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Polymorphisms in xenobiotic-metabolizing genes and the risk of chronic lymphocytic leukemia and non-Hodgkin's lymphoma in adult Russian patients.

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Polymorphisms in xenobiotic-metabolizing genes and the risk
of chronic lymphocytic leukemia and non-Hodgkin’s lymphoma
in adult Russian patients
Olga A. Gra,1 Andrey S. Glotov,1,2 Eugene A. Nikitin,3 Oleg S. Glotov,2 Viktoria E. Kuznetsova,1
Alexander V. Chudinov,1 Andrey B. Sudarikov,3 and Tatyana V. Nasedkina1*
Polymorphisms in genes coding xenobiotic-metabolizing enzymes are considered as risk factors modifying
susceptibility to cancer. We developed a biochip for the analysis of 18 mutations in 10 genes of metabolizing system: CYP1A1, CYP2D6, GSTT1, GSTM1, MTHFR, MTRR, NQO1, CYP2C9, CYP2C19, and NAT2. Using
allele-specific hybridization on the biochip 76 T-cell non-Hodgkin’s lymphoma (NHL) patients, 83 B-cell
chronic lymphocytic leukemia (B-CLL) patients, and 177 healthy donors were tested. Polymorphic CYP1A1
alleles were more frequent in B-CLL patients relative to normal controls, for example, a combination of polymorphic variants 4887C > A, 4889A > G, and 6235T > C (OR 5 1.76, 95% CI 5 1.0–3.1). The GSTM1 null genotype was more frequent in NHL patients relative to controls (OR 5 1.82, 95% CI 5 1.1–3.1). The combination of unfavorable polymorphic CYP1A1 variants and GSTM1 null genotype was found more frequently in
B-CLL patients relative to controls (OR 5 2.52, 95% CI 5 1.3–4.9). In addition, male B-CLL patients demonstrated a significantly increased occurrence of heterozygous and homozygous allele *2 of CYP2C9 gene
(OR 5 2.38, 95% CI 5 1.1–5.2) as well as a combination of alleles *2 and *3 of the gene (OR 5 2.09, 95%
CI 5 1.1–3.9). Thus, our findings show the association between polymorphic alleles of CYP1A1, GSTM1,
and CYP2C9 genes and the risk to develop NHL or B-CLL. The developed biochip can be considered as a
convenient analytical tool for research studies and predictive analysis in oncohematology. Am. J. Hematol.
C 2007 Wiley-Liss, Inc.
83:279–287, 2008. V
Introduction
Genetic susceptibility studies of lymphoproliferative disorders may serve to identify at risk populations and to clarify
important disease mechanisms. B-cell chronic lymphocytic
leukemia (B-CLL) is the most common leukemia amounting
to about 30% of cases in adults [1,2]. Non-Hodgkin lymphoma (NHL) is a group of histologically and biologically heterogeneous malignant lymphoid neoplasms of unknown etilology [3]. T-cell lymphomas account for 15–20% of NHL in
Western countries, as well as in Russia. Over the last several decades the significant growth of incidence for B-CLL
and NHL, has been observed, especially, in developed countries. This fact greatly stimulates searching for hereditary
and environmental risk factors which may impact to the development of these malignancies. Familial aggregation has
been well documented for both B-CLL and lymphomas, indicating the substantial contribution of hereditary factors to the
development of disease. The risk to develop B-CLL was 3–7
folds higher among close relatives of CLL patients [4,5]. In
the case of lymphomas, a family history of any hematopoietic malignancy was found to be associated with 2–3 fold
increased risk of NHL [6,7]. Genome-wide linkage scans of
CLL families revealed a number of chromosome bands with
potential candidate genes, for example, 11p11 [8] and
13q22.1 [9]. The role and function of these candidate
regions are under investigation now. But, it is very likely
also, that common genetic variants, each with apparently
minor effects on tumor phenotype, may influence disease
susceptibility in hematological malignancies. It is especially
true for lymphomas, where known risk factors like viral infections and dysfunctions of immune system account for only a
small proportion of the total NHL cases [3,10].
To date, a number of case-control association studies
have examined the role of genetic polymorphisms in the risk
of B-CLL and NHL and several genetic variants have been
identified as potential susceptibility loci [11]. Positive associations have been found between polymorphic alleles of
genes ATM, BRCA2, and CHEK2 involved in the DNA damage-response and cell-cycle pathways and risk of B-CLL
[12]. Among potential biomarkers increasing NHL risk two
susceptibility alleles in TNF and IL10 have been identified
[13]. Several B-CLL and NHL studies have examined polymorphisms involved in folate metabolism; although, results
have been inconsistent [14–17]. Among low-penetrance
candidate genes, those involved in xenobiotic metabolism
draw a special attention, because they may provide clues to
identify potential lymphomagens and to estimate carcinogen
effects of environmental pollution. Published data indicate
that xenobiotic-metabolizing polymorphic alleles in some
populations correlate with increased risk of different lymphoproliferative diseases [18–22]. The majority of articles were
devoted to the analysis of acute leukemia and, particularly,
childhood leukemia [21,23–25]. Thus, it would be interesting
to investigate associations between polymorphous variants
1
Engelhardt Institute of Molecular Biology, Russian Academy of Sciences,
Moscow, Russia; 2Ott Research Institute of Obstetrics and Gynecology, Russian Academy of Medical Sciences, St. Petersburg, Russia; 3National Hematology Research Center, Russian Academy of Medical Sciences, Moscow,
Russia
Contract grant sponsor: Russian Foundation; Contract grant number: 06-0449771.
*Correspondence to: Tatyana V. Nasedkina, EIMB, 32 Vavilov St., Moscow
119991, Russia. E-mail: nased@eimb.ru
Received for publication 5 May 2006; Revised 10 October 2007; Accepted 15
October 2007
Am. J. Hematol. 83:279–287, 2008.
Published online 5 December 2007 in Wiley InterScience (www.interscience.
wiley.com).
DOI: 10.1002/ajh.21113
C 2007 Wiley-Liss, Inc.
