NIH Public Access Author Manuscript Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1.

NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Cancer Epidemiol Biomarkers Prev. 2010 January ; 19(1): 219±228. doi:10.1158/1055-9965.EPI-09-0771.

Multiple genetic variants in pathway and breast cancer risk

Jing Shen1,*, Marilie D. Gammon2, Hui-Chen Wu1, Mary Beth Terry3, Qiao Wang1, Patrick T. Bradshaw2, Susan L. Teitelbaum4, Alfred I. Neugut3, and Regina M. Santella1 1Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA 2Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA 3Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA 4Department of Community and Preventive Medicine, Mt. Sinai School of Medicine, New York, NY 10029, USA

Abstract Purpose—To explore the etiologic role of genetic variants in telomere pathway genes and breast cancer risk. Methods—A population-based case-control study — the Long Island Breast Cancer Study Project (LIBCSP) was conducted, and 1,067 cases and 1,110 controls were included in the present study. Fifty-two genetic variants of nine telomere related genes were genotyped. Results—There were a total of seven single nucleotide polymorphisms (SNPs) showing significant case-control differences at the level p<0.05. The top three statistically significant SNPs under a dominant model were TERT-07 (rs2736109), TERT-54 (rs3816659) and POT1-03 (rs33964002). The ORs were 1.56 (95%CI: 1.22-1.99) for TERT-07 G-allele, 1.27 (95%CI: 1.05-1.52) for TERT-54 T- allele and 0.79 (95%CI: 0.67-0.95) for POT1-03 A-allele. TERT-67 (rs2853669) was statistically significant under a recessive model; the OR of the CC genotype was 0.69 (95%CI: 0.69-0.93) compared with the T-allele. However, none of the SNPs retained significance after Bonferroni adjustment for multiple testing at the level of p<0.001 (0.05/52) except for TERT-07. When restricted to Caucasians (94% of the study subjects), a stronger association for the TERT-07 G-allele was observed with an OR of 1.60 (95%CI: 1.24-2.05, p=0.0002). No effect modifications were found for variant alleles and menopausal status, telomere length, cigarette smoking, BMI status and family history on breast cancer risk.

* Correspondence author: Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 630 West 168th Street, P & S 19-418, New York, NY 10032, USA, Phone: 212-305-8158, Fax: 212-305-5328, [email protected]. Translational Relevance We examined 52 genetic variants in telomere maintenance genes and relationships with breast cancer risk in a population-based case- control study. Seven single nucleotide polymorphisms (SNPs) showed significant associations with breast cancer (p<0.05). The top three significant ORs under a dominant model were 1.56 (95%CI: 1.22-1.99) for the TERT-07 G-allele, 1.27 (95%CI: 1.05-1.52) for the TERT-54 T-allele and 0.79 (95%CI: 0.67-0.95) for the POT1-03 A-allele but only TERT-07 retained significance after 100,000 random permutation analyses and Bonferroni adjustment for multiple testing at the level of p<0.001 (0.05/52). Our findings, if confirmed by other studies, may have significant clinical utility in identifying high-risk individuals and improving early diagnosis of breast cancer. Evaluation of the role of these SNPs in predicting breast cancer prognosis is a future plan. Disclosure of Potential Conflicts of Interest No potential conflicts of interest were disclosed. Shen et al. Page 2

Conclusions—Four SNPs in TERT and POT1 genes were significantly related with overall breast cancer risk. This initial analysis provides valuable clues for further exploration of the biological role

NIH-PA Author Manuscript NIH-PA Author Manuscriptof telomere pathway NIH-PA Author Manuscript genes in breast cancer.

Keywords Genetic variants; telomere; breast cancer

Introduction Molecular epidemiological studies undertaken to uncover genetic risk factors for beast cancer have expanded from examining single/several genetic variants to exploring the role of multiple polymorphisms involved in different biological pathways for tumorigenesis. Recently, five genome-wide association (GWA) studies focused on breast cancer risk have been completed. Only seven novel single nucleotide polymorphisms (SNPs) (rs1219648, rs2981582, rs3803662, rs889312, rs3817198, rs13281615 and rs13387042) among four genes (FGFR2, TNRC9, MAP3K1 and LSP1) and two loci (2q35 and 16q12) were identified as potentially related to breast cancer risk through screening 150,000 to 528,000 SNPs (1-5). Thus, we are far from understanding the “polygenic” characteristic of breast cancer. At the same time, none of the SNPs identified in the GWA studies are involved in the DNA damage/repair pathway, one of the well recognized mechanisms underlying breast cancer risk (6;7). Although GWA studies screen a mass of known SNPs covering the whole genome, this approach may not always be the most optimal for detecting certain main effects of important variant alleles. Systematic analysis of candidate breast cancer genes have found that more than one third (37.7%) are involved in an unknown pathway, suggesting that there are still many genomic gaps that need to be filled in (8-10). A pathway-based approach may be an ideal alternative to contribute to our knowledge of critical biological pathways in breast cancer risk.

