their most recent prospective ALL protocol (PG4KDS), providing a model for what is possible in clinical practice [105].

Acknowledgments

Supported partially by grants from the National Cancer Institute Grant CA16056 (LM, EPO, EAG, JET, ESW, MW), the Szefel Foundation, Roswell Park Cancer Institute, the Leonard S. LuVullo Endowment for Leukemia Research, the Nancy C. Cully Endowment for Leukemia Research, the Babcock Family Endowment and the Heidi Leukemia Research Fund, Buffalo, NY. EW is also supported by Cancer Clinical Investigator Team Leadership Award (CCITLA) awarded by National Cancer Institute through a supplement to P30CA016056.

Footnotes

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Conflict of interest

Dr. Meir Wetzler is a consultant for Sigma Tau, Jazz Pharmaceuticals and Novartis.

Dr. Elizabeth Griffiths is a consultant for Alexion Pharmaceuticals, Norvartis and Celgene and receives grant funding from Astex Pharmaceuticals.

Dr. Eunice Wang has received consultancy fees from Spectrum Pharmaceuticals.

The other coauthors declare no conflict of interest.

References

1. Jaffe ES. Pathology and genetics of tumours of haematopoietic and lymphoid tissues. Lyon; Washington, D.C: IARC Press; 2001.
2. Swerdlow SH, International Agency for Research on Cancer World Health Organization . WHO classification of tumours of haematopoietic and lymphoid tissues. 4. Lyon, France: International Agency for Research on Cancer; 2008.
3. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63:11–30. [PubMed]
4. Lee HJ, Thompson JE, Wang ES, Wetzler M. Philadelphia chromosome-positive acute lymphoblastic leukemia: current treatment and future perspectives. Cancer. 2011;117:1583–94. [PubMed]
5. Pui CH, Robison LL, Look AT. Acute lymphoblastic leukaemia. Lancet. 2008;371:1030–43. [PubMed]
6. Hunger SP, Lu X, Devidas M, Camitta BM, Gaynon PS, Winick NJ, et al. Improved survival for children and adolescents with acute lymphoblastic leukemia between 1990 and 2005: a report from the children’s oncology group. J Clin Oncol. 2012;30:1663–9. [PMC free article] [PubMed]
7. Inaba H, Greaves M, Mullighan CG. Acute lymphoblastic leukaemia. Lancet. 2013;381:1943–55. [PMC free article] [PubMed]
8. Alvarnas JC, Brown PA, Aoun P, Ballen KK, Bellam N, Blum W, et al. Acute lymphoblastic leukemia. J Natl Compr Canc Netw. 2012;10:858–914. [PubMed]
9. Yang JJ, Cheng C, Devidas M, Cao X, Fan Y, Campana D, et al. Ancestry and pharmacogenomics of relapse in acute lymphoblastic leukemia. Nat Genet. 2011;43:237–41. [PMC free article] [PubMed]
10. Pieters R, Hunger SP, Boos J, Rizzari C, Silverman L, Baruchel A, et al. L-asparaginase treatment in acute lymphoblastic leukemia: a focus on Erwinia asparaginase. Cancer. 2011;117:238–49. [PMC free article] [PubMed]
11. Gervasini G, Vagace JM. Impact of genetic polymorphisms on chemotherapy toxicity in childhood acute lymphoblastic leukemia. Front Genet. 2012;3:249. [PMC free article] [PubMed]
12. Zeidan A, Wang ES, Wetzler M. Pegasparaginase: where do we stand? Expert Opin Biol Ther. 2009;9:111–9. [PubMed]
