Purpose: Human DNA glycosylases NEIL1 and NEIL2 participate in oxidized base excision repair and protect cells from DNA damage. NEIL1 (MIM:608844) and NEIL2 (MIM:608933) variants may affect their protein functions, leading to altered cell death and carcinogenesis. To date, only one reported study has investigated the association between NEIL1 and NEIL2 polymorphisms and cancer risk.

Experimental Design: Genotype and haplotypes of the NEIL1 NT_010194.16:g.46434077G>T (rs7182283) and g.46438282C>G (rs4462560) and NEIL2 NT_077531.3:g.4102971C>G (rs804270) polymorphisms were determined for 872 patients with newly diagnosed squamous cell carcinomas of the oral cavity and oropharynx (SCCOOP) and 1,044 cancer-free non–Hispanic white control subjects frequency-matched by age and sex. Crude and adjusted odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using multivariate logistic regression, and false-positive report probabilities were also calculated.

Results: We found no overall differences in the frequencies of alleles, genotypes, and haplotypes of NEIL1 g.46434077G>T and NEIL1 g.46438282C>G polymorphisms between cases and controls. However, the NEIL2 g.4102971CC genotype was associated with a significantly increased risk of SCCOOP (adjusted OR, 1.30; 95% CI, 1.02-1.65); this increase in risk was the highest among current alcohol drinkers (adjusted OR, 1.87; 95% CI, 1.28-2.72), particularly in patients with oropharyngeal cancer (adjusted OR, 1.35; 95% CI, 1.04-1.76). The NEIL2 g.4102971CC genotype was also significantly associated with SCCOOP of advanced stages.

Conclusions: Polymorphisms of the NEIL2 gene may be markers for risk and progression of SCCOOP, particularly in patients with oropharyngeal cancer. Larger studies are needed to confirm our findings.

Head and neck cancers are the sixth most common cancers, with a prevalence of >1.6 million cases worldwide (1). They account for ∼2.8% of all malignancies in the United States (1, 2). Despite a slight decrease in its incidence rate (∼4% since 1980) and a modest improvement in 5-year survival (from 54.4% to 59.4% over the last 20 years), these cancers continue to be a clinical challenge (1, 2).

The squamous cell carcinomas of the oral cavity and oropharynx (SCCOOP) are an etiologically similar subgroup of head and neck cancers, and it is estimated that 34,360 new cases of SCCOOP and 7,550 deaths from it will have occurred in the United States alone in 2007 (2, 3). Even with the use of modern therapeutic options such as surgical management, radiation treatment, and chemotherapeutic intervention, ∼50% of all patients will ultimately die of this disease, especially for those patients who were diagnosed with advanced or relapsed disease, which is almost uniformly fatal (2).

The importance of an individual's lifestyle, particularly the use of tobacco and alcohol, has been well recognized in the etiology of SCCOOP. However, despite these risk factors, relatively few people actually develop these diseases; likewise, some individuals develop SCCOOP in the absence of such habits or other identifiable lifestyle and environmental factors. In this case, genetic susceptibility may play a role in the initiation and development of SCCOOP. For instance, genetically determined DNA repair capacity may contribute to the variation in susceptibility to head and neck cancers (46). Identifying genetic factors that modulate the risk of SCCOOP will thus likely help determine at-risk subgroups that can benefit from primary prevention programs.

DNA repair systems play an important role in the maintenance of genomic integrity and stability in response to environmental exposure, replication errors, and cumulative effects of aging. In humans, more than 100 genes are involved in the five major DNA repair pathways: direct reversal, basal excision repair, nucleotide excision repair, mismatch repair, and recombination repair (7). Nucleotide excision repair targets bulky, helix-distorting adducts, such as the benzo(a)pyrene-guanine adduct, whereas basal excision repair removes smaller altered bases produced by oxidation, methylation, radiation, and other minor base modifications (8). In a series of association studies, we found that variants in genes involved in both basal excision repair and nucleotide excision repair contributed to an individual's susceptibility to head and neck cancers (913).

In mammalian cells, the repair of DNA bases that have been damaged by reactive oxygen species is initiated primarily by a series of DNA glycosylases, including two that belong to a class of DNA glycosylases homologous to the bacterial Fpg/Nei family, NEIL1 (nei endonuclease VIII-like 1) and NEIL2 (nei-like 2). These glycosylases initiate the first step in basal excision repair by cleaving bases damaged by reactive oxygen species and introducing a DNA strand break via the associated lyase reaction (1417). NEIL1 and NEIL2 protect cells from radiation-mediated cell death, and functional variants of NEIL1 and NEIL2 may affect the protein functions, leading to altered cell-death probability and carcinogenesis potential.

The human NEIL1 gene is located on chromosome 15q23, and mutations in NEIL1 have been shown to cause increased risk of developing primary gastric cancer in a Japanese cohort (18). NEIL1 has been resequenced by the National Institute of Environmental Health Sciences Environmental Genome Project,4

and at least 62 single nucleotide polymorphisms (SNP)5 have been reported; four of those are nonsynonymous SNPs: p.Ser82Cys, p.Gly83Asp, p.Cys136Arg, and p.Asp252Asn, with very low minor allele frequencies (all = 0.01).6 Two of those polymorphic variants, p.Ser82Cys and p.Asp252Asn, showed near wild-type enzyme specificity and kinetics, whereas p.Gly83Asp was devoid of glycosylase activity and p.Cys136Arg may be glycosylase-deficient (19). NEIL2 is located on chromosome 8p23.1, and at least 250 SNPs in this gene are reported in the dbSNP database.7 Four of these SNPs were confirmed as nonsynonymous SNPs (p.Thr70Ser, p.Arg103Gln, p.Arg257Leu, and p.Pro304Thr) in the National Institute of Environmental Health Sciences Environmental Genome Project SNP database,8 and an additional one, P123T, was reported recently (20). All these nonsynonymous SNPs have rarely been found in both healthy control participants and patients with colon cancer (20).