V
American Journal of Hematology
279
http://www3.interscience.wiley.com/cgi-bin/jhome/35105
Figure 1. Scheme of biochip for the analysis of xenobioticmetabolizing gene polymorphisms. In the case of CYP1A1
gene (C4887A and A4889G), 5-nt central sequences of the
probes are given; the first nucleotide corresponds to the polymorphic variant C4887A, the third nucleotide corresponds to
the polymorphic variant A4889G. Two upper left positions
show the CCATT sequence revealing the wild type alleles; two
lower left positions show the CCGTT sequence corresponding
to the polymorphic variant A4889A/G; two upper right ones
show the ACATT sequence corresponding to the polymorphic
variant 4887C/A; two lower right ones show the ACGTT
sequence corresponding to the polymorphic variants 4887A/G
and 4889A/G. In the case of CYP1A1 (T6235C), CYP2D6
(G1934A and DelA2637), MTHFR (C677T and A1298C),
MTRR (A66G), NQO1 (C609T), CYP2C9 (C430T and
C1075T), CYP2C19 (G681A), and NAT2 (T341C, C481T,
G590A, and G857A) genes, the central nucleotides determining polymorphic variants of the genes are given. Two upper
and lower positions contain the duplicated oligonucleotide
probes corresponding to the wild type and mutant allele,
respectively. In the case of GSTT1 (deletion) and GSTM1 (deletion) genes, two upper rows have plus signs corresponding
to oligonucleotides without deletion, while two lower rows have
minus signs corresponding to oligonucleotides with deleted
central nucleotide in the probe used as internal control.
of xenobiotic-metabolizing genes and risk of development of
other lymphoproliferative diseases. The data concerning
B-CLL and NHL susceptibility regarding xenobiotic-metabolizing genes status are limited and sometimes contradictory
[26–32]. There might be gender-specific and subtype-specific associations that require further investigations. No special study on T-cell lymphoma susceptibility and xenobioticmetabolizing gene polymorphisms has been carried out.
Besides, in different populations the realization of the same
genotypes can be modulated by different genetic context.
Previously we developed a biochip, allowing to analyze polymorphic alleles in such xenobiotic-metabolizing genes as
CYP1A1, CYP2D6, GSTT1, GSTM, CYP2C9, CYP2C19,
and NAT2 [33]. In this study the polymorphic alleles of methylenetetrahydrofolate reductase (MTHFR) and methionine
synthase (MTRR) genes, involved in folate metabolism were
added. Folate participates in DNA methylation and nucleotide
synthesis, thus metabolic imbalance of this compound may
have an impact to carcinogenesis [34,35].
280
Figure 2. Hybridization pattern obtained on the biochip for
the analysis of CYP1A1, CYP2D6, GSTT1, GSTM1, MTHFR,
MTRR, NQO1, CYP2C9, CYP2C19, and NAT2 genes polymorphism. Arrows indicate identified polymorphic variants.
The aim of the study was to determine if there is association between main polymorphic genetic variants of metabolizing enzymes, which process environmental carcinogens
or play key role in intracellular methylation, and individual
susceptibility to such malignant diseases as T-cell NHL and
B-CLL in a Russian population.
Results
The genotypes were assigned according to fluorescent
signal patterns obtained in hybridization experiments using
biochip. The scheme of biochip is shown in Figure 1. Figure
2 exemplifies a biochip hybridization pattern for a sample
with the following genotype: CYP1A1 (*4/*1), CYP2D6 (*4/
*1), GSTT1 (1/1), GSTM1 (1/1), MTHFR (C/T; A/C),
MTRR (A/G), NQO1 (*1/*1), CYP2C9 (*2/*1), CYP2C19
(*1/*1), and NAT2 (S2/S2). The correctness of biochip analysis was confirmed in experiments with 35 control samples
of known genotype.
Distribution of metabolizing genes genotypes
The distribution of CYP1A1, CYP2D6, GSTT1, GSTM1,
MTHFR, MTRR, NQO1, CYP2C9, CYP2C19, and NAT2
genotypes in NHL (n 5 76), B-CLL (n 5 83) patients and
healthy controls (n 5 177) is given in Table I. No statistically significant difference in polymorphic genotype frequencies of CYP2D6, MTHFR, MTRR, NQO1, GSTT1,
CYP2C19, and NAT2 genes have been revealed between
T-cell NHL or B-CLL patients and normal controls. Both
NHL and B-CLL patients demonstrated higher incidence
of the GSTM1 null genotype relative to normal controls
(Table I). The difference was significant for NHL patients
(OR 5 1.82, 95% CI 5 1.05–3.14, P 5 0.0395). For
CYP2C9 gene the higher incidence of *2/*3 genotype in BCLL patients relative to normal controls have been found
and the difference is statistically significant (OR 5 9.48,
95% CI 5 1.03–86.85, P 5 0.0329).
