Polymorphisms in Telomere Maintenance Genes and Risk of Lung Cancer

This study was conducted to comprehensively evaluate the associations between polymorphisms in telomere maintenance genes (TERT, TRF1, TNKS1, TRF2, RAP1, and POT1) and lung cancer risk. We captured 35 polymorphisms in the genes and determined their frequencies in 27 healthy Koreans. Ten haplotype-tagging polymorphisms were examined in a case-control study that consisted of 720 lung cancer patients and 720 healthy controls. The TERT rs2735940 g.C > T and rs2736098 g.G > A, and TNKS1 rs6985140 g.A > G were significantly associated with the risk of lung cancer. In the haplotype analysis, the TERT rs2735940T/rs2736098A haplotype (ht4) was associated with a significantly increased risk of lung cancer compared with the rs2735940C/rs2736098G haplotype (adjusted odds ratio, 1.26; 95% confidence interval, 1.07-1.50; P = 0.008). When the TERT ht4 and TNKS1 rs6985140G as risk alleles, the risk of lung cancer increased in a dose-dependent manner as the number of risk alleles increased (P_trend < 0.001). Subjects with two to four risk alleles were at a significantly increased risk of lung cancer (adjusted odds ratio, 1.67; 95% confidence interval, 1.23-2.27; P = 0.001) compared with subjects with zero risk allele. These findings suggest that genetic variants in the TERT and TNKS1 genes contribute to genetic susceptibility to lung cancer. (Cancer Epidemiol Biomarkers Prev 2009;18(10):2773–81)

Telomeres are specialized nucleic acid-protein complexes that protect chromosomes from degradation, end-to-end fusion, and atypical recombination; thus, telomeres play a key role in the maintenance of chromosomal stability (1). Telomeres are composed of TTAGGG repeats that are bound by a multiprotein complex, known as “shelterin” or the telosome (2, 3). Telomere integrity and function require both a minimal length of TTAGGG repeats and the integrity of the shelterin complex (2-4). Telomerase, a ribonucleoprotein that consists of a telomere reverse transcriptase (TERT) and a telomere RNA component, is the main positive regulator of telomere length and adds TTAGGG repeats de novo after each cell division (3-6).

A number of telomeric proteins have been identified that participate in the shelterin complex (7-11). These proteins are responsible for stabilizing telomere structure and length. TTAGGG repeat binding factor 1 (TRF1, also known as TERF1) binds to double-stranded telomeric DNA and regulates telomere length either directly or by their interactions with tankylase [a telomeric ankyrin-like poly(ADP-ribose) polymerase, TNKS] and TRF1-interacting nuclear protein 2 (TIN2, also known as TINF2; ref. 7). TNKS1 catalyzes the ADP ribosylation of TRF1 and thus inhibits the ability of TRF1 to bind to the telomere. As a consequence, telomerase can access the telomere and allow telomere elongation (8). On the contrary, binding TRF1 to the protein TIN2 functions as a negative regulator of telomere length by leading to compaction of telomeric DNA, stabilization of the T-loop, and limitation of accessibility to telomerase (7). Like TRF1, TRF2 binds to double-stranded telomeric DNA. Although TRF2 also functions as a negative regulator of telomere length, more importantly, it protects telomeres from end-to-end fusions; thus, TRF2 plays a key role in maintaining telomere integrity (9). Repressor activator protein 1 [RAP1, also known as TERF2 interacting protein (TERF2IP)] is recruited to the telomere by TRF2 and negatively regulates telomere length (10). Protection of telomeres 1 (POT1) binds to and protects the 3′ single-stranded TTAGGG overhanging. In addition to the protective role, POT1 limits elongation of the telomere by telomerase (11).

Several studies have documented considerable interindividual variations in the telomere length and telomerase activity among normal individuals of the same age (12-14). In addition, cigarette smoking, oxidative stress, and chronic inflammation may also cause telomere shortening (15, 16). It has been observed that individuals with shorter telomeres are at an increased risk of human cancers including lung cancer (17-19). Like many other phenotypic traits, variation in the telomere length and telomerase activity may be the result of functional polymorphisms in the genes involved in telomere biology. We hypothesized that genetic polymorphisms in these genes may have effect on telomere length and stability, thereby modulating the susceptibility to lung cancer. To test this hypothesis, we performed a case-control study to investigate the association between polymorphisms in seven genes (TERT, TRF1, TNKS1, TIN2, TRF2, RAP1, and POT1) important in telomere biology and the risk of lung cancer.

