ORIGINAL ARTICLE

Polymorphisms in XPC provide prognostic informationin acute myeloid leukemia

Peipei Xu • Baoan Chen • Jifeng Feng •

Lu Cheng • Guohua Xia • Yufeng Li •

Jun Qian • Jiahua Ding • Zuhong Lu

Received: 7 March 2012 / Revised: 3 July 2012 / Accepted: 3 July 2012

� The Japanese Society of Hematology 2012

Abstract Acute myeloid leukemia (AML) is the most

common type of adult leukemia for which cytosine arabi-

noside-based chemotherapy is the main treatment. Single

nucleotide polymorphisms within the nucleotide excision

repair pathway may alter the susceptibility of leukemia

cells to chemotherapy. We investigated the roles of six

single nucleotide polymorphisms (ERCC5rs76871136,

ERCC5rs77569659, ERCC5rs873601, XPCrs2228000,

XPCrs2228001, and XPCrs1870134) in the nucleotide

excision repair pathway in influencing the outcome of

patients with AML treated with cytosine arabinoside-based

chemotherapy. One hundred fifty-one patients with AML

in a Chinese population were enrolled in this study.

Genotypes were determined by matrix-assisted laser

desorption/ionization time-of-flight mass spectrometry. We

found that the distribution of three genotypes of

XPCrs1870134 significantly differed in the cytogenetic risk

groups (P = 0.04). A statistically significant correlation

between polymorphisms of XPCrs2228001 and gender

was found among the gender groups (P = 0.03). More-

over, patients carrying at least one variant allele

(XPCrs2228001AA?CC) were more likely to respond

better than those who did not carry a variant. However, no

significant association was detected between polymor-

phisms in ERCC5 and treatment response. These findings

suggest that XPC polymorphisms are important markers for

the outcome of patients with AML in the Chinese

population.

Keywords Single nucleotide polymorphism � Nucleotide

excision repair � Acute myeloid leukemia � Mass

spectrometry

Introduction

Acute myeloid leukemia (AML) is a heterogeneous group

of leukemia resulting from the clonal transformation of

hematopoietic precursors through chromosomal rear-

rangements and multiple gene mutations [1]. AML is the

most common acute leukemia in adults in the United

States, and less than 23 % of patients with AML live more

than 5 years after being diagnosed [2]. Chemotherapy is

the most effective method of treating AML, with various

Electronic supplementary material The online version of thisarticle (doi:10.1007/s12185-012-1145-3) contains supplementarymaterial, which is available to authorized users.

P. Xu � B. Chen (&) � G. Xia � J. Ding

Department of Hematology, Zhongda Hospital,

Medical School, Southeast University, Dingjiaqiao 87,

Nanjing 210009, People’s Republic of China

e-mail: cba8888@hotmail.com

P. Xu � B. Chen � G. Xia � J. Ding

Faculty of Oncology, Medical School, Southeast University,

Nanjing, People’s Republic of China

J. Feng

Jiangsu Province Cancer Institute,

Nanjing, People’s Republic of China

L. Cheng � Z. Lu

State Key Laboratory for Bioelectronics, School of Biological

Science and Medical Engineering, Southeast University,

Nanjing, People’s Republic of China

Y. Li

Huaian No. 1 People’s Hospital, Huaian,

People’s Republic of China

J. Qian

Zhenjiang No. 1 People’s Hospital, Zhenjiang,

People’s Republic of China

123

Int J Hematol

DOI 10.1007/s12185-012-1145-3

anticancer drugs being used either in combination or as

single agents. At present, more than 50 % of patients with

AML achieve a complete response (CR) following induc-

tion therapy with cytosine arabinoside (Ara-C)-based che-

motherapy [3, 4]. Ara-C has served as one of the most

important elements of AML treatment regimens for more

than 50 years now. Figure 1 illustrates the cellular

metabolism of Ara-C by many enzymes. However, there is

a significant difference in treatment response and survival,

especially among large groups of patients with the same

disease classification.

Single nucleotide polymorphisms (SNPs) are the most

frequently occurring genetic variation in the human gen-

ome. Currently, the total number of SNPs from SNP dat-

abases exceeds in public 9 million [5, 6]. SNPs are

important markers that can account for phenotypic diver-

sity, which influence the risk of certain diseases, and vari-

able responses to drugs or the environment. Genetic

association studies using SNP markers are expected to

facilitate the identification of genetic factors responsible for

complex diseases as well as the early diagnosis, prevention,

prognosis, and possibly, treatment of diseases [7, 8].