To date, no reports have been published about the possible association between variants of NEIL1 and NEIL2 genes, and the risk of head and neck cancers. Because of the role of the NEIL1 and NEIL2 genes in regulating DNA repair and because decreased DNA repair capacity has been associated with increased risk of head and neck cancers, we hypothesized that NEIL1 and NEIL2 polymorphisms contribute to genetic susceptibility to SCCOOP. To test this hypothesis, we conducted a hospital-based case-control study to identify associations between SCCOOP and newly reported common (i.e., with a minor allele frequency of ≥ 0.05) functional SNPs of the NEIL1 gene, NT_010194.16:g.46434077 (rs7182283) and NT_010194.16:g.46438282 (rs4462560), and the NEIL2 gene, g.4102971 (rs804270).

Study subjects and data collection. The recruitment of our study participants has been previously described (21, 22). Briefly, the study population consisted of 872 patients with SCCOOP and 1,044 cancer-free control participants recruited from May 1, 1995 to September 30, 2006. All patients had newly diagnosed, untreated SCCOOP that was histologically confirmed at The University of Texas M.D. Anderson Cancer Center. Twenty-four percent of all patients with SCCOOP were eligible, and 90% of the eligible patients contacted chose to participate in this study. Only non–Hispanic white patients were included in the final analysis because genotype frequencies can vary between ethnic groups and relatively few minority patients were seen at M.D. Anderson. Among the 872 SCCOOP patients with primary tumors included in the analysis, 299 (34.3%) had cancers of the oral cavity and 573 (65.7%) had cancers of the oropharynx. Patients with secondary oral cavity and oropharyngeal tumors; primary tumors of the hypopharynx, nasopharynx, or sinonasal tract; primary tumors outside the upper aerodigestive tract; cervical metastases of unknown origin; or histopathologic diagnoses other than SCCOOP were excluded from the analysis.

The regional lymph node involvement of SCCOOP was defined as N0 to N3 as follows (23): N0, no regional node metastasis; N1, metastasis in a single ipsilateral lymph node, ≤3 cm in the greatest dimension; N2, metastasis in a single ipsilateral lymph node, >3 cm but <6 cm in the greatest dimension; or in multiple ipsilateral lymph nodes, none ≥6 cm in the greatest dimension; or in any bilateral or contralateral lymph node, <6 cm in the greatest dimension; N3, metastasis in any lymph node, ≥6 cm in the greatest dimension. The extent of the primary SCCOOP was defined as T1 to T4 as follows: T1, tumor ≤2 cm at the greatest dimension; T2, tumor >2 cm but <4 cm in the greatest dimension; T3, tumor ≥4 cm in the greatest dimension; T4, tumor invading adjacent structures.

Cancer-free control participants were recruited from persons who were not hospital patients or seeking health care but who had accompanied the case patients visiting the clinics; controls could not be genetically related to any cases or controls already selected. We first surveyed potential control participants at the clinics by using a short questionnaire to determine their willingness to participate in our research studies and to obtain information about demographic features, smoking and alcohol drinking status (current, former, or never), and personal history of cancer. Our control participants were required to have no previous history of cancer and were not under medical care or receiving treatment for any known disease. They were frequency-matched to the case patients by age (±5 years) and sex. Among the visitors to our institution who were screened for possible participation as controls, 73% were eligible for and were therefore offered participation. Of these eligible potential controls, 85% agreed to and ultimately did participate. We interviewed each enrolled control subject to obtain data about their personal history of exposure to known etiologic factors in SCCOOP, such as tobacco smoking and alcohol use. After signing the informed consent form, each participant donated 30 mL of blood, of which 1 mL was used for genomic DNA extraction. The protocol for this research study was approved by the M.D. Anderson Cancer Center Institutional Review Board.

Genotyping. We extracted genomic DNA from the buffy coat fraction of the blood samples by using a blood DNA mini kit (Qiagen, Inc.) according to the manufacturer's instructions. The selected NEIL1 and NEIL2 polymorphisms were determined using the PCR-RFLP method, as previously described (21). We did the PCRs with a PTC-200 DNA engine (Peltier Thermal Cycler, MJ Research, Inc.) in 10 μL of PCR mixture. This PCR mixture included ∼20 ng of genomic DNA, 0.1 mmol/L of deoxynucleotide triphosphate, and 1× PCR buffer (50 mmol/L KCl, 10 mmol/L Tris-HCl, and 0.1% Triton X-100); 1.5 mmol/L of MgCl2, 0.5 units of Taq polymerase (Denville Scientific, Inc.); and 2 pmol of each primer. The following primers were used to amplify the target fragments containing these four polymorphisms (mismatch bases are underlined): 5′-CAACCTCCTGATTAACTGGAACCACA-3′ (forward) and 5′-TCACTTCAGCCCAGGAGACCAG-3′ (reverse) for NEIL1 NT_010194.16:g.46434077G>T (rs7182283); 5′-GTCTCTTCACTGGCTTTTGGGG-3′ (forward) and 5′-TCCCAGGTATTTGGTGGGTAGG-3′ (reverse) for NEIL1 NT_010194.16:g.46438282C>G (rs4462560); and 5′-ACCCCCCACCTCGGGCACTCGG-3′ (forward) and 5′-AAGATGCCGCGCCCACCCGC-3′ (reverse) for NEIL2 NT_077531.3:g.4102971C>G (rs804270). There were 119-bp, 118-bp, and 131-bp–amplified PCR products for the NEIL1 g.46434077, NEIL1 g.46438282, and NEIL2 g.4102971 polymorphisms, respectively. The NlaIII, HaeIII, and SacII restriction enzymes (New England Biolabs) were used to distinguish the NEIL1 g.46434077, NEIL1 g.46438282, and NEIL2 g.4102971 polymorphisms, respectively, which resulted in 91-bp and 28-bp fragments in the presence of the NEIL1 g.46434077T allele; 96-bp and 22-bp fragments in the presence of the NEIL1 g.46438282C allele; and 112-bp and 19-bp fragments in the presence of the NEIL2 g.4102971C allele. More than 10% of the samples were randomly selected for confirmation, and the results were 100% concordant.

