Association of DNA Repair Genes XRCC1 (Arg399Gln),(Arg194Trp) and XRCC3 (Thr241Met) Polymorphisms with the Risk of Breast Cancer: A Case-Control Study in Egypt

Abstract

Various DNA damage, induced by endogenous and exogenous factors, is handled through DNA repair pathways such as X-ray repair cross-complementing protein (XRCC). Genetic variations in these pathways may have a joint or additive effect on various types of cancer, including the risk of breast cancer (BC). Aim: To evaluate the association of three single-nucleotide polymorphisms (SNPs) Arg399Gln, Arg194Trp, and Thr241Met in DNA repair genes XRCC1 and XRCC3 on the risk of BC, and to assess their interaction with risk factors and prognostic markers in a case-control study in Egypt. Methods: We detected the studied SNPs using polymerase chain reaction-restriction enzyme polymorphism (PCR-RFLP) in peripheral blood from 100 BC patients and 75 healthy females. Results: The dominant model of inheritance of Arg399Gln and Arg194Thr revealed an increase in BC risk of odds ratio (OR) of 3.56, 95% confidence interval (CI)=1.22-10.39, p=0.017 and OR: 4.45, 95% CI=2.35-8.45, p<0.001 respectively. However, there was no clear interaction between the studied SNPs and the known risk factors, or tumor criteria. No association between the Thr241Met genotype and BC risk was observed. Conclusion: XRCC1 Arg399Gln and Arg164Trp variant genotypes are associated with an increased risk of BC in Egyptian females.

Introduction

Intracellularly the exposure to endogenous and exogenous mutagens promotes DNA damage, which can cause genetic instability and carcinogenesis. Cells respond to such damage by activating DNA repair mechanisms, initiating apoptosis, and cell cycle arrest (Lahtz and Pfeifer, 2011). Typically, DNA repair enzymes can repair most DNA damage. The X-ray repair cross-complementing protein 1 (XRCC1) participates in base excision repair (BER) of small lesions, including oxidized or reduced bases, fragmented or non-bulky adducts, and lesions caused by methylating agents. XRCC1 is located on the long arm of chromosome 19(19q 13.2-13.3) with 17exons. It has a direct role in DNA kinase stimulation at damaged DNA termini, thereby accelerating the overall repair reaction. Three nonconservative amino acid substitutions in XRCC1 have been identified; an arginine to glutamine change at codon 399 (G→A) in exon 10, an arginine to tryptophan change at codon 194 (C→T) in exon 6, and an arginine to histidine change at codon 280 (G→A) in exon 9 (Xue et al., 2011).

XRCC3 is an integral player in the DNA double-strand break pathway, located in the 14q32.3 region. It is responsible for repairing DNA breaks that result from exogenous agents, such as ionizing radiation or tobacco smoke, and from endogenously generated reactive oxygen species. The XRCC3 function is not limited to initiation of homologous recombination, but extends to later stages in the formation and resolution of intermediates by stabilizing heteroduplex DNA (Manuguerra et al., 2006). XRCC3 Thr241Met (C→T) has been associated with increased formation of DNA adducts and chromosomal deletions (Romanowicz-Makowska et al., 2011).

Polymorphisms in XRCC may affect the repair of bulky DNA adducts and oxidative DNA damage leading to genomic rearrangements, transcriptional deregulation, and eventually malignancies (Romanowicz-Makowska et al., 2011), thus encouraging their study as candidate cancer susceptibility genes. Actually, a positive association has been reported in head and neck cancer (Sturgis et al., 1999) as well as lung cancer (Divine et al., 2001), but contrary results were found in bladder (Stern et al., 2001) and nonmelanoma skin cancers (Nelson et al., 2000). Owing to the high prevalence of breast cancer (BC) in Egypt (18.9% of total cancers) (Omar et al., 2003), the aim of our study was the role of three single-nucleotide polymorphisms (SNPs) Arg399Gln, Arg194Trp, and Thr241Met in DNA repair genes XRCC1 and XRCC3 in susceptibility to BC and their correlation with risk factors and prognostic markers.

Subjects

One hundred (BC) patients were consecutively enrolled from 2010 to 2013 from the Medical Research Institute Teaching Hospital, Alexandria University, Egypt. All patients were newly diagnosed, histopathologically confirmed, and untreated.

