The role of CCNH Val270Ala (rs2230641) and other nucleotide excision repair polymorphisms in individual susceptibility to well-differentiated thyroid cancer

  • Authors:
    • Luís S. Santos
    • Bruno C. Gomes
    • Rita Gouveia
    • Susana N. Silva
    • Ana  P. Azevedo
    • Vanessa Camacho
    • Isabel Manita
    • Octávia M. Gil
    • Teresa  C. Ferreira
    • Edward Limbert
    • José Rueff
    • Jorge F. Gaspar
  • View Affiliations

  • Published online on: August 27, 2013     https://doi.org/10.3892/or.2013.2702
  • Pages: 2458-2466
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Well-differentiated thyroid cancer (DTC) is the most common form of thyroid cancer (TC); however, with the exception of radiation exposure, its etiology remains largely unknown. Several single nucleotide polymorphisms (SNPs) have previously been implicated in DTC risk. Nucleotide excision repair (NER) polymorphisms, despite having been associated with cancer risk at other locations, have received little attention in the context of thyroid carcinogenesis. In order to evaluate the role of NER pathway SNPs in DTC susceptibility, we performed a case-control study in 106 Caucasian Portuguese DTC patients and 212 matched controls. rs2230641 (CCNH), rs2972388 (CDK7), rs1805329 (RAD23B), rs3212986 (ERCC1), rs1800067 (ERCC4), rs17655, rs2227869 (ERCC5), rs4253211 and rs2228529 (ERCC6) were genotyped using TaqMan® methodology, while conventional PCR-RFLP was employed for rs2228000 and rs2228001 (XPC). When considering all DTC cases, only rs2230641 (CCNH) was associated with DTC risk; a consistent increase in overall DTC risk was observed for both the heterozygous genotype (OR=1.89, 95% CI=1.14-3.14) and the variant allele carriers (OR=1.79, 95% CI=1.09-2.93). Histological stratification analysis confirmed an identical effect on follicular TC (OR=2.72, 95% CI=1.19-6.22, for heterozygous; OR=2.44, 95% CI=1.07‑5.55, for variant allele carriers). Considering papillary TC, the rs2228001 (XPC) variant genotype was associated with increased risk (OR=2.33, 95% CI=1.05-5.16), while a protective effect was observed for rs2227869 (ERCC5) (OR=0.26, 95% CI=0.08‑0.90, for heterozygous; OR=0.25, 95% CI=0.07-0.86, for variant allele carriers). No further significant results were observed. Our results suggest that NER polymorphisms such as rs2230641 (CCNH) and, possibly, rs2227869 (ERCC5) and rs2228001 (XPC), may influence DTC susceptibility. However, larger studies are required to confirm these results.

Introduction

Thyroid cancer (TC) is a rare neoplasia, but is the most frequent endocrine malignancy (1). In general, it originates from thyroid follicular cells and its most common histological types are papillary carcinoma (≈70–80%) and follicular carcinoma (≈10–20%) (2). Papillary and follicular TC are often categorized together as non-medullary well-differentiated thyroid cancer (DTC), and, in contrast to undifferentiated (anaplastic) TC, have indolent behaviour and can be treated with high survival rates, particularly if they are localized and small-sized (1). TC can occur in any age group but its incidence increases with age (1). This type of cancer (particularly DTC) is 3 times more likely to occur in women than in men and, in the past 2 decades, its incidence has increased (1). The best-established cause of thyroid carcinogenesis is exposure to ionizing radiation, although other candidate risk factors such as dietary iodine deficiency, hormonal factors, benign thyroid conditions and familial history have also been noted (2).

DTC frequency is significantly higher in relatives (particularly first-degree) of DTC patients compared to the general population (2,3). However, familial DTC accounts for only a minor percentage of cases (2), suggesting that other genetic risk factors could be involved. Identifying such individual genetic differences so that these may be used as genetic susceptibility markers for DTC in the remaining sporadic cases is therefore an important challenge. In line with this, several DNA polymorphisms in genes involved in endobiotic or xenobiotic metabolism (including GST and CYP superfamilies), in hormonal and iodine metabolism (such as TG), in cell-cycle control and regulation of apoptosis (such as TP53), in kinase-dependent signaling pathways (such as RET) and in DNA repair (among others) have been associated with differential susceptibility to DTC [reviewed in reference (3)]. The first genome-wide association study (GWAS) performed on TC identified 2 other polymorphisms located near the FOXE1 (TTF-2) and NKX2-1 (TTF-1) genes (which encode for thyroid-specific transcription factors) as strong genetic risk markers of sporadic DTC in European populations (4).

Since patients with papillary TC present a significant increase in DNA damage (5) and DNA repair mechanisms are important in correcting such damage, it is reasonable to assume that defective DNA repair capacity may contribute to DTC risk. Variants in DNA repair genes may affect the DNA repair capacity and, in fact, several single nucleotide polymorphisms (SNPs) in almost all DNA repair pathways have been shown to incrementally contribute to cancer risk (6). Regarding TC, polymorphisms in DNA repair genes such as XRCC1(79) and possibly MUTYH(10) (BER pathway), Ku80(11) (NHEJ pathway), BRCA1(12), XRCC3 and possibly RAD51(13) (HR pathway) have been associated with either TC or, more specifically, DTC risk [reviewed in references (3,14,15)].

Nucleotide excision repair (NER) is a versatile DNA repair mechanism capable of repairing UV light-induced lesions, bulky DNA adducts, distorting interstrand crosslinks and even certain oxidative lesions (16). A significant association between an ERCC2 haplotype (rs13181/rs1799793) and TC risk (mainly papillary) was previously reported by our team (17), suggesting that NER polymorphisms may also be relevant for thyroid carcinogenesis. However, to our knowledge, no other published study has thus far focused on a possible role of NER pathway SNPs in DTC susceptibility.

Therefore, we carried out an exploratory hospital-based case-control study in a Caucasian Portuguese population to evaluate the potential modifying role of a panel of 11 NER pathway SNPs (CCNH rs2230641, CDK7 rs2972388, RAD23B rs1805329, ERCC1 rs3212986, ERCC4 rs1800067, ERCC5 rs17655 and rs2227869, ERCC6 rs4253211 and rs2228529 and XPC rs2228000 and rs2228001) on the individual susceptibility to non-familial DTC.

