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Functional Pharmacogenomics of Childhood Acute Lymphoblastic Leukemia in Taiwan


N/A
1 Year
18 Years
Open (Enrolling)
Both
Leukemia, Lymphocytic, Acute

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Trial Information

Functional Pharmacogenomics of Childhood Acute Lymphoblastic Leukemia in Taiwan


In the 1990s, the five-year event-free survival rates for childhood ALL generally ranged
from 70 to 83 percent in developed countries, with an overall cure rate of approximately 80
percent. Emerging results suggest that a cure rate of nearly 90 percent will be attained in
the near future. Progress in the treatment of ALL, however, has been made largely by the
optimization of the use of existing medicines rather than by the discovery of new agents.
These factors predicting clinical outcomes include treatment regime, clinical features,
global gene expression patterns and genetics of leukemia cells, host pharmacodynamics and
pharmacogenetics, early response to treatment. In Taiwan, detection the most recurrent
fusion gene occurred in ALL were not popular applied yet. Minimal residual disease (MRD)
detection is not commonly available for the evaluation of initial response to chemotherapy
protocol we have assigned. The TPOG (Taiwan Pediatric Oncology Group) use only clinical
features (age, PB white blood counts, immunophenotypes, and cytogenetics) to assign the
protocols. Only around 60-70% of patients were successful treated. The ultimate goal of this
project is to establish the methods for better risk classifications for pediatric ALL
patients in Taiwan in order increase cure rate.

Classification of childhood ALL by molecular methods Risk factors based on a patient's
physical manifestations or hematologic and biochemical tests have been largely replaced by
more specific tests of the biologic features of leukemic cells. The recently introduced
World Health Organization (WHO) classification takes into consideration of morphologic and
immunologic features plus well-studied, common nonrandom chromosomal abnormalities that
clearly influence the laboratory and clinical features of ALL. Genetic makeup of the
leukemic cells has been recognized as the most important prognostic factors in childhood
ALL. The most frequent fusion gene TEL-AML1 (about 25% of the childhood B-ALL) which was
caused by t(12;21) and hyperdiploidy (>50 chromosomes)(accounts for about 25% of B-ALL) were
noticed to be associated with favorable prognosis. The recurrent chromosome translocation
changes/fusion genes t(4;11)/MLL-AF4, t(9:22)/BCR-ABL, t(1;19)/E2A-PBX1 were recognized as
adverse prognostic factors. Recently, treatment of t(1;19) B-ALL with high dose chemotherapy
gave successful results. Cytogenetic analysis has been the standard method for identifying
chromosomal translocations in childhood ALL for many years. However, this approach is
technically difficult and takes at least two weeks to obtain the results. Undetermined
results were inevitable in a substantial proportion of cases. This is most prevalent in
patients with t(12; 21), which is not visible by routine cytogenetics examinations. A
multiplex RT-PCR assay for the detection of common chimeric transcripts TEL-AML1, MLL/AF4,
BCR-ABL , and E2A-PBX1 has been designed to classify pediatric ALL patients. The application
of this assay to routine clinical screening will significantly improve the clinical
diagnosis of childhood ALL.