The control group, frequency matched to cases by age interval, was receiving routine mammography at the breast diagnostic center. Exclusion criteria for controls included abnormal mammography or prior personal history of any cancer. All subjects provided informed consent approved by the local ethics committee. Demographic data were obtained through interviews and standardized questionnaires. Family history of cancer was defined as self-reported BC in first-degree relatives. Physical activity was classified as positive if exercise was performed more than once per month regardless of exercise time. Current smokers were those smoking at least one cigarette/day for >1 year, while former smokers are those who had abstained from smoking for >1 year. Women were considered postmenopausal if they had no menses for at least 12 months due to natural, chemical, or surgical causes. There were no reports of alcohol consumption, genotoxic medications, or exposure to radiation for at least 1 month previously.

Methods

Genomic DNA was extracted using a commercially available kit (Qiagen) from blood samples, which had been collected in ethylenediaminetetracetic acid tubes, and then stored at −20°C till use. DNA was quantitated by NanoDrop 8000 to determine concentration and purity. Finally, the polymorphisms were detected using the polymerase chain reaction-restriction enzyme polymorphism (PCR-RFLP) technique.

Arg194Trp and Arg399Gln polymorphisms

PCR amplification was performed in a Veriti thermal cycler (Applied Biosystems) (Ruth, 1999). PCR conditions for both polymorphisms consisted of 50 ng of genomic DNA, 3 mM MgCl₂, 200 mM each dNTPS, 1 U Taq (Fermentas), specific primers 30 pg (Table 1). The PCR program was 94°C for 4 min followed by 30 cycles of 30 s at 94°C, 45 s at 62°C, and 72°C for 1 min, with a final extension step of 7 min at 72°C. The PCR products were digested with Msp1 fast digest restriction enzyme (Thermoscientific) and incubated in 37°C (Fig. 1).

FIG. 1.

Genotyping of XRCC1 (A399G), lane 1, 50 bp DNA ladder; lane 2, XRCC1 399(G/G); lane 3, XRCC1 399(A/G).

Table 1.

Single-Nucleotide Polymorphism Characteristics and Genotypic Frequencies

			(ob/exp)		HWE
SNP (rs no.)	Primer sequence	Genotype (bp)	Cases	Controls	Cases	Controls
XRCC1 Arg399Gln (rs25487)	F: 5′-TTG TGC TTT CTC CCC GTC CA-3′	AA (374+221)	26/30.8	37/37.5	0.052	0.801
	R:5′-TCC TCC AGC CTT CAG TGA TA-3′	AG (615+374+221)	59/49.4	32/31.1
		GG (615)	15/19.8	6/6.5
XRCC1 Arg194Trp (rs1799782)	F:5′-ATG CCG TCC CAG GTA AGC-3′	AA (292)	31/35.4	50/48	0.068	0.149
	R:5′-AGC CCC AAG ACC CGG TCA CT-3′	TA (313+292)	57/48.2	20/24
		TT (313)	12/16.4	5/3
XRCC3 Thr241Met (rs861539)	F:5′-GCT CGC CTG GTG GTC ATC CAC TCG-3′	CC (335)	28/31.9	30/31.4	0.110	0.491
		CT (335+233)	57/49.2	37/34.3
	R:5′-AAG AGC ACA GTC CAG CAC TGC TG-3′	TT (233)	15/18.9	8/9.4

SNP, single-nucleotide polymorphism; bp, base pair; ob/exp, observed/expected; HWE, Hardy-Weinberg equilibrium; XRCC, X-ray repair cross-complementing protein; F, forward primer; R, reverse primer.

Thr241Met polymorphism

The PCR conditions were as above, but the PCR program was 94°C for 4 min followed by 30 cycles of 30 s at 94°C, 45 s at 66°C, and 72°C for 1 min, with a final extension step of 7 min at 72°C (Tumalia and Norrpa, 2002). The PCR products were digested with the NlIII fast digest restriction enzyme (Thermoscientific) and incubated in 37°C.

The resultant PCR products were resolved by electrophoresis on 3% agarose gel and stained with ethidium bromide for visualization under UV light.

Statistical methods

Statistical analyses were analyzed by SPSS.18. Descriptive measures were done for all variables and a p-value less than 0.05 was considered statistically significant. The Student's t-test, chi-squared (χ²) test, and Fisher exact test were used to assess the general characteristics between groups.

Agreement with the Hardy-Weinberg equilibrium (HWE) was assessed by comparing expected to observed genotype frequencies. The odds ratios (ORs) and 95% confidence intervals (95% CIs) from unconditional logistic regression were measured. The conditional logistic regression model was used to estimate adjusted ORs according to potential confounders selected a priori. Population-attributable risk was calculated using the following formula: P_Ho(OR_Ho−1)+P_He(OR_He−1)/(1+P_Ho(OR_Ho−1)+P_He(OR_He−1), where P_Ho and P_He are the proportions of homozygotes and heterozygotes of the risk allele, respectively, while OR_Ho and OR_He are the estimated ORs for homozygotes and heterozygotes of the risk allele, respectively (Kawase et al., 2009).

