XPG gene contributes to DNA repair defects and genomic instability, which may lead to the initiation of uterine leiomyoma. We hypothesized that genetic variants of XPG gene may alter the carriers’ susceptibility to leiomyoma. The association between five potential functional single nucleotide polymorphisms (SNPs), i.e. rs2094258 C>T, rs751402 C>T, rs2296147 T>C, rs1047768 T>C, rs873601 G>A, and uterine leiomyoma risk in Chinese, was investigated in this case–control study, which included 398 incident leiomyoma cases and 733 controls. We found that rs873601 was significantly associated with tumor risk in a recessive genetic model after being adjusting for age and menopause. When compared with rs873601 GG/GA genotypes, the AA genotype had an increased leiomyoma risk (adjusted OR = 1.59, 95% CI = 1.16–2.18, P=0.004; Bonferroni adjusted P=0.040). Furthermore, stratified analysis revealed that the association between the rs873601 AA genotype and leiomyoma risk was more evident among subjects younger than 40 years old (adjusted OR = 1.58, 95% CI = 1.06–2.35, P=0.023) and patients who had more than three myomas (adjusted OR = 2.05, 95% CI = 1.24–3.41, P=0.006). Yet, no significant association between the other four polymorphisms and leiomyoma risk was observed. To sum up, the present study reported on the association between XPG gene polymorphisms and myoma risk. The observed data indicated that SNP rs873601 G>A contributes to uterine leiomyoma susceptibility in a Southern Chinese population.

Introduction

Uterine leiomyoma, also known as myomata or fibroids, is the most common pelvic tumor in women [1]. Increased serum oxidative stress, which induces DNA lesions, has been associated with this type of benign tumor [2]. Likewise, environmental tumorigenic agents can also damage DNA, while different DNA repair mechanisms have been reported to alleviate such DNA damages [3]. Therefore, the polymorphisms of some DNA repair genes have been reported associated with leiomyoma risk [4–6].

Xeroderma pigmentosum group G, also known as XPG, RAD2 or ERCC5, is a 1,186-amino acid structure-specific endonucleases, which belongs to the nucleotide excision repair (NER) pathway, one of five known major DNA repair mechanisms [7]. The endonucleases XPG is important in maintaining genomic stability. XPG is a DNA damage recognition protein that binds and cleaves damaged DNA, which is followed by the excision of a 24- to 32-bp segment containing the bulky adduct at the 3’ and 5’ ends of the damaged site; finally, the resultant gap is filled by DNA synthesis and ligation [8]. In addition, XPG is involved in the RNA transcription through interaction with other transcription activator complexes, such as TFIIH [9], RNA polymerase II [10] and Gadd45a [11], which eventually influences mutagenesis and cell death. This protein is encoded by XPG gene, which is located on human chromosome 13q22-q33, spans 69kb length, contains 15 exons, and is highly polymorphic [12]. A serious of reports have revealed the association between the XPG gene polymorphisms and tumor risk, including colorectal cancer [13], gastric cancer [14–16], lung cancer [17], head and neck cancer [18], and neuroblastoma [19]. Nevertheless, no associations between XPG gene and leiomyoma risk have been reported so far. We hypothesized that genetic variants of XPC gene may modulate the carriers’ susceptibility to uterine leiomyoma.

Therefore, we conducted the current case–control study in a Southern Chinese population to understand the associations between the potential functional polymorphisms of XPG gene and the risk of uterine leiomyoma.

Materials and methods

Study population

Three hundred and ninety-eight patients with incidentally histologically confirmed leiomyoma and 733 healthy controls without uterine tumor (or other diseases), verified by ultrasonic examination, were enrolled at Bao’an Maternal and Child Health Hospital, Jinan University between January 2015 and February 2018. The respond rate of patiens and controls were 98.8% and 85.9%, respectively. All the research subjects were unrelated ethnic Han Chinese population from Southern China.

First, demographic characteristics (age and menopause), and tumor characteristics, including, numbers, sites, and diameters were obtained from all patients. Next, 2 ml of venous blood sample was collected from each subject after interview and signing the consent form.

The present study was approved by the Ethics Committee of the Bao’an Maternal and Child Health Hospital, Jinan University (IRB No: LLSC2018-02-01).