Materials and methods

Study subjects

This study included 106 Caucasian Portuguese DTC patients without familial history of TC, previous neoplastic pathology and recent blood transfusion. Patients were recruited in the Department of Nuclear Medicine of the Portuguese Oncology Institute of Lisbon, where they received Iodine-131 treatment. Histological diagnosis was confirmed for all cases. For each case, 2 age- (±2 years) and gender-matched controls were recruited. Controls (n=212), with no previous or current malignant disease and no personal or familiar history of thyroid pathology, were recruited at São Francisco Xavier Hospital, where they were observed for non-neoplastic pathology. Information on demographic characteristics, family history of cancer, lifestyle habits (such as smoking, alcohol drinking) and exposure to ionizing radiation was collected using a questionnaire administered by trained interviewers. Former smokers were considered as non-smokers if they had given up smoking either 2 years before DTC diagnosis or 2 years before their inclusion as controls. The response rate was >95% for cases and controls. The anonymity of patients and controls was guaranteed and written informed consent was obtained from all those involved, prior to blood withdrawal, in agreement with the Declaration of Helsinki. Approval by the institutional ethics boards of the involved institutions was mandatory.

DNA extraction

Peripheral blood samples of all patients and controls were collected into 10 ml heparinized tubes and kept at -80°C. Genomic DNA was obtained from each sample using a commercially available kit (QIAamp® DNA mini kit; Qiagen) according to the manufacturer’s instructions. All DNA samples were stored at −20°C until analysis.

SNP selection

Publicly available databases such as NCBI (http://www.ncbi.nlm.nih.gov/snp/), Genecards (http://www.genecards.org) and SNP500Cancer (http://variantgps.nci.nih.gov/cgfseq/pages/snp500.do) were used to search for NER polymorphisms. Eligible SNP’s had to be located either in a coding or splice region and had to exhibit minor allele frequency (MAF) >0.05 in Caucasian populations. Despite being located on the 3′UTR region, rs3212986 (ERCC1) was also selected since it is one of the most extensively studied ERCC1 SNPs and evidence exists for functional significance (18,19). In total, 9 common nsSNP’s, 1 synonymous SNP and 1 SNP located on 3′UTR were selected (Table I).

Table I

Selected SNP’s and detailed information on the corresponding base and aminoacid exchanges, minor allele frequency and AB assay used for genotyping.

Table I

Selected SNP’s and detailed information on the corresponding base and aminoacid exchanges, minor allele frequency and AB assay used for genotyping.

GeneLocationdbSNP cluster ID (rs no.)Base changeAminoacid changeMAF (%)aAB assay ID
CCNH5q13.3-q14rs2230641T→CVal270Ala13.8C_11685807_10
CDK75q12.1rs2972388T→CAsn33Asn40.5C_1191757_10
RAD23B9q31.2rs1805329C→TAla249Val16.7C_11493966_10
ERCC119q13.32rs3212986C→A-b29.4C_2532948_10
ERCC416p13.3rs1800067G→AArg415Gln3.1C_3285104_10
ERCC513q22-q34rs17655G→CAsp1104His37.7C_1891743_10
ERCC513q22-q34rs2227869G→CCys529Ser4.9C_15956775_10
ERCC610q11rs4253211G→CArg1230Pro6.4C_25762749_10
ERCC610q11rs2228529A→GGln1413Arg15.6C_16171343_10
XPC3p25rs2228000C→TAla499Val24.8-c
XPC3p25rs2228001A→CLys939Gln34.4-c

a Minor allele frequency, according to http://www.ncbi.nlm.nih.gov/projects/SNP/;

b SNP located on 3′UTR;

c not applicable (genotyping performed by PCR-RFLP).

{ label (or @symbol) needed for fn[@id='tfn4-or-30-05-2458'] } SNPs, single nucleotide polymorphisms.

Genotyping

rs2230641 (CCNH), rs2972388 (CDK7), rs1805329 (RAD23B), rs3212986 (ERCC1), rs1800067 (ERCC4), rs17655 and rs2227869 (ERCC5), rs4253211 and rs2228529 (ERCC6) were genotyped by real-time PCR, using TaqMan SNP Genotyping Assays (Applied Biosystems). To assure uniformity in genomic DNA content (2.5 ng/μl) in all samples, DNA was quantified using the fluorimetric Quant-iT™ Picogreen® dsDNA Assay kit (Invitrogen Life Technologies) and a Zenyth 3100 plate reader (Anthos Labtec Instruments), according to the manufacturer’s recommendations. PCR was performed in a 7300 Real-Time PCR system thermal cycler (Applied Biosystems). Genotyping assays used are identified in Table I. The amplification conditions consisted of an initial activation step (10 min, 95°C), followed by ≥40 amplification cycles of denaturation (15 sec, 92°C) and annealing/extension (60 sec, 60°C). Allelic discrimination was performed by measuring fluorescence emitted by VIC and FAM dyes in each well (60 sec) and computing the results into the System SDS software version 1.3.1.

rs2228000 and rs2228001 (XPC) genotyping was performed by PCR-RFLP. Primer sequences, PCR conditions, PCR product sizes, restriction analysis conditions and expected digestion pattern for each XPC genotype have been described elsewhere (20).

Genotyping was repeated for all inconclusive samples. Also, genotype determinations were carried out twice in independent experiments (100% of concordance between experiments) for all samples when SNPs were genotyped by PCR-RFLP and for 10–15% of samples when SNPs were genotyped by real-time PCR.

Statistical analysis

Hardy-Weinberg frequencies for all alleles in patients and controls were analysed using exact probability tests available in Mendel software (V5.7.2) (21). The Kolmogorov-Smirnov and Shapiro-Wilk tests were used to verify the normality of continuous variables and the Levene’s test was used to analyze the homogeneity of variances. Differences in genotype frequency, smoking status, age class and gender distributions between patients and controls were evaluated by the χ2 test. Adjusted odds ratio (OR) and corresponding 95% confidence interval (CI) were calculated using unconditional multiple logistic regression. The model for adjusted OR included terms for gender, age at diagnosis (≤30, 31–49, 50–69 and ≥70 years) and smoking habits (smokers/non-smokers). Male gender, lower age group and non-smokers were considered the reference groups for these variables. For controls, age at diagnosis was defined as the matched case age of diagnosis. All analyses were performed using SPSS 15.0 (SPSS, Inc.).

Results

This study comprised 106 DTC patients and 212 age- and gender-matched controls. The histological classification of DTC cases was 73.6% papillary tumours (78 patients) and 26.4% follicular tumours (28 patients). Table II lists the general characteristics of both case and control populations. In the case group, the frequency of females (90 patients) was significantly higher than the frequency of males (16 patients), in accordance with the worldwide estimation for gender distribution in DTC (1). Case and control populations are not statistically different in respect to age distribution, gender and smoking habits.

Table II

General characteristics for the DTC cases (n=106) and control population (n=212).