13. Avramis VI, Sencer S, Periclou AP, Sather H, Bostrom BC, Cohen LJ, et al. A randomized comparison of native Escherichia coli asparaginase and polyethylene glycol conjugated asparaginase for treatment of children with newly diagnosed standard-risk acute lymphoblastic leukemia: a Children’s Cancer Group study. Blood. 2002;99:1986–94. [PubMed]
14. Panosyan EH, Seibel NL, Martin-Aragon S, Gaynon PS, Avramis IA, Sather H, et al. Asparaginase antibody and asparaginase activity in children with higher-risk acute lymphoblastic leukemia: Children’s Cancer Group Study CCG-1961. J Pediatr Hematol Oncol. 2004;26:217–26. [PubMed]
15. Molineux G. Pegylation: engineering improved biopharmaceuticals for oncology. Pharmacotherapy. 2003;23:3S–8S. [PubMed]
16. Paugh SW, Stocco G, Evans WE. Pharmacogenomics in pediatric leukemia. Curr Opin Pediatr. 2010;22:703–10. [PMC free article] [PubMed]
17. Avramis VI, Panosyan EH. Pharmacokinetic/pharmacodynamic relationships of asparaginase formulations: the past, the present and recommendations for the future. Clin Pharmacokinet. 2005;44:367–93. [PubMed]
18. Tong WH, Pieters R, Kaspers GJ, te Loo DM, Bierings MB, van den Bos C, et al. A prospective study on drug monitoring of PEGasparaginase and Erwinia asparaginase and asparaginase antibodies in pediatric acute lymphoblastic leukemia. Blood. 2014;123:2026–33. [PubMed]
19. Su N, Pan YX, Zhou M, Harvey RC, Hunger SP, Kilberg MS. Correlation between asparaginase sensitivity and asparagine synthetase protein content, but not mRNA, in acute lymphoblastic leukemia cell lines. Pediatr Blood Cancer. 2008;50:274–9. [PubMed]
20. Hutson RG, Kitoh T, Moraga Amador DA, Cosic S, Schuster SM, Kilberg MS. Amino acid control of asparagine synthetase: relation to asparaginase resistance in human leukemia cells. Am J Physiol. 1997;272:C1691–9. [PubMed]
21. Rousseau J, Gagne V, Labuda M, Beaubois C, Sinnett D, Laverdiere C, et al. ATF5 polymorphisms influence ATF function and response to treatment in children with childhood acute lymphoblastic leukemia. Blood. 2011;118:5883–90. [PubMed]
22. Pastorczak A, Fendler W, Zalewska-Szewczyk B, Gorniak P, Lejman M, Trelinska J, et al. Asparagine synthetase (ASNS) gene polymorphism is associated with the outcome of childhood acute lymphoblastic leukemia by affecting early response to treatment. Leuk Res. 2014;38:180–3. [PubMed]
23. Chen SH, Pei D, Yang W, Cheng C, Jeha S, Cox NJ, et al. Genetic variations in GRIA1 on chromosome 5q33 related to asparaginase hypersensitivity. Clin Pharmacol Ther. 2010;88:191–6. [PMC free article] [PubMed]
24. Franco R, Pacheco R, Lluis C, Ahern GP, O’Connell PJ. The emergence of neurotransmitters as immune modulators. Trends Immunol. 2007;28:400–7. [PubMed]
25. Fernandez CA, Smith C, Yang W, Date M, Bashford D, Larsen E, et al. HLA-DRB1*07:01 is associated with a higher risk of asparaginase allergies. Blood. 2014;124:1266–76. [PubMed]
26. Mallal S, Phillips E, Carosi G, Molina JM, Workman C, Tomazic J, et al. HLA-B*5701 screening for hypersensitivity to abacavir. N Engl J Med. 2008;358:568–79. [PubMed]