SNPs selection and genotyping

The potentially functional single nucleotide polymorphisms (SNPs) were selected by using the NCBI dbSNP database and SNPinfo (http://snpinfo.niehs.nih.gov/snpinfo/snpfunc.htm). The applied criteria were described earlier [13,15], briefly as following: (1) the minor allele frequency reported in HapMap was more than 5% for Chinese Han subjects; (2) SNPs were located in the 5’-flanking region, exon, 5’-untranslated region (5’-UTR) and 3’-UTR, which might affect transcription activity and the microRNA-binding site activity and (3) SNPs were in low linkage disequilibrium with each other (R2 < 0.8). The widely reported SNP rs17655 G>C was excluded because of its linkage disequilibrium (LD) with rs873601 G>A (R2 = 0.91). As a result, five potential functional SNPs (rs2094258 C>T, rs751402 C>T, rs2296147 T>C, rs1047768 T>C, and rs873601 G>A) were included in the present study.

Genomic DNA was extracted from blood samples using the Qiagen Blood DNA Mini Kit (Qiagen Inc., Valencia, CA, U.S.A.) according to the manufacturer’s instructions of the manufacturer. As described previously [20], we performed genotyping of above SNPs was performed by the Taqman real-time polymerase chain reaction method using a 7900 Sequence Detection System (Thermo Fisher Scientific, Waltham, MA, U.S.A.). To achieve more reliable genotyping results, four duplicated positive controls and four negative controls without DNA template were loaded in each of 384-well plates. Genotyping was repeated on 10% of the samples randomly selected from the subjects, and the results were 100% concordant.

Statistical analysis

Statistical analyses were performed as described earlier [21]. Briefly, we compared the differences between cases and controls regarding demographic characteristics, such as age and menopause, by using Chi-square test and Student’s t test; then we tested whether the genotype frequency distribution of each polymorphism in controls was in Hardy–Weinberg equilibrium through Goodness-of-fit χ2 test. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the associations between each SNP and gastric cancer risk, using univariate and multivariate logistic regression models. Bonferroni correction was used to correct for multiple comparisons of SNPs, that is, the Bonferroni adjusted P value = (P value of tested SNP) × k!/(2!(k − 2)!), where k was the number of total SNPs. Further stratification analysis by age, menopause, and tumor characteristics (numbers, sites, and diameters) was also performed. All statistical analysis was performed using SPSS software (version 18.0; SAS Institute Inc., Chicago, IL, U.S.A.). A two-sided statistical significance level of 0.05 was chosen.

Results

Subject’s characteristics

The clinical and demographic characteristics of the study population, including 398 leiomyoma cases and 733 healthy controls, was described as Supplementary Table S1. Compared with controls, the cases were more likely to be younger (for subjects <40 years, 68.8% vs. 39.4%, P<0.001) and reproductive females (98.2% vs. 67.3%, P<0.001). Among the leiomyoma cases, nearly 40% (156 cases) had more than two myomas, and they were more commonly located in intramural (66.8%, 266 cases) and subserous (20.9%, 83 cases) region.