Statistical analysis. The χ2 test was used to evaluate differences between cases and controls in the frequency distributions of selected demographic variables, smoking status, alcohol use, and each allele and genotype of the three NEIL1 and NEIL2 polymorphisms. Unconditional univariate and multivariate logistic regression analyses were done to obtain the crude and adjusted odds ratios (OR) and their 95% confidence intervals (CI) for cancer risk, assuming a genetic recessive model. Multivariate adjustment was conditional on the effect of age, sex, smoking status, and alcohol use. Subjects who had smoked more than 100 cigarettes in their lifetimes were categorized as ever smokers, and others were never smokers. Ever smokers who had quit smoking >1 year previously (prior to disease diagnosis for the cases and before the time the questionnaire was administered for the controls) were categorized as former smokers, and the other smokers were categorized as current smokers. Similarly, subjects who had drunk alcoholic beverages at least once a week for >1 year previously were categorized as ever drinkers, and others were never drinkers. Ever drinkers who had quit drinking >1 year previously were categorized as former drinkers, and the other drinkers were categorized as current drinkers. We further stratified the genotype data by subgroups of age, sex, smoking, alcohol drinking, and tumor site and assessed any trend in risk in multivariate logistic regression models. Hardy-Weinberg equilibrium of the NEIL1 and NEIL2 genotypes was tested by performing a goodness-of-fit χ2 test. The linkage disequilibrium D′ value, logarithm of odds score, and r2 value were computed for two-locus models. We estimated NEIL1 haplotypes using unphased genotypes. The haplotype of the highest frequency was used as the reference group to calculate ORs for haplotypes associated with SCCOOP. Logistic regression was used to evaluate the association between the SCCOOP and NEIL1 haplotypes. Haplotypes were reconstructed using PHASE version 2 software (24).9

We used the false-positive report probability (FPRP) to test for false-positive associations (25). For all significant genetic effects observed in our study, we calculated FPRP with prior probabilities of 0.0001, 0.001, 0.01, 0.1, and 0.25. The OR was set close to the observed value obtained in our study, and a probability of <0.2 was considered noteworthy. We analyzed our data by using SAS software (Version 8e; SAS Institute, Inc.); P < 0.05 was considered statistically significant, and all statistical tests were two-sided.

Characteristics of nongenetic risk factors for SCCOOP in the study population. The frequency distributions of selected characteristics of the cases and controls are presented in Table 1. The cases and controls were well-matched for age and sex, with a mean age of 56.5 years for the cases (±11.2 years; range, 18-85 years) and 56.4 years for the controls (±11.0 years; range, 20-85 years; P = 0.975); there was also no difference in the distribution of age groups (≤50, 51-64, and ≥65) nor in sex groups between the case and control groups, with men constituting 77.2% of patients and 76.8% of controls (P = 0.853). However, there were more current smokers (33.6%) and current drinkers (51.7%) among the cases than among the controls (15.3% and 40.7%, respectively), and these differences were statistically significant (P < 0.001). There was an increased risk of SCCOOP in former and current smokers (OR, 1.62; 95% CI, 1.31-2.01 and OR, 3.55; 95% CI, 2.78-4.53, respectively) and in former or current alcohol drinkers (OR, 2.06; 95% CI, 1.59-2.68, and OR, 2.01; 95% CI, 1.64-2.47, respectively) compared with nonsmokers and nondrinkers, respectively (Table 1). Therefore, we made further adjustment for these covariates in the multivariate logistic regression analysis.

Table 1.

Characteristics and ORs of covariate variables in the study

VariableCases, n = 872 (%)Controls, n = 1,044 (%)OR*P
Mean age (±SD) 56.5 (±11.2) 56.4 (±11.0)  0.975 
Age (y)     
    ≤50 245 (28.1) 303 (29.0) Reference 0.898 
    51-64 410 (47.0) 487 (46.7) 1.04 (0.84-1.29)  
    ≥65 217 (24.9) 254 (24.3) 1.06 (0.83-1.35)  
Gender     
    Female 199 (22.8) 242 (23.2) Reference 0.853 
    Male 673 (77.2) 802 (76.8) 1.02 (0.82-1.26)  
Smoking status     
    Never 259 (29.7) 502 (48.1) Reference <0.001 
    Former 320 (36.7) 382 (36.6) 1.62 (1.31-2.01)  
    Current 293 (33.6) 160 (15.3) 3.55 (2.78-4.53)  
Alcohol use     
    Never 238 (27.3) 451 (43.2) Reference <0.001 
    Former 183 (21.0) 168 (16.1) 2.06 (1.59-2.68)  
    Current 451 (51.7) 425 (40.7) 2.01 (1.64-2.47)  
Tumor site     
    Oral cavity 299 (34.3)    
    Oropharynx 573 (65.7)    
VariableCases, n = 872 (%)Controls, n = 1,044 (%)OR*P
Mean age (±SD) 56.5 (±11.2) 56.4 (±11.0)  0.975 
Age (y)     
    ≤50 245 (28.1) 303 (29.0) Reference 0.898 
    51-64 410 (47.0) 487 (46.7) 1.04 (0.84-1.29)  
    ≥65 217 (24.9) 254 (24.3) 1.06 (0.83-1.35)  
Gender     
    Female 199 (22.8) 242 (23.2) Reference 0.853 
    Male 673 (77.2) 802 (76.8) 1.02 (0.82-1.26)  
Smoking status     
    Never 259 (29.7) 502 (48.1) Reference <0.001 
    Former 320 (36.7) 382 (36.6) 1.62 (1.31-2.01)  
    Current 293 (33.6) 160 (15.3) 3.55 (2.78-4.53)  
Alcohol use     
    Never 238 (27.3) 451 (43.2) Reference <0.001 
    Former 183 (21.0) 168 (16.1) 2.06 (1.59-2.68)  
    Current 451 (51.7) 425 (40.7) 2.01 (1.64-2.47)  
Tumor site     
    Oral cavity 299 (34.3)    
    Oropharynx 573 (65.7)    
*

Odds ratio was calculated for categorical variables of age, gender, smoking, and alcohol use.

P value is from the χ2 test for categorical variables. The P value for mean age was from the Wilcoxon rank test.

Mean (±SD) of variable age.