27. Pavlos R, Mallal S, Phillips E. HLA and pharmacogenetics of drug hypersensitivity. Pharmacogenomics. 2012;13:1285–306. [PubMed]
28. Hoffmeyer S, Burk O, von Richter O, Arnold HP, Brockmoller J, Johne A, et al. Functional polymorphisms of the human multidrug-resistance gene: multiple sequence variations and correlation of one allele with P-glycoprotein expression and activity in vivo. Proc Natl Acad Sci U S A. 2000;97:3473–8. [PubMed]
29. Maeda K, Sugiyama Y. Impact of genetic polymorphisms of transporters on the pharmacokinetic, pharmacodynamic and toxicological properties of anionic drugs. Drug Metab Pharmacokinet. 2008;23:223–35. [PubMed]
30. Tanabe M, Ieiri I, Nagata N, Inoue K, Ito S, Kanamori Y, et al. Expression of P-glycoprotein in human placenta: relation to genetic polymorphism of the multidrug resistance (MDR)-1 gene. J Pharmacol Exp Ther. 2001;297:1137–43. [PubMed]
31. Lauten M, Matthias T, Stanulla M, Beger C, Welte K, Schrappe M. Association of initial response to prednisone treatment in childhood acute lymphoblastic leukaemia and polymorphisms within the tumour necrosis factor and the interleukin-10 genes. Leukemia. 2002;16:1437–42. [PubMed]
32. Marino S, Verzegnassi F, Tamaro P, Stocco G, Bartoli F, Decorti G, et al. Response to glucocorticoids and toxicity in childhood acute lymphoblastic leukemia: role of polymorphisms of genes involved in glucocorticoid response. Pediatr Blood Cancer. 2009;53:984–91. [PubMed]
33. Meissner B, Stanulla M, Ludwig WD, Harbott J, Moricke A, Welte K, et al. The GSTT1 deletion polymorphism is associated with initial response to glucocorticoids in childhood acute lymphoblastic leukemia. Leukemia. 2004;18:1920–3. [PubMed]
34. Pottier N, Yang W, Assem M, Panetta JC, Pei D, Paugh SW, et al. The SWI/SNF chromatin-remodeling complex and glucocorticoid resistance in acute lymphoblastic leukemia. J Natl Cancer Inst. 2008;100:1792–803. [PMC free article] [PubMed]
35. Real PJ, Tosello V, Palomero T, Castillo M, Hernando E, de Stanchina E, et al. Gamma-secretase inhibitors reverse glucocorticoid resistance in T cell acute lymphoblastic leukemia. Nat Med. 2009;15:50–8. [PMC free article] [PubMed]
36. Hulleman E, Kazemier KM, Holleman A, VanderWeele DJ, Rudin CM, Broekhuis MJ, et al. Inhibition of glycolysis modulates prednisolone resistance in acute lymphoblastic leukemia cells. Blood. 2009;113:2014–21. [PubMed]
37. Hundsdoerfer P, Dietrich I, Schmelz K, Eckert C, Henze G. XIAP expression is post-transcriptionally upregulated in childhood ALL and is associated with glucocorticoid response in T-cell ALL. Pediatr Blood Cancer. 2010;55:260–6. [PubMed]
38. Jones CL, Bhatla T, Blum R, Wang J, Paugh SW, Wen X, et al. Loss of TBL1XR1 disrupts glucocorticoid receptor recruitment to chromatin and results in glucocorticoid resistance in a B-lymphoblastic leukemia model. J Biol Chem. 2014;289:20502–15. [PMC free article] [PubMed]
39. Aries IM, Jerchel IS, van den Dungen RE, van den Berk LC, Boer JM, Horstmann MA, et al. EMP1, a novel poor prognostic factor in pediatric leukemia regulates prednisolone resistance, cell proliferation, migration and adhesion. Leukemia. 2014;28:1828–37. [PubMed]