Combined analysis for CYP1A1 and GSTM1 loci
Both NHL and B-CLL patients demonstrated an
increased incidence of heterozygous and homozygous
American Journal of Hematology
TABLE I. Distribution of Genotypes of Xenobiotic-Metabolizing Genes
NHL (n 5 76)
Allele/genotype
CYP1A1
*1/*1
*1/*2A
*1/*2B
*1/*4
*2A/*2A
*2B/*4
*4/*4
CYP2D6
*1/*1
*1/*3
*1/*4
*3/*3
*3/*4
*4/*4
GSTT1
Present
Null
GSTM1
Present
Null
MTHFR C677T
CC
CT
TT
MTHFR 1298C
AA
AC
CC
MTRR A66G
AA
AG
GG
NQO1
*1/*1
*1/*2
*2/*2
CYP2C9
*1/*1
*1/*2
*1/*3
*2/*3
*3/*3
CYP2C19
*1/*1
*1/*2
*2/*2
NAT2 T341C
TT
TC
CC
NAT2 C481T
CC
CT
TT
NAT2 G590A
GG
GA
AA
NAT2 G857A
GG
GA
AA
n (%)
B-CLL (n 5 83)
OR (95% CI)
P
n (%)
OR (95% CI)
P
Controls (n 5 177), n (%)
53
10
9
3
0
1
0
(69.7)
(13.2)
(11.8)
(4.0)
(0.0)
(1.3)
(0.0)
1
1.4 (0.6–3.2)
1.6 (0.7–4.0)
0.8 (0.2–3.2)
–
–
–
0.51
0.33
1.00
–
–
–
53
11
12
7
0
0
0
(63.9)
(13.3)
(14.4)
(8.4)
(0.0)
(0.0)
(0.0)
1
1.5 (0.7–3.5)
2.2 (0.9–5.0)
2.0 (0.7–5.6)
–
–
–
0.28
0.07
0.25
–
–
–
134
18
14
9
1
0
1
(75.7)
(10.2)
(7.9)
(5.1)
(0.55)
(0.0)
(0.55)
52
1
20
0
0
3
(68.4)
(1.3)
(26.3)
(0.0)
(0.0)
(4.0)
1
0.7 (0.1–7.3)
0.9 (0.5–1.7)
–
–
0.8 (0.2–3.3)
1.00
0.88
–
–
1.00
55
1
24
0
0
3
(66.3)
(1.2)
(28.9)
(0.0)
(0.0)
(3.6)
1
0.7 (0.1–6.9)
1.1 (0.6–1.9)
–
–
0.8 (0.2–3.1)
1.00
0.88
–
–
0.79
116
3
48
1
1
8
(65.6)
(1.7)
(27.1)
(0.55)
(0.55)
(4.5)
56 (73.5)
20 (26.5)
1
0.9 (0.5–1.6)
0.76
58 (70.0)
25 (30.0)
1
1.1 (0.6–1.9)
0.88
126 (71.2)
51 (28.8)
30 (39.5)
46 (60.5)
1
1.8 (1.1–3.1)
0.04
38 (46.0)
45 (54.0)
1
1.4 (0.8–2.4)
0.23
96 (54.2)
81 (45.8)
39 (51.3)
28 (36.9)
9 (11.8)
1
0.8 (0.4–1.4)
1.5 (0.6–3.8)
0.39
0.46
44 (53.0)
35 (42.2)
4 (4.8)
1
0.9 (0.5–1.5)
0.6 (0.2–1.9)
0.59
0.58
85 (48.0)
79 (44.6)
13 (7.4)
36 (47.4)
30 (39.5)
10 (13.1)
1
0.8 (0.5–1.5)
1.6 (0.7–4.0)
0.56
0.34
39 (47.0)
38 (45.8)
6 (7.2)
1
1.0 (0.6–1.7)
0.9 (0.3–2.5)
1.00
1.00
81 (45.8)
82 (46.3)
14 (7.9)
16 (21.1)
40 (52.6)
20 (26.3)
1
0.9 (0.4–1.8)
0.8 (0.4–1.7)
0.86
0.69
20 (24.1)
32 (38.6)
31 (37.3)
1
0.6 (0.3–1.1)
1.0 (0.5–2.0)
0.15
1.00
33 (18.6)
92 (52.0)
52 (29.4)
54 (71.1)
20 (26.3)
2 (2.6)
1
0.8 (0.5–1.6)
0.7 (0.1–3.8)
0.65
1.00
52 (62.7)
28 (33.7)
3 (3.6)
1
1.2 (0.7–2.2)
1.1 (0.3–4.8)
0.47
1.00
119 (67.2)
52 (29.4)
6 (3.4)
52
8
14
1
1
1
0.7 (0.3–1.6)
1.7 (0.8–3.7)
2.5 (0.2–40.1)
–
0.54
0.16
0.50
–
54
16
9
4
0
1
1.4 (0.7–2.7)
1.1 (0.5–2.5)
9.5 (1.0–86.8)
–
0.47
1.00
0.03
–
128
28
20
1
0
64 (84.2)
12 (15.8)
0 (0.0)
1
0.8 (0.4–1.6)
–
0.59
–
65 (78.3)
18 (21.7)
0 (0.0)
1
1.2 (0.6–2.2)
–
0.74
–
139 (78.5)
33 (18.7)
5 (2.8)
26 (34.2)
35 (46.1)
15 (19.7)
1
1.0 (0.5–1.8)
1.1 (0.5–2.5)
1.00
0.84
31 (37.3)
38 (45.8)
14 (16.9)
1
0.9 (0.5–1.6)
0.9 (0.4–1.9)
0.77
0.85
61 (34.5)
85 (48.0)
31 (17.5)
37 (48.7)
26 (34.2)
13 (17.1)
1
0.5 (0.3–1.0)
0.8 (0.4–1.6)
0.05
0.57
38 (45.8)
32 (38.5)
13 (15.7)
1
0.6 (0.4–1.2)
0.7 (0.3–1.6)
0.15
0.45
64 (36.2)
83 (46.9)
30 (16.9)
40 (52.6)
31 (40.8)
5 (6.6)
1
1.1 (0.6–1.9)
0.9 (0.3–2.7)
0.89
1.00
37 (44.6)
35 (42.2)
11 (13.2)
1
1.3 (0.7–2.3)
2.2 (0.9–5.3)
0.39
0.10
95 (53.7)
69 (39.0)
13 (7.3)
73 (96.1)
3 (3.9)
0 (0.0)
1
0.8 (0.2–2.9)
–
1.00
–
79 (95.2)
4 (4.8)
0 (0.0)
1
0.9 (0.3–3.1)
–
1.00
–
166 (93.8)
9 (5.1)
2 (1.1)
(68.4)
(10.6)
(18.4)
(1.3)
(1.3)
American Journal of Hematology
(65.1)
(19.3)
(10.8)
(4.8)
(0.0)
(72.3)
(15.8)
(11.3)
(0.6)
(0.0)
281
TABLE II. Combination of GSTM1 Null Genotype and CYP1A1 Genotypes in NHL and B-CLL Patients and Normal Controls
GSTM1 null genotype 1 CYP1A1
T6235C
Control (n 5 177)
NHL (n 5 76)
B-CLL (n 5 83)
A4889G
Control (n 5 177)
NHL (n 5 76)
B-CLL (n 5 83)
C4887A
Control (n 5 177)
NHL (n 5 76)
B-CLL (n 5 83)
T6235C 1 A4889G 1 C4887A
Control (n 5 177)
NHL (n 5 76)
B-CLL (n 5 83)
Genotype, n (%)
C/2
17 (9.6)
11 (14.5)
17 (20.5)
A/G
9 (5.1)
6 (7.9)
8 (9.6)
A/2
4 (2.3)
3 (3.9)
4 (4.8)
V/2
21 (11.9)
13 (17.1)
21 (25.3)
Other combinations of allelic
160 (90.4)
65 (85.5)
66 (79.5)
Other combinations of allelic
168 (94.9)
70 (92.1)
75 (90.4)
Other combinations of allelic
173 (97.7)
73 (96.1)
79 (95.2)
Other combinations of allelic
156 (88.1)
63 (82.9)
62 (74.7)
OR
95% CI
P
1.0
1.59
2.42
0.71–3.59
1.17–5.04
0.278
0.0186
1.0
1.60
1.99
0.55–4.67
0.74–5.36
0.393
0.184
1.0
1.78
2.19
0.39–8.14
0.53–8.98
0.432
0.271
1.0
1.53
2.52
0.72–3.25
1.28–4.93
0.315
0.0106
variants
variants
variants
variants
C/2, heterozygous variant or homozygous mutation which corresponds to presence of genotypes *1/2A, *1/*2B, *2B/*4, or *2A/*2A in combination
with GSTM1 null genotype; Other combinations of allelic variants, homozygous wild type which corresponds to presence of allele combinations *1/
*1 and other genotypes except for referred above C/2 in combination with GSTM1 null genotype and also all possible CYP1A1 genotypes in combination with GSTM1 non-null genotype.