Telomere pathway genes are essential for maintaining genomic integrity and stability by regulating telomere length and the higher-order structure of the complex at the end of linear (11-15). A dysfunctional telomere pathway may lead to less efficient DNA damage repair, genomic instability, and ultimately, initiate tumorigenesis. Theoretically, functional genetic variants in telomere pathway genes, which potentially influence telomere length, activity of and the protein-complex, might play a key role in the process of breast cancer development. Previous studies have observed that genetic variation in telomere- binding (including TERF1, TERF2, POT1 and TINF2, etc.) might accelerate telomere shortening and dysfunction (16;17), and data on the TERF1 first exon deletion and null mutations in murine embryonic stem cells indicated its negative regulator role for telomere length and telomeric structures (18;19).

Two genome-wide studies measuring mutant telomere maintenance genes in yeast identified 272 related genes altering telomere length (lengthening or shortening telomeric DNA sequence) (20;21). Several functional SNPs in human telomerase reverse transcriptase (TERT) have been noted to positively affect enzyme activity, mRNA expression and telomere length (22-24), although not confirmed by another study (25). However, the only population- based study, conducted in Poland, did not identify any significant associations between 24 SNPs or haplotypes within five telomere-related genes (POT1, TEP1, TERF1, TERF2 and TERT) and breast cancer risk. Only three correlated SNPs in TERT indicated an association with reduced breast cancer risk among the subgroup of individuals with a family history of breast cancer (26). Thus, the role of genetic variants in telomere pathway genes and breast cancer risk is unclear, especially at the population level. In the current study, we utilized the population-base case-control data and DNAs from Long Island Breast Cancer Study Project (LIBCSP) to examine 52 polymorphisms of nine key genes (PINX1, POT1, RAD18, TERC,

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TERF1, TERF2, TERF2IP, TERT and TNKS) in the telomere pathway and analyzed their relationships with breast cancer risk. NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript Materials and Methods Study Population The LIBCSP was conducted with approval from participating institutional review boards, and in accordance with an assurance filed with and approved by the United States Department of Health and Human Services. The study methods have been described in detail previously (27). In brief, case eligibility included adult female residents of Nassau and Suffolk counties on Long Island, NY, who were of any age or race, who spoke English, and were newly diagnosed with in situ or invasive breast cancer between August 1, 1996, and July 31, 1997. Potentially eligible controls were frequency matched to the expected age distribution of the cases and identified through random digit dialing for women under age 65 years, and through the Center for Medicare and Medicaid Services (CMS) rosters for women 65 and over. Eligible controls were defined as women who spoke English, and resided in the same Long Island counties as the cases, but with no personal history of breast cancer. In-person interviews were completed for 82.1% of cases (n = 1,508) and 62.8% of controls (n = 1,556). Of those who completed the main questionnaire, 73.1% of cases (1,102) and 73.3% of controls (1,141) donated a blood sample. Of these, 1,067 cases and 1,110 controls with enough DNA for genotyping were included in the present study. Ethnicity (94% white, 4% African American and 2% other) and age (ranging from 20-98 years) distributions were similar between respondents who completed the main questionnaire and the subjects analyzed in the present study (data not shown).

Questionnaire Data Collect In-person interviews were conducted within a few months of diagnosis by trained personnel. The main questionnaire collected information on known and suspected risk factors for breast cancer, including family history of breast cancer, reproductive history, menopausal status, exogenous hormone use, body mass index (BMI), history of alcohol use and active cigarette smoking. Menopausal status was based on the subject's self-reported information at the baseline interview. Postmenopausal status was defined as having the last menstrual period at least 6 months prior to the reference date or having both ovaries removed (28). Ever cigarette smoker was defined as smoking within the last 12 months prior to the reference date or who quit smoking more than 12 months prior to the reference date (29). BMI was calculated from self- reported weight and height data using the formula weight (kg)/height (m2). BMI just prior to the reference date was categorized as <25 or ≥25 based on the World Health Organization definition of overweight (30).