To screen all the potentially functional variants of the seven genes, we used the public database⁵

to search for candidate variants in the promoter region, all exons including intron-exon boundaries (50 bp on either side of the introns) and the 3′-untranslated region (UTR) of the gene because variants in these regions are most likely to affect the gene function. Thirty-five single nucleotide polymorphisms (SNP) were captured, and their frequencies were determined by direct sequencing in a preliminary study that included 27 healthy Korean individuals. Information regarding all SNPs, SNP Ids, and allele frequencies was obtained from the National Center for Biotechnology Information homepage. In the genomic reference sequences, the transcription start site was counted as +1. The PCR primers were designed based on the Genbank reference sequences. Supplementary Table S1 shows the primer sequences and annealing temperature that were used for the PCR analysis. Sequence variations were confirmed by two authors independently. The frequencies and LD status of the 35 SNPs in 27 healthy Koreans are shown in Table 1 and Fig. 1. Of 35 SNPs evaluated, 17 had minor allele frequencies of ≥10% in the 27 subjects. Finally, 10 haplotype-tagging SNPs were selected on the basis of their pairwise LD with an r² threshold of 0.8 for the case-control study. The 10 SNPs studied in a case-control study were as follows: TERT rs2735940 (−1327C > T) and rs2736098 (A305A, 659G > A in exon 2); TRF1 rs2975843 (−1119A > G) and rs2975841 (IVS2+11T > G); TNKS1 rs6990097 (−588T > C), rs6985140 (IVS3-34A > G), and rs7006985 (T462T, A > G); TRF2 rs251796 (IVS7-41T > C); RAP1 rs1865493 (+59G > C); and POT1 rs10228682 (−809A > G).

This case-control study consisted of 720 lung cancer patients and 720 healthy controls that were enrolled using the same method as described for our previous studies (20). Briefly, the eligible cases included all the patients who were newly diagnosed with primary lung cancer between January 2001 and December 2002 at Kyungpook National University Hospital, Daegu, Korea. There were no gender, histologic, or stage restrictions; however, those patients over the age of 75 y or who had a prior history of cancers were excluded from this study. All patients included agreed to participate in this study. The cases included 320 (44.4%) squamous cell carcinomas, 273 (37.9%) adenocarcinomas, 115 (16.0%) small cell carcinomas, and 12 (1.7%) large cell carcinomas. The control subjects were randomly selected from a pool of healthy volunteers who visited the general health check-up center at Kyungpook National University Hospital during the same period. The control subjects were frequency matched (1:1) to the cancer cases based on gender and age (±5 y). Compared with subjects who refused to participate, the enrolled subjects had similar gender distributions. A total of 3,065 (1,598 males and 1,467 females) of 5,578 healthy subjects agreed to participate in this study (participation rate, 54.9%). Compared with the subjects that declined to participate, the enrolled subjects showed similar gender (% of male, 52.5% versus 52.1%; P = 0.77) and age (52.2 ± 11.4 versus 52.1 ± 11.3 y; P = 0.80) distributions. From 3,065 healthy volunteers, we randomly selected 720 control subjects by generating random numbers using SAS, version 8.12. All the subjects enrolled in this study (cases and controls) were ethnic Koreans who resided in Daegu City or the surrounding regions. This study was approved by the institutional review board of the Kyungpook National University Hospital, and written informed consent was obtained from each participant.

Genomic DNA was extracted from peripheral blood lymphocytes by proteinase K digestion and phenol/chloroform extraction. Of the 10 SNPs, the rs2736098 was genotyped by PCR-RFLP analysis, and the other 9 SNPs were genotyped by melting-curve analysis using fluorescence-labeled hybridization probes (LightCycler 480, Roche Diagnostic). Primer sequences and hybridization probes are listed in Supplementary Table S2. A genotype success rate of >98% was achieved using the LightCycler. Samples that could not be scored using the LightCycler were regenotyped by direct sequencing using an ABI PRISM 3700 genetic analyzer (Applied Biosystems). All genotyping analyses were blinded with respect to the case/control status to ensure quality control. In addition, approximately 10% of the samples were randomly selected to be genotyped again by a different investigator, and the results were 100% concordant.