Table 1
Association between XPG gene polymorphisms and uterine fibroid risk
Genotypes Cases, n (%) Controls, n (%) HWE P* OR (95% CI) P AOR (95% CI) P 
rs2094258 C>T        
CC 167 (42.0) 330 (45.0) 0.813 1.00  1.00  
CT 178 (44.7) 328 (44.7)  1.07 (0.83–1.39) 0.599 1.09 (0.82–1.43) 0.562 
TT 53 (13.3) 75 (10.3)  1.40 (0.94–2.08) 0.100 1.48 (0.95–2.29) 0.081 
Dominant 231 (58.0) 403 (55.0)  1.13 (0.89–1.45) 0.322 1.16 (0.89–1.51) 0.285 
Recessive 345 (86.7) 658 (89.8)  1.35 (0.93–1.96) 0.119 1.42 (0.94–2.14) 0.100 
rs751402 C>T        
CC 150 (37.6) 271 (37.0) 0.553 1.00  1.00  
CT 194 (48.4) 358 (48.8)  0.98 (0.75–1.28) 0.876 0.95 (0.71–1.26) 0.718 
TT 54 (13.6) 104 (14.2)  0.94 (0.64–1.38) 0.745 0.89 (0.59–1.34) 0.573 
Dominant 248 (62.3) 462 (63.0)  0.97 (0.75–1.25) 0.812 0.94 (0.71–1.23) 0.628 
Recessive 344 (86.4) 629 (85.8)  0.95 (0.67–1.35) 0.774 0.92 (0.63–1.34) 0.648 
rs2296147 T>C        
TT 257 (64.6) 443 (60.4) 0.171 1.00  1.00  
CT 121 (30.4) 260 (35.5)  0.80 (0.62–1.03) 0.089 0.80 (0.60–1.07) 0.128 
CC 20 (5.0) 30 (4.1)  1.15 (0.48–2.74) 0.754 1.20 (0.81–2.97) 0.679 
Dominant 141 (35.4) 290 (39.6)  0.84 (0.66–1.07) 0.152 0.86 (0.66–1.14) 0.294 
Recessive 378 (95.0) 703 (95.9)  1.24 (0.60–-2.57) 0.564 1.32 (0.78–3.19) 0.579 
rs1047768 T>C        
TT 209 (52.5) 367 (50.0) 0.338 1.00  1.00  
CT 154 (38.7) 311 (42.4)  0.87 (0.67–1.13) 0.287 0.86 (0.65–1.13) 0.282 
CC 35 (8.8) 55 (7.5)  1.12 (0.71–1.76) 0.634 1.10 (0.67–1.81) 0.703 
Dominant 189 (47.5) 366 (49.9)  0.91 (0.71–1.16) 0.432 0.90 (0.69–1.17) 0.410 
Recessive 363 (91.2) 678 (92.5)  1.19 (0.77–1.85) 0.444 1.18 (0.73–1.91) 0.505 
rs873601 G>A        
GG 108 (27.1) 201 (27.4) 0.305 1.00  1.00  
GA 183 (46.0) 381 (52.0)  0.89 (0.67–1.20) 0.453 0.83 (0.61–1.14) 0.251 
AA 107 (26.9) 151 (20.6)  1.32 (0.94–1.86) 0.111 1.41 (0.97–2.06) 0.071 
Dominant 290 (72.9) 532 (72.6)  1.02 (0.77–1.33) 0.918 0.98 (0.73–1.32) 0.900 
Recessive 291 (73.1) 582 (79.4)  1.42 (1.07–1.89) 0.016 1.59 (1.16–2.18) 0.004 
Genotypes Cases, n (%) Controls, n (%) HWE P* OR (95% CI) P AOR (95% CI) P 
rs2094258 C>T        
CC 167 (42.0) 330 (45.0) 0.813 1.00  1.00  
CT 178 (44.7) 328 (44.7)  1.07 (0.83–1.39) 0.599 1.09 (0.82–1.43) 0.562 
TT 53 (13.3) 75 (10.3)  1.40 (0.94–2.08) 0.100 1.48 (0.95–2.29) 0.081 
Dominant 231 (58.0) 403 (55.0)  1.13 (0.89–1.45) 0.322 1.16 (0.89–1.51) 0.285 
Recessive 345 (86.7) 658 (89.8)  1.35 (0.93–1.96) 0.119 1.42 (0.94–2.14) 0.100 
rs751402 C>T        
CC 150 (37.6) 271 (37.0) 0.553 1.00  1.00  
CT 194 (48.4) 358 (48.8)  0.98 (0.75–1.28) 0.876 0.95 (0.71–1.26) 0.718 
TT 54 (13.6) 104 (14.2)  0.94 (0.64–1.38) 0.745 0.89 (0.59–1.34) 0.573 
Dominant 248 (62.3) 462 (63.0)  0.97 (0.75–1.25) 0.812 0.94 (0.71–1.23) 0.628 
Recessive 344 (86.4) 629 (85.8)  0.95 (0.67–1.35) 0.774 0.92 (0.63–1.34) 0.648 
rs2296147 T>C        
TT 257 (64.6) 443 (60.4) 0.171 1.00  1.00  
CT 121 (30.4) 260 (35.5)  0.80 (0.62–1.03) 0.089 0.80 (0.60–1.07) 0.128 
CC 20 (5.0) 30 (4.1)  1.15 (0.48–2.74) 0.754 1.20 (0.81–2.97) 0.679 
Dominant 141 (35.4) 290 (39.6)  0.84 (0.66–1.07) 0.152 0.86 (0.66–1.14) 0.294 
Recessive 378 (95.0) 703 (95.9)  1.24 (0.60–-2.57) 0.564 1.32 (0.78–3.19) 0.579 
rs1047768 T>C        
TT 209 (52.5) 367 (50.0) 0.338 1.00  1.00  
CT 154 (38.7) 311 (42.4)  0.87 (0.67–1.13) 0.287 0.86 (0.65–1.13) 0.282 
CC 35 (8.8) 55 (7.5)  1.12 (0.71–1.76) 0.634 1.10 (0.67–1.81) 0.703 
Dominant 189 (47.5) 366 (49.9)  0.91 (0.71–1.16) 0.432 0.90 (0.69–1.17) 0.410 
Recessive 363 (91.2) 678 (92.5)  1.19 (0.77–1.85) 0.444 1.18 (0.73–1.91) 0.505 
rs873601 G>A        
GG 108 (27.1) 201 (27.4) 0.305 1.00  1.00  
GA 183 (46.0) 381 (52.0)  0.89 (0.67–1.20) 0.453 0.83 (0.61–1.14) 0.251 
AA 107 (26.9) 151 (20.6)  1.32 (0.94–1.86) 0.111 1.41 (0.97–2.06) 0.071 
Dominant 290 (72.9) 532 (72.6)  1.02 (0.77–1.33) 0.918 0.98 (0.73–1.32) 0.900 
Recessive 291 (73.1) 582 (79.4)  1.42 (1.07–1.89) 0.016 1.59 (1.16–2.18) 0.004 