Among DNA repair mechanisms, the nucleotide excision

repair (NER) pathway is able to eliminate a wide variety of

damage, including many adducts [9]. The mechanism of

action of Ara-C in standard treatment regimens for AML is

via induction of single- and double-strand breaks (DSBs) and

other DNA lesions [10]. Thus, inherent variability in certain

DNA repair pathways may modify the effects of AML

treatment with Ara-C. Recent studies have suggested that

associations between AML and SNPs of certain DNA repair

genes exist [10–13]. Certain SNPs of DNA repair genes alter

not only the constitutive capacity of host cells to deal with

DNA lesions, but also the susceptibility of leukemia cells to

specific malignancies or their sensitivity to chemotherapy

and radiotherapy. Whether certain SNPs influence predis-

position to AML treatment response individually or

collectively is of considerable research interest. In this study,

we evaluated 151 adult patients with AML and explored

the effects of six polymorphisms in genes within the

NER pathway, including ERCC5rs76871136 (Gly1271Ter),

ERCC5rs77569659 (Lys580Gln), ERCC5rs873601

(*84G[T), XPCrs2228000 (Ala499Val), XPCrs2228001

(Lys939Gln), and XPCrs1870134 (Leu16Val).

Materials and methods

Patient characteristics

One hundred fifty-one patients diagnosed with AML

according to World Health Organization (WHO) criteria

Fig. 1 Candidate genes involved in the metabolism, transport, and

cellular activity of Ara-C. The mechanism of action of Ara-C is via

induction of single- and double-strand breaks and other DNA lesions.

SNPs within the NER pathway (e.g., XPC and ERCC5) are able to

eliminate a wide variety of damage, including double-strand breaks.

Thus, inherent variability in XPC and ERCC5 may modify the effects

of AML treatment with Ara-C. DCK deoxycytidine kinase, CDAcytidine deaminase, hENT human equilibrative nucleoside transporter

1, dCMPD deoxycytidylate deaminase, XPC xeroderma pigmento-

sum, complementation group C; XPD xeroderma pigmentosum group

D, ERCC5 excision repair cross-complementing rodent repair defi-

ciency, complementation group 5

P. Xu et al.

123

[14] in six large hospitals in Jiangsu Province, China, were

enrolled between September 2008 and March 2011.

Patients diagnosed with other cancers or other hemato-

logical malignancies were excluded in this study. All study

patients were genetically unrelated ethnic Han Chinese.

This study was approved by the ethics committee of

Southeast University in compliance with Chinese guide-

lines for blood donation, and informed consent for genetic

analysis was obtained from all participants according to the

Declaration of Helsinki.

Of the 151 study patients, 6 were specifically diagnosed

with minimally differentiated AML (M0), 9 with AML

without maturation (M1), 77 with AML with maturation

(M2), 22 with acute myelomonocytic leukemia (M4), 28

with acute monocytic leukemia (M5), 7 with erythroleu-

kemia (M6), and 2 with acute megakaryoblastic leukemia

(M7). The characteristics of the patients are detailed in

Tables 1 and 2. Cytogenetic risk groups were defined as

follows: unfavorable, -7/del(7q), -5/del(5q), abn3q,

abn9q, abn17p, and abn11q; complex aberrations (three or

more independent aberrations), t(6;9), and t(9;22); favor-

able, t(15;17), inv(16)/t(16;16)/del(16q), and t(8;21);

intermediate risk, all other karyotypic aberrations or a

normal karyotype [15]. Moreover, patients were divided

into two groups according to the following indices:

hemoglobin level, number of white blood cells (WBCs),

and platelet count. Complete clinical examination and

history taking, bone marrow biopsy, serum biochemical

analysis, and complete blood count were performed to

confirm the patients’ diagnosis before the chemotherapy

regimens were initiated.