The differences between the cases and controls in smoking status and in allele and genotype frequencies were evaluated by a χ² test. A Student's t test was performed to evaluate the difference in age and pack-years smoked. Deviations of the genotype frequencies in the controls from those expected under the Hardy-Weinberg equilibrium were assessed by a goodness-of-fit χ² test, as implemented through SAS Genetics. The linkage disequilibrium (LD) among polymorphisms was measured by using HaploView.⁶

LD blocks were inferred from the definition proposed by Gabriel et al. (21). The haplotypes and their frequencies were estimated based on a Bayesian algorithm using the phase program (22). The cancer risk associated with the genotypes and haplotypes was estimated as an odds ratio (OR) and 95% confidence interval (CI) using unconditional logistic regression. In addition to the overall association analysis, we performed a stratified analysis by age, smoking status, and tumor histology to further explore the association between SNPs and the risk of lung cancer in each stratum. The issue of multiple tests was controlled by using 10,000-time permutation tests. For the gene-smoking interaction analyses, we used three approaches to evaluate the consistency of results: (a) gene-smoking joint effects, (b) logistic regression model, including the interaction term between genotype/haplotype and smoking, and (c) stratified analyses in specific categories of cumulative smoking exposure. For these analyses, the subjects were categorized into three groups according to the level of smoking exposure: never-smokers, ever-smokers ≤33 pack-years (light smokers), and ever-smokers >33 pack-years (heavy smokers, by median pack-year value of the ever-smokers). All the analyses were done using Statistical Analysis Software for Windows, version 9.1.3 (SAS institute).

Table 2 shows the demographics of the cases and controls enrolled in the case-control study. There were no significant differences in mean age or gender distribution between cases and controls. However, there were more current smokers among the cases than the controls (P < 0.001), and the number of pack-years in smokers was significantly higher in the cases than in the controls (39.8 ± 18.1 versus 32.8 ± 18.0 pack-year; P < 0.001). These differences were controlled in the later multivariate analyses.

The genotype and polymorphic allele frequencies of the 10 SNPs in the cases and controls are shown in Table 3. The genotype distributions of the 10 SNPs among the controls were in Hardy-Weinberg equilibrium. Of the 10 SNPs studied, only three SNPs (TERT rs2735940 g.C > T and rs2736098 g.G > A; and TNKS1 rs6985140 g.A > G) were significantly associated with the risk of lung cancer. The TERT rs2735940 g.C > T and rs2736098 g.G > A were associated with a significantly increased risk of lung cancer under a dominant model and a recessive model, respectively, for the variant allele of each SNP (adjusted OR, 1.31; 95% CI, 1.04-1.63; P = 0.02; and adjusted OR, 1.74; 95% CI, 1.21-2.51; P = 0.003, respectively). For the TNKS1 rs6985140 g.A > G, the combined AG and GG genotype was associated with a significantly increased risk of lung cancer compared with the AA genotype (under a dominant model for the variant G allele, adjusted OR, 1.36; 95% CI, 1.06-1.76; P = 0.02).

The associations between the TERT and TNKS1 haplotypes and the risk of lung cancer are shown in Table 4. Consistent with the results of genotyping analyses, the TERT rs2735940T/rs2736098A haplotype (ht4) carrying variant alleles at the two loci was associated with a significantly increased risk of lung cancer compared with the rs2735940C/rs2736098G haplotype carrying wild-type alleles at both loci (adjusted OR, 1.26; 95% CI, 1.06-1.50; P = 0.008 and Pc = 0.024). In the TNKS1 haplotype analysis, the C-G-A haplotype (rs6990097C/rs6985140G/rs7006985A), which is the only haplotype carrying the rs6985140G allele in the population, was associated with a significantly increased risk compared with other haplotypes (adjusted OR, 1.36; 95% CI, 1.07-1.72; P = 0.02 and Pc = 0.08). This result suggests that genetic effect of the TNKS1 SNPs on the risk of lung cancer is more likely attributed to the rs6985140 g.A > G rather than haplotypes.