The multiplicative model was used to study the interaction between the studied genotypes and some factors, including body-mass index (BMI) (0, >25; 1, ≥25), menopausal status (0, premenopausal; 1, postmenopausal), age at menarche (0, ≤11; 1, 12-13; 2, ≥14 years), smoking habit (0, never; 1, current; 2, former), physical activity (0, yes; 1, no), family history of BC (0, yes; 1, no), and parity (0, nulliparous; 1, 1-2; 2, ≤3). Cross products of scores for genotype (0, homozygous genotype for reference allele; 1, heterozygote genotype or homozygous genotype for nonreference allele) and scores for each factor were included in the model as interaction terms.

Results

We included a total of 175 subjects from the Alexandria population in this case-control study; 100 BC cases and 75 apparently healthy females. Cases had a significantly higher BMI and an increased family history of cancer (Table 2). Tumor characteristics were retrieved from the pathology reports (Table 3).

Table 2.

Demographic Criteria of the Studied Participants

Variable	Cases (n=100)	Control (n=75)	p-Value
Age (years)
Mean±SD	41.9±8.3	42.1±9.8	t=0.73
Median (min-max)	40 (26-60)	43 (25-60)	p=0.94
BMI (kg/m²)
Mean±SD	25.7±1.8	23.9±2.5	t =−5.14
Median (min-max)	25.9 (19.8-29.1)	23.8 (18.7-29.4)	p<0.001^a
Menopausal state, n (%)
Premenopausal	75 (75)	51 (68)	χ²=1.042
Postmenopausal	25 (25)	24 (32)	p=0.31
Age of menarche (years)
Mean±SD	12.4±1.6	12.6±1.8	t=0.73
Median (min-max)	12 (9-17)	12 (10-16)	p=0.47
Parity, n (%)
Nulliparous	12 (12)	9 (12)	χ²=0.049
1-2	41 (41)	29 (38.7)	p=0.824
≥3	47 (47)	37 (49.3)
Physical activity, n (%)
Yes	74 (74)	51 (68)	χ²=0.75
No	26 (26)	24 (32)	p=0.39
Smoking, n (%)
Never	77 (77)	59 (78.7)	χ²=1.077
Current	19 (19)	11 (14.7)	p=0.58
Former	4 (4)	5 (6.7)
Family history of cancer, n (%)
Yes	30 (30)	12 (16)	χ²=4.61
No	70 (70)	63 (84)	p=0.03^a

Statistically significant at p≤0.005.

BMI, body-mass index; t, t-test; χ², chi-square test.

Table 3.

Pathological Features of Breast Cancer Patients

Variable	n
Histopathological type
Ductal	78
Lobular	16
Others	6
Tumor stage
I	0
II	50
III	41
IV	9
Tumor size
≤2 cm	7
>2 cm	93
Axillary lymph node involvement
Yes	90
No	10
Metastasis
Yes	4
No	96
ER status
Positive	87
Negative	13
PR status
Positive	87
Negative	13
HER2 expression status
Overexpression	26
Non-overexpression	74
CA15-3 (U/mL)
Mean±SD	33.97±23.99
Median (min-max)	33 (5.9-190)

ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2.

Genotype distributions at each studied locus were consistent with HWE in cases and controls (p>0.05, Table 1). The variant allele frequencies in controls were 29.3% for Arg399Gln, 20% for Arg194Trp, and 35.3% for Thr241Met (Table 4). Similar variant allele frequencies were reported (Butkiewicz et al., 2001; Shu et al., 2003). However, still higher (Figueiredo et al., 2004) as well as lower frequencies (Santos et al., 2010) were found by others.

Table 4.