Notes: *Goodness-of-fit χ2 test; adjusted for age, and menopause

Abbreviations: AOR, adjusted OR; CI, confidence interval; HWE, Hardy–Weinberg equilibrium; OR, odds ratio.

Statistically significant associations are indicated by bold text.

Associations between XPG gene polymorphisms and leiomyoma risk

Table 1 summarized the genotype distributions of the selected XPG gene polymorphisms in all subjects. The genotype frequency distributions of all SNPs in the control subjects were in agreement with Hardy–Weinberg equilibrium (all P>0.05, Table 1).

Next, we examined the association between the above morphisms and myoma risk. Variables including age and menopause were adjusted for in the subsequent multivariate logistic regression analyses (Table 1). The logistic regression analysis showed that polymorphism rs873601 G>A was significant associated with tumor risk in a recessive genetic model after adjusting for age and menopause. When compared with rs873601 GG+GA genotypes, the rs873601 AA variant genotype had an increased leiomyoma risk (adjusted OR = 1.59, 95% CI = 1.16–2.18, P=0.004; Bonferroni adjusted P=0.040). While no associations between other four polymorphisms (rs2094258 C>T, rs751402 C>T, rs2296147 T>C, and rs1047768 T>C) and tumor risk were observed in either of the three genetic models.

Stratification analysis

We further investigated the potential association between the most important polymorphism rs873601 G>A of XPG gene and the leiomyoma risk in the stratified study by age, menopause, and tumor characteristics (numbers, sites, and diameters) (Table 2). The rs873601 AA variant genotype was found to be associated with a significantly increased risk of uterine leiomyoma among individuals younger than 40 (adjusted OR = 1.58, 95% CI = 1.06–2.35, P=0.023), when GG+GA genotypes served as the reference. Similarly, when compared with the reference genotypes, carriers of rs873601AA genotype had a significantly increased risk of leiomyoma among reproductive females (adjusted OR = 1.65, 95% CI = 1.20–2.28, P=0.002), cases with one myoma (adjusted OR = 1.55, 95% CI = 1.08–2.24, P=0.019) or more than three myomas (adjusted OR = 2.05, 95% CI = 1.24–3.41, P=0.006), subjects with myomas located in subserous (adjusted OR = 2.60, 95% CI = 1.56–4.32, P<0.001), and myomas’ diameter less than 5 mm (adjusted OR = 1.96, 95% CI = 1.31–2.94, P=0.001).