We next evaluated the combined effects of the three SNPs (TERT rs2735940 g.C > T and rs2736098 g.G > A; and TNKS1 rs6985140 g.A > G), which had a significant association with lung cancer in the individual SNP analysis, on the risk of lung cancer. Because the TERT ht4 and the TNKS1 rs6985140G allele were associated with an increased risk of lung cancer, we considered the TERT ht4 and TNKS1 rs6985140G as risk alleles and then evaluated their combined effects by grouping the subjects into four or three groups based on the number of risk alleles. Because only one case carried four risk alleles (none in the control group), we combined subjects with three risk alleles and those with four risk alleles into one group when categorized into four groups [subjects with 0 (group 1), 1 (group 2), 2 (group 3), and 3 or 4 (group 4) risk alleles]. As shown in Table 5, the distribution of the combined genotypes in the cases significantly differed from that in the controls (P = 0.02 when grouped into four groups and P = 0.01 when grouped into three groups), and the risk of lung cancer increased in a dose-dependent manner as the number of risk alleles increased (P_trend < 0.001). When the subjects were categorized into three groups [subjects with 0 (group 1), 1 (group 2), and 2-4 (group 3) risk alleles], and the group 1 was used as the reference group, the OR of the group 3 for lung cancer was 1.67 (95% CI, 1.23-2.27; P = 0.001). These results indicate an additive effect of the TERT ht4 and TNKS1 rs6985140G allele on an increased risk of lung cancer.

The association between the combined genotypes of TERT (rs2735940 g.C > T and rs2736098 g.G > A) and TNKS1 (rs6985140 g.A > G) SNPs and the risk of lung cancer was further examined after stratifying the subjects according to age, smoking status, and histologic types of lung cancer. The effect of the combined genotypes on the risk of lung cancer was similar in younger and older individuals [P value of test for homogeneity (P_H) = 0.21 for group 2 and 0.33 for group 3; Table 6]. In addition, the effect of the combined genotypes on the risk of lung cancer did not differ according to smoking status and smoking exposure levels. Lung cancers are composed of different histologic types, and the different histologic types of lung cancer are different diseases in the etiologies and carcinogenic pathways. Therefore, the effect of the combined TERT and TNKS1 genotypes on the risk of lung cancer was estimated according to the histologic type of lung cancer. However, the effect of the combined genotypes on the risk of lung cancer was not statistically different among the three major histologic types (Table 6).

The joint effect of the three SNPs (TERT haplotypes of the rs2735940 g.C > T and rs2736098 g.G > A and TNKS1 rs6985140 g.A > G genotypes) and smoking status on the risk of lung cancer was shown in Table 7. When the group of never-smokers with zero risk allele was used as the reference group, the group of heavier smokers with two to four risk alleles was found to have the highest risk of lung cancer (adjusted OR, 7.24; 95% CI, 3.84-13.68; P < 0.0001). However, we did not find statistically significant evidence of a gene-smoking interaction in the multivariate logistic regression analysis (P = 0.94 for multiplicative interaction).

Polymorphisms in the telomere maintenance genes may have an influence on disease progression. In the present study, however, no significant difference was observed in the genotype and haplotype distributions of the polymorphisms according to the stage of lung cancer (Supplementary Table S3).

We evaluated the potential association of polymorphisms in telomere maintenance genes (TRF1, TNKS1, TIN2, TRF2, RAP1, and POT1) with the risk of lung cancer. To comprehensively assess the potentially functional variants in these genes, we first determined frequencies and haplotype-tagging status of the 35 SNPs, which were captured from the National Center for Biotechnology Information database and then examined 10 SNPs in a case-control study. The TERT rs2735940 g.C > T and rs2736098 g.G > A, and the TNKS1 rs6985140 g.A > G were significantly associated with the risk of lung cancer. In addition, there was an additive effect of the TERT and TNKS1 SNPs on the risk for lung cancer. These findings suggest that SNPs in the TERT and TNKS1 genes might be useful markers for determining genetic susceptibility to lung cancer. Although a study has identified an SNP (rs2853669) at the TERT promoter in non–small cell lung cancer tissues and reported variation in telomerase activity and terminal restriction fragment length ratio in different genotypes of the SNP (23), this is the first molecular epidemiologic study of telomere-maintenance gene polymorphisms in relation to lung cancer risk.