A/G, heterozygous variant which corresponds to presence of genotypes *1/*2B or *2B/*4 in combination with GSTM1 null genotype; Other combinations of allelic variants, homozygous wild type which corresponds to presence of allele combinations *1/*1 and other genotypes except for
referred above A/G in combination with GSTM1 null genotype and also all possible CYP1A1 genotypes in combination with GSTM1 non-null genotype.
A/2, heterozygous variant or homozygous mutation which corresponds to presence of genotypes *1/*4, *2B/*4, or *4/*4 in combination with
GSTM1 null genotype; Other combinations of allelic variants, homozygous wild type which corresponds to presence of allele combinations *1/*1
and other genotypes except for referred above A/2 in combination with GSTM1 null genotype and also all possible CYP1A1 genotypes in combination with GSTM1 non-null genotype.
V/2, heterozygous variant or homozygous mutation which corresponds to presence of genotypes *1/2A, *1/*2B, *1/*4, *2B/*4, *2A/*2A or *4/*4 in
combination with GSTM1 null genotype; Other combinations of allelic variants, homozygous wild type which corresponds to genotype *1/*1 in combination with GSTM1 null genotype and also all possible CYP1A1 genotypes in combination with GSTM1 non-null genotype.
Other combinations of allelic variants, homozygous wild type which corresponds to presence of allele combinations *1/*1 and other genotypes
except for referred at the left in combination with GSTM1 null genotype and also all possible CYP1A1 genotypes in combination with GSTM1 nonnull genotype.
Statistically significant data are shown in bold and italic type.
4887A, 4889G, and 6235C polymorphisms of CYP1A1
gene in combination with the GSTM1 null genotype relative
to controls (Table II). For B-CLL patients the combination of
heterozygous and homozygous variant 6235C with GSTM1
null genotype (OR 5 2.42, 95% CI 5 1.17–5.04, P 5
0.0186) and combination of polymorphic variants 4887A,
4889G, and 6235C with GSTM1 null genotype (OR 5 2.52,
95% CI 5 1.28–4.93, P 5 0.0106) occur more frequently
and it was statistically significant event.
Sex differences in the occurrence of polymorphic
variants of the metabolizing system genes
For the majority of genes no significant sex differences in
the occurrence of polymorphic variants of drug-metabolizing
genes have been revealed. However, male patients with BCLL demonstrated a statistically significant increased occurrence for all three polymorphic 4887T > C, 4889A > G, and
6235T > C of CYP1A1 gene against normal male controls
(OR 5 2.35, 95% CI 5 1.10–4.99, P 5 0.0317) (Table III).
Female patients with NHL or B-CLL demonstrated
increased frequencies of the GSTT1 and GSTM1 null genotypes relative to normal female controls (Table IV). In the
case of female NHL patients, the difference in the incidence
of the GSTM1 null genotype was significant (OR 5 2.78,
95% CI 5 1.27–6.09, P 5 0.012). In addition, female
patients with NHL or B-CLL demonstrated an increased frequency of the GSTT1/GSTM1 double null genotype relative
282
to normal female controls (OR 5 2.96, 95% CI 5 1.05–
8.39, P 5 0.0481 and OR 5 2.93, 95% CI 5 0.77–14.78,
P 5 0.071, respectively). The difference was significant
only for female NHL patients.
The results showed a higher frequencies of CYP2C9 *2
and CYP2C9 *3 genotypes in male B-CLL patients comparing with normal male controls (Table V). The difference is
significant for CYP2C9 *2 homo- and heterozygous carriers
(OR 5 2.38, 95% CI 5 1.08–5.24, P 5 0.0359) and for
CYP2C9 *2/*3 genotypes (OR 5 2.09, 95% CI 5 1.13–
3.87, P 5 0.0226).