40. Kamdem LK, Hamilton L, Cheng C, Liu W, Yang W, Johnson JA, et al. Genetic predictors of glucocorticoid-induced hypertension in children with acute lymphoblastic leukemia. Pharmacogenet Genomics. 2008;18:507–14. [PubMed]
41. Jones TS, Kaste SC, Liu W, Cheng C, Yang W, Tantisira KG, et al. CRHR1 polymorphisms predict bone density in survivors of acute lymphoblastic leukemia. J Clin Oncol. 2008;26:3031–7. [PubMed]
42. Mattano LA, Jr, Sather HN, Trigg ME, Nachman JB. Osteonecrosis as a complication of treating acute lymphoblastic leukemia in children: a report from the Children’s Cancer Group. J Clin Oncol. 2000;18:3262–72. [PubMed]
43. Meeker ND, Yang JJ, Schiffman JD. Pharmacogenomics of pediatric acute lymphoblastic leukemia. Expert Opin Pharmacother. 2010;11:1621–32. [PubMed]
44. Relling MV, Yang W, Das S, Cook EH, Rosner GL, Neel M, et al. Pharmacogenetic risk factors for osteonecrosis of the hip among children with leukemia. J Clin Oncol. 2004;22:3930–6. [PubMed]
45. French D, Hamilton LH, Mattano LA, Jr, Sather HN, Devidas M, Nachman JB, et al. A PAI-1 (SERPINE1) polymorphism predicts osteonecrosis in children with acute lymphoblastic leukemia: a report from the Children’s Oncology Group. Blood. 2008;111:4496–9. [PubMed]
46. Kawedia JD, Kaste SC, Pei D, Panetta JC, Cai X, Cheng C, et al. Pharmacokinetic, pharmacodynamic, and pharmacogenetic determinants of osteonecrosis in children with acute lymphoblastic leukemia. Blood. 2011;117:2340–7. quiz 556. [PubMed]
47. Vallance K, Liu W, Mandrell BN, Panetta JC, Gattuso JS, Hockenberry M, et al. Mechanisms of dexamethasone-induced disturbed sleep and fatigue in paediatric patients receiving treatment for ALL. Eur J Cancer. 2010;46:1848–55. [PMC free article] [PubMed]
48. Landier W, Hageman L, Sun C-L, Kim H, Kornegay N, Evans WE, et al. High Intra-Individual Variability In Systemic Exposure To 6 Mercaptopurine (6MP) In Children With Acute Lymphoblastic Leukemia (ALL) Contributes To ALL Relapse: Results From a Children’s Oncology Group (COG) Study (AALL03N1) Blood. 2013;122:59.
49. Paugh SW, Stocco G, McCorkle JR, Diouf B, Crews KR, Evans WE. Cancer pharmacogenomics. Clin Pharmacol Ther. 2011;90:461–6. [PMC free article] [PubMed]
50. Relling MV, Gardner EE, Sandborn WJ, Schmiegelow K, Pui CH, Yee SW, et al. Clinical Pharmacogenetics Implementation Consortium guidelines for thiopurine methyltransferase genotype and thiopurine dosing. Clin Pharmacol Ther. 2011;89:387–91. [PMC free article] [PubMed]
51. Pui CH, Relling MV, Downing JR. Acute lymphoblastic leukemia. N Engl J Med. 2004;350:1535–48. [PubMed]
52. Lennard L, Lilleyman JS. Individualizing therapy with 6-mercaptopurine and 6-thioguanine related to the thiopurine methyltransferase genetic polymorphism. Ther Drug Monit. 1996;18:328–34. [PubMed]
53. Stocco G, Franca R, Verzegnassi F, Londero M, Rabusin M, Decorti G. Multilocus genotypes of relevance for drug metabolizing enzymes and therapy with thiopurines in patients with acute lymphoblastic leukemia. Front Genet. 2012;3:309. [PMC free article] [PubMed]