Seventy patients intravenously received 45 mg/m2/day

of daunorubicin (DNR) for 1–3 days and 100 mg/m2/day

of Ara-C for 1–7 days (DA induction chemotherapy regi-

men), 36 received 93–4 mg/m2/day of homoharringtonine

(HHT) for 5–7 days and 100 mg/m2/day of Ara-C for

1–7 days (HA induction chemotherapy regimen), and 45

received 4 mg/m2/day of mitoxantrone for 1–5 days and

100 mg/m2/day of Ara-C for 1–7 days (MA induction

chemotherapy regimen). Study patients were considered to

have achieved a complete response (CR) if their absolute

values of granular leukocytes and platelets in peripheral

blood did not exceed 1.5 9 109 and 100 9 109/L, respec-

tively; their blast cell count in the bone marrow was less

than 5 % for at least 4 weeks; they no longer exhibited

signs and symptoms of leukemia; and they were found to

have granulopoiesis and megakaryocytopoiesis cells after

chemotherapy with normalized peripheral blood counts

persisting for at least 4 weeks without intervening che-

motherapy. On the other hand, the study patients were

considered to have achieved partial remission (PR) if their

clinical manifestation, blood analysis, and bone marrow

biopsy did not meet the standard criteria for CR and they

had less than 20 % blast and promyelocytic cells in the

bone marrow. Non-remission (NR) was defined as clinical

manifestation, blood analysis, and bone marrow biopsy not

meeting the standard criteria for CR and the presence of

more than 20 % promyelocytic cells in the bone marrow.

Early death was defined as death within 8 weeks from the

start of the first induction therapy course. For data analysis,

CR and PR were combined as good response, and NR and

early death were grouped as poor response [16, 17].

DNA collection and polymerase chain reaction (PCR)

We selected six SNPs within the NER pathway that have

been reported to be associated with cancer development

and outcome [18]. These SNPs coding polymorphisms for

amino acid substitutions likely affect the resulting protein

structure and function. They occur at a relatively high

frequency, thereby affecting a relatively large segment of

the general population.

Genomic DNA was isolated from blood samples of the

study participants using TIANGEN DNA Mini Kits

(TIANGEN) and stored at -20 �C for later use. DNA

integrity was detected by electrophoresis (Fig. 2), and PCR

was performed in a 25-lL reaction solution. Primers were

designed by Primer Premier 6.0. The sequences of the

primers are shown in Table 3. Excess PCR primers and

dNTPs were removed. Electrophoretic identification of the

alleles was carried out according to their PCR product

length (Fig. 2).

Single-base extension

Single-base extension primers were designed by Primer

Premier 6.0. The sequences of the primers are shown in

Table 3, whereas the total reaction volume is provided in

Supplementary Table 1. The PCR program consisted of 40

two-step cycles with a 5-cycle loop each. The thermal

protocol was initiated at 95 �C for 30 s, followed by 95 �C

for 5 s for the outer loop and then by 52 �C for 5 s and

85 �C for 5 s for the inner loop. The program lasted for

3 min at 72 �C.

Matrix-assisted laser desorption/ionization

time-of-flight mass spectrometry (MALDI-TOF MS)

genotyping

SNP genotyping was performed with MALDI-TOF MS

using a MassARRAY System (Sequenom) according to the

manufacturer’s instructions. Briefly, completed genotyping

reactions were spotted onto a 384-well spectro CHIP

(Sequenom) using a Mass ARRAY Nanodispenser (Seque-

nom) and determined by MALDI-TOF MS. Sequencing of

10 % samples was performed to validate the results.

XPCrs2228001 and acute myeloblastic leukemia

123

Statistical analysis

Deviations from the Hardy–Weinberg equilibrium for

genotypes and haplotype frequencies as well as haplotype–

trait associations were assessed with Pearson’s v2 analysis

using SHEsis. Once the expected number in any cell was less

than five, demographic and clinical data across genotypes

were compared using Pearson’s v2 analysis or Fisher’s exact

test. Significant genotypic differences among the different

responders were calculated using Pearson’s v2 analysis.

P \ 0.05 was considered statistically significant. We esti-

mated the relative risk of responding to treatment with the

genotypes as odds ratio (OR) and 95 % confidence intervals

(95 %CI) using conditional logistic regression with adjust-

ment for the effects of covariates. All statistical tests were

two-sided and performed using SPSS 17.0.