Table II

General characteristics for the DTC cases (n=106) and control population (n=212).

CharacteristicsControls, n (%)Cases, n (%)P-valuec
Gender
 Male31 (14.6)16 (15.1)0.91
 Female181 (85.4)90 (84.9)
Agea,b
 ≤309 (4.2)4 (3.8)0.99
 31–4977 (36.3)39 (36.8)
 50–69100 (47.2)49 (46.2)
 ≥7026 (12.3)14 (13.2)
Smoking habits
 Non-smokers172 (81.1)94 (88.7)0.12
 Smokers38 (17.9)12 (11.3)
 Missing2 (0.9)0 (0.0)

a Age of diagnosis, for cases;

b age at the time of diagnosis of the matched case, for controls;

c P-value determined by χ2 test (cases vs. control group).

{ label (or @symbol) needed for fn[@id='tfn8-or-30-05-2458'] } DTC, well-differentiated thyroid cancer.

This report includes a set of 11 SNPs in 8 NER pathway genes (Table I). The MAF and genotypic frequencies of these SNPs, in both DTC cases and controls, are depicted in Table III. All SNPs considered are in Hardy-Weinberg equilibrium (P≥0.05), both in case and control populations, except for rs2972388 (CDK7) and rs2228000 (XPC) that show a significant deviation in the control (rs2972388) or case population (rs2228000).

Table III

Genotype distribution in case (n=106) and control (n=212) populations and associated DTC risk (adjusted ORs).

Table III

Genotype distribution in case (n=106) and control (n=212) populations and associated DTC risk (adjusted ORs).

MAFGenotype frequency


GenotypeControlsCasesControls, n (%)Cases, n (%)P-valueaAdjusted OR (95% CI)b
CCNH rs2230641212 (100)106 (100)
 Val/ValC: 0.17C: 0.23148 (69.8)60 (56.6)1 (Reference)
 Val/Ala56 (26.4)43 (40.6)0.04c1.89 (1.14–3.14)c
 Ala/Ala8 (3.8)3 (2.8)1.01 (0.25–4.03)
 Val/Ala + Ala/Ala64 (30.2)46 (43.4)0.02c1.79 (1.09–2.93)c
CDK7 rs2972388206 (100)101 (100)
 T/TC: 0.48C: 0.4263 (30.6)37 (36.6)1 (Reference)
 T/C88 (42.7)43 (42.6)0.420.86 (0.50–1.49)
 C/C55 (26.7)21 (20.8)0.62 (0.32–1.19)
 T/C + C/C143 (69.4)64 (63.4)0.290.77 (0.46–1.27)
RAD23B rs1805329212 (100)106 (100)
 Ala/AlaT: 0.16T: 0.17150 (70.8)75 (70.8)1 (Reference)
 Ala/Val55 (25.9)27 (25.5)0.980.94 (0.54–1.62)
 Val/Val7 (3.3)4 (3.8)1.19 (0.33–4.30)
 Ala/Val + Val/Val62 (29.2)31 (29.2)1.000.96 (0.57–1.62)
ERCC1 rs3212986211 (100)106 (100)
 C/CA: 0.24A: 0.21118 (55.9)64 (60.4)1 (Reference)
 C/A83 (39.3)39 (36.8)0.610.84 (0.51–1.37)
 A/A10 (4.7)3 (2.8)0.52 (0.14–1.99)
 C/A + A/A93 (44.1)42 (39.6)0.450.80 (0.50–1.30)
ERCC4 rs1800067210 (100)102 (100)
 Arg/ArgA: 0.11A: 0.13168 (80.0)77 (75.5)1 (Reference)
 Arg/Gln38 (18.1)23 (22.5)0.651.34 (0.74–2.43)
 Gln/Gln4 (1.9)2 (2.0)1.05 (0.19–5.98)
 Arg/Gln + Gln/Gln42 (20.0)25 (24.5)0.361.31 (0.74–2.33)
ERCC5 rs17655212 (100)105 (100)
 Asp/AspC: 0.30C: 0.28106 (50.0)51 (48.6)1 (Reference)
 Asp/His85 (40.1)50 (47.6)0.121.22 (0.75–1.98)
 His/His21 (9.9)4 (3.8)0.42 (0.13–1.29)
 Asp/His + His/His106 (50.0)54 (51.4)0.811.07 (0.67–1.72)
ERCC5 rs2227869212 (100)106 (100)
 Cys/CysC: 0.07C: 0.04184 (86.8)99 (93.4)1 (Reference)
 Cys/Ser27 (12.7)6 (5.7)0.140.39 (0.16–1.00)
 Ser/Ser1 (0.5)1 (0.9)1.77 (0.11–29.10)
 Cys/Ser + Ser/Ser28 (13.2)7 (6.6)0.080.44 (0.19–1.06)
ERCC6 rs4253211211 (100)102 (100)
 Arg/ArgC: 0.11C: 0.13170 (80.6)79 (77.5)1 (Reference)
 Arg/Pro37 (17.5)20 (19.6)0.751.26 (0.68–2.33)
 Pro/Pro4 (1.9)3 (2.9)1.86 (0.39–8.91)
 Arg/Pro + Pro/Pro41 (19.4)23 (22.5)0.521.31 (0.72–2.37)
ERCC6 rs2228529211 (100)104 (100)
 Gln/GlnG: 0.24G: 0.20118 (55.9)66 (63.5)1 (Reference)
 Gln/Arg86 (40.8)35 (33.7)0.440.67 (0.40–1.12)
 Arg/Arg7 (3.3)3 (2.9)0.72 (0.18–2.89)
 Gln/Arg + Arg/Arg93 (44.1)38 (36.5)0.200.67 (0.41–1.11)
XPC rs2228000212 (100)106 (100)
 Ala/AlaT: 0.32T: 0.3095 (44.8)47 (44.3)1 (Reference)
 Ala/Val98 (46.2)55 (51.9)0.211.16 (0.71–1.88)
 Val/Val19 (9.0)4 (3.8)0.43 (0.14–1.37)
 Ala/Val + Val/Val117 (55.2)59 (55.7)0.941.04 (0.65–1.67)
XPC rs2228001212 (100)106 (100)
 Lys/LysC: 0.36C: 0.4182 (38.7)39 (36.8)1 (Reference)
 Lys/Gln108 (50.9)47 (44.3)0.100.96 (0.57–1.61)
 Gln/Gln22 (10.4)20 (18.9)1.93 (0.93–4.00)
 Lys/Gln + Gln/Gln130 (61.3)67 (63.2)0.741.12 (0.69–1.83)

a P-value determined by χ2 test (cases vs. control group);

b ORs were adjusted for gender (male and female), age (≤30, 31–49, 50–69, ≥70 years) and smoking status (non-smoker and smoker).

c P<0.05.