TERT expression is primarily regulated at the transcriptional level (24, 25). The proximal region of the TERT promoter, particularly the 181-bp core promoter region upstream of the transcription start site, has been reported to be responsible for basal transcriptional activity of the TERT gene. This promoter region contains multiple transcription factor binding sites, including c-Myc/Mad/Max binding sites (E-boxes) and Sp1 binding sites (24-27). The rs2735940 g.C > T (−1327C > T) and rs2853669 g.T > C (−244T > C) in the promoter of the TERT gene have been shown to affect transcription factor bindings and thereby to modulate TERT expression (23, 28). Therefore, the observed association of the TERT SNPs (rs2735940 g.C > T and rs2736098 g.G > A) with the risk of lung cancer is biologically plausible. In the present study, the rs2853669 g.T > C was not evaluated in a case-control study because it was strongly linked with the rs2736098 g.G > A in the preliminary study (∣D′∣ = 1.0 and r² = 0.85; Fig. 1). Therefore, the observed association between the rs2736098 g.G > A and the risk of lung cancer may be due to LD with the rs2853669 g.T > C, as previously suggested (29). Another novel finding of the present study is that the rs6985140 (IVS3-34A > G) of TNKS1 gene was associated with the risk of lung cancer. However, the functional significance of the SNP is unknown. Further functional studies on the TNKS1 rs6985140 g.A > G and related variants are therefore needed to elucidate the underlying mechanisms of the observed association.

In this study, the TERT ht4 was associated with a 1.26-fold increased risk of lung cancer, and the presence of at least one TNKS1 rs6985140G allele was associated with a 1.36-fold increased risk of lung cancer. When these two risk alleles were combined, the risk of lung cancer increased in a dose-dependent manner as the number of variant alleles increased, and the presence of two to four risk alleles was associated with a 1.67-fold increased risk of lung cancer compared with the presence of zero risk allele. These results indicate that the TERT and TNKS1 SNPs have an additive effect on an increased risk of lung cancer (30). TNKS1 inactivates TRF1 binding to telomere DNA and results in an “open” telomere configuration, which in turn could render the access of TERT to the telomere (7, 8). Therefore, it is possible that the TERT and TNKS1 SNPs may have an additive effect on the risk of lung cancer. However, because the interaction term between the TERT and TNKS1 SNPs was not significant, additional studies are needed to confirm this finding.

To date, there have been a few published studies on telomere-associated gene polymorphisms and cancer susceptibility. Savage et al. (29) investigated the associations of 24 SNPs (29, 31) in the TERT, TRF1, TRF2, POT1, and TEP1 genes with the risk breast in a Polish population. In their study, although the SNPs showed no significant overall associations with the risk of breast cancer, the TERT rs2735940 g.C > T, rs2853669 g.T > C, and rs2736098 g.G > A were associated with the risk of breast cancer among individuals with a family history of breast cancer. In concordance with their study, we also found that the TERT rs2735940 g.C > T and rs2736098 g.G > A were significantly associated with the risk of lung cancer. However, in contrast to the Polish study (29) in which the polymorphic alleles of the three SNPs were associated with a decreased risk of breast cancer, the polymorphic alleles of the rs2735940 g.C > T and rs2736098 g.G > A and the corresponding haplotype (rs2735940T/rs2736098A) were associated with an increased risk of lung cancer in the present study. Although it is hard to decipher the reason for the oppositely directed (flip-flop) associations of the TERT SNPs with cancer risk in the previous and current studies, the different genetic backgrounds in the study populations or interactive effects of multiple polymorphisms might contribute to the discrepancy (32). In a complex polygenic disease such as cancer, it is likely that multiple loci act in concert to cause a disease, which would result in the genetic susceptibility being dependent on the coincidence of several polymorphisms acting together. Therefore, multilocus effects and population variation in LD with other causal variants might have been caused such flip-flop associations (32). Another possible explanation is that the discrepancy between the two studies may be that breast cancer and lung cancer have different etiologies and different carcinogenesis pathways. For example, p53 plays an important role in stem cell checkpoints induced by telomere shortening (33), and checkpoint failure cooperates with telomere dysfunction to induce chromosomal instability and cancer initiation (34). Loss-of-function mutations in the p53 gene more commonly occur in lung cancers (∼56%) than in breast cancers (∼22%; ref. 35). Therefore, polymorphisms in telomere maintenance genes might play different roles in these two different cell types of cancer. However, the inadequacies in the study design, such as nonrandom sampling, limited sample sizes and the pitfalls arising from unknown confounders, also need be considered.