Table 1 Characteristics of patients according to the XPCrs1870134 and the XPCrs2228000 genotype

Variable Overall (n = 151) XPCrs1870134 XPCrs2228000

GG CC GC G allele C allele TT CC TC T allele C allele

Gender

Female 65 31 4 30 70.8 29.2 6 29 30 32.3 67.7

Male 86 47 6 33 73.8 26.2 9 40 37 32.0 68.0

P value 0.657 0.554 0.916 0.951

Age (years)

B40 53 29 4 20 73.6 26.4 6 22 25 34.9 65.1

40–60 52 27 4 21 72.1 27.9 8 23 21 35.6 64.4

C60 46 22 2 22 71.7 28.3 1 24 21 25.0 75.0

P value 0.857 0.935 0.181 0.202

FAB classification

M0 6 2 1 3 58.3 41.7 0 3 3 25.0 75.0

M1 9 5 0 4 77.8 22.2 3 4 2 44.4 55.6

M2 77 45 4 28 72.8 27.2 8 38 31 28.1 71.9

M4 22 8 3 11 61.4 38.6 3 10 9 35.3 64.7

M5 28 19 1 8 82.1 17.9 3 10 15 37.5 62.5

M6 7 5 0 2 85.7 14.3 0 4 3 21.4 78.6

M7 2 0 0 2 50.0 50.0 0 1 1 25.0 75.0

P value 0.681 \0.001* 0.661 0.007*

Cytogenetic risk group

Favorable 16 11 0 5 84.4 15.6 1 10 5 21.9 78.1

Intermediate 108 48 8 52 68.5 31.5 11 48 49 32.9 67.1

Unfavorable 27 19 2 6 81.5 18.5 3 11 13 35.2 64.8

P value 0.040* 0.017* 0.735 0.110

Lab at diagnosis

WBC (9109/L)

B50 127 64 8 55 72.0 28.0 13 59 55 31.9 68.1

[50 24 14 2 8 75.0 25.0 2 10 12 33.3 66.7

P value 0.677 0.674 0.809 0.844

Hemoglobin (g/L)

B100 107 54 9 44 71.0 29.0 9 56 42 28.0 72.0

[100 44 24 1 19 76.1 23.9 6 13 25 42.0 58.0

P value 0.378 0.366 0.039* 0.017*

Platelets (9109/L)

B60 103 57 7 39 74.3 25.7 12 50 41 31.6 68.4

[60 48 21 3 24 68.75 31.25 3 19 26 33.3 66.7

P value 0.387 0.316 0.241 0.757

WHO World Health Organization, WBC white blood cell count

* P \ 0.05

P. Xu et al.

123

Results

MALDI-TOF MS for genotyping

A typical MALDI-TOF MS spectrum after mini

sequencing by standard ddNTPs is shown in Fig. 3. A

corresponding scatter plot is illustrated in Supplementary

Fig. 1.

Characteristics of patients and genotypes

The demographic and relevant clinical characteristics of

the study patients are listed in Tables 1 and 2. Sixty-five

males and 86 females (age range 15–81 years, median age

46.20 years) constituted the study sample. The evaluation

standard of these patients were evaluated by age (B40,

40–60, and C60 years), WBC ([50 9 109 vs. B50 9 109/L),

Table 2 Characteristics of patients according to the XPCrs2228001 and the ERCC5rs873601 genotype

Variable Overall (n = 151) XPCrs2228001 ERCC5rs873601

AA CC AC A allele C allele AA GG AG A allele G allele

Gender

Female 65 27 4 34 67.7 32.3 8 24 33 37.7 62.3

Male 86 37 15 34 62.8 37.2 17 25 44 45.3 54.7

P value 0.030* 0.323 0.489 0.256

Age (years)

B40 53 19 6 28 62.3 37.7 12 18 23 44.3 55.7

40–60 52 24 6 22 67.3 32.7 7 18 27 39.4 60.6

C60 46 21 7 18 65.2 34.8 6 13 27 42.4 57.6

P value 0.716 0.778 0.521 0.789

FAB classification

M0 6 3 0 3 75.0 25.0 0 2 4 33.3 66.7

M1 9 5 1 3 72.2 27.8 3 4 2 44.4 55.6

M2 77 31 13 33 61.4 38.6 10 29 38 35.1 64.9

M4 22 14 1 7 79.4 20.6 6 4 12 52.9 47.1

M5 28 10 5 13 58.9 41.1 6 5 17 51.8 48.2

M6 7 2 3 2 42.9 57.1 0 2 5 35.7 64.3

M7 2 2 0 0 100.0 0.0 0 1 1 25.0 75.0

P value 0.399 0.557 0.353 \0.001*

Cytogenetic risk group

Favorable 16 4 5 7 46.9 53.1 4 7 5 40.6 59.4

Intermediate 108 51 10 47 69.0 31.0 18 31 59 44.0 56.0

Unfavorable 27 9 4 14 59.3 40.7 3 11 13 35.2 64.8

P value 0.246 0.007* 0.344 0.435

Lab at diagnosis

WBC (9109/L)