Table 2
Stratification analysis for association between XPG rs873601 G>A genotypes and uterine fibroid risk
Genotypes rs873601 G>A (cases/controls) OR (95% CI) P AOR (95% CI) P 
 GG+GA AA     
Age, years       
  <40 200/234 74/55 1.58 (1.06–2.34) 0.025 1.58 (1.06–2.35) 0.023 
  ≥40 91/348 33/96 1.32 (0.832.08) 0.242 1.65 (0.982.77) 0.066 
Menopause       
  No 285/403 106/90 1.67 (1.21–2.29) 0.002 1.65 (1.20–2.28) 0.002 
  Yes 6/179 1/61 0.49 (0.064.14) 0.512 0.59 (0.075.12) 0.630 
No. of myoma       
  1 178/582 64/151 1.39 (0.991.94) 0.058 1.55 (1.08–2.24) 0.019 
  2 54/582 16/151 1.14 (0.642.05) 0.657 1.31 (0.722.39) 0.380 
  ≥3 59/582 27/151 1.76 (1.08–2.88) 0.023 2.05 (1.24–3.41) 0.006 
Site of myoma*       
  Intramural 204/582 62/151 1.17 (0.841.64) 0.356 1.32 (0.921.90) 0.128 
  Subserous 52/582 31/151 2.30 (1.42–3.71) 0.001 2.60 (1.56–4.32) <0.001 
  Other types 35/582 14/151 1.54 (0.812.94) 0.188 1.80 (0.933.49) 0.081 
Diameter, mm*       
  ≤5.0 110/582 50/151 1.74 (1.19–2.54) 0.004 1.96 (1.31–2.94) 0.001 
  >5.0 180/582 57/151 1.22 (0.861.73) 0.261 1.39 (0.952.02) 0.086 
Genotypes rs873601 G>A (cases/controls) OR (95% CI) P AOR (95% CI) P 
 GG+GA AA     
Age, years       
  <40 200/234 74/55 1.58 (1.06–2.34) 0.025 1.58 (1.06–2.35) 0.023 
  ≥40 91/348 33/96 1.32 (0.832.08) 0.242 1.65 (0.982.77) 0.066 
Menopause       
  No 285/403 106/90 1.67 (1.21–2.29) 0.002 1.65 (1.20–2.28) 0.002 
  Yes 6/179 1/61 0.49 (0.064.14) 0.512 0.59 (0.075.12) 0.630 
No. of myoma       
  1 178/582 64/151 1.39 (0.991.94) 0.058 1.55 (1.08–2.24) 0.019 
  2 54/582 16/151 1.14 (0.642.05) 0.657 1.31 (0.722.39) 0.380 
  ≥3 59/582 27/151 1.76 (1.08–2.88) 0.023 2.05 (1.24–3.41) 0.006 
Site of myoma*       
  Intramural 204/582 62/151 1.17 (0.841.64) 0.356 1.32 (0.921.90) 0.128 
  Subserous 52/582 31/151 2.30 (1.42–3.71) 0.001 2.60 (1.56–4.32) <0.001 
  Other types 35/582 14/151 1.54 (0.812.94) 0.188 1.80 (0.933.49) 0.081 
Diameter, mm*       
  ≤5.0 110/582 50/151 1.74 (1.19–2.54) 0.004 1.96 (1.31–2.94) 0.001 
  >5.0 180/582 57/151 1.22 (0.861.73) 0.261 1.39 (0.952.02) 0.086 

Notes: *in the biggest myoma; adjusted for age, and menopause.

Abbreviations: AOR, adjusted OR; CI, confidence interval; OR, odds ratio.

Statistically significant associations are indicated by bold text.

Because of very few subjects in the subgroups, such as menopause females, some subgroups were not significantly associated with the risk of leiomyoma risk.

Discussion

In the present study, we found that XPG polymorphism rs873601 G>A was associated with an increased leiomyoma risk. In addition, this association was more evident among younger subjects and those with multiple myomas. To the best of our knowledge, this is the first study that reported on the association of XPG polymorphisms with uterine leiomyoma.

Some studies have investigated the role of XPG polymorphisms in different other tumors. In an Eastern Chinese population, rs873601A variant genotypes (GA+AA) was associated with a significantly elevated risk of gastric cancer [15]. However, the association between this SNP and gastric cancer has not been validated in a Southern Chinese population in another study [22]. Moreover, Wang et al. [23] reported that this SNP was associated with hepatocellular cancer risk by single-locus analysis only in screening stage. Besides, Hua et al. [24] reported that rs873601 A allele can also contribute to the susceptibility of colorectal cancer in a Southern Chinese population with a total of 1,901 cases and 1,976 controls. Two studies have performed comprehensive meta-analyses to evaluate the association of XPG polymorphism rs873601 with cancer risk: Han et al. [25] found that polymorphism rs873601 was significantly associated with overall cancer risk, using data from 12 studies, including 9,158 cases and 10,073 controls focus on rs873601; while another meta-analysis study that included data from 23 reports found that this polymorphism was related to the cancer susceptibility only in Asians [26]. The ethnic and demographic differences among studies might be partly due to the enormously different frequencies of the rs873601 A allele in different groups (0.48 in Chinese, CHB; 0.53 in Caucasian, CEU; 0.30 in Africans (YRI), according to HAPMAP database, www.hapmap.org/). In addition to tumorigenesis, polymorphism rs873601G>A has also been reported the association with poorer disease-free survival and overall survival, in Chinese patients with esophageal squamous cell cancer receiving platinum-based adjuvant chemotherapy [27]. Combined with the above reports, our results suggested that this SNP might be used as surrogate marker for tumor risk.