Discussion
It is generally accepted that exogenous carcinogens are
metabolized in human organism with the formation of active
metabolites, binding and damaging nuclear and mitochondrial DNA [18–20], so the exposure to cytotoxic chemicals
capable to cause oxidative stress may contribute to the development of many diseases including cancer. Oxidative
metabolism of xenobiotics is mediated by phase I enzymes,
members of the cytochrome P450 superfamily (CYP1A1,
CYP2D6, CYP2C9, and CYP2C19). Cytochromes P450,
mainly localized in the liver, use singlet oxygen to activate
xenobiotics, thus transforming them into highly active intermediate metabolites [19]. Intermediate genotoxic metabolites are substrates for subsequent detoxification mediated
by phase II enzymes such as glutathione S-transferases
American Journal of Hematology
TABLE III. CYP1A1 Genotype in Male NHL and B-CLL Patients and Normal Male Controls
CYP1A1
Genotype, n (%)
T6235C
Control (n 5 90)
NHL (n 5 37)
B-CLL (n 5 48)
A4889G
Control (n 5 90)
NHL (n 5 37)
B-CLL (n 5 48)
C4887A
Control (n 5 90)
NHL (n 5 37)
B-CLL (n 5 48)
T6235C 1 A4889G 1 C4887A
Control (n 5 90)
NHL (n 5 37)
B-CLL (n 5 48)
C/2
18 (20.0)
12 (32.4)
15 (31.3)
A/G
9 (10.0)
6 (16.2)
9 (18.8)
A/2
3 (3.3)
2 (5.4)
5 (10.4)
V/2
21 (23.3)
13 (35.1)
20 (41.7)
T/T
72 (80.0)
25 (67.6)
33 (68.8)
A/A
81 (90.0)
31 (83.8)
39 (81.3)
C/C
87 (96.7)
35 (94.6)
43 (89.6)
N/N
69 (76.7)
24 (64.9)
28 (58.3)
OR
95% CI
P
1.0
1.92
1.82
0.81–4.54
0.82–4.05
0.168
0.149
1.0
1.74
2.08
0.57–5.30
0.76–5.65
0.368
0.186
1.0
1.66
3.37
0.27–10.35
0.77–14.78
0.628
0.126
1.0
1.78
2.35
0.77–4.10
1.10–4.99
0.191
0.0317
C/2, heterozygous variant or homozygous mutation which corresponds to presence of allele combinations *1/2A, *1/*2B, *2B/*4 or *2A/*2A; T/T,
homozygous wild type which corresponds to presence of allele combinations *1/*1 and other genotypes except for referred above C/2.
A/G, heterozygous variant which corresponds to presence of allele combinations *1/*2B or *2B/*4; A/A, homozygous wild type which corresponds
to presence of allele combinations *1/*1 and other genotypes except for referred above A/G.
A/2, heterozygous variant or homozygous mutation which corresponds to presence of allele combinations *1/*4, *2B/*4, or *4/*4; C/C, homozygous wild type which corresponds to presence of allele combinations *1/*1 and other genotypes except for referred above A/2.
V/2, heterozygous variant or homozygous mutation which corresponds to presence of allele combinations *1/2A, *1/*2B, *1/*4, *2B/*4, *2A/*2A, or
*4/*4; N/N, homozygous wild type which corresponds to genotype *1/*1.
Statistically significant data are shown in bold and italic type.
TABLE IV. GSTT1 and GSTM1 Genotype in Female NHL and B-CLL Patients and Normal Female Controls
GST’s
GSTT1
Control (n 5 87)
NHL (n 5 39)
B-CLL (n 5 35)
GSTM1
Control (n 5 87)
NHL (n 5 39)
B-CLL (n 5 35)
GSTT1 1 GSTM1
Control (n 5 87)
NHL (n 5 39)
B-CLL (n 5 35)
Genotype, n (%)
2/2
21 (24.1)
11 (28.2)
14 (40.0)
2/2
34 (39.1)
25 (64.1)
20 (57.1)
Double deletion
8 (9.2)
9 (23.1)
8 (22.9)
2/1, 1/1
66 (75.9)
28 (71.8)
21 (60.0)
2/1, 1/1
53 (60.9)
14 (35.9)
15 (42.9)
Other combinations of allelic variants
79 (90.8)
30 (76.9)
27 (77.1)
OR
95% CI
P
1.0
1.24
2.10
0.53–2.90
0.91–4.83
0.661
0.120
1.0
2.78
2.08
1.27–6.09
0.94–4.61
0.012
0.075
1.0
2.96
2.93
1.05–8.39
0.77–14.78
0.0481
0.071
GSTT1 2/2, homozygous deletion GSTT1; GSTT1 2/1, 1/1, presence of at list one GSTT1 allele.
GSTM1 2/2, homozygous deletion GSTM1; GSTM1 2/1, 1/1, presence of at list one GSTM1 allele;
Double deletion, homozygous deletions of both GSTT1 and GSTM1; Other combinations of allelic variants, presence of at list one GSTT1 and/or
GSTM1 allele.
Statistically significant data are shown in bold and italic type.
(GSTs), arylamine N-acetyltransferases (NATs), and
NAD(P)H:quinone oxidoreductase (NQO1). Changes in the
activities of these enzymes may influence detoxification of
carcinogens or harmful metabolites. There are a number of
single nucleotide polymorphisms (SNPs) in genes coding
these xenobiotic-metabolizing enzymes, which are known
to influence their functional properties. Besides aforementioned enzymes, MTHFR and MTRR, which play an important role in folate metabolism, may be of interest. MTHFR
catalyzes irreversible reduction of 5,10-methylentetrahydrofolate to 5-methyltetrahydrofolate. The most significant polymorphic variants of the MTHFR gene are, probably, C677T
and A1298C, which are suggested to modulate the risk to
develop different multifactorial diseases including some
cancers [14,15,34,35]. The MTRR enzyme participates in
transferring of methyl group from 5-tetrahydrophosphate to
American Journal of Hematology
homocysteine. The most significant and well-studied polymorphic variant of the MTRR gene is A66G, the change of
A to G leads to decrease of catalytic activity of the enzyme,
that in turn hampers homocysteine re-methylation and may
cause different genetic defects [34,35].
In the present study, we analyzed the association
between susceptibility to B-CLL and T-cell NHL and 18
polymorphisms in 10 metabolizing genes, namely, CYP1A1,
CYP2D6, GSTT1, GSTM1, MTHFR, MTRR, NQO1,
CYP2C9, CYP2C19, and NAT2. The B-CLL and T-cell NHL
patients and healthy controls were residents of the European part of the Russian Federation. The B-CLL, as well
as T-cell NHL usually peak in age between 60 and 70 years.
In our study, the mean age of NHL and B-CLL patients was
50 years and 53 years, respectively. This fact suggests the
possible involving of genetic factors for these patient
283
TABLE V. Allelic Frequencies of CYP2C9 Gene in Male B-CLL
Patients and Normal Controls
CYP2C9
Allelic frequency, n (%)
*2
Control (n 5 90)
B-CLL (n 5 48)
*3
Control (n 5 90)
B-CLL (n 5 48)
*2/*3
Control (n 5 90)
B-CLL (n 5 48)
1/2
13 (7.2)
15 (15.6)
1/1, 1/2
13 (7.2)
10 (10.4)
V/2
26 (14.4)
25 (26.0)
2/2
167 (92.8)
81 (84.4)
2/2
167 (92.8)
86 (89.6)
N/N
154 (85.6)
71 (74.0)
OR
95% CI
P
1.0
2.38
1.08–5.24
0.0359
1.0
1.49
0.63–3.55
0.368
1.0
2.09
1.13–3.87
0.0226
*2 allele 1/2, presence of allele *2 in next combinations *1/*2 or *2/*3;
*2 allele 2/2, absence of allele *2 and presence of other allelic combinations such as *1/*1, *1/*3 or *3/*3.