{ label (or @symbol) needed for fn[@id='tfn12-or-30-05-2458'] } DTC, well-differentiated thyroid cancer; MAF, minor allele frequencies.

Genotypic distributions were compared among cases and controls (Table III). A significant difference was observed only for rs2230641 (CCNH) (P=0.04). When considering a dominant model of inheritance, the difference in rs2230641 (CCNH) genotypic frequency between cases and controls was even more significant (P=0.02).

Through logistic regression analysis (Table III), we observed that the rs2230641 (CCNH) heterozygous genotype was significantly associated with increased DTC risk (adjusted OR=1.89, 95% CI=1.14–3.14, P=0.01). Similar results were verified when considering at least one variant allele (adjusted OR=1.79, 95% CI=1.09–2.93, P=0.02), further supporting an association between rs2230641 (CCNH) and DTC risk. Also, an almost significant association between the rs2227869 (ERCC5) heterozygous genotype and reduced DTC risk was observed (adjusted OR=0.39, 95% CI=0.16–1.00, P=0.05).

Following stratification according to histological criteria (Table IV), the DTC risk increase observed for rs2230641 (CCNH) remained in the follicular subset (adjusted OR=2.72, 95% CI=1.19–6.22, P=0.02, for heterozygous; adjusted OR=2.44, 95% CI=1.07–5.55, P=0.03, for variant allele carriers) and almost reached significance in the papillary subset (adjusted OR=1.74, 95% CI=0.99–3.07, P=0.05, for heterozygous; adjusted OR=1.69, 95% CI=0.98–2.92, P=0.06, for variant allele carriers), supporting the idea that this polymorphism may influence DTC susceptibility, irrespective of tumour type. The risk of papillary TC was significantly increased in rs2228001 (XPC) homozygous variant individuals (adjusted OR=2.33, 95% CI=1.05–5.16, P=0.04) and significantly reduced in rs2227869 (ERCC5) variant allele carriers (adjusted OR=0.25, 95% CI=0.07–0.86, P=0.03) and heterozygous individuals (adjusted OR=0.26, 95% CI=0.08–0.90, P=0.03). No significant differences in genotypic frequencies or adjusted ORs were observed for the remaining SNPs, either when considering overall DTC cases or its histological subsets, suggesting that these SNPs alone do not contribute to individual susceptibility to DTC.

Table IV

Genotype distribution in the case population (n=106) and associated DTC risk (adjusted ORs), after stratification according to histological type.

Table IV

Genotype distribution in the case population (n=106) and associated DTC risk (adjusted ORs), after stratification according to histological type.

Papillary carcinomaFollicular carcinoma


Genotypen (%)Adjusted OR (95% CI)an (%)Adjusted OR (95% CI)a
CCNH rs223064178 (100)28 (100)
 Val/Val45 (57.7)1 (Reference)15 (53.6)1 (Reference)
 Val/Ala30 (38.5)1.74 (0.99–3.07)13 (46.4)2.72 (1.19–6.22)b
 Ala/Ala3 (3.8)1.27 (0.32–5.15)0 (0.0)-
 Val/Ala + Ala/Ala33 (42.3)1.69 (0.98–2.92)13 (46.4)2.44 (1.07–5.55)b
CDK7 rs297238875 (100)26 (100)
 T/T27 (36.0)1 (Reference)10 (38.5)1 (Reference)
 T/C31 (41.3)0.87 (0.47–1.60)12 (46.2)0.93 (0.37–2.31)
 C/C17 (22.7)0.70 (0.35–1.43)4 (15.4)0.40 (0.12–1.37)
 T/C + C/C48 (64.0)0.80 (0.46–1.40)16 (61.5)0.70 (0.30–1.65)
RAD23B rs180532978 (100)28 (100)
 Ala/Ala53 (67.9)1 (Reference)22 (78.6)1 (Reference)
 Ala/Val22 (28.2)1.06 (0.59–1.91)5 (17.9)0.56 (0.20–1.58)
 Val/Val3 (3.8)1.27 (0.31–5.25)1 (3.6)1.26 (0.14–11.28)
 Ala/Val + Val/Val25 (32.1)1.08 (0.61–1.90)6 (21.4)0.62 (0.24–1.63)
ERCC1 rs321298678 (100)28 (100)
 C/C49 (62.8)1 (Reference)15 (53.6)1 (Reference)
 C/A27 (34.6)0.72 (0.41–1.25)12 (42.9)1.07 (0.47–2.44)
 A/A2 (2.6)0.46 (0.10–2.21)1 (3.6)0.76 (0.09–6.64)
 C/A + A/A29 (37.2)0.69 (0.40–1.19)13 (46.4)1.04 (0.47–2.33)
ERCC4 rs180006775 (100)27 (100)
 Arg/Arg57 (76.0)1 (Reference)20 (74.1)1 (Reference)
 Arg/Gln17 (22.7)1.38 (0.71–2.66)6 (22.2)1.46 (0.54–3.99)
 Gln/Gln1 (1.3)0.76 (0.08–7.20)1 (3.7)1.87 (0.18–19.10)
 Arg/Gln + Gln/Gln18 (24.0)1.32 (0.69–2.50)7 (25.9)1.51 (0.59–3.88)
ERCC5 rs1765577 (100)28 (100)
 Asp/Asp39 (50.6)1 (Reference)12 (42.9)1 (Reference)
 Asp/His36 (46.8)1.15 (0.67–1.96)14 (50.0)1.48 (0.64–3.43)
 His/His2 (2.6)0.28 (0.06–1.27)2 (7.1)0.82 (0.17–4.03)
 Asp/His + His/His38 (49.4)0.99 (0.59–1.68)16 (57.1)1.35 (0.60–3.05)
ERCC5 rs222786978 (100)28 (100)
 Cys/Cys75 (96.2)1 (Reference)24 (85.7)1 (Reference)
 Cys/Ser3 (3.8)0.26 (0.08–0.90)b3 (10.7)0.87 (0.24–3.15)
 Ser/Ser0 (0.0)-1 (3.6)5.49 (0.32–95.50)
 Cys/Ser + Ser/Ser3 (3.8)0.25 (0.07–0.86)b4 (14.3)1.09 (0.34–3.46)
ERCC6 rs425321176 (100)26 (100)
 Arg/Arg60 (78.9)1 (Reference)19 (73.1)1 (Reference)
 Arg/Pro13 (17.1)1.06 (0.52–2.15)7 (26.9)1.90 (0.71–5.07)
 Pro/Pro3 (3.9)2.41 (0.50–11.72)0 (0.0)-
 Arg/Pro + Pro/Pro16 (21.1)1.17 (0.60–2.28)7 (26.9)1.79 (0.67–4.78)
ERCC6 rs222852976 (100)28 (100)
 Gln/Gln47 (61.8)1 (Reference)19 (67.9)1 (Reference)
 Gln/Arg26 (34.2)0.71 (0.40–1.25)9 (32.1)0.64 (0.27–1.51)
 Arg/Arg3 (3.9)0.95 (0.24–3.80)0 (0.0)-
 Gln/Arg + Arg/Arg29 (38.2)0.73 (0.42–1.26)9 (32.1)0.58 (0.24–1.36)
XPC rs222800078 (100)28 (100)
 Ala/Ala34 (43.6)1 (Reference)13 (46.4)1 (Reference)
 Ala/Val43 (55.1)1.23 (0.72–2.10)12 (42.9)0.92 (0.39–2.13)
 Val/Val1 (1.3)0.15 (0.02–1.18)3 (10.7)1.30 (0.32–5.24)
 Ala/Val + Val/Val44 (56.4)1.06 (0.63–1.80)15 (53.6)0.97 (0.44–2.16)
XPC rs222800178 (100)28 (100)
 Lys/Lys26 (33.3)1 (Reference)13 (46.4)1 (Reference)
 Lys/Gln36 (46.2)1.08 (0.60–1.95)11 (39.3)0.65 (0.27–1.54)
 Gln/Gln16 (20.5)2.33 (1.05–5.16)b4 (14.3)1.17 (0.34–4.07)
 Lys/Gln + Gln/Gln52 (66.7)1.28 (0.74–2.24)15 (53.6)0.73 (0.33–1.65)