XPG gene plays the critical role in the NER pathway. Briefly, XPG cleaves the DNA strand at the 3’ side of the damaged site and stabilizes the DNA repair complex [28–30]. Thus, functional XPG variants may alter the DNA repair capacity of NER, thus modifying the risk of leiomyoma. Additionally, XPG rs873601 is a cis-regulatory SNP, which might be related to gene expression [31]. Thereby, our results on the association of leiomyoma risk and XPG rs873601 G>A polymorphism are biologically plausible.

Our data suggested that the risk effect of XPG rs873601 AA genotypes remained significant in the subgroups of younger subjects (<40 years old) and those with multiple myomas (≥3). Youngers are usually more exposed to less environmental mutagens, thus the role of genetic variants in tumor case might outweighed than enviromental factors in tumorigenesis. In addition, we also found that the association between an increased tumor risk and this SNP (rs873601 AA) was more evident in cases carrying more myomas. Because the activities of NER are associated with cell proliferation, i.e. tumor number [31], it is possible to explain the association between this SNP and an increased risk in tumor numbers.

The present study had some limitations: first, it was a hospital-based case–control study, restricted only to a Chinese Han population. However, the genotype frequencies of all studied SNP among controls well fit the Hardy–Weinberg disequilibrium law, suggesting the subjects’ selection is in random. Second, the controls were older than the cases in the present study. Nevertheless, these selection criteria might be helpful for excluding some “future” tumor case. Third, some other risk factors should be considered in later studies, such as metabolism, hormones, and environmental factors [32].

In conclusion, our data suggested that the XPG rs873601 G>A polymorphism was associated with an increased leiomyoma risk. Future well-designed, prospective studies with larger sample size, involving different ethnicities, are needed to confirm these findings.

Funding

The study was partially supported by Sanming Project of Medicine in Shenzhen [SZSM201406007]. The authors have no financial relationships relevant to this article to disclose.

Competing Interests

The authors declare that there are no competing interests associated with the manuscript.

Author Contribution

B. Liu conceptualized and designed the study, and reviewed and revised the manuscript. Z.-Q. Liu designed the data collection instruments, and drafted the initial manuscript. G.-G. Chen performed genotyping analyses. R.-L. Sun and M.-Y. Lu cleaned the database and carried out the initial analyses. C. Chen, L.-F. Guan, and X.-L. Chi enrolled uterine leiomyoma patients, collected the blood samples with their consents, and reviewed their medical records. Y.-Q. Jian, X. Zhu, and R.-Q. Liu performed random recruitment of tumor-free controls from the subjects coming for physical examination in the study hospital. B.-Y. Cai and F.F. Chen performed histological diagnoses of uterine leiomyoma. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Abbreviations