54. Pui CH, Sandlund JT, Pei D, Campana D, Rivera GK, Ribeiro RC, et al. Improved outcome for children with acute lymphoblastic leukemia: results of Total Therapy Study XIIIB at St Jude Children’s Research Hospital. Blood. 2004;104:2690–6. [PubMed]
55. Stocco G, Crews KR, Evans WE. Genetic polymorphism of inosine-triphosphate-pyrophosphatase influences mercaptopurine metabolism and toxicity during treatment of acute lymphoblastic leukemia individualized for thiopurine-S-methyl-transferase status. Expert Opin Drug Saf. 2010;9:23–37. [PubMed]
56. Stocco G, Cheok MH, Crews KR, Dervieux T, French D, Pei D, et al. Genetic polymorphism of inosine triphosphate pyrophosphatase is a determinant of mercaptopurine metabolism and toxicity during treatment for acute lymphoblastic leukemia. Clin Pharmacol Ther. 2009;85:164–72. [PMC free article] [PubMed]
57. Adam de Beaumais T, Dervieux T, Fakhoury M, Medard Y, Azougagh S, Zhang D, et al. The impact of high-dose methotrexate on intracellular 6-mercaptopurine disposition during interval therapy of childhood acute lymphoblastic leukemia. Cancer Chemother Pharmacol. 2010;66:653–8. [PubMed]
58. Adam de Beaumais T, Jacqz-Aigrain E. Pharmacogenetic determinants of mercaptopurine disposition in children with acute lymphoblastic leukemia. Eur J Clin Pharmacol. 2012;68:1233–42. [PubMed]
59. Heller T, Oellerich M, Armstrong VW, von Ahsen N. Rapid detection of ITPA 94C>A and IVS2 + 21A>C gene mutations by real-time fluorescence PCR and in vitro demonstration of effect of ITPA IVS2 + 21A>C polymorphism on splicing efficiency. Clin Chem. 2004;50:2182–4. [PubMed]
60. Gervasini G. Polymorphisms in methotrexate pathways: what is clinically relevant, what is not, and what is promising. Curr Drug Metab. 2009;10:547–66. [PubMed]
61. Moscow JA, Gong M, He R, Sgagias MK, Dixon KH, Anzick SL, et al. Isolation of a gene encoding a human reduced folate carrier (RFC1) and analysis of its expression in transport-deficient, methotrexate-resistant human breast cancer cells. Cancer Res. 1995;55:3790–4. [PubMed]
62. Gorlick R, Goker E, Trippett T, Waltham M, Banerjee D, Bertino JR. Intrinsic and acquired resistance to methotrexate in acute leukemia. N Engl J Med. 1996;335:1041–8. [PubMed]
63. Chango A, Emery-Fillon N, de Courcy GP, Lambert D, Pfister M, Rosenblatt DS, et al. A polymorphism (80G->A) in the reduced folate carrier gene and its associations with folate status and homocysteinemia. Mol Genet Metab. 2000;70:310–5. [PubMed]
64. Laverdiere C, Chiasson S, Costea I, Moghrabi A, Krajinovic M. Polymorphism G80A in the reduced folate carrier gene and its relationship to methotrexate plasma levels and outcome of childhood acute lymphoblastic leukemia. Blood. 2002;100:3832–4. [PubMed]
65. Radtke S, Zolk O, Renner B, Paulides M, Zimmermann M, Moricke A, et al. Germline genetic variations in methotrexate candidate genes are associated with pharmacokinetics, toxicity, and outcome in childhood acute lymphoblastic leukemia. Blood. 2013;121:5145–53. [PubMed]
66. Pakakasama S, Kanchanakamhaeng K, Kajanachumpol S, Udomsubpayakul U, Sirachainan N, Thithapandha A, et al. Genetic polymorphisms of folate metabolic enzymes and toxicities of high dose methotrexate in children with acute lymphoblastic leukemia. Ann Hematol. 2007;86:609–11. [PubMed]