Prediction of the therapy-resistant leukemia clones---global gene expression pattern of the
leukemic cells Recent work indicates that global gene expression profiling using DNA
microarrays can identify genes with levels of expression that are related to drug response.
Significant differences in the expression of genes involved in cell-cycle regulation, DNA
repair, and apoptosis were noticed between diagnostic and early relapse samples or between
therapy-sensitive and therapy-resistant samples. These discoveries provide means to enhance
classification systems based on relapse hazard and to identify signaling pathways that wound
be potentially targeted with novel therapies. Holleman A et al used microarrays to
investigate the expression of 70 apoptosis genes and revealed that BCL2L13 expression was an
independent prognostic factor. Flotho C et al analyzed gene expression of diagnostic
lymphoblasts and compared the findings with MRD levels on days 19 and 46 of remission
induction therapy. Seventeen genes were identified to be significantly associated with MRD.
Caspase 8-associated protein 2 gene(CASP8AP2) was studied further and showed a strong
relationship with prognosis. The study of Cario et al demonstrated that low expression of
TTK was associated with poorer treatment response and the presence of MRD on both days 19
and 46 after chemotherapy. These studies demonstrated the association of apoptosis pathways
with treatment prognosis and treatment failure. These genes may serve as
functionally-defined risk factor for treatment stratification in addition to the currently
used risk factors.Recent evidence indicates that small non-protein-coding RNA molecules,
microRNAs (miRNAs), might function as tumor suppressors and oncogenes. A recent report by
Cimmino et al showed that miR-15a and miR-16-1 negatively regulate anti-apoptotic gene BCL2.
Therefore, it is thought that the deletion or down-regulation of mir-15a and mir-16-1
promotes leukaemogenesis and lymphomagenesis in haematopoietic cells. These studies hint the
oncogenesis roles the miRNA might play. A report by Sonoki et a. also linked mir-125b-1 with
leukemia. A recent report from Lu J et al. found that the expression profiles of relatively
few miRNAs (~200 genes), accurately classify human cancers. They examined the miRNA profiles
of 73 bone marrow samples obtained from children with acute lymphoblastic leukemia.
Hierarchical clustering revealed non-random partitioning of the samples into three major
branches. This patter is similar to the classification drawn by microarray analysis.
Therefore, we expect that different microRNA profile could be associated with drug
resistancein childhood ALL.

Host pharmacogenetics and genetic polymorphisms associated with drug metabolism,
disposition, chemotherapy cross-resistance, and complications Genetic polymorphisms of the
drug-metabolizing enzymes (drug transporters) or drug targets in ALL patients can influence
the efficacy or toxicity of antileukemic agents. The most intriguing example of
pharmacogenomic application was thiopurine S-methyltransferase (TPMT). The purine analogs
antimetabolites, Azathioprine and 6-mercaptopurine (6MP), interfere with nucleic acid
metabolism and cell proliferation and used to treat leukemia. Thiopurine S-methyltransferase
(TPMT) is a cytosolic enzyme that preferentially catalyzes the S-methylation and
inactivation of the purine analogs. About 90% of white and black persons have high TPM
activity, and 10% have intermediate activity caused by heterozygosity at the TPMT locus.
About 1 out of 300 persons inherits TPMT deficiency. Clinical studies have established an
inverse correlation between TPMT activity and accumulation of the active thioguanine
nucleotide metabolites of mercaptopurine and azathioprine in erythrocytes. Accumulation of
nucleotides usually leads to severe hematopoietic toxicity and possibly death, but this
outcome can be averted if the thiopurine dose is decreased substantially (an 8- to 15-fold
reduction). Patients who have intermediate TPMT activity were at an intermediate risk for
toxicity. To avoid bone marrow toxicity in TPMT deficiency patients, a prospective
measurement of erythrocyte TPMT activity prior to therapy was advocated. However, TPMT
assays are not easily available. The genetic basis for TPMT deficiency can be defined and
polymerase chain reaction (PCR)-based methods, and has been well established to diagnose
TPMT deficiency and heterozygosity in Western countries to the adjustment thiopurine dose.
Recently, the TPMT genotype was linked to early ALL treatment response (MRD on day 78 after
remission-induction therapy including mercaptopurine for 4 weeks).

Other germ line polymorphisms in the MTX associated genes are plausibly linked to drug
resistance or prognosis of childhood ALL under current regimes. It may also affect the
development of de novo or therapy-related leukemias. The polymorphisms in the folate-related
genes MTHFR, MTRR, and SHMT1 are reported to relate to resistance to methotrexate in
childhood ALL. Rocha JC et al. found that the GSTM1 non-null and TYMS 3/3 genotype are
linked to drug resistance. It is important to investigate these common polymorphisms of
patients in Taiwan. We will detect these polymorphisms in Taiwan pediatric patients and
revealed their relationship with outcome and complications.