Telomere Pathway Genes and Genetic Variants Select A total of 24 genes were identified within the human telomere pathway by a literature review (13;31-33). Information on genetic variation among these genes was collected from publicly available databases (dbSNP a; UCSC Genome Bioinformatics b; GeneCards c and SNP500Cancer d). Totally, 6,515 SNPs are known for these genes. The nine genes (PINX1, POT1, RAD18, TERC, TERF1, TERF2, TERF2IP, TERT and TNKS) considered as candidate targets in the current study are those with previous evidence related to cancer development, and have been explored in “Cancer Genome Anatomy Project” (Supplemental Table 1).

ahttp://www.ncbi.nlm.nih.gov/SNP/ bhttp://genome.ucsc.edu/ chttp://genecards.bcgsc.bc.ca/ dhttp://snp500cancer.nci.nih.gov/home_1.cfm

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Potential functional variants were chosen from these genes according to the criteria: (a) a minor allele frequency ≥5% and heterozygosity ≥ 0.1 in Caucasians; and (b) >80% homology between

NIH-PA Author Manuscript NIH-PA Author Manuscripthuman NIH-PA Author Manuscript and rat/mouse genomes; or (c) located in exons (including untranslated regions), exon- intron junctions, or promoter regions; or (d) previous evidence indicating a significant functional effect; or (e) previous findings indicating associations with cancer risk or telomere function. Fifty-five genetic variants were selected at the beginning of the current study, and three of the SNPs were excluded because they were not in Hardy Weinberg equilibrium and minor allele frequency was <5%. Finally, 52 variants were evaluated in the final analyses.

Laboratory Methods Genomic DNA was isolated by standard phenol and chloroform/isoamyl alcohol extraction and RNase treatment as previously described (34) and genotyped on a BioTrove OpenArray™ system with TaqMan assays. For the BioTrove platform, DNAs (2ul, 200ng) were used to detect 32 SNPs in a plate with 3,072 through-holes arranged in a pattern of 96 sub-arrays. The PCR mixtures for 96 samples included 1× (144ul) TaqMan Universal PCR Master Mix (Applied Biosystems, Foster City, CA), 1% (14.4ul) Pluronic F38 (BioTrove, Woburn, MA), 0.5% (9.6ul) glycerol (Sigma–Aldrich, St. Louis, MO), 0.05 mg/ml (1.5ul) BSA (Sigma– Aldrich) and 5.0ul PCR grade water (Sigma–Aldrich). The OpenArray™ AutoLoader enables loading of the mixed solution (DNA and PCR mixture) onto an OpenArray™ plate from a 384- well plate. The PCR thermal cycling protocol consisted of 92°C for 10 min followed by 50 cycles of 92°C for 15s, 55°C for 1 min and 72°C for 1 min (imaging step). Following amplification, amplicon dissociation was measured by cooling the PCR array to 65°C then slowly heating to 92°C for 1°C per min, with images collected every 0.25°C.

The “Image” program was used to obtain the three genotyping clusters in the scatter plot (Supplemental Figure 1). Samples that failed to amplify were repeated, and samples that failed on the second run were scored as missing. SNPs that could not be well genotyped on the BioTrove OpenArray™ system were genotyped by TaqMan assays on 384 well plates (Supplemental Figure 2 showing one example of a TaqMan assay scatter plot). Genotype reproducibility was verified by randomly duplicated DNAs. The overall consistent rates were ranged from 96.4-97.7%. All genotyping was performed with the laboratory personnel blinded to the subject's case-control status.

Telomere length was measure by a quantitative PCR (Q-PCR) method described by Cawthon (35), and data has been reported previously (36).

Statistical Analysis Allele frequencies were calculated, and Hardy-Weinberg equilibrium determined for each SNP (37). Age at reference-adjusted logistic regression assessed associations of individual SNPs with breast cancer risk, and odds ratios (OR) and corresponding 95% confidence intervals (CI) were estimated (38). All SNPs were first evaluated by a co-dominant (additive) model. If the estimated ORs for heterozygous and homozygous genotypes were in the same direction, a dominant model was also used. A recessive model was used only when the ORs for heterozygous and homozygous genotypes were in the opposite direction. Linkage disequilibrium (LD) structure and haplotype blocks (frequencies) were estimated for genes with data on at least 5 SNPs by the Expectation Maximization Algorithm (EM-algorithm) applied in Haploview (39). Bonferroni adjustment for multiple testing at the level of p<0.001 (0.05/52) was considered as significance. At the same time, a two-tailed significant level of 0.05 (permutation p-value) was used after 100,000 permutations corrected for multiple testing bias (39). Genetic variants showing case-control difference at the level of p<0.05 were further analyzed after stratification by menopausal, smoking status, BMI and telomere length. One way ANOVA was used to compare the means of telomere length across the various genotypes

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for each . The potential functions of significant SNPs were estimated by PupaSuite (Spanish National Genotyping Center, Valencia, Spain)e. NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript A variable was considered a confounder if the estimated OR for a main effect changed 10% or more when the covariate was included in the logistical regression model. A number of covariates (family history of breast cancer in a first-degree relative, history of benign breast disease, age at menarche, parity, lactation, months of lactation, age at first birth, number of miscarriages, history of fertility problems, use of contraceptives or hormone replacement therapy, alcohol drinking