67. Trevino LR, Shimasaki N, Yang W, Panetta JC, Cheng C, Pei D, et al. Germline genetic variation in an organic anion transporter polypeptide associated with methotrexate pharmacokinetics and clinical effects. J Clin Oncol. 2009;27:5972–8. [PMC free article] [PubMed]
68. Ramsey LB, Panetta JC, Smith C, Yang W, Fan Y, Winick NJ, et al. Genome-wide study of methotrexate clearance replicates SLCO1B1. Blood. 2013;121:898–904. [PubMed]
69. Lopez-Lopez E, Martin-Guerrero I, Ballesteros J, Pinan MA, Garcia-Miguel P, Navajas A, et al. Polymorphisms of the SLCO1B1 gene predict methotrexate-related toxicity in childhood acute lymphoblastic leukemia. Pediatr Blood Cancer. 2011;57:612–9. [PubMed]
70. Ramsey LB, Bruun GH, Yang W, Trevino LR, Vattathil S, Scheet P, et al. Rare versus common variants in pharmacogenetics: SLCO1B1 variation and methotrexate disposition. Genome Res. 2012;22:1–8. [PubMed]
71. Kodidela S, Suresh Chandra P, Dubashi B. Pharmacogenetics of methotrexate in acute lymphoblastic leukaemia: why still at the bench level? Eur J Clin Pharmacol. 2014;70:253–60. [PubMed]
72. Kantar M, Kosova B, Cetingul N, Gumus S, Toroslu E, Zafer N, et al. Methylenetetrahydrofolate reductase C677T and A1298C gene polymorphisms and therapy-related toxicity in children treated for acute lymphoblastic leukemia and non-Hodgkin lymphoma. Leuk Lymphoma. 2009;50:912–7. [PubMed]
73. D’Angelo V, Ramaglia M, Iannotta A, Crisci S, Indolfi P, Francese M, et al. Methotrexate toxicity and efficacy during the consolidation phase in paediatric acute lymphoblastic leukaemia and MTHFR polymorphisms as pharmacogenetic determinants. Cancer Chemother Pharmacol. 2011;68:1339–46. [PubMed]
74. Vagace JM, de la Maya MD, Caceres-Marzal C, Gonzalez de Murillo S, Gervasini G. Central nervous system chemotoxicity during treatment of pediatric acute lymphoblastic leukemia/lymphoma. Crit Rev Oncol Hematol. 2012;84:274–86. [PubMed]
75. Tanaka Y, Manabe A, Nakadate H, Kondoh K, Nakamura K, Koh K, et al. Methylenetetrahydrofolate reductase gene haplotypes affect toxicity during maintenance therapy for childhood acute lymphoblastic leukemia in Japanese patients. Leuk Lymphoma. 2014;55:1126–31. [PubMed]
76. Kishi S, Griener J, Cheng C, Das S, Cook EH, Pei D, et al. Homocysteine, pharmacogenetics, and neurotoxicity in children with leukemia. J Clin Oncol. 2003;21:3084–91. [PubMed]
77. Aplenc R, Thompson J, Han P, La M, Zhao H, Lange B, et al. Methylenetetrahydrofolate reductase polymorphisms and therapy response in pediatric acute lymphoblastic leukemia. Cancer Res. 2005;65:2482–7. [PubMed]
78. Chiusolo P, Reddiconto G, Farina G, Mannocci A, Fiorini A, Palladino M, et al. MTHFR polymorphisms’ influence on outcome and toxicity in acute lymphoblastic leukemia patients. Leuk Res. 2007;31:1669–74. [PubMed]
79. Krajinovic M, Costea I, Chiasson S. Polymorphism of the thymidylate synthase gene and outcome of acute lymphoblastic leukaemia. Lancet. 2002;359:1033–4. [PubMed]