Distribution of Genotypes and Odds Ratios in the Studied Participants

Genotypes/alleles	Cases n (%)	Controls n (%)	χ²	p-Value	Crude OR (95% CI)	Adjusted OR (95% CI)
Arg399Gln
A/A®	26	37
A/G	59	32	8.36^a	0.004^a	2.62^a (1.35-5.08)	2.64^a (1.20-5.08)
G/G	15	6	5.73^a	0.017^a	3.56^a (1.22-10.39)	4.42^a (1.28-15.31)
A/A vs. A/G -G/G	74	38	10.14^a	0.001^a	2.77^a (1.47-5.24)	2.89^a (1.35-6.21)
A allele®	111 (55.5)	106 (70.7)	8.37^a	0.004^a	1.93^a (1.23-3.03)	1.98^a (1.55-3.24)
G allele	89 (44.5)	44 (29.3)
Arg194Trp
A/A®	31	50
A/T	57	20	20.45^a	<0.001^a	4.59^a (2.33-9.06)	4.42^a (2.08-9.41)
T/T	12	5	5.96	0.015^a	3.87^a (1.24-12.05)	3.76^a (1.07-13.17)
A/A® vs. A/T-T/T	69	25	21.93	<0.001^a	4.45^a (2.35-8.45)	4.283^a (2.11-8.70)
A allele®	119 (59.5)	120 (80)			2.72^a (1.67-4.44)	2.45 (1.39-4.27)
T allele	81 (40.5)	30 (20)	16.63	<0.001^a
Thr241Met
C/C®	28	30
C/T	57	37	2.22	0.136	1.65 (0.85-3.19)	1.94 (0.82-3.05)
T/T	15	8	1.89	0.168	2.01 (0.74-5.47)	1.89 (0.64-5.27)
C/C® vs. C/T-T/T	72	45	2.79	0.095	1.71 (0.91-3.24)	1.64 (0.83-3.01)
C allele®	113 (56.5)	97 (64.7)	2.72	0.099	1.41 (0.91-2.18)	1.28 (0.75-2.03)
T allele	87 (43.5)	53 (35.3)

Statistically significant at p≤0.05.

®, reference; OR, odds ratio; CI, confidence interval.

There was a significant association between BC risk and both Arg399Gln and Arg194Trp with a population-attributable risk of 53.5% and 65.1%, respectively, but no significant association was observed with Thr241Met. The genotype and allele distribution of Arg399Gln and Arg194Trp revealed significant differences between cases and controls. There was a significant reduction of the A/A genotype frequency and elevation of the G/G and T/T genotype frequency in patients as compared to controls (Table 4). The allele frequency also showed a similar trend indicating that the G and T alleles might confer risk to BC and that the A allele offers protection against the disease.

To elucidate the relationship between studied SNPs and BC susceptibility, we conducted further statistical analyses. First, the crude OR was adjusted for age, BMI, parity, menopausal status, age at menarche, family history of BC, smoking, or physical activity, resulting in multivariate adjusted ORs, which were not altered significantly from the crude ones (Table 4). Second, when subjects were stratified according to menopausal status, similar statistical results were obtained (data not shown). Third, we analyzed the interactions between the studied genotypes and known environmental risk factors, but none showed any significant interaction (Table 5). Finally, the genotype frequency of the SNPs was assessed in relation to tumor criteria, but no significant association was denoted (Table 6).

Table 5.

Interaction Between XRCC Polymorphisms and Environmental Factors

	Arg399Trp			Arg164Trp
	No. of cases/controls			No. of cases/controls
Variable	AA	AG,GG	p_int	AA	AT,TT	p_int
Age at menarche (years)
≤11	5/4	5/6	0.175	1/6	9/4	0.403
			0.051			0.329
11-13	15/19	47/23		19/28	43/14
≥14	6/14	22/9		11/16	17/7
BMI (kg/m²)
<25	8/25	24/24	0.694	9/35	23/14	0.244
≥25	18/12	50/14		22/15	46/11
Parity
Nulliparous	2/4	10/5	0.967	2/6	10/3	0.597
			0.538			0.327
1-2	10/16	31/13		12/20	29/9
≥3	14/17	33/20		17/24	30/13
Physical activity
Yes	8/9	20/13	0.354	9/15	19/7	0.974
No	18/28	54/25		22/35	50/18
Smoking
Never	15/27	63/31	0.216	23/37	55/21	0.712
Current	9/7	9/5		5/9	13/3
Former	2/3	2/2		3/4	1/1
Family history of cancer
Yes	10/7	18/7	0.409	8/9	20/5	0.970
No	16/30	56/31		23/41	49/20

p_int, p interaction.

Table 6.