     
  • CI

    confidence interval

  •  
  • HWE

    Hardy–Weinberg equilibrium

  •  
  • NER

    nucleotide excision repair

  •  
  • OR

    odds ratio

  •  
  • SNP

    single nucleotide polymorphism

References

References
1
Stewart
E.A.
,
Laughlin-Tommaso
S.K.
,
Catherino
W.H.
,
Lalitkumar
S.
,
Gupta
D.
and
Vollenhoven
B.
(
2016
)
Uterine fibroids
.
Nat. Rev. Disease Primers
2
,
16043
2
Santulli
P.
,
Borghese
B.
,
Lemarechal
H.
,
Leconte
M.
,
Millischer
A.E.
,
Batteux
F.
et al. 
(
2013
)
Increased serum oxidative stress markers in women with uterine leiomyoma
.
PLoS One
8
,
e72069
[PubMed]
3
Pramanik
S.
,
Devi
S.
,
Chowdhary
S.
,
Surendran
S.T.
,
Krishnamurthi
K.
and
Chakrabarti
T.
(
2011
)
DNA repair gene polymorphisms at XRCC1, XRCC3, XPD, and OGG1 loci in Maharashtrian population of central India
.
Chemosphere
82
,
941
946
[PubMed]
4
Jeon
Y.T.
,
Kim
J.W.
,
Park
N.H.
,
Song
Y.S.
,
Kang
S.B.
and
Lee
H.P.
(
2005
)
DNA repair gene XRCC1 Arg399Gln polymorphism is associated with increased risk of uterine leiomyoma
.
Hum. Reprod.
20
,
1586
1589
[PubMed]
5
Chang
W.S.
,
Tsai
C.W.
,
Wang
J.Y.
,
Ying
T.H.
,
Hsiao
T.S.
,
Chuang
C.L.
et al. 
(
2015
)
Contribution of X-Ray Repair Complementing Defective Repair in Chinese Hamster Cells 3 (XRCC3) Genotype to Leiomyoma Risk
.
Anticancer Res.
35
,
4691
4696
[PubMed]
6
Hsieh
Y.Y.
,
Chang
C.C.
,
Bau
D.T.
,
Yeh
L.S.
,
Tsai
F.J.
and
Tsai
C.H.
(
2008
)
X-ray repair cross-complementing group 4 (XRCC4) promoter -1394(*)T-related genotype, but not XRCC4 codon 247/intron 3 or xeroderma pigmentosum group D codon 312, 751/promoter -114, polymorphisms are correlated with higher susceptibility to myoma
.
Fertil. Steril.
90
,
1417
1423
[PubMed]
7
Gillet
L.C.
and
Scharer
O.D.
(
2006
)
Molecular mechanisms of mammalian global genome nucleotide excision repair
.
Chem. Rev.
106
,
253
276
[PubMed]
8
Lin
J.
,
Swan
G.E.
,
Shields
P.G.
,
Benowitz
N.L.
,
Gu
J.
,
Amos
C.I.
et al. 
(
2007
)
Mutagen sensitivity and genetic variants in nucleotide excision repair pathway: genotype-phenotype correlation
.
Cancer Epidemiol. Biomarkers Prev.
16
,
2065
2071
9
Bradsher
J.
,
Auriol
J.
,
Proietti de Santis
L.
,
Iben
S.
,
Vonesch
J.L.
,
Grummt
I.
et al. 
(
2002
)
CSB is a component of RNA pol I transcription
.
Mol. Cell
10
,
819
829
[PubMed]
10
Lee
S.K.
,
Yu
S.L.
,
Prakash
L.
and
Prakash
S.
(
2002
)
Requirement of yeast RAD2, a homolog of human XPG gene, for efficient RNA polymerase II transcription. implications for Cockayne syndrome
.
Cell
109
,
823
834
[PubMed]
11
Barreto
G.
,
Schafer
A.
,
Marhold
J.
,
Stach
D.
,
Swaminathan
S.K.
,
Handa
V.
et al. 
(
2007
)
Gadd45a promotes epigenetic gene activation by repair-mediated DNA demethylation
.
Nature
445
,
671
675
[PubMed]
12
Emmert
S.
,
Schneider
T.D.
,
Khan
S.G.
and
Kraemer
K.H.
(
2001
)
The human XPG gene: gene architecture, alternative splicing and single nucleotide polymorphisms
.
Nucleic Acids Res.
29
,
1443
1452
[PubMed]
13
Hua
R.X.
,
Zhu
J.
,
Jiang
D.H.
,
Zhang
S.D.
,
Zhang
J.B.
,
Xue
W.Q.
et al. 
(
2016
)
Association of XPC Gene Polymorphisms with Colorectal Cancer Risk in a Southern Chinese Population: A Case-Control Study and Meta-Analysis
.
Genes
7
,
pii: E73
[PubMed]
14
Li
Y.
,
Liu
Z.
,
Liu
H.
,
Wang
L.E.
,
Onodera
H.
,
Suzuki
A.
et al. 
(
2014
)
Potentially functional variants in the core nucleotide excision repair genes predict survival in Japanese gastric cancer patients
.
Carcinogenesis
35
,
2031
2038
[PubMed]
15
He
J.
,
Qiu
L.X.
,
Wang
M.Y.
,
Hua
R.X.
,
Zhang
R.X.
,
Yu
H.P.
et al. 
(
2012
)
Polymorphisms in the XPG gene and risk of gastric cancer in Chinese populations
.
Hum. Genet.
131
,
1235
1244
[PubMed]