80. Krajinovic M, Costea I, Primeau M, Dulucq S, Moghrabi A. Combining several polymorphisms of thymidylate synthase gene for pharmacogenetic analysis. Pharmacogenomics J. 2005;5:374–80. [PubMed]
81. Lauten M, Asgedom G, Welte K, Schrappe M, Stanulla M. Thymidylate synthase gene polymorphism and its association with relapse in childhood B-cell precursor acute lymphoblastic leukemia. Haematologica. 2003;88:353–4. [PubMed]
82. Mishra PJ, Humeniuk R, Mishra PJ, Longo-Sorbello GS, Banerjee D, Bertino JR. A miR-24 microRNA binding-site polymorphism in dihydrofolate reductase gene leads to methotrexate resistance. Proc Natl Acad Sci U S A. 2007;104:13513–8. [PubMed]
83. Lopez-Lopez E, Ballesteros J, Pinan MA, Sanchez de Toledo J, Garcia de Andoin N, Garcia-Miguel P, et al. Polymorphisms in the methotrexate transport pathway: a new tool for MTX plasma level prediction in pediatric acute lymphoblastic leukemia. Pharmacogenet Genomics. 2013;23:53–61. [PubMed]
84. Lopez-Lopez E, Gutierrez-Camino A, Pinan MA, Sanchez-Toledo J, Uriz JJ, Ballesteros J, et al. Pharmacogenetics of microRNAs and microRNAs biogenesis machinery in pediatric acute lymphoblastic leukemia. PLoS One. 2014;9:e91261. [PMC free article] [PubMed]
85. Dennison JB, Kulanthaivel P, Barbuch RJ, Renbarger JL, Ehlhardt WJ, Hall SD. Selective metabolism of vincristine in vitro by CYP3A5. Drug Metab Dispos. 2006;34:1317–27. [PubMed]
86. Renbarger JL, McCammack KC, Rouse CE, Hall SD. Effect of race on vincristine-associated neurotoxicity in pediatric acute lymphoblastic leukemia patients. Pediatr Blood Cancer. 2008;50:769–71. [PubMed]
87. Borst L, Wallerek S, Dalhoff K, Rasmussen KK, Wesenberg F, Wehner PS, et al. The impact of CYP3A5*3 on risk and prognosis in childhood acute lymphoblastic leukemia. Eur J Haematol. 2011;86:477–83. [PubMed]
88. Egbelakin A, Ferguson MJ, MacGill EA, Lehmann AS, Topletz AR, Quinney SK, et al. Increased risk of vincristine neurotoxicity associated with low CYP3A5 expression genotype in children with acute lymphoblastic leukemia. Pediatr Blood Cancer. 2011;56:361–7. [PMC free article] [PubMed]
89. Hartman A, van Schaik RH, van der Heiden IP, Broekhuis MJ, Meier M, den Boer ML, et al. Polymorphisms in genes involved in vincristine pharmacokinetics or pharmacodynamics are not related to impaired motor performance in children with leukemia. Leuk Res. 2010;34:154–9. [PubMed]
90. Plasschaert SL, Groninger E, Boezen M, Kema I, de Vries EG, Uges D, et al. Influence of functional polymorphisms of the MDR1 gene on vincristine pharmacokinetics in childhood acute lymphoblastic leukemia. Clin Pharmacol Ther. 2004;76:220–9. [PubMed]
91. Moore AS, Norris R, Price G, Nguyen T, Ni M, George R, et al. Vincristine pharmacodynamics and pharmacogenetics in children with cancer: a limited-sampling, population modelling approach. J Paediatr Child Health. 2011;47:875–82. [PubMed]
92. Crews K, Lew G, Pei D, Cheng C, Bao J, Zheng J, et al. Genome-Wide Association Analyses Identify Susceptibility Loci For Vincristine-Induced Peripheral Neuropathy In Children With Acute Lymphoblastic Leukemia. Blood. 2013;122:618.