B50 127 56 16 55 65.7 34.3 19 43 65 40.6 59.4

[50 24 8 3 13 60.4 39.6 6 6 12 50.0 50.0

P value 0.669 0.511 0.654 0.316

Hemoglobin (g/L)

B100 107 44 17 46 62.6 37.4 18 37 52 41.1 58.9

[100 44 20 2 22 70.5 29.5 7 12 25 44.3 55.7

P value 0.202 0.268 0.587 0.685

Platelets (9109/L)

B60 103 39 12 52 63.1 36.9 19 30 54 44.7 55.3

[60 48 25 7 16 68.75 31.25 6 19 23 36.5 63.5

P value 0.147 0.436 0.448 0.234

WHO World Health Organization, WBC white blood cell count

* P \ 0.05

XPCrs2228001 and acute myeloblastic leukemia

123

hemoglobin level ([100 vs. B100 g/L), and platelet count

([60 9 109 vs. B60 9 109/L). The results showed significant

differences among XPCrs1870134, XPCrs2228001, and

XPCrs2228000 (Tables 1, 2). The distribution of the three

genotypes of XPCrs1870134 among the cytogenetic risk

groups showed significant difference (P = 0.04). The fre-

quency of the CC genotype of XPCrs2228001 was

significantly higher in male patients than in female patients

(P = 0.03), whereas that of the CC genotype of

XPCrs2228000 was significantly higher in patients with a

hemoglobin level of 100 g/L or less compared with those who

had a hemoglobin level greater than 100 g/L (P = 0.039).

However, significant differences in WBC and platelet count

were not detected (P [ 0.05).

Fig. 2 a Detection of DNA

integrity. b SNPs within the

NER pathway investigated in

this study. c PCR products of

ERCC5rs76871136 for different

samples: a–d sample 1,

e–h sample 2, and i–l sample 3.

d PCR analysis of the six SNPs:

a ERCC5rs76871136;

b ERCC5rs77569659;

c ERCC5rs873601;

d XPCrs1870134;