*3 allele 1/1, 1/2, presence of allele *3 in next combinations *1/*3,
*2/*3 or *3/*3; *3 allele 2/2, absence of allele *3 and presence of other
allelic combinations such as *1/*1 or *1/*2.
*2/*3 alleles V/2, presence of alleles *2 and/or *3 in next combinations
*1/*2, *1/*3, *2/*3 or *3/*3; *2/*3 alleles N/N, absence of alleles *2 and/
or *3 and presence of homozygous wild genotype *1/*1.
Statistically significant data are shown in bold and italic type.
groups in the development of the disease. The data
obtained point to the significance of specific genotypes for
CYP1A1, GSTM1, CYP2C9 genes in case of B-CLL and
for GSTT1, GSTM1 genes in case of T-cell NHL.
CYP1A1
The association of different polymorphic variants of
CYP1A1 gene with susceptibility to lymphoproliferative diseases has been described in many articles. For instance,
Krajinovic et al. [21] demonstrated a notably higher risk of
acute lymphoblastic leukemia (ALL) in carriers of allele *2A
of CYP1A1 gene (OR 5 1.8, 95% CI 5 1.1–3.1, P 5
0.03). Italian scientists D’Alo et al. [22] found higher incidence of heterozygous and homozygous allele *4 of
CYP1A1 gene in patients with acute myeloid leukemia compared to healthy donors (OR 5 2.2, 95% CI 5 1.3–3.7,
P 5 0.006).
Our results demonstrated notably high frequencies of
heterozygous and homozygous variants 4887C > A, 4889A
> G, and 6235T > C of CYP1A1 gene in B-CLL patients.
The CYP1A1 gene encodes an aromatic hydrocarbons
hydroxylase, which is responsible for the first oxidative
stage in the metabolism of many xenobiotics including polycyclic aromatic hydrocarbons such as benzopyrene [36].
The catalytic reaction yields reactive metabolites that can
form covalent bonds with proteins and nucleic acids, which
underlies their cytotoxic, mutagenic, and carcinogenic
effects. The polymorphism of the CYP1A1 gene provides
for increased enzyme activity and consequently increases
the toxic effect of the enzyme substrates [37,38]. For
instance, CYP1A1*2A variant was shown to increase the
risk of leukemia, particularly in children exposed to pesticides or tobacco smoke [39].
In our study, we also analyzed the frequency of CYP1A1
polymorphic variants depending on gender. Statistical analysis showed that the same distribution is characteristic in
males, while in females it is less evident. From the literature
it is known that endogenous steroids and other non-genetic
factors may induce transcription and take part in regulation
of transcription of CYP1A1 gene [36]. Thus, it was
described that benzopyrene-induced CYP1A1 gene expression in androgen-dependent normal epithelial cells as well
as in prostate cancer cells [40]. Besides, benzopyrene and
its active metabolites may decrease the expression level of
284
androgen receptor (AR) in androgen-sensitive tissues and
organs [41]. Normally, the suppression of AR expression is
necessary for effective induction of CYP1A1 gene [42]. The
constant exposure of benzopyrene in combination with
male steroid hormones may provide for higher levels of the
CYP1A1 gene expression, in the presence of CYP1A1*2A
allele this may lead to an additional increasing of CYP1A1
catalytic activity in male patients. The increasing toxic effect
of CYP1A1 substrates may predispose males more than
females to the development of lymphoproliferative disorders.
GSTM1, GSTT1
Occurrence of the GSTM1 null genotype proved to correlate with an increased risk of NHL and B-CLL. GSTs are a
superfamily of phase II enzymes catalyzing conjugation of
reactive intermediates with glutathione. GSTM1 enzyme
mediates detoxification of carcinogenic polycyclic aromatic
hydrocarbons such as benzopyrene [36]. Two null alleles of
GSTM1 gene abolish GSTM1 enzyme activity, which consequently leads to the accumulation of genotoxic metabolites of the phase I detoxification.
The obtained results agree with published data [30,31].
For instance, Yuille et al. [30] tested 138 adult B-CLL
patients and 280 normal controls to demonstrate a 1.3
times higher frequency of the GSTM1 null genotype in the
former group than in the latter (95% CI 5 0.8–1.9).
In addition, female NHL and B-CLL patients had an
increased frequency of the GSTT1/GSTM1 double null genotype. The double null genotype abolishes two main
phase II biotransformation enzymes GSTT1 and GSTM1,
which increases the level of DNA adducts [43] and, thus,
favors tumors including leukemias and lymphomas. The
GSTT1 and GSTM1 genes are located on different chromosomes, so there is no genetic linkage between these loci.
It should be noticed, that in females the differences in
frequencies of null GSTM1 genotype and double null
GSTT1/GSTM1 were more pronounced than in males. It is
known from the literature, that estrogens can regulate the
expression of phase II enzymes via cis-active DNA elements, so-called antioxidant/electrophile response element
ARE, which are located in promoter regions of corresponding genes [44]. For instance, it was described, that 17bestradiol [E2] administration induced the decrease of catalytic activity of GSTs in cervical cells using ARE-mediated
mechanism. The decreased catalytic activity of GSTs may
lead to strengthening of cellular oxidative stress mediated
by slow metabolism of active oxygen forms, which possess
a mutagenic activity and may increase the level of DNA
damage [45]. Thus, the estrogen-mediated suppression of
GSTs catalytic activity may have an additional impact in
females, carrying functionally inactive alleles of GSTT1
and/or GSTM1 genes.
CYP2C9
One of our findings was substantial increase of heteroand homozygotes carrying polymorphic alleles *2 and *3 of
CYP2C9 gene in male B-CLL patients.