93. Moorman AV, Harrison CJ, Buck GA, Richards SM, Secker-Walker LM, Martineau M, et al. Karyotype is an independent prognostic factor in adult acute lymphoblastic leukemia (ALL): analysis of cytogenetic data from patients treated on the Medical Research Council (MRC) UKALLXII/Eastern Cooperative Oncology Group (ECOG) 2993 trial. Blood. 2007;109:3189–97. [PubMed]
94. Wetzler M, Dodge RK, Mrozek K, Carroll AJ, Tantravahi R, Block AW, et al. Prospective karyotype analysis in adult acute lymphoblastic leukemia: the cancer and leukemia Group B experience. Blood. 1999;93:3983–93. [PubMed]
95. Fielding AK, Rowe JM, Buck G, Foroni L, Gerrard G, Litzow MR, et al. UKALLXII/ECOG2993: addition of imatinib to a standard treatment regimen enhances long-term outcomes in Philadelphia positive acute lymphoblastic leukemia. Blood. 2014;123:843–50. [PubMed]
96. van der Veer A, Zaliova M, Mottadelli F, De Lorenzo P, Te Kronnie G, Harrison CJ, et al. IKZF1 status as a prognostic feature in BCR-ABL1-positive childhood ALL. Blood. 2014;123:1691–8. [PubMed]
97. Judson I, Ma P, Peng B, Verweij J, Racine A, di Paola ED, et al. Imatinib pharmacokinetics in patients with gastrointestinal stromal tumour: a retrospective population pharmacokinetic study over time. EORTC Soft Tissue and Bone Sarcoma Group. Cancer Chemother Pharmacol. 2005;55:379–86. [PubMed]
98. Kong JH, Mun YC, Kim S, Choi HS, Kim YK, Kim HJ, et al. Polymorphisms of ERCC1 genotype associated with response to imatinib therapy in chronic phase chronic myeloid leukemia. Int J Hematol. 2012;96:327–33. [PubMed]
99. Vivona D, Bueno CT, Lima LT, Hirata RD, Hirata MH, Luchessi AD, et al. ABCB1 haplotype is associated with major molecular response in chronic myeloid leukemia patients treated with standard-dose of imatinib. Blood Cells Mol Dis. 2012;48:132–6. [PubMed]
100. Gurney H, Wong M, Balleine RL, Rivory LP, McLachlan AJ, Hoskins JM, et al. Imatinib disposition and ABCB1 (MDR1, P-glycoprotein) genotype. Clin Pharmacol Ther. 2007;82:33–40. [PubMed]
101. Gardner ER, Burger H, van Schaik RH, van Oosterom AT, de Bruijn EA, Guetens G, et al. Association of enzyme and transporter genotypes with the pharmacokinetics of imatinib. Clin Pharmacol Ther. 2006;80:192–201. [PubMed]
102. Petain A, Kattygnarath D, Azard J, Chatelut E, Delbaldo C, Geoerger B, et al. Population pharmacokinetics and pharmacogenetics of imatinib in children and adults. Clin Cancer Res. 2008;14:7102–9. [PubMed]
103. Hofmann WK, Jones LC, Lemp NA, de Vos S, Gschaidmeier H, Hoelzer D, et al. Ph(+) acute lymphoblastic leukemia resistant to the tyrosine kinase inhibitor STI571 has a unique BCR-ABL gene mutation. Blood. 2002;99:1860–2. [PubMed]
104. Soverini S, De Benedittis C, Papayannidis C, Paolini S, Venturi C, Iacobucci I, et al. Drug resistance and BCR-ABL kinase domain mutations in Philadelphia chromosome-positive acute lymphoblastic leukemia from the imatinib to the second-generation tyrosine kinase inhibitor era: The main changes are in the type of mutations, but not in the frequency of mutation involvement. Cancer. 2014;120:1002–9. [PubMed]
105. Hoffman JM, Haidar CE, Wilkinson MR, Crews KR, Baker DK, Kornegay NM, et al. PG4KDS: a model for the clinical implementation of pre-emptive pharmacogenetics. Am J Med Genet C Semin Med Genet. 2014;166C:45–55. [PMC free article] [PubMed]