Allele and genotype distributions of the NEIL1 and NEIL2 polymorphisms among the cases and controls. As shown in Table 2, the frequencies of minor alleles of NEIL1 g.46434077T and g.46438282G, and NEIL2 g.4102971C were 47.2%, 31.5%, and 44.4%, respectively, for the cases and 46.4%, 31.8%, and 43.0%, respectively, for the controls, but none of the differences between the cases and controls were statistically significant (P = 0.611, 0.809, and 0.359, respectively). All distributions of the frequencies of observed genotypes in the controls were consistent with those obtained from the Hardy-Weinberg equilibrium model (P > 0.05). The NEIL1 g.46434077TT genotype was more frequent in the cases (22.3%) than in the controls (20.6%) but was not associated with risk of SCCOOP compared with either the GG genotype (OR, 0.99; 95% CI, 0.76-1.29) or the combined GG + GT genotypes (OR, 1.03; 95% CI, 0.82-1.29). The NEIL1 g.46438282GG genotype was less frequent in the cases (8.9%) than in the controls (9.5%), and similarly was not associated with risk of SCCOOP compared with either the CC genotype (OR, 0.99; 95% CI, 0.71-1.39) or the combined CC + CG genotypes (OR, 0.97; 95% CI, 0.70-1.34). The NEIL2 g.4102971CC genotype was more frequent in the cases (20.7%) than in the controls (17.1%), and although this genotype was not associated with risk of SCCOOP compared with the NEIL2 g.4102971GG genotype (adjusted OR, 1.18; 95% CI, 0.90-1.56), it was associated with a significant elevation in risk when compared with the combined GG + CG genotypes (OR, 1.30; 95% CI, 1.02-1.65; P < 0.05, assuming a recessive genetic model).

Table 2.

Genotype frequencies and ORs of NEIL1 g.46434077 and g.46438282 and NEIL2 g.4102971 variants among SCCOOP cases and controls in a non–Hispanic white population

SNPCases, n (%)Controls, n (%)Crude ORAdjusted OR*P
NEIL1 g.46434077G>T      
    GG 243 (28.0) 291 (27.9) Reference Reference 0.624 
    GT 432 (49.7) 537 (51.5) 0.96 (0.78-1.19) 0.94 (0.76-1.17)  
    TT 194 (22.3) 215 (20.6) 1.08 (0.83-1.4) 0.99 (0.76-1.29)  
    GG + GT 675 (77.7) 828 (79.4) Reference Reference 0.364 
    TT 194 (22.3) 215 (20.6) 1.11 (0.89-1.38) 1.03 (0.82-1.29)  
T allele 820 (47.2) 967 (46.4)   0.611 
NEIL1 g.46438282C>G§      
    CC 392 (46.0) 477 (45.8) Reference Reference 0.902 
    CG 385 (45.1) 465 (44.7) 1.01 (0.83-1.22) 1.05 (0.87-1.28)  
    GG 76 (8.9) 99 (9.5) 0.93 (0.67-1.3) 0.99 (0.71-1.39)  
    CC + CG 777 (91.1) 942 (90.5) Reference Reference 0.656 
    GG 76 (8.9) 99 (9.5) 0.93 (0.68-1.27) 0.97 (0.70-1.34)  
    G allele 537 (31.5) 663 (31.8)   0.809 
NEIL2 g.4102971G>C      
    GG 273 (31.9) 322 (31.1) Reference Reference 0.069 
    CG 405 (47.4) 538 (51.9) 0.89 (0.72-1.09) 0.86 (0.69-1.06)  
    CC 177 (20.7) 177 (17.1) 1.18 (0.91-1.54) 1.18 (0.90-1.56)  
    GG + CG 678 (79.3) 860 (82.9) Reference Reference 0.044 
    CC 177 (20.7) 177 (17.1) 1.27 (1.01-1.6) 1.30 (1.02-1.65)  
    C allele 759 (44.4) 892 (43.0)   0.359 
SNPCases, n (%)Controls, n (%)Crude ORAdjusted OR*P
NEIL1 g.46434077G>T      
    GG 243 (28.0) 291 (27.9) Reference Reference 0.624 
    GT 432 (49.7) 537 (51.5) 0.96 (0.78-1.19) 0.94 (0.76-1.17)  
    TT 194 (22.3) 215 (20.6) 1.08 (0.83-1.4) 0.99 (0.76-1.29)  
    GG + GT 675 (77.7) 828 (79.4) Reference Reference 0.364 
    TT 194 (22.3) 215 (20.6) 1.11 (0.89-1.38) 1.03 (0.82-1.29)  
T allele 820 (47.2) 967 (46.4)   0.611 
NEIL1 g.46438282C>G§      
    CC 392 (46.0) 477 (45.8) Reference Reference 0.902 
    CG 385 (45.1) 465 (44.7) 1.01 (0.83-1.22) 1.05 (0.87-1.28)  
    GG 76 (8.9) 99 (9.5) 0.93 (0.67-1.3) 0.99 (0.71-1.39)  
    CC + CG 777 (91.1) 942 (90.5) Reference Reference 0.656 
    GG 76 (8.9) 99 (9.5) 0.93 (0.68-1.27) 0.97 (0.70-1.34)  
    G allele 537 (31.5) 663 (31.8)   0.809 
NEIL2 g.4102971G>C      
    GG 273 (31.9) 322 (31.1) Reference Reference 0.069 
    CG 405 (47.4) 538 (51.9) 0.89 (0.72-1.09) 0.86 (0.69-1.06)  
    CC 177 (20.7) 177 (17.1) 1.18 (0.91-1.54) 1.18 (0.90-1.56)  
    GG + CG 678 (79.3) 860 (82.9) Reference Reference 0.044 
    CC 177 (20.7) 177 (17.1) 1.27 (1.01-1.6) 1.30 (1.02-1.65)  
    C allele 759 (44.4) 892 (43.0)   0.359 
*

Adjusted OR: adjusted for age, gender, smoking, and alcohol use.

P value is from the χ2 test for the frequency distribution of genotypes in each SNP.

NEIL1 g.46434077G>T: missing genotype information in three cases and one control.

§

NEIL1 g.46438282C>G: missing genotype information in 19 cases and 3 controls.

NEIL2 g.4102971G>C: missing genotype information in 17 cases and 7 controls.