e XPCrs2228000; and

f XPCrs2228001

Table 3 Sequences of primers

and single-base extension

primer

Locus Primers and single-base extension primer

XPC

rs1870134 Forward primer: 50-ACGTTGGATGTCTTGGCCTTGGATTTCTGG-30

46C[G Reverse primer: 50-ACGTTGGATGAAGCAACATGGCTCGGAAAC-30

Leu16Val Single-base extension primer: 50-GGGGAGCCGCGGGGACGCGAA-30

rs2228000 Forward primer: 50-ACGTTGGATGAGCCATCGTAAGGACCCAAG -30

1496C[T Reverse primer: 50-ACGTTGGATGTCGCTGCACATTTTCTTGCC -30

Ala499Val Single-base extension primer: 50-GAAGAGCTTGAGGATGCC -30

rs2228001 Forward primer:50-ACGTTGGATGAGCAGCTTCCCACCTGTTC -30

2815C[A Reverse primer: 50-ACGTTGGATGAACTGGTGGGTGCCCCTCTA -30

Gln939Lys Single-base extension primer: 50-CACCTGTTCCCATTTGAG -30

ERCC5

rs76871136 Forward primer: 50-ACGTTGGATGACTGATCAGACTTCCGGAAC-30

3811G[T Reverse primer: 50-ACGTTGGATGAAGTTTCTATAGACATGCC-30

Gly817Ter Single-base extension primer: 50-CAGTGATATCTGGCTGTTT-30

rs77569659 Forward primer: 50-ACGTTGGATGGACAAGCCATCAAAACTGCC-30

376A[C Reverse primer: 50-ACGTTGGATGAACTTCATCTCTAACACGAC-30

Lys126Gln Single-base extension primer: 50-ATAATTTTCCTCTTGCCTTT-30

rs873601 Forward primer:50-ACGTTGGATGATGAATTTGTCGCAAAGACG-30

*84G[A Reverse primer: 50-ACGTTGGATGTGTTTTTAGGAACCACACAC-30

30-UTR Single-base extension primer: 50-AAGACGTAATAAAATTAACTGGT-30

P. Xu et al.

123

Distribution of alleles

Genotype frequencies for the polymorphisms were found to

be in Hardy–Weinberg equilibrium (Tables 1, 2). The

results showed four major patterns: (1) the frequency of the

C allele of XPCrs1870134 was significantly higher in the

intermediate risk group (P = 0.017) and in patients with

acute megakaryoblastic leukemia (P \ 0.001). (2) Among

the polymorphisms, the frequency of the XPCrs2228000 T

allele was significantly higher in patients with AML

without maturation (P = 0.007) and in those whose

hemoglobin level was 100 g/L or higher (P = 0.017). (3)

The frequency of the C allele of XPCrs2228001 was sig-

nificantly lower in the intermediate risk group than in the

other groups (P = 0.007). (4) The distribution of the two

alleles of ERCC5rs873601 among the study sample

showed significant difference (P \ 0.001). However, sig-

nificant genotypic differences by gender, FAB classifica-

tion, laboratory diagnosis, and chemotherapy regimen were

not detected.

Fig. 3 MALDI-TOF MS spectrum of the six SNPs: XPCrs1870134, XPCrs2228000, XPCrs2228001, ERCC5rs873601, ERCC5rs76871136,

ERCC5rs77569659

0

20

40

60

80

100

148

150

152

154

P=0.152P<0.001*P=0.189

ERCC5rs77569659

ERCC5rs76871136

ERCC5rs873601

XPCrs2228001

XPCrs2228000

Num

ber

of p

atie

nts

CR+PR NR+early death

GG GC CC TTTC CC GG AA

XPCrs1870134

AC AA CC AG AA GG

Genotype

P=0.003*

Fig. 4 Outcomes of treatment

according to genotype

(n = 151). The polymorphic

genotypes of XPCrs1870134

(P = 0.003) and XPCrs2228001

(P \ 0.001) were significantly

different between good

responses group and poor

response group. Two-sided

v2-test for either genotype

distributions or allele

frequencies between good

responses group (CR ? PR) and

poor response group

(NR ? early death). *P \ 0.05.

CR complete response, PRpartial remission, NR non-

remission

XPCrs2228001 and acute myeloblastic leukemia

123

Treatment outcome according to the XPC

and ERCC5 genotypes

All patients were treated with Ara-C-based standard induc-

tion chemotherapy regimens (DA, HA, or MA). Treatment

effects were evaluated after the second cycle of chemo-

therapy. The frequencies of genotypes in patients with AML

who had different treatment responses are shown in Fig. 4,

and correlations between genotypes and treatment response

are given in Table 4. One hundred six patients (70.2 %) had a

good response (CR ? PR), whereas the remaining 45

(29.8 %) showed a poor response (NR ? early death). The

results showed that the polymorphic genotypes of

XPCrs1870134 and XPCrs2228001 were significantly dif-

ferent between the patients responding to Ara-C-based

treatment and the nonresponsive ones. After combining the

heterozygous and homozygous variant genotypes, the dif-

ference remained statistically significant, confirming that the

XPCrs1870134 and XPCrs2228001 genotypes differed

between groups. The results also demonstrated that the

genotypes influenced treatment response. Patients carrying

at least one variant allele (XPCrs2228001AA?CC) were

more likely to respond better compared with those who did

not carry a variant. After adjusting for gender, age at diag-

nosis, tumor histology, and chemotherapy regimen, the OR

for response was 0.295 (95 % CI = 0.136–0.643)

(P = 0.002). For the other SNP loci, the genotypes did

not substantially differ among the groups. Table 5 lists the

statistical results from the case–control tests performed on

each haplotype of XPCrs1870134, XPCrs2228000, and

XPCrs2228001. Significant associations between the hap-

lotypes and treatment response were not observed.