Cytochrome CYP2C9 is an important member of biotransformation system, also metabolizing several widely
used drugs. The CYP2C9 enzyme expression is induced
on the transcription level and is mediated via constant androstane receptor CAR [46]. The majority of drugs (particularly, phenobarbital), which induce CYP2C9 gene expression via CAR-dependent mechanism, cause CAR translocation into nucleus. After heterodimerization with retinoid X
receptor in the nucleus CAR communicate with recognizing
elements in promoter region of CYP2C9 gene, then it associates with co-activators/co-repressors for the further regu-
American Journal of Hematology
lation of transcription [47]. On the other hand, endocrine
factors, like steroid hormones, growth factors etc., can
modulate the induction of CYP2C9 in vivo. Thus, Forman
et al. [48] showed that androgene metabolites may bind
with CAR and inhibit its constitutional activity. Genetic polymorphisms CYP2C9*2 (R144C) and CYP2C9*3 (L208V)
sharply decrease the enzyme activity of CYP2C9; thus, the
association of deficient polymorphic variants of this gene
with risk to develop B-CLL in male patients may additionally
point to the fact, that internal hormonal environment can
modify the metabolism of many xenobiotics and probably
needs to be taken into account. Previously published data
indicate that hetero- and homozygous alleles *2 and *3 alleles of CYP2C9 gene occur more frequently in patients
with colorectal cancer [49].
Combination of CYP1A1 and GSTM1
Analysis of combined genotypes in B-CLL patients
allowed us to reveal a significant increase in the occurrence
of heterozygous and homozygous variants 4887T > C,
4889A > G, and 6235T > C of CYP1A1 gene and GSTM1
null genotype. The association of ‘‘unfavorable’’ CYP1A1 alleles and GSTM1 null genotype with high leukemia risk has
also been reported for acute leukemia [21,50]. Apparently,
carriers of this genotype are more sensitive to carcinogenic
environmental impacts. Appearance of polycyclic aromatic
hydrocarbons (e.g., benzopyrene) in individual carrying polymorphic CYP1A1 alleles provides for an increased cytotoxic
effect of the reactive metabolites not detoxified in the absence of functionally competent GSTM1 alleles, which is
the risk factor for tumor development. The CYP1A1 gene is
located on chromosome 15q22-q24, while the GSTM1
gene on chromosome 1p13.3, so there is no genetic linkage between these loci.
This work demonstrates that the developed biochip is a
convenient tool to evaluate gene polymorphisms in the
xenobiotic-metabolizing system as risk factors for hematological malignancies. The studied polymorphic alleles of
CYP1A1, GSTM1, and CYP2C9 genes were notably more
frequent in NHL and B-CLL patients than in normal controls. But we also have to mention, that due to relatively
small number of patients, the confidence intervals sometimes are large suggesting that the data will not be easy to
replicate. Our study has not revealed associations between
polymorphic variants of genes CYP2D6, MTHFR, MTRR,
NQO1, CYP2C19, and NAT2. These data may indicate that
these genes are not involved in the development of disease, but also reflect the complexity of such kind of investigations and the importance to address other factors of individual lifestyle: carcinogens exposure, smoking, alcohol
consumption, folate intake (especially for MTHFR and
MTRR genes), other dietary factors. Thus, to confirm our
findings and to estimate the predictive value of the analysis
further investigations involving larger cohorts of well-characterized patients may be required.
Methods
Patients
Seventy-six patients with clinical diagnosis of T-cell NHL and eightythree patients with B-CLL were included in the study. All patients were
diagnosed with lymphomas at the National Hematology Research Center of Russian Academy of Medical Sciences. The mean age of NHL
and B-CLL patients was 50 years (from 18 to 78 years; 48.7% males)
and 53 years (from 31 to 83 years; 57.8% males), respectively. Diagnosis was done according to the WHO classification (1997) [51]. The
main techniques used for the diagnosis of lymphomas included clinical,
histological, and immunohistochemical investigation, cell immunophenotyping by flow cytometry or indirect immunofluorescence, and cytogenetic analysis. In many cases (40 out of 76), the diagnosis of T-cell tumor was confirmed by the identification of a pathological T-cell popula-
American Journal of Hematology
TABLE VI. Sequences of Oligonucleotide Probes Immobilized on
Microchip for MTHFR, MTRR, NQO1, and NAT2 Genes
Polymorphism
Sequence from 50 to 30
MTHFR
A1298C
MTRR
A66G
NQO1
C609T
NAT2
T341C
GACCAGTGAAGAAAGTGTC
GACCAGTGAAGCAAGTGTC
CGCAGAAGAAATATGTGAGC
GCAGAAGAAATGTGTGAGC
GTCTTAGAACCTCAACTG
GTCTTAGAATCTCAACTG
GGTGACCATTGACGGCA
GGTGACCACTGACGGCA
Gene
tion with an aberrant phenotype. The number of cells with an aberrant
phenotype ranged from 12 to 99% (74.5% on average) of the whole
T-cell population.
The control group included 177 healthy donors. Blood was taken at
the blood transfusion center of the National Hematology Research Center. The mean age of healthy donors was 51 years (from 20 to 102
years; 50.8% males). All patients and healthy donors were residents of
European part of Russia. The study was approved by the Institutional
Review Boards of the participating institutions. All patients gave
informed consent according to the Declaration of Helsinki.
Oligonucleotide synthesis and microchip production
Oligonucleotides were synthesized with a 394 DNA/RNA synthesizer
(Applied Biosystems, USA) using standard phosphoramidite chemistry.
The oligonucleotides carried a 30 spacer with a free amino group introduced during synthesis using 30 -amino modifier C7 CPG (Glen
Research, USA). The nucleotide sequences of the immobilized oligonucleotides, corresponding to the polymorphic regions of MTHFR
(A1298C), MTRR (A66G), NQO1 (C609T), and NAT2 (T341C) genes
are shown in Table VI. Sequences of other immobilized oligonucleotides have been published elsewhere [33]. Microarrays of polyacrylamide gel pads were prepared by photoinduced copolymerization of oligonucleotides and polyacrylamide gel components as described previously [52].
DNA isolation and multiplex polymerase chain reaction
DNA samples were isolated from peripheral blood leukocytes or homogenized fresh or frozen tissue using the Wizard Genomic DNA purification system (Promega, USA).