Association between the combined genotypes and haplotype of the NEIL1 gene and the risk of SCCOOP. Further analysis suggested that there was a linkage disequilibrium between the two NEIL1 polymorphisms (D′ = 1.0, r2 = 0.304, and P < 0.001). Because the haplotype preserves the joint linkage disequilibrium structure, we reconstructed haplotypes using the unphased genotypes based on the observed NEIL1 g.46434077 and g.46438282 genotypes to further assess their association with risk of SCCOOP. There were four haplotypes: TC, GG, GC, and TG; haplotype TC was the most common (occurring in 43.02% of the cases and in 43.44% of the controls) and haplotype TG was the least frequent, with a frequency of <5% in both cases and controls. The frequency distributions of these four haplotypes were comparable between cases and controls (χ2 test, P = 0.87). Therefore, neither the genotypes nor haplotypes of NEIL1 g.46434077 and NEIL1 g.46438282 were associated with the risk of SCCOOP (data not shown).

Stratified analysis of the associations between NEIL1 and NEIL2 polymorphisms and the risk of SCCOOP. We further stratified the data by age, sex, smoking status, alcohol drinking status, and cancer site. To facilitate the analysis, we evaluated the risk of SCCOOP by estimating the ORs associated with the combined NEIL1 g.46434077 (GG + GT), NEIL1 g.46438282 (CC + CG), and NEIL2 g.4102971 (GG + CG) genotypes compared with their homozygous genotypes (NEIL1 g.46434077TT, NEIL1 g.46438282GG, and NEIL2 g.4102971CC, respectively), with adjustment for the aforementioned variables. As shown in Table 3, although none of the genotypes of the NIEL1 gene were associated with cancer risk in all subgroups examined, the OR was virtually always elevated (except for former alcohol drinkers), sometimes significantly so, for the CC genotype of NEIL2 g.4102971 compared with the combined GG + CG genotypes. In former smokers and current drinkers, the ORs for the CC genotype of NEIL2 g.4102971 were 1.51 (95% CI, 1.03-2.23; P = 0.082) and 1.87 (95% CI, 1.28-2.72; P = 0.003), respectively, compared with either the GG or CG genotype, and this risk was more evident for oropharynx (OR, 1.35; 95% CI, 1.04-1.76; P = 0.02) than for oral cavity (OR, 1.19; 95% CI, 0.83-1.69; P = 0.545), although this difference was not statistically significant (data not shown).

Table 3.

ORs of SCCOOP associated with genotypes in the stratified analysis

Stratified variablesCases/controls (n)*NEIL1 g.46434077G > T
PCases/controls (n)§NEIL1 g.46438282C > G
PCases/controls (n)NEIL2 g.4102971G > C
P
Cases/controls (%)
Adjusted OR (95% CI)
Cases/controls (%)
Adjusted OR (95% CI)
Cases/controls (%)
Adjusted OR (95% CI)
TTTT vs. GG + GTGGGG vs. CC + CGCCCC vs. CG + GG
Age             
    ≤50 243/303 21.0/20.5 0.98 (0.64-1.50) 0.88 237/303 10.5/7.6 1.47 (0.80-2.68) 0.231 236/301 19.9/16.9 1.25 (0.80-1.95) 0.376 
    51 to 64 409/487 24.0/20.5 1.06 (0.75-1.48) 0.218 404/485 9.7/11.1 0.89 (0.56-1.42) 0.473 404/484 20.8/18.2 1.27 (0.90-1.81) 0.327 
    ≥65 217/253 20.7/20.9 0.92 (0.58-1.46) 0.955 212/253 5.7/8.7 0.63 (0.30-1.32) 0.211 215/252 21.4/15.1 1.40 (0.85-2.28) 0.077 
Gender             
    Male 671/801 23.4/20.5 1.11 (0.86-1.43) 0.176 662/800 8.6/9.1 1.00 (0.69-1.45) 0.731 659/797 21.1/17.8 1.27 (0.97-1.66) 0.115 
    Female 198/242 18.7/21.1 0.76 (0.46-1.25) 0.533 191/241 9.9/10.8 0.86 (0.44-1.66) 0.776 196/240 19.4/14.6 1.49 (0.87-2.54) 0.181 
Smoking status             
    Never 258/502 18.6/18.7 0.98 (0.67-1.44) 0.968 252/502 7.5/10.6 0.68 (0.39-1.18) 0.184 251/499 19.5/17.6 1.13 (0.76-1.66) 0.528 
    Former 320/381 20.9/22.6 0.91 (0.63-1.31) 0.602 315/379 10.5/8.4 1.35 (0.81-2.27) 0.36 317/380 21.8/16.6 1.51 (1.03-2.23) 0.082 
    Current 291/160 27.1/21.9 1.29 (0.80-2.06) 0.218 286/160 8.4/8.8 0.96 (0.46-1.97) 0.897 287/158 20.6/16.5 1.41 (0.83-2.39) 0.292 
Alcohol use             
    Never 237/451 21.5/20.6 1.05 (0.72-1.55) 0.783 234/450 9.8/11.1 0.87 (0.52-1.47) 0.606 235/449 20.9/19.6 1.10 (0.74-1.63) 0.698 
    Former 183/168 19.7/16.1 1.26 (0.72-2.20) 0.38 179/168 5.6/10.1 0.51 (0.23-1.16) 0.115 181/166 18.8/18.7 0.97 (0.56-1.69) 0.979 
    Current 449/424 23.8/22.4 0.98 (0.70-1.37) 0.618 440/423 9.8/7.6 1.43 (0.87-2.38) 0.25 439/422 21.4/13.7 1.87 (1.28-2.72) 0.003 
Tumor site             
    Oral cavity 297/1,043 22.6/20.6 1.04 (0.75-1.44) 0.468 294/1,041 7.8/9.5 0.83 (0.50-1.36) 0.375 296/1,037 18.6/17.1 1.19 (0.83-1.69) 0.545 
    Oropharynx 572/1,043 22.2/20.6 1.03 (0.80-1.33) 0.455 559/1,041 9.5/9.5 1.04 (0.73-1.49) 0.985 559/1,037 21.8/17.1 1.35 (1.04-1.76) 0.020 
Stratified variablesCases/controls (n)*NEIL1 g.46434077G > T
PCases/controls (n)§NEIL1 g.46438282C > G
PCases/controls (n)NEIL2 g.4102971G > C
P
Cases/controls (%)
Adjusted OR (95% CI)
Cases/controls (%)
Adjusted OR (95% CI)
Cases/controls (%)
Adjusted OR (95% CI)
TTTT vs. GG + GTGGGG vs. CC + CGCCCC vs. CG + GG
Age             
    ≤50 243/303 21.0/20.5 0.98 (0.64-1.50) 0.88 237/303 10.5/7.6 1.47 (0.80-2.68) 0.231 236/301 19.9/16.9 1.25 (0.80-1.95) 0.376 
    51 to 64 409/487 24.0/20.5 1.06 (0.75-1.48) 0.218 404/485 9.7/11.1 0.89 (0.56-1.42) 0.473 404/484 20.8/18.2 1.27 (0.90-1.81) 0.327 
    ≥65 217/253 20.7/20.9 0.92 (0.58-1.46) 0.955 212/253 5.7/8.7 0.63 (0.30-1.32) 0.211 215/252 21.4/15.1 1.40 (0.85-2.28) 0.077 
Gender             
    Male 671/801 23.4/20.5 1.11 (0.86-1.43) 0.176 662/800 8.6/9.1 1.00 (0.69-1.45) 0.731 659/797 21.1/17.8 1.27 (0.97-1.66) 0.115 
    Female 198/242 18.7/21.1 0.76 (0.46-1.25) 0.533 191/241 9.9/10.8 0.86 (0.44-1.66) 0.776 196/240 19.4/14.6 1.49 (0.87-2.54) 0.181 
Smoking status             
    Never 258/502 18.6/18.7 0.98 (0.67-1.44) 0.968 252/502 7.5/10.6 0.68 (0.39-1.18) 0.184 251/499 19.5/17.6 1.13 (0.76-1.66) 0.528 
    Former 320/381 20.9/22.6 0.91 (0.63-1.31) 0.602 315/379 10.5/8.4 1.35 (0.81-2.27) 0.36 317/380 21.8/16.6 1.51 (1.03-2.23) 0.082 
    Current 291/160 27.1/21.9 1.29 (0.80-2.06) 0.218 286/160 8.4/8.8 0.96 (0.46-1.97) 0.897 287/158 20.6/16.5 1.41 (0.83-2.39) 0.292 
Alcohol use             
    Never 237/451 21.5/20.6 1.05 (0.72-1.55) 0.783 234/450 9.8/11.1 0.87 (0.52-1.47) 0.606 235/449 20.9/19.6 1.10 (0.74-1.63) 0.698 
    Former 183/168 19.7/16.1 1.26 (0.72-2.20) 0.38 179/168 5.6/10.1 0.51 (0.23-1.16) 0.115 181/166 18.8/18.7 0.97 (0.56-1.69) 0.979 
    Current 449/424 23.8/22.4 0.98 (0.70-1.37) 0.618 440/423 9.8/7.6 1.43 (0.87-2.38) 0.25 439/422 21.4/13.7 1.87 (1.28-2.72) 0.003 
Tumor site             
    Oral cavity 297/1,043 22.6/20.6 1.04 (0.75-1.44) 0.468 294/1,041 7.8/9.5 0.83 (0.50-1.36) 0.375 296/1,037 18.6/17.1 1.19 (0.83-1.69) 0.545 
    Oropharynx 572/1,043 22.2/20.6 1.03 (0.80-1.33) 0.455 559/1,041 9.5/9.5 1.04 (0.73-1.49) 0.985 559/1,037 21.8/17.1 1.35 (1.04-1.76) 0.020 