Table 4 Genotype and response to chemotherapy among AML patients (n = 151)

Genotype Cases Response to chemotherapy OR (95 % CI) P value Adjusted OR (95 %CI) Adjusted P value

CR ? PR (%) NR ? early death (%)

XPC

rs1870134

GG 78 60 (56.60) 18 (40) 1 1

GC 63 40 (37.74) 23 (51.11) 0.522 (0.250–1.008) 0.082 0.510 (0.243–1.071) 0.075

CC 10 6 (5.66) 4 (8.89) 0.450 (0.114–1.772) 0.253 0.450 (0.114–1.777) 0.254

GC?CC 73 46 (43.40) 27 (60) 0.511 (0.251–1.039) 0.063 0.501 (0.245–1.024) 0.057

rs2228000

TC 67 48 (45.28) 19 (42.22) 1 1

CC 69 47 (44.34) 22 (48.89) 0.846 (0.406–1.762) 0.654 0.849 (0.407–1.771) 0.662

TT 15 11 (10.38) 4 (8.89) 1.089 (0.308–3.844) 0.895 1.101 (0.310–3.916) 0.881

CT?TT 84 58 (54.72) 26 (57.78) 0.883 (0.437–1.786) 0.729 0.888 (0.438–1.797) 0.740

rs2228001

AC 68 56 (52.83) 12 (26.67) 1 1

AA 64 40 (37.74) 24 (53.33) 0.322 (0.144–0.720) 0.005 0.316 (0.140–0.712) 0.005*

CC 19 10 (9.43) 9 (20) 0.203 (0.067–0.619) 0.005 0.203 (0.067–0.619) 0.005*

CC?AA 66 50 (47.17) 33 (70.33) 0.300 (0.139–0.645) 0.002 0.295 (0.136–0.643) 0.002*

ERCC5

rs873601

AG 77 53 (50) 24 (53.33) 1 1

AA 25 13 (12.26) 12 (26.67) 0.505 (0.196–1.300) 0.156 0.504 (0.193–1.313) 0.160

GG 49 40 (37.74) 9 (20) 2.058 (0.867–4.885) 0.101 2.037 (0.855–4.854) 0.108

AG?GG 74 53 (50) 21 (46.67) 1.204 (0.597–2.425) 0.604 1.201 (0.593–2.435) 0.610

rs76871136

GG 151 106 (70.20) 45 (29.80) 1 – 1 –

rs77569659

AA 151 102 (67.55) 49 (22.45) 1 – 1 –

Adjusted OR (95 % CI): OR (95 % CI) after adjusting for patient gender, age at diagnosis, and chemotherapy regimens

OR odds ratio, CI confidence interval, CR complete remission, PR partial remission, NR non-remission

* P \ 0.05

P. Xu et al.

123

Discussion

In this retrospective study, we explored the associations

between NER polymorphisms and treatment outcome in

patients with AML in a Chinese population. Our analysis

highlights the relevance of the gene variant in Ara-C-based

chemotherapy response. We found that the XPCrs1870134

CC genotype was more frequent in the intermediate risk

group but that the XPCrs1870134 C allele and

XPCrs2228001 C allele were significantly lower in the

same group. The XPCrs2228001 CC genotype was more

frequent in the male patients.

DNA repair enzymes in the NER pathway recognize and

eliminate a wide variety of damage, including that induced

by chemotherapy. Therefore, a testable hypothesis is that

common variants within the NER pathway may lead to

interindividual differences in DNA repair capacity, which

could result in greater susceptibility to the genotoxic

effects of treatment [9, 19]. Batar et al. [20] found that

females carrying the XRCC1 194 Trp allele had an

increased risk of developing childhood acute lymphoblastic

leukemia (ALL). Several mutants within the NER pathway

similar to XRCC1 have been reported in polycythemia

vera, colorectal cancer, ALL, AML, unclassified myelo-

proliferative syndrome, and Down syndrome [21–24].

The XPC protein can bind to HR23B and centrin 2 to

form the XPC–HR23B heterotrimeric complex, which is

involved in DNA damage recognition and/or in altering the

chromatin structure to allow access by damage-processing

enzymes [25–28]. The XPCrs1870134, which is located at

nucleotide 46 within the 50 precursor peptide sequence,

causes an amino acid substitution of leucine to valine at

codon 16 (Leu16Val). XPCrs2228001 also causes the

substitution of a single amino acid from lysine to glutamine

(Lys939Gln). The SNP XPCrs2228000 has been identified

at nucleotide 1496 within the 50 precursor peptide sequence

and causes an amino acid substitution of alanine to valine

at codon 499 (Ala499Val). Some studies have shown that

XPC polymorphisms are associated with the risk of various

tumors, such as AML, gastric cancer, bladder cancer, and

lung cancer [29–32]. For example, the mutated homozy-

gous genotype for XPCrs2228001 has been reported to be

associated with a 2.09-fold increased risk of developing

bladder cancer compared with the wild-type genotype [31].