a ORs were adjusted for gender (male and female), age (≤30, 31–49, 50–69, and ≥70 years), and smoking status (non-smoker and smoker).

b P-value <0.05.

{ label (or @symbol) needed for fn[@id='tfn15-or-30-05-2458'] } DTC, well-differentiated thyroid cancer.

To assess the effect of combined genotypes, further statistical analysis was applied to those SNPs that are located in the same gene (rs17655 and rs2227869 on ERCC5; rs4253211 and rs2228529 on ERCC6; rs2228000 and rs2228001 on XPC). Also, since SNPs in different NER genes may influence the way their expression products interact (hence, their repair activity), we also analyzed SNP-SNP interactions between different genes, as long as these interactions were biologically plausible. The genotype distribution of the rs17655/rs2227869 (ERCC5) combination was significantly different in cases and controls (P=0.01); however, no specific ERCC5 genotype combination was associated with altered DTC risk (data not shown), probably due to the low number of patients included in each genetic subgroup. None of the remaining genotype combinations showed association with disease (data not shown).

Discussion

We conducted a hospital-based case-control study in a Caucasian Portuguese population to evaluate the potential modifying role of a comprehensive selection of 11 SNPs in 8 NER pathway genes in individual susceptibility to non-familial DTC. Overall, we observed that NER polymorphisms such as rs2230641 (CCNH) and, possibly, rs2227869 (ERCC5) and rs2228001 (XPC) were associated with DTC susceptibility. A consistent risk increase was observed for rs2230641 (CCNH) heterozygous and variant allele carriers, compared to wild-type individuals, both when considering all DTC cases and only the follicular subset. When considering only the papillary subset, the risk association almost reached significance for rs2230641 (CCNH) but was significant for the rs2228001 (XPC) variant genotype (increased risk). Also, a protective effect was observed for rs2227869 (ERCC5) in heterozygous and variant allele carriers, in the papillary subset. The association between the rs2227869 (ERCC5) heterozygous genotype and reduced DTC risk almost reached significance when all DTC cases were considered. No other significant correlation was observed for the remaining SNPs.

To our knowledge, this is the first study to assess the effect of these SNPs on DTC susceptibility. Our previous study reporting an association between an ERCC2 haplotype (rs13181/rs1799793) and increased TC (mainly papillary) risk (17) is the only other association study that we are aware of, focusing on the role of NER pathway SNPs in TC susceptibility. However, studies correlating the polymorphisms considered in this study with cancer risk have been published for other types of cancer.

Concerning rs2230641 (CCNH), studies on oesophageal (22) bladder (23) and renal cell carcinoma (24) have yielded mostly negative results. Two significant associations have been reported, with opposite findings; according to Enjuanes et al(25), the minor allele is associated with decreased risk for chronic lymphocytic leukaemia; on the contrary, in line with our results, Chen et al(26), observed, in ever smokers, a significant association for the rs2230641 variant allele with bladder cancer risk and an almost 30-fold increased risk in carriers of the rs2230641 (CCNH), rs2228526 (ERCC6) and rs1805329 (RAD23B) variant alleles.

Previous evidence on the role of XPC polymorphisms on cancer risk is also conflicting; both rs2228001 and rs2228000 have been extensively investigated in case-control cancer association studies but, when considered separately, results are mostly negative, possibly due to insufficient sample size. Increasing the power through performance of meta-analysis has revealed small but significant increases in overall (2729), bladder (2731) and breast (29) cancer risk for rs2228000 and in overall (28,29), lung (2730), bladder (29) and colorectal (29) cancer risk for rs2228001. Meta-analyses yielding negative results have also been published (32,33). The effect of XPC polymorphisms may be best represented by its haplotype since significantly increased cancer risk has been observed more frequently when considering both polymorphisms together, as a haplotype block (22,34), or in combined analysis with other NER variants (23,35,36).

With respect to rs2227869 (ERCC5), notably, results similar to our own have been reported by Hussain et al(37) in the only cancer association study we retrieved from our literature review; decreased stomach cancer risk was observed in heterozygous individuals, according to this study.

As for the remaining SNPs, rs3212986 (ERCC1), rs1800067 (ERCC4), rs17655 (ERCC5) and rs1805329 (RAD23B) have been extensively analyzed in prior cancer association studies, mostly with negative results. For rs3212986 (ERCC1), rs1800067 (ERCC4) and rs17655 (ERCC5) these findings are further corroborated by several meta-analyses that, in agreement with our report, demonstrated no clear association with overall (3841), lung (42) or breast (43) cancer risk. rs2972388 (CDK7), rs4253211 and rs2228529 (ERCC6) have received little attention in the context of cancer susceptibility but the unique reports we found for each of these SNPs are substantially different from ours, as rs2972388 (CDK7) and rs2228529 (ERCC6) were associated, respectively, with increased breast cancer risk in a Korean population (44) and increased non-melanoma skin cancer risk in an American population (45). For rs4253211 (ERCC6), the variant allele seems to confer a protective effect towards laryngeal (36) and oesophageal (22) cancer, but no association with bladder cancer was observed (23).