NOTE: Results are shown in boldface if the 95% CI did not include 1 or P < 0.05.

*

No. (cases/controls): three cases and one control had missing values for NEIL1 g.46434077G > T.

Adjusted ORs for all covariates (age, gender, smoking status, and alcohol use), excluding the stratified variable.

P value was from the χ2 test statistics from comparisons of genotype frequency in cases and controls.

§

No. (cases/controls): 19 cases and 3 controls had missing values for NEIL1 g.46438282C > G.

No. (cases/controls): 17 cases and 7 controls had missing values for NEIL2 g.4102971G > C.

Association between the NEIL2 g.4102971 polymorphisms and progression of SCCOOP. Because only the NEIL2 g.4102971 polymorphism was associated with the risk of SCCOOP, we further evaluated its association with progression of SCCOOP. We found a statistically significant association between the NEIL2 g.4102971CC genotype and advanced stages of primary SCCOOP tumor (T) as well as regional lymph node metastasis at diagnosis (N). The genotype frequency distributions were statistically significantly different between cases and controls for tumor stages T2 and T3 and for node stages N2 and N3. Using the 1,044 controls as the reference group, the adjusted ORs for the CC genotype of NEIL2 g.4102971 were calculated for each stratum by T or N stage. ORs for the CC genotype were significantly increased as the stages increased with the highest risk for T3 and N3 stage after adjustment for other covariates. For example, the OR for the genotype CC of NEIL2 g.4102971 in SCCOOP patients with N3 was 3.06 (95% CI, 1.49-6.26). When we arranged SCCOOP patients into two groups according to their T and N status [i.e., a group with less-advanced disease (N0 or N1 and T1 or T2) and a group with more-advanced disease (N2, N3, T3, or T4)], the OR for the genotype CC versus other genotypes was 1.39 (95% CI, 1.07-1.81) in SCCOOP patients with more-advanced disease, compared with those patients with less-advanced disease, after adjusting for other covariates (Table 4).

Table 4.