In the present study, we found the joint effect of the SNPs in telomere maintenance genes and smoking on the risk of lung cancer. Such a finding is biologically plausible because smoking has been shown to induce telomere shortening and to increase telomerase activity (15, 36); therefore, polymorphisms that can influence telomere shortening may have synergistic effects with smoking on lung cancer development. However, because the interaction term between the genotype and smoking was not statistically significant in the multivariate logistic regression analysis, additional studies must be conducted with a greater number of subjects to confirm this finding.

A number of genome-wide association studies have identified chromosomal regions that are likely to contain genes that contribute to the susceptibility to lung cancer (37-39). Interestingly, McKay et al. (39) reported that two SNPs (rs2736100 and rs402710) mapping to 15p15.33 containing TERT and CLPTM1L genes were significantly associated with the risk of lung cancer. Because rs2736100 and rs402710 are located in intron of the TERT or CLPTM1L gene, it was suggested that the associations of these two SNPs with lung cancer may be due to LD with other functional variant(s) rather than to a direct effect of one of these two variants. In the present study, rs2736100 and rs402710 were not tested because we focused only on the potentially functional variants that are located in the promoter region, exons including intron-exon boundaries, and the 3′-UTR of the TERT gene. Notably, we found that rs2735940, and rs2736098, which is strongly linked with the rs2853669, in the TERT gene, were significantly associated with the risk of lung cancer in the present study. None of these three SNPs (rs2735940, rs2736098, and rs2853669) were in strong LD (r² > 0.80) with rs2736100 or rs402710 based on HapMap data of the public database.⁵ However, because the HapMap data were derived from a small number of subjects from heterogeneous populations, we cannot exclude the possibility that rs2735940 and/or rs2853669 may be the causal variant(s) for the association of rs2736100 with lung cancer in the previous study (39), when considering the potential functionality of rs2735940 and rs2853669 (23, 28), as well as our finding of a significant association between these SNPs and lung cancer. Therefore, larger studies are needed in near future to confirm this.

Interestingly, a recent genome-wide association analysis has identified that the TERT rs2736100 also contributes to susceptibility to idiopathic pulmonary fibrosis (40). As described previously, because the rs2736100 is located in intron 2 of the TERT gene, the rs2735940 and rs2853669 located in the TERT promoter that were associated with the susceptibility to lung cancer in the present study may be causal variant(s) of the rs2736100 for susceptibility to idiopathic pulmonary fibrosis.

A number of limitations in the present study need to be addressed. Our study lacked the related functional assays, which limited our inquiry into biological mechanism of the observed associations between the SNPs and lung cancer risk. Secondary, although our study was relatively large, our sample size was apparently not large enough to identify significant gene-environment interactions. In addition, one must consider potential biases that might influence the results of hospital-based case-control studies, primarily selection bias and information bias, which were described in the previous our study (20).

In conclusion, we found that the TERT rs2735940 g.C > T and rs2736098 g.G > A, and the TNKS1 rs6985140 g.A > G were associated with the risk of lung cancer. In addition, we showed an additive effect of these TERT and TNKS1 SNPs on the risk of lung cancer. However, because this is the first molecular epidemiologic study of telomere-maintenance gene polymorphisms in relation to lung cancer, additional studies with larger sample size are required to confirm our findings. In addition, further studies on biological functions of the TERT and TNKS1 SNPs are also needed to understand the role of these SNPs in determining the risk of lung cancer. Moreover, because genetic polymorphisms often vary between different ethnic groups, further studies are needed to clarify the association between the TERT and TNKS1 SNPs and lung cancer in diverse ethnic populations.

No potential conflicts of interest were disclosed.

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