CCNH codes for Cyclin H, a protein that, together with CDK7 and MAT1, forms the cyclin-activated kinase (CAK) complex. CAK integrates TFIIH, a larger complex implicated in DNA denaturation prior to damage excision. CAK can also phosphorylate nuclear receptors such as the retinoic acid or the estrogen receptors and a very different range of substrates (16). It is also involved in cell cycle regulation (46). Although data on the functional consequences of rs2230641 is lacking, the pleiotropic effects of CCNH on NER, cell cycle regulation and oestrogen receptor phosphorylation, among others, confer biological plausibility to our hypothesis that CCNH variants (namely, rs2230641) may be involved in cancer susceptibility. Its role in oestrogen receptor phosphorylation could be of particular significance for DTC, which, as previously noted, is an endocrine tumour 3 times more prevalent in women than in men. Discrepancies with prior studies could therefore be explained on the basis of the specific hormonal involvement on DTC, insignificant for the types of cancer previously evaluated.

XPC codes for a DNA binding protein that, together with RAD23B and centrin 2, forms the distortion-sensing component of NER, thus playing a central role in the process of early damage recognition (16,47). XPC is also involved in DNA damage-induced cell cycle checkpoint regulation and apoptosis, removal of oxidative DNA damage and redox homeostasis (47,48). XPC deficiency has been correlated with decreased DNA repair capacity (48), and hypersensitivity to DNA-oxidizing agents such as X-rays (47), a well-known DTC risk factor, providing the rational basis for a putative involvement of XPC polymorphisms in DTC susceptibility. Notably, multinodular TC was recently reported as the most frequently observed internal tumour in Xeroderma pigmentosum type C patients (49), further substantiating the potential role of XPC in thyroid carcinogenesis. rs2228001 originates an aminoacid substitution in the interaction domain with TFIIH. In silico analysis indicates that rs2228001 may possibly be damaging and in vitro evidence demonstrates differential repair capacity [reviewed in reference (27)]. rs2228000 is located in the interaction domain of XPC with RAD23B and, although its functional significance remains unclear, it is predicted to be benign through in silico analysis (27). It is possible that both these variants, particularly their haplotypes, may alter NER capacity, thereby modulating cancer susceptibility. Despite the numerous case-control studies and meta-analyses that exist, clinical evidence is conflicting and, thus, further studies are warranted.

ERCC5 codes for an endonuclease that exerts its activity at the 3′ side of the damaged strand (16). ERCC5 also plays a structural role, stabilizing the TFIIH complex; in its absence, the CAK complex and the ERCC2 subunit dissociate from the TFIIH core (50). Point mutations in ERCC5 may give rise to Xeroderma pigmentosum and Cockayne syndrome, highlighting its importance for effective DNA repair.

It is possible that NER polymorphisms, through impairing oxidative DNA damage repair, may contribute to DTC development. In addition, it is possible that the pleiotropic actions of some NER proteins (such as CCNH or XPC, demonstrated to be involved in cell cycle regulation, apoptosis or hormone signalling), may convey these specific proteins a relevant role in carcinogenesis, particularly DTC.

Discrepancies from prior studies may have originated from the inherent characteristics of each cancer and respective organ. Divergent genetic background and environmental exposure of study populations may have also contributed. The low statistical power inherent to small sample use may explain some of our negative results. The histology-dependent differences observed for some SNPs could derive from different carcinogenesis pathways (hence, different genetic risk factors) among DTC histological types, as occurs between well-differentiated and anaplastic TC, or, more likely, from small sample size on stratified analysis.

Indeed, the main limitation of our study was sample size; small samples may be underpowered to detect modest effects of low penetrance genes and, on the other hand, may increase the probability that findings are attributable to chance, particularly after stratification (small numbers in the subgroups). The success of more sophisticated statistical analysis, such as haplotype analysis and evaluation of gene-gene and gene-environment interactions, is also limited. Moreover, we cannot exclude the possibility that other variants in linkage disequilibrium with the ones considered here could be responsible for the observed associations.

In conclusion, our study provides, for the first time, insight into the potential role of CCNH, ERCC5, XPC and other NER polymorphisms in DTC susceptibility. Additional studies with larger sample sizes are necessary to validate our findings and to provide conclusive evidence for associations between these and other NER variants and DTC risk. Such studies should be powered to allow for haplotype analysis and evaluation of gene-gene and gene-environment interactions. Functional studies are also warranted, as well as a broader analysis of the involvement of NER variants in DTC progression and therapy response.

Acknowledgements

This study was supported by the Projects PTDC/SAu-OSM/105572/2008 and PTDC/SAu-ESA/102367/2008, Projecto Estratégico N° Pest-E/SAU/UI0009/2011 from Fundação para a Ciência e Tecnologia (FCT).

References

1 

Grubbs EG, Rich TA, Li G, et al: Recent advances in thyroid cancer. Curr Probl Surg. 45:156–250. 2008. View Article : Google Scholar

2 

Dal Maso L, Bosetti C, La Vecchia C and Franceschi S: Risk factors for thyroid cancer: an epidemiological review focused on nutritional factors. Cancer Causes Control. 20:75–86. 2009.PubMed/NCBI

3 

Adjadj E, Schlumberger M and de Vathaire F: Germ-line DNA polymorphisms and susceptibility to differentiated thyroid cancer. Lancet Oncol. 10:181–190. 2009. View Article : Google Scholar : PubMed/NCBI

4 

Gudmundsson J, Sulem P, Gudbjartsson DF, et al: Common variants on 9q22.33 and 14q13.3 predispose to thyroid cancer in European populations. Nat Genet. 41:460–464. 2009. View Article : Google Scholar

5 

Sigurdson AJ, Hauptmann M, Alexander BH, Doody MM, Thomas CB, Struewing JP and Jones IM: DNA damage among thyroid cancer and multiple cancer cases, controls, and long-lived individuals. Mutat Res. 586:173–188. 2005. View Article : Google Scholar : PubMed/NCBI

6 

Hoeijmakers JH: Genome maintenance mechanisms for preventing cancer. Nature. 411:366–374. 2001. View Article : Google Scholar : PubMed/NCBI

7 

Ho T, Li G, Lu J, Zhao C, Wei Q and Sturgis EM: Association of XRCC1 polymorphisms and risk of differentiated thyroid carcinoma: a case-control analysis. Thyroid. 19:129–135. 2009.