Strom et al. [22] found that no significant association

between XPCrs2228001/XPCrs2228000 and disease-free

survival of patients with AML in the United States exists.

Our results indicated that patients carrying at least one

variant allele (XPCrs2228001AA?CC) were more likely to

respond better compared with those not carrying any wild-

type and variant alleles (AC). Our findings differ from

those of the above-described studies, which can be attrib-

uted to the differences in ethnic groups and sample sizes

that may have influenced the results of genetic analysis.

As a single-stranded structure-specific DNA endonu-

clease, ERCC5 is involved in DNA excision repair and acts

as a cofactor for a DNA glycosylase that removes oxidized

pyrimidines from DNA. The human ERCC5 sequence has

an open reading frame of 1186 amino acids, and it encodes

a 133 kDa acidic protein [33]. Mutations in this gene can

result in the ERCC5 protein. ERCC5rs873601 polymor-

phisms are located in the 30-untranslated region, which may

affect miRNA expression and its potential targets and

might play a role in regulatory processes during NER

pathway. ERCC5rs76871136 has been identified at nucle-

otide 3811 within the 50 precursor peptide sequence and

causes an amino acid substitution of glycine to chain ter-

mination (Gly817Ter). ERCC5rs77569659 is also a func-

tional polymorphism in exon 9. The ERCC5 gene has been

reported to be associated with the risk of many tumors in

some previous studies. ERCC5 promoter polymorphisms at

-763 and ?25 may be important predictors of response to

oxaliplatin chemotherapy [34]. ERCC5 codon 1104 poly-

morphisms are independent prognostic factors in patients

with cutaneous melanoma [35]. Strom et al. [22] found that

the ERCC5 (rs17655) did not influence the outcome of

Table 5 Tests for haplotype–trait association among XPCrs1870134, XPCrs2228000, XPCrs2228001

Haplotype Frequencies P value OR (95 % CI)

Trait 1 Trait 2 Combined

GTA* 66.76 (0.315) 25.91 (0.288) 0.130 0.719 1.105 (0.641–1.904)

GCA* 16.24 (0.077) 5.19 (0.058) 0.296 0.586 1.327 (0.478–3.685)

GCC* 75.89 (0.358) 27.90 (0.310) 0.477 0.489 1.206 (0.709–2.052)

CTA 2.13 (0.010) 1.09 (0.012) – – –

CCA* 49.87 (0.235) 27.81 (0.309) 2.101 0.147 0.666 (0.383–1.156)

CCC 0.00 (0.000) 2.10 (0.023) – – –

GTC 1.11 (0.005) 0.00 (0.000) – – –

Treatment response to chemotherapy, Trait 1, CR ? PR (n = 106); Trait 2, NR ? early death (n = 45)

OR odds ratio, CI confidence interval, CR complete response, PR partial remission, NR non-remission

XPCrs2228001 and acute myeloblastic leukemia

123

patients with AML in an American population. In contrast,

the polymorphisms described in the present study have not

been previously evaluated in relation to AML. We did not

find any significant differences in genotype frequencies for

the three polymorphisms between patients and control

subjects.

In conclusion, we have developed a genotyping assay

based on MALDI-TOF MS for the detection of polymor-

phisms in NER. Our results suggest that XPC polymor-

phisms are important markers for the outcome of therapy in

patients with AML in the Chinese population. This study

has several differences from previous studies, indicating

that prospective studies with larger sample sizes and eth-

nically diverse populations are needed to further under-

stand the correlations between NER polymorphisms and

treatment response of patients with AML.

Acknowledgments This work was financially supported by National

Key Basic Research Program 973 of China (No. 2010CB732404),

National Natural Science Funds of People’s Republic of China

(No. 81170492) and Key Medical Disciplines of Jiangsu Province, and

Innovation Program of Jiangsu Province (CXLX_0150).

Conflict of interest The authors declare no conflict of interest.

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