Associations between the combined genotypes of the NEIL2 g.4102971 polymorphism and progression of SCCOOP

Stratified variables*NEIL2 g.4102971G>C
Crude ORAdjusted ORP
Cases/controls (n)CCGG + CG
Primary tumor (T)       
    T1 216/1,037 16.2/17.1 83.8/82.9 0.94 (0.63-1.40) 0.98 (0.65-1.46) 0.758 
    T2 315/1,037 22.5/17.1 77.5/82.9 1.41 (1.04-1.93) 1.48 (1.07-2.03) 0.028 
    T3 159/1,037 24.5/17.1 75.5/82.9 1.58 (1.06-2.35) 1.75 (1.16-2.64) 0.023 
    T4 165/1,037 19.4/17.1 80.6/82.9 1.17 (0.77-1.78) 1.19 (0.76-1.87) 0.464 
Lymph node metastasis       
    N0 277/1,037 19.5/17.1 80.5/82.9 1.18 (0.84-1.65) 1.24 (0.87-1.77) 0.346 
    N1 127/1,037 15.7/17.1 84.3/82.9 0.91 (0.55-1.50) 1.01 (0.60-1.69) 0.708 
    N2 413/1,037 21.8/17.1 78.2/82.9 1.35 (1.02-1.80) 1.40 (1.05-1.88) 0.036 
    N3 38/1,037 34.2/17.1 65.8/82.9 2.53 (1.27-5.03) 3.06 (1.49-6.26) 0.007 
Combine N and T       
    N0,1 and T1,2 260/1,037 18.8/17.1 81.2/82.9 1.13 (0.79-1.60) 1.19 (0.83-1.72) 0.500 
    N2,3 or T3,4 595/1,037 21.5/17.1 78.5/82.9 1.33 (1.03-1.72) 1.39 (1.07-1.81) 0.027 
Stratified variables*NEIL2 g.4102971G>C
Crude ORAdjusted ORP
Cases/controls (n)CCGG + CG
Primary tumor (T)       
    T1 216/1,037 16.2/17.1 83.8/82.9 0.94 (0.63-1.40) 0.98 (0.65-1.46) 0.758 
    T2 315/1,037 22.5/17.1 77.5/82.9 1.41 (1.04-1.93) 1.48 (1.07-2.03) 0.028 
    T3 159/1,037 24.5/17.1 75.5/82.9 1.58 (1.06-2.35) 1.75 (1.16-2.64) 0.023 
    T4 165/1,037 19.4/17.1 80.6/82.9 1.17 (0.77-1.78) 1.19 (0.76-1.87) 0.464 
Lymph node metastasis       
    N0 277/1,037 19.5/17.1 80.5/82.9 1.18 (0.84-1.65) 1.24 (0.87-1.77) 0.346 
    N1 127/1,037 15.7/17.1 84.3/82.9 0.91 (0.55-1.50) 1.01 (0.60-1.69) 0.708 
    N2 413/1,037 21.8/17.1 78.2/82.9 1.35 (1.02-1.80) 1.40 (1.05-1.88) 0.036 
    N3 38/1,037 34.2/17.1 65.8/82.9 2.53 (1.27-5.03) 3.06 (1.49-6.26) 0.007 
Combine N and T       
    N0,1 and T1,2 260/1,037 18.8/17.1 81.2/82.9 1.13 (0.79-1.60) 1.19 (0.83-1.72) 0.500 
    N2,3 or T3,4 595/1,037 21.5/17.1 78.5/82.9 1.33 (1.03-1.72) 1.39 (1.07-1.81) 0.027 

NOTE: Results are shown in boldface if the 95% CI did not include 1 or P < 0.05.

*

Stratified variables: T, the extent of the primary SCCOOP. T1, tumor ≤2 cm at the greatest dimension; T2 to T4, increasing greatest dimensions; N, regional lymph node involvement; N0, no regional lymph nodes involved; N1 to N3, increasing involvement of regional lymph nodes.

Adjusted ORs for age, gender, smoking status, and alcohol use.

P value from the χ2 test of different frequencies of NEIL2 g.4102971 genotypes in cases and controls.

Because most of the significant findings were in the subgroup analysis, we calculated the FPRP value for all the significant associations. As shown in Table 5, when the assumption of prior probability was 0.1, the NEIL2 g.4102971CC genotype was still associated with an elevated risk of SCCOOP in current alcohol drinkers and in those with tumor stage N3, with a FPRP of 0.05 and 0.1, respectively. However, if the prior probability was set to 0.01, all significant associations we found in this study became false-positive findings.

Table 5.

FPRP for significant associations of NEIL2 g.4102971 and SCCOOP

SubgroupPositive OR, 95% CI*PORStatistical power§Prior probability
0.250.10.010.0010.0001
All participants 1.27 (1.01-1.60) 0.044 1.2 0.69 0.16 0.36 0.86 0.98 1.00 
Current alcohol users 1.71 (1.19-2.45) 0.003 1.7 0.51 0.02 0.05 0.38 0.86 0.98 
Oropharynx cancers 1.36 (1.05-1.76) 0.02 1.3 0.63 0.09 0.22 0.76 0.97 1.00 
T2 1.41 (1.04-1.93) 0.028 1.4 0.53 0.14 0.32 0.84 0.98 1.00 
T3 1.58 (1.06-2.35) 0.023 1.5 0.6 0.10 0.25 0.79 0.97 1.00 
N2 1.35 (1.02-1.80) 0.036 1.3 0.61 0.15 0.35 0.85 0.98 1.00 
N3 2.53 (1.27-5.03) 0.007 2.5 0.51 0.04 0.10 0.56 0.93 0.99 
N2,3 or T3,4 1.33 (1.03-1.72) 0.027 1.3 0.58 0.12 0.29 0.82 0.98 1.00 
SubgroupPositive OR, 95% CI*PORStatistical power§Prior probability
0.250.10.010.0010.0001
All participants 1.27 (1.01-1.60) 0.044 1.2 0.69 0.16 0.36 0.86 0.98 1.00 
Current alcohol users 1.71 (1.19-2.45) 0.003 1.7 0.51 0.02 0.05 0.38 0.86 0.98 
Oropharynx cancers 1.36 (1.05-1.76) 0.02 1.3 0.63 0.09 0.22 0.76 0.97 1.00 
T2 1.41 (1.04-1.93) 0.028 1.4 0.53 0.14 0.32 0.84 0.98 1.00 
T3 1.58 (1.06-2.35) 0.023 1.5 0.6 0.10 0.25 0.79 0.97 1.00 
N2 1.35 (1.02-1.80) 0.036 1.3 0.61 0.15 0.35 0.85 0.98 1.00 
N3 2.53 (1.27-5.03) 0.007 2.5 0.51 0.04 0.10 0.56 0.93 0.99 
N2,3 or T3,4 1.33 (1.03-1.72) 0.027 1.3 0.58 0.12 0.29 0.82 0.98 1.00 
*

OR, 95% CI calculated from the study sample by univariate logistic regression analysis.