8 

Chiang FY, Wu CW, Hsiao PJ, et al: Association between polymorphisms in DNA base excision repair genes XRCC1, APE1, and ADPRT and differentiated thyroid carcinoma. Clin Cancer Res. 14:5919–5924. 2008. View Article : Google Scholar : PubMed/NCBI

9 

Akulevich NM, Saenko VA, Rogounovitch TI, et al: Polymorphisms of DNA damage response genes in radiation-related and sporadic papillary thyroid carcinoma. Endocr Relat Cancer. 16:491–503. 2009. View Article : Google Scholar : PubMed/NCBI

10 

Santos LS, Branco SC, Silva SN, et al: Polymorphisms in base excision repair genes and thyroid cancer risk. Oncol Rep. 28:1859–1868. 2012.PubMed/NCBI

11 

Gomes BC, Silva SN, Azevedo AP, et al: The role of common variants of non-homologous end-joining repair genes XRCC4, LIG4 and Ku80 in thyroid cancer risk. Oncol Rep. 24:1079–1085. 2010.PubMed/NCBI

12 

Xu L, Doan PC, Wei Q, Liu Y, Li G and Sturgis EM: Association of BRCA1 functional single nucleotide polymorphisms with risk of differentiated thyroid carcinoma. Thyroid. 22:35–43. 2012.

13 

Bastos HN, Antão MR, Silva SN, et al: Association of polymorphisms in genes of the homologous recombination DNA repair pathway and thyroid cancer risk. Thyroid. 19:1067–1075. 2009. View Article : Google Scholar : PubMed/NCBI

14 

Gatzidou E, Michailidi C, Tseleni-Balafouta S and Theocharis S: An epitome of DNA repair related genes and mechanisms in thyroid carcinoma. Cancer Lett. 290:139–147. 2010. View Article : Google Scholar : PubMed/NCBI

15 

Silva SN, Gomes BC, Rueff J and Gaspar JF: DNA repair perspectives in thyroid and breast cancer: the role of DNA repair polymorphisms. DNA Repair and Human Health. Vengrova S: InTech; pp. 459–484. 2011

16 

Nouspikel T: DNA repair in mammalian cells: nucleotide excision repair: variations on versatility. Cell Mol Life Sci. 66:994–1009. 2009. View Article : Google Scholar : PubMed/NCBI

17 

Silva SN, Gil OM, Oliveira VC, et al: Association of polymorphisms in ERCC2 gene with non-familial thyroid cancer risk. Cancer Epidemiol Biomarkers Prev. 14:2407–2412. 2005.PubMed/NCBI

18 

Zhao H, Wang LE, Li D, Chamberlain RM, Sturgis EM and Wei Q: Genotypes and haplotypes of ERCC1 and ERCC2/XPD genes predict levels of benzo[α]pyrene diol epoxide-induced DNA adducts in cultured primary lymphocytes from healthy individuals: a genotype-phenotype correlation analysis. Carcinogenesis. 29:1560–1566. 2008.

19 

Yu T, Liu Y, Lu X, et al: Excision repair of BPDE-adducts in human lymphocytes: diminished capacity associated with ERCC1 C8092A (rs3212986) polymorphism. Arch Toxicol. 87:699–709. 2013. View Article : Google Scholar : PubMed/NCBI

20 

Pingarilho M, Oliveira NG, Martins C, Fernandes AS, de Lima JP, Rueff J and Gaspar JF: Genetic polymorphisms in detoxification and DNA repair genes and susceptibility to glycidamide-induced DNA damage. J Toxicol Environ Health A. 75:920–933. 2012. View Article : Google Scholar : PubMed/NCBI

21 

Lange K, Cantor R, Horvath S, Perola M, Sabatti C, Sinsheimer J and Sobel E: Mendel version 4.0: a complete package for the exact genetic analysis of discrete traits in pedigree and population data sets. Am J Hum Genet. 69:A18862001.

22 

Pan J, Lin J, Izzo JG, et al: Genetic susceptibility to esophageal cancer: the role of the nucleotide excision repair pathway. Carcinogenesis. 30:785–792. 2009. View Article : Google Scholar : PubMed/NCBI

23 

Wu X, Gu J, Grossman HB, et al: Bladder cancer predisposition: a multigenic approach to DNA-repair and cell-cycle-control genes. Am J Hum Genet. 78:464–479. 2006. View Article : Google Scholar

24 

Lin J, Pu X, Wang W, Matin S, Tannir NM, Wood CG and Wu X: Case-control analysis of nucleotide excision repair pathway and the risk of renal cell carcinoma. Carcinogenesis. 29:2112–2119. 2008. View Article : Google Scholar : PubMed/NCBI

25 

Enjuanes A, Benavente Y, Bosch F, et al: Genetic variants in apoptosis and immunoregulation-related genes are associated with risk of chronic lymphocytic leukemia. Cancer Res. 68:10178–10186. 2008. View Article : Google Scholar : PubMed/NCBI

26 

Chen M, Kamat AM, Huang M, et al: High-order interactions among genetic polymorphisms in nucleotide excision repair pathway genes and smoking in modulating bladder cancer risk. Carcinogenesis. 28:2160–2165. 2007. View Article : Google Scholar

27 

Francisco G, Menezes PR, Eluf-Neto J and Chammas R: XPC polymorphisms play a role in tissue-specific carcinogenesis: a meta-analysis. Eur J Hum Genet. 16:724–734. 2008. View Article : Google Scholar : PubMed/NCBI

28 

Qiu L and Wang Z, Shi X and Wang Z: Associations between XPC polymorphisms and risk of cancers: a meta-analysis. Eur J Cancer. 44:2241–2253. 2008. View Article : Google Scholar : PubMed/NCBI

29 

He J, Shi TY, Zhu ML, Wang MY, Li QX and Wei QY: Associations of Lys939Gln and Ala499Val polymorphisms of the XPC gene with cancer susceptibility: a meta-analysis. Int J Cancer. Feb 7–2013.(Epub ahead of print). View Article : Google Scholar

30 

Zhang D, Chen C, Fu X, et al: A meta-analysis of DNA repair gene XPC polymorphisms and cancer risk. J Hum Genet. 53:18–33. 2008. View Article : Google Scholar : PubMed/NCBI

31 

Stern MC, Lin J, Figueroa JD, et al: Polymorphisms in DNA repair genes, smoking, and bladder cancer risk: findings from the international consortium of bladder cancer. Cancer Res. 69:6857–6864. 2009. View Article : Google Scholar : PubMed/NCBI

32 

Zheng W, Cong XF, Cai WH, Yang S, Mao C and Zou HW: Current evidences on XPC polymorphisms and breast cancer susceptibility: a meta-analysis. Breast Cancer Res Treat. 128:811–815. 2011. View Article : Google Scholar : PubMed/NCBI