Effect of XRCC Polymorphisms on Tumor Criteria

	Arg399Trp				Arg164Trp
	n (%)				n (%)
Variable	AA	AG,GG	OR (95% CI)	p_trend	AA	AT,TT	OR (95% CI)	p_trend
ER
+	23 (26.4)	64 (73.6)	1.19 (0.30-4.74)	1	27 (31)	60 (69)	1.5 (3.82-5.89)	0.749
−	3 (23.1)	10 (76.9)			3 (23.1)	10 (76.9)
PR
+	23 (26.4)	64 (73.6)	1.19 (0.30-4.74)	1	26 (29.9)	61 (70.1)	0.96 (0.27-3.39)	1
−	3 (23.1)	10 (76.9)			4 (30.8)	9 (69.2)
HER2
+	6 (23.1)	20 (76.9)	0.81 (0.28-2.31)	0.693	9 (34.6)	17 (65.4)	1.34 (0.52-3.47)	0.551
−	20 (27)	54 (73)			21 (28.4)	53 (71.6)
Lymph node metastasis
No	1 (10)	9 (90)	0.29 (0.04-2.39)	0.447	1 (10)	9 (90)	0.23 (0.03-1.93)	0.274
Yes	25 (27.8)	65 (72.2)			29 (32.2)	61 (67.8)
Distant metastasis
No	24 (25)	72 (75)	0.33 (0.04-2.49)	0.277	29 (30.2)	67 (69.8)	1.29 (0.13-13.01)	1
Yes	2 (50)	2 (50)			1 (25)	3 (75)
Tumor size
<2 cm	2 (28.6)	5 (71.4)	1.15 (0.21-6.32)	1	2 (28.6)	5 (71.4)	0.93 (0.17-5.08)	1
>2 cm	24 (25.8)	69 (74.2)			28 (30.1)	65 (69.9)

Discussion

We found a significant association between BC risk and both XRCC1 SNPs Arg399Gln and Arg194Trp. Several studies defined this association with a trend of increased BC risk when using both dominant and recessive models (Duell et al., 2001; Kim et al., 2002; Smith et al., 2003; Saadat et al., 2008; Al Mutairi et al., 2013). On the other hand, some authors could not ascertain such association (Costa et al., 2007; Santos et al., 2010). Additionally, one study (Jorgensen et al., 2009) reported a significant association between the Arg194Trp variant and benign breast disease, which is an important risk factor for BC with a heritable component. It is therefore obvious that the polymorphism of XRCC1 at codons 399 and 194 may be associated with functional changes of essential DNA repair proteins, which result in nonsynonymous amino acid substitutions that are highly conserved, hence constitute potential BC risk.

In the current study, Thr241Met polymorphism did not show any significant association between BC cases when compared to controls. This is supported by the fact that XRCC3 Thr241Met polymorphism does not reside in known XRCC3 functional domains (Romanowicz-Makowska et al., 2011) and further defined in a study by Jacobsen et al. (2003). However, a positive association for XRCC3-241 M/M compared with T/T genotype was reported (Figueiredo et al., 2004; Costa et al., 2007).

In summary, results are inconsistent and studies vary considerably in design, methodology, and analyses. Besides, the tissue-specific balance between the outcome of repair pathways of XRCC and apoptotic signals in different tissues should be considered. Less efficient repair variants can cause a protective signal (accumulation of damage, cell cycle block, and apoptosis) in some tissues, whereas in others, they could be risk factors (unrepaired or abortive attempt to repair damage and consequent mutation). Moreover, the presence of multiple interrelating repair pathways can compensate for each other.

Although many genetic susceptibility loci have been identified for BC, it is still unclear how they interact with the established reproductive and lifestyle risk factors (referred to as environmental risk factors). Therefore, it was imperative to analyze the effect of these nongenetic factors on the observed genetic association with BC. Similar to other work (Shu et al., 2003), we observed no modifying effect in the adjusted ORs and also no significant interactions were found. Indeed, the menopausal status is a cornerstone variable in relation to BC; in our study, we stratified the studied population according to their menopausal status, but there were no noticeably significant findings. This was supported by large-scale evidence meta-analysis for Arg399Gln polymorphism (Huang et al., 2009).

Although cases in our study had increased family history of BC and higher BMI than controls, this was not reflected on a significant interaction with the studied SNPs and contradictory findings were reported in this issue (Figueiredo et al., 2004; Costa et al., 2007).

We did not find any significant difference in the studied SNPs of XRCC1 in relation to tumor criteria. To the best of our knowledge, XRCC3 and not XRCC1 was similarly assessed in previous studies and the same null effect was observed (Krupa et al., 2009; Romanowicz-Makowska et al., 2011). Thus, we can suggest that these potential cancer susceptibility genes are related to BC occurrence and not progression, which is expected through their role in the DNA repair pathway. However, results should be interpreted cautiously because the low study power cannot demonstrate small effects and few cases to investigate disease heterogeneity by different environmental and pathological variables. Another limitation of our small sample size was the inability to assess SNP-SNP interactions or linkage disequilibrium between polymorphisms within the same pathway and different pathways, which we recommend in future studies.

Nevertheless, our findings could provide a starting point for further analysis of the role of XRCC gene polymorphisms on the risk of BC in the Egyptian population to explain the molecular pathways through in vitro and in vivo future studies for the remaining genes within the BER pathway.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

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