Methods to monitor the early response to chemotherapy Response to therapy reflects the
genetics of leukemia cells and the pharmacodynamics and pharmacogenetics of the host, has
greater prognostic strength than does any other biologic or clinical feature tested to date.
The measurement of minimal residual disease, with the use of either flow cytometry or
quantitative reverse transcription polymerase-chain-reaction (Q-RT-PCR) analysis, affords a
level of sensitivity and specificity that cannot be attained through traditional morphologic
assessments.

A simplified flow cytometric assay of CD19, CD10, and CD34 antigens on bone marrow
mononuclear cells on day 14 or 21 of remission induction therapy would provide the means to
achieve the goal of MRD detection and could be readily applied in centers with only minimal
laboratory resources (Coustan-Smith E et al).

RESEARCH DESIGN AND METHODS Experimental Design A total of 160 ALL patients will be
recruited to this study as well as age-matched controls. Patients with newly diagnosed ALL
and enrolled on the TPOG ALL 2002 protocols and those previously diagnosed patients in the
past 3 years will be recruited under theirs or their parents' informed consent. For each
patient, we will prepare their total RNA and genomic DNA samples form the blast cells in the
initial diagnostic samples (leukemic cells from bone marrow aspirations and peripheral
blood).

Multiplex RT-PCR for recurrent BCR-ABL, MLL-AF4, E2A-PBX1, and TEL-AML1 fusion genes will be
setup for the more specific initial prognostic factors assignment ALL patients. We will also
analyze the relationships between the presence of the 16 genetic polymorphisms on the 6
important drug-metabolizing genes (CYP3A4*1B (A>G at position -392) and CYP3A5*3 (G>A at
position 22893); GSTP1 313A>G, GSTM1 deletion and GSTT1 deletion; MDR1 exon 21 (2677G>T/A)
and MDR1 exon 26 (3435C>T); MTHFR 677C>T and MTHFR 1298A>C; NR3C1 1088A>G; RFC 80G>A; TPMT
238G>C, TPMT 460G>A, and TPMT 719A>G; TYMS enhancer repeat; UGT1A1 promoter repeat
polymorphism; VDR intron 8 G>A, and VDR FokI (start-site) T>C) and their influences in the
pharmacodynamics of anti-leukemic agents received by the ALL eill be investigated.After
induction chemotherapy, flow cytometric assay to detect the MRD levels will be applied to
reflect the early response to initial chemotherapy protocols. A residual disease level of
less than 0.01 percent during or on completion of initial remission-induction therapy
reliably identifies patients with an exceptionally good treatment outcome. By contrast,
patients with a level of 1 percent or more at the end of remission-induction therapy or
those with a level of 0.1 percent or more at later times have a very high risk of relapse.
Patients who have a residual leukemia level of 0.01 percent or more after six weeks of
remission-induction therapy will be managed with intensified therapy protocols or seek
hematopoietic stem cell transplantation donors.The expression profile of 12 genes associated
with prognosis will be assayed (CASP8AP2, PTTG1, BCL2L13 BIRC5 (survivin), HRK TOP2A, TTK,
CCNB1, TNF, RAB5C, BCL7A GRP58). MicroRNA array profiles will be applied also.

Clinical courses such as acute or chronic complicationswill be followed and recorded to
assess the relationships between these polymorphisms and clinical courses.


Inclusion Criteria:



- ALL, healthy

Type of Study:

Observational

Study Design:

Observational Model: Defined Population, Primary Purpose: Screening, Time Perspective: Cross-Sectional, Time Perspective: Retrospective

Principal Investigator

Chung-Yi Hu, PhD

Investigator Role:

Principal Investigator

Investigator Affiliation:

Department of Clinical Laboratory Sciences and Medical Biotechonology

Authority:

Taiwan: Department of Health

Study ID:

9561709144

NCT ID:

NCT00526084

Start Date:

March 2007

Completion Date:

December 2009

Related Keywords:

  • Leukemia, Lymphocytic, Acute
  • ALL
  • Healthy subjects
  • Leukemia
  • Leukemia, Lymphoid
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma

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