33 

Liu C, Yin Q, Hu J, Li L, Zhang Y and Wang Y: A meta-analysis of evidences on XPC polymorphisms and lung cancer susceptibility. Tumor Biol. 34:1205–1213. 2013. View Article : Google Scholar : PubMed/NCBI

34 

D’Amelio AM, Monroy C, El-Zein R and Etzel CJ: Using haplotype analysis to elucidate significant associations between genes and Hodgkin lymphoma. Leuk Res. 36:1359–1364. 2012.PubMed/NCBI

35 

Bai Y, Xu L, Yang X, et al: Sequence variations in DNA repair gene XPC is associated with lung cancer risk in a Chinese population: a case-control study. BMC Cancer. 7:812007.PubMed/NCBI

36 

Abbasi R, Ramroth H, Becher H, Dietz A, Schmezer P and Popanda O: Laryngeal cancer risk associated with smoking and alcohol consumption is modified by genetic polymorphisms in ERCC5, ERCC6 and RAD23B but not by polymorphisms in five other nucleotide excision repair genes. Int J Cancer. 125:1431–1439. 2009. View Article : Google Scholar : PubMed/NCBI

37 

Hussain SK, Mu LN, Cai L, et al: Genetic variation in immune regulation and DNA repair pathways and stomach cancer in China. Cancer Epidemiol Biomarkers Prev. 18:2304–2309. 2009. View Article : Google Scholar : PubMed/NCBI

38 

Li Y, Gu S, Wu Q, et al: No association of ERCC1 C8092A and T19007C polymorphisms to cancer risk: a meta-analysis. Eur J Hum Genet. 15:967–973. 2007.

39 

Shi TY, He J, Qiu LX, et al: Association between XPF polymorphisms and cancer risk: a meta-analysis. PLoS One. 7:e386062012.PubMed/NCBI

40 

Zhang L, Wang J, Xu L, et al: Nucleotide excision repair gene ERCC1 polymorphisms contribute to cancer susceptibility: a meta-analysis. Mutagenesis. 27:67–76. 2012.

41 

Zhu ML, Wang M, Cao ZG, et al: Association between the ERCC5 Asp1104His polymorphism and cancer risk: a meta-analysis. PLoS One. 7:e362932012.

42 

Hung RJ, Christiani DC, Risch A, et al: International Lung Cancer Consortium: pooled analysis of sequence variants in DNA repair and cell cycle pathways. Cancer Epidemiol Biomarkers Prev. 17:3081–3089. 2008. View Article : Google Scholar : PubMed/NCBI

43 

Ding DP, He XF and Zhang Y: Lack of association between XPG Asp1104His and XPF Arg415Gln polymorphism and breast cancer risk: a meta-analysis of case-control studies. Breast Cancer Res Treat. 129:203–209. 2011. View Article : Google Scholar : PubMed/NCBI

44 

Jeon S, Choi JY, Lee KM, et al: Combined genetic effect of CDK7 and ESR1 polymorphisms on breast cancer. Breast Cancer Res Treat. 121:737–742. 2010.

45 

Wheless L, Kistner-Griffin E, Jorgensen TJ, et al: A community-based study of nucleotide excision repair polymorphisms in relation to the risk of non-melanoma skin cancer. J Invest Dermatol. 132:1354–1362. 2012. View Article : Google Scholar : PubMed/NCBI

46 

Lolli G and Johnson LN: CAK-cyclin-dependent activating kinase: a key kinase in cell cycle control and a target for drugs? Cell Cycle. 4:572–577. 2005. View Article : Google Scholar : PubMed/NCBI

47 

Melis JP, Luijten M, Mullenders LH and van Steeg H: The role of XPC: implications in cancer and oxidative DNA damage. Mutat Res. 728:107–117. 2011. View Article : Google Scholar : PubMed/NCBI

48 

Chen Z, Yang J, Wang G, Song B, Li J and Xu Z: Attenuated expression of xeroderma pigmentosum group C is associated with critical events in human bladder cancer carcinogenesis and progression. Cancer Res. 67:4578–4585. 2007. View Article : Google Scholar : PubMed/NCBI

49 

Hadj-Rabia S, Oriot D, Soufir N, et al: Unexpected extradermatological findings in 31 patients with xeroderma pigmentosum type C. Br J Dermatol. 168:1109–1113. 2013. View Article : Google Scholar : PubMed/NCBI

50 

Ito S, Kuraoka I, Chymkowitch P, et al: XPG stabilizes TFIIH, allowing transactivation of nuclear receptors: implications for Cockayne syndrome in XP-G/CS patients. Mol Cell. 26:231–243. 2007. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

November 2013
Volume 30 Issue 5

Print ISSN: 1021-335X
Online ISSN:1791-2431

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Santos LS, Gomes BC, Gouveia R, Silva SN, Azevedo AP, Camacho V, Manita I, Gil OM, Ferreira TC, Limbert E, Limbert E, et al: The role of CCNH Val270Ala (rs2230641) and other nucleotide excision repair polymorphisms in individual susceptibility to well-differentiated thyroid cancer. Oncol Rep 30: 2458-2466, 2013
APA
Santos, L.S., Gomes, B.C., Gouveia, R., Silva, S.N., Azevedo, A.P., Camacho, V. ... Gaspar, J.F. (2013). The role of CCNH Val270Ala (rs2230641) and other nucleotide excision repair polymorphisms in individual susceptibility to well-differentiated thyroid cancer. Oncology Reports, 30, 2458-2466. https://doi.org/10.3892/or.2013.2702
MLA
Santos, L. S., Gomes, B. C., Gouveia, R., Silva, S. N., Azevedo, A. P., Camacho, V., Manita, I., Gil, O. M., Ferreira, T. C., Limbert, E., Rueff, J., Gaspar, J. F."The role of CCNH Val270Ala (rs2230641) and other nucleotide excision repair polymorphisms in individual susceptibility to well-differentiated thyroid cancer". Oncology Reports 30.5 (2013): 2458-2466.
Chicago
Santos, L. S., Gomes, B. C., Gouveia, R., Silva, S. N., Azevedo, A. P., Camacho, V., Manita, I., Gil, O. M., Ferreira, T. C., Limbert, E., Rueff, J., Gaspar, J. F."The role of CCNH Val270Ala (rs2230641) and other nucleotide excision repair polymorphisms in individual susceptibility to well-differentiated thyroid cancer". Oncology Reports 30, no. 5 (2013): 2458-2466. https://doi.org/10.3892/or.2013.2702