P value calculated by the χ2 test in comparisons of genotype distributions in cases and controls.

ORs were closest to the observed ORs in each stratified subgroup used to calculate FPRP.

§

Statistical power was calculated using the number of observations in the subgroup and the OR and P values in this table.

In this study, we investigated the associations between three common, potentially functional polymorphisms of NEIL1 and NEIL2 genes and the risk of SCCOOP in a hospital-based case-control study. When we evaluated each polymorphism separately, only the NEIL2 g.4102971 polymorphism, but not NEIL1 g.46434077 or g.46438282, was associated with risk of SCCOOP. In addition, the NEIL2 g.4102971 polymorphism seemed to be associated with more advanced SCCOOP, particularly, for oropharyngeal cancer. Given the role of the NEIL genes in the base excision repair pathway, it is biologically plausible that functional NEIL2 polymorphisms may modulate the risk and/or progression of cancer.

Several groups have reported that NEIL1 and NEIL2 sequence variants are associated with the risk of diseases such as colorectal cancer, gastric cancer, and metabolic syndrome as well as brain ontogeny in different ethnic groups (20, 26, 27). One study suggested that mutations in NEIL1 may reduce the gene expression and protein activities in a subset of gastric cancers (18), but another study reported that some sequence variations in both NEIL1 and NEIL2 were apparently not associated with the risk of colorectal cancer (20). However, no previous studies investigated the associations between NEIL1 and NEIL2 polymorphisms and the risk of SCCOOP. Our current large case-control study supports the notion that selected variants in NEIL2 may contribute to the etiology of SCCOOP.

Several lines of evidence of molecular mechanisms support our findings. Oxidized DNA base lesions such as thymine glycol and 8-hydroxyguanine are often toxic, mutagenic, or even carcinogenic (12). In mammalian cells, the repair of DNA bases that have been damaged by reactive oxygen species is primarily initiated by a series of DNA glycosylases that include OGG1, NTH1, NEIL1, and NEIL2. It has been shown that in vitro–translated mouse or human NEIL1 could remove thymine glycol and 5-hydroxyuracil much more efficiently than 8-oxoG in double-stranded and single-stranded DNA (28, 29). With the loss of the NEIL1 functions, NEIL1 knockout mice develop metabolic syndrome, manifesting as severe obesity, dyslipidemia, and fatty liver disease (26). The genetic variants of NEIL1 selected in the present study may not have been sufficient to cause severe loss of NEIL1 functions; alternatively, our study may not have had enough power to detect small differences in terms of cancer risk, if any existed. NEIL2 primarily functions to excise oxidative products of cytosine, with its greatest activity for 5-hydroxyuracil, but it shows negligible or undetectable activity for 8-oxoG (14). Our finding of an association between the selected NEIL2 variant and risk of SCCOOP could be due to a function loss; alternatively, this variant may be in linkage disequilibrium with other causal variants. These hypotheses should be tested in future mechanistic studies.

In the present study, we observed an increased risk associated with the variant NIEL2 genotype in former smokers but not in current smokers, and this is likely to be a chance finding. Likewise, we also observed a significantly increased risk of SCCOOP among current drinkers of alcohol, suggesting that a gene-environment interaction may be involved in the development of SCCOOP; however, our study did not have enough statistical power to confirm any such gene-environment interaction. Ethanol reportedly induces oxidative stress via metabolic activation, leading to oxidative DNA damage and a decrease in hepatic antioxidant defense (27, 30), which may explain the putative role of the NEIL2 g.4102971 polymorphism in alcohol-induced SCCOOP. However, this finding may also have occurred by chance, owing to the small number of observations in our stratified analysis.

More interesting is our finding that the NEIL2 g.4102971CC genotype was significantly associated with more-advanced SCCOOP, suggesting that the NEIL2 g.4102971CC genotype may be associated with SCCOOP progression, although it is also possible that our results may be due to selection bias commonly occurring in hospital-based case-control studies. However, we can speculate that because NEIL2 is involved in the repair of oxidative damage to DNA either accumulated in the aging process or as a result of fast-growing tumors due to their enhanced metabolic activities (31), an altered function of NEIL2 due to the variant may lead to excessive oxidative damage to DNA, causing additional mutations or a mutator phenotype with genomic instability that may promote tumor progression (32). This hypothesis needs to be tested in additional mechanistic studies.

It is difficult to compare our genotyping data with those from other studies, because few studies on NEIL1 and NEIL2 polymorphisms have been published. Additionally, because other less common functional variants of these two genes were not assayed in the present study, our finding must be confirmed in studies that enroll larger numbers of patients with SCCOOP with genotyping data based on dense gene maps, such as the HapMap database (33).

In conclusion, we found that the NEIL2 g.4102971CC genotype was associated with a significantly increased risk of SCCOOP, in particular, advanced SCCOOP or oropharygeal cancer, compared with other genotypes. However, the FPRP values for all the significant findings in our study were >0.2 when the prior probability was set at 0.01, suggesting that these findings could all be false-positives. Therefore, our findings should validate future population-based studies that will include larger numbers of patients with oropharyngeal cancer, more detailed data on environmental exposure, more SNPs in more genes in the same biological pathway, and survival data. Because the majority of patients did not yet have enough follow-up time or death events, we will evaluate the role of the NEIL2 g.4102971CC genotype on disease prognosis in this patient cohort in future follow-up studies.Disclosure of Potential Conflicts of Interest.

E. Sturgis received an honorarium for attending a consultants' meeting sponsored by Merck in December 2007 regarding HPV vaccine and head and neck cancer. The other authors disclose no potential conflict of interest.

Grant support: NIH grants ES11740 (Q. Wei), CA100264 (Q. Wei), and CA16672 (the University of Texas M. D. Anderson Cancer Center).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank Margaret Lung, Kathryn Patterson, and Leanel Fairly for their assistance in recruiting the subjects; Yawei Qiao, Jianzhong He, and Kejing Xu for their laboratory assistance; and Kathryn Carnes and Chris Hengst for scientific editing.

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