The following gene sequences were used for primer and probe construction: CYP1A1 (15q22-q24), CYP2D6 (22q13.1), GSTT1 (22q11.2),
GSTM1 (1p13.3), MTHFR (1p36.3), MTRR (5p15.3-p15.2),
NQO1(16q22.1), NAT2 (8p23.1-p21.3), CYP2C9 (10q24), CYP2C19
(10q24.1-q24.3). Primers were designed using the Oligo 6 program
(Molecular Biology Insights, USA). Primer sequences for the polymorphic regions of genes MTHFR (A1298C), MTRR (A66G), NQO1
(C609T), and NAT2 (T341C) genes are shown in Table VII. Other
genes of drug-metabolizing system were amplified using primers published earlier [33].
For multiplex polymerase chain reaction (PCR) the primers were
combined into groups corresponding to blocks of oligonucleotide probes
on the microarray (Fig. 1). Group 1 (block 1) included the following
genes: CYP1A1 (C4887A, A4889G, and T6235C) and CYP2D6
(G1934A and DelA2637); Group 2 (block 2): GSTT1 (deletion) and
GSTM1 (deletion); Group 3 (block 3): MTHFR (C677T), MTHFR
(A1298C), MTRR (A66G), and NQO1 (C609T); Group 4 (block 4):
CYP2C9 (C430T and C61075T) and CYP2C19 (G681A); and Group 5
(block 5): NAT2 (T341C, C481T, G590A, and G857A). Two-round
nested multiplex PCR was used to amplify gene fragments. The first
round involved multiplex PCR amplification of gene fragments from
blocks 1, 3, 4, and 5, while those from blocks 1–5 were amplified at the
second round.
The reaction mixture (25 ll) at the first round included 0.4 pM each
primer, 67 mM Tris-HCl (pH 8.6), 166 mM (NH4)2SO4, 0.01% Triton X100, 1.5 mM MgCl2, 0.2 mM each dNTP (Sileks, Russia), and 2.5 U
Taq polymerase (Sileks, Russia). PCR was run on a programmable
Termocycler 1 (Biometra, USA). Amplification involved denaturation at
948C for 5 min; then 35 amplification cycles of 948C for 30 s, 608C for
30 s, and 728C for 1 min; and then 728C for 5 min.
285
TABLE VII. Nucleotide Sequences of Primers Used in Multiplex PCR for MTHFR, MTRR, NQO1, and NAT2 Genes
Primer
Gene
Polymorphism
Name
Sequence from 50 to 30
A1298C
MTF2ex
MTR2ex
MRF1ex
MRR1ex
NQO1F1ex
NQO1R1ex
NA2F1ex
NA2R1ex
CTGGGCATGTGGTGGCACT
CTTCCAGGTGGAGGTCTCC
GGGTTGCACTTAGGAAACACAGATTC
CGGTAAAATCCACTGTAACGGCTC
GCTCTGAACTGATTCTCTAGTGTGC
CACGAATACGGTCGATTCCCTC
TTGAGCACCAGATCCGGGCT
GAGTTGGGTGATACATACACAAGGGT
MTF2in
MTR2in
MRF1in
MRR1in
NQO1F1in
NQO1R1in
NA2F1in3
NA2R1in3
GGACTACTACCTCTTCTACCTGAAG
TCCCCACTCCAGCATCACTCAC
CTATATGCTACACAGCAGGGACAGG
CGGTAAAATCCACTGTAACGGCTC
GGCATTCTGCATTTCTGTGGCTTCC
GGATTTGAATTCGGTCGTCTGCTGG
CCATGGAGTTGGGCTTAGAGGC
AGGCTGCCACATCTGGGAGG
Step 1
MTHFR
MTRR
A66G
NQO1
C609T
NAT2
T341C
Step 2
MTHFR
A1298C
MTRR
A66G
NQO1
C609T
NAT2
T341C
The product of the first round (2 ll) was used as a template in the
second round. The aforementioned reaction mixture was supplemented
with 2 pM of fluorescent labeled primers and 0.2 pM of unlabeled primers in order to produce an excess of the labeled single-stranded PCR
product. The reaction involved denaturation at 948C for 5 min; 35
amplification cycles of 948C for 30 s, 628C for 30 s, and 728C for
1 min; and then 728C for 5 min.
Fluorescent labeled samples obtained in the second round of multiplex PCR were used for hybridization on biochip. The hybridization mixture (30 ll) included 7.5 ll formamide (Serva, USA), 7.5 ll 20 3 SSPE
(Promega, USA), and 15 ll of the amplification product (3 ll from each
multiplex PCR mixture). The hybridization mixture was fully denatured
at 958C (5 min), rapidly chilled on ice (1 min), applied to the biochip,
and it was incubated at 378C overnight. Then the biochip was washed
with 1 3 SSPE at room temperature (10 min) and dried.
Signal detection
Fluorescent signals from the gel pads were detected using a portable
biochip analyzer with a CCD camera and the Imageware software
(Biochip-IMB, Russia) as described elsewhere [33,53].
Statistical analysis
The fit of the genotype frequencies to the expected distribution in
Hardy-Weinberg equilibrium was tested using the standard v2 test
(GraphPad InStat software, USA). The genotype frequencies for all
studied biotransformation system genes corresponded to the HardyWeinberg distribution (the highest v2 was 2.1305; P > 0.05). Pairwise
comparison of allelic and genotypic frequencies and evaluation of the
relationship between the alleles and risk of NHL and B-CLL relied on
two-sided exact Fisher test. The odds ratio (OR) of the disease was
calculated for particular genotypes using the following equation:
OR ¼
a=b
;
c=d
where a 5 n1, b 5 N12n1, c 5 n2, d 5 N22n2, N1 and N2 are sample
size, n1 and n2 are numbers of individuals with the studied character in
these two samples. OR values were computed in this work using a
95% confidence interval (95% CI). The threshold for rejecting the null
hypothesis was set to 5%.
Acknowledgments
The authors thank T.E. Ivashchenko and B.S. Baranov
for DNA samples from normal controls, D.V. Prokopenko
and R.A. Yurasov for help in data processing, and S.V.
Pan’kov for the manufacturing of biochips, and S.A. Surzhikov for the synthesis of oligonucleotides.
286
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