16
Chen
Y.Z.
,
Guo
F.
,
Sun
H.W.
,
Kong
H.R.
,
Dai
S.J.
,
Huang
S.H.
et al. 
(
2016
)
Association between XPG polymorphisms and stomach cancer susceptibility in a Chinese population
.
J. Cell. Mol. Med.
20
,
903
908
[PubMed]
17
Sun
X.
,
Li
F.
,
Sun
N.
,
Shukui
Q.
,
Baoan
C.
,
Jifeng
F.
et al. 
(
2009
)
Polymorphisms in XRCC1 and XPG and response to platinum-based chemotherapy in advanced non-small cell lung cancer patients
.
Lung Cancer
65
,
230
236
[PubMed]
18
Ma
H.
,
Yu
H.
,
Liu
Z.
,
Wang
L.E.
,
Sturgis
E.M.
and
Wei
Q.
(
2012
)
Polymorphisms of XPG/ERCC5 and risk of squamous cell carcinoma of the head and neck
.
Pharmacogenet. Genomics
22
,
50
57
[PubMed]
19
He
J.
,
Wang
F.
,
Zhu
J.
,
Zhang
R.
,
Yang
T.
,
Zou
Y.
et al. 
(
2016
)
Association of potentially functional variants in the XPG gene with neuroblastoma risk in a Chinese population
.
J. Cell. Mol. Med.
20
,
1481
1490
[PubMed]
20
Liu
B.
,
Chen
D.
,
Yang
L.
,
Li
Y.
,
Ling
X.
,
Liu
L.
et al. 
(
2010
)
A functional variant (-1304T>G) in the MKK4 promoter contributes to a decreased risk of lung cancer by increasing the promoter activity
.
Carcinogenesis
31
,
1405
1411
[PubMed]
21
Liu
B.
,
Yang
L.
,
Huang
B.
,
Cheng
M.
,
Wang
H.
,
Li
Y.
et al. 
(
2012
)
A functional copy-number variation in MAPKAPK2 predicts risk and prognosis of lung cancer
.
Am. J. Hum. Genet.
91
,
384
390
[PubMed]
22
Hua
R.X.
,
Zhuo
Z.J.
,
Zhu
J.
,
Jiang
D.H.
,
Xue
W.Q.
,
Zhang
S.D.
et al. 
(
2016
)
Association between genetic variants in the XPG gene and gastric cancer risk in a Southern Chinese population
.
Aging
8
,
3311
3320
[PubMed]
23
Wang
B.
,
Xu
Q.
,
Yang
H.W.
,
Sun
L.P.
and
Yuan
Y.
(
2016
)
The association of six polymorphisms of five genes involved in three steps of nucleotide excision repair pathways with hepatocellular cancer risk
.
Oncotarget
7
,
20357
20367
[PubMed]
24
Hua
R.X.
,
Zhuo
Z.J.
,
Zhu
J.
,
Zhang
S.D.
,
Xue
W.Q.
,
Zhang
J.B.
et al. 
(
2016
)
XPG gene polymorphisms contribute to colorectal cancer susceptibility: a two-stage case-control study
.
J. Cancer
7
,
1731
1739
[PubMed]
25
Han
C.
,
Huang
X.
,
Hua
R.
,
Song
S.
,
Lyu
L.
,
Ta
N.
et al. 
(
2017
)
The association between XPG polymorphisms and cancer susceptibility: Evidence from observational studies
.
Medicine
96
,
e7467
26
Huang
J.
,
Liu
X.
,
Tang
L.L.
,
Long
J.T.
,
Zhu
J.
,
Hua
R.X.
et al. 
(
2017
)
XPG gene polymorphisms and cancer susceptibility: evidence from 47 studies
.
Oncotarget
8
,
37263
37277
[PubMed]
27
Zhou
F.
,
Zhu
M.
,
Wang
M.
,
Qiu
L.
,
Cheng
L.
,
Jia
M.
et al. 
(
2016
)
Genetic variants of DNA repair genes predict the survival of patients with esophageal squamous cell cancer receiving platinum-based adjuvant chemotherapy
.
J. Transl. Med.
14
,
154
28
Friedberg
E.C.
(
2003
)
DNA damage and repair
.
Nature
421
,
436
440
[PubMed]
29
O’Donovan
A.
,
Davies
A.A.
,
Moggs
J.G.
,
West
S.C.
and
Wood
R.D.
(
1994
)
XPG endonuclease makes the 3′ incision in human DNA nucleotide excision repair
.
Nature
371
,
432
435
[PubMed]
30
Wakasugi
M.
,
Reardon
J.T.
and
Sancar
A.
(
1997
)
The non-catalytic function of XPG protein during dual incision in human nucleotide excision repair
.
J. Biol. Chem.
272
,
16030
16034
[PubMed]
31
Zhang
X.
,
Crawford
E.L.
,
Blomquist
T.M.
,
Khuder
S.A.
,
Yeo
J.
,
Levin
A.M.
et al. 
(
2016
)
Haplotype and diplotype analyses of variation in ERCC5 transcription cis-regulation in normal bronchial epithelial cells
.
Physiol. Genomics
48
,
537
543
[PubMed]
32
Sparic
R.
,
Mirkovic
L.
,
Malvasi
A.
and
Tinelli
A.
(
2016
)
Epidemiology of uterine myomas: a review
.
Int. J. Fertility Sterility
9
,
424
435
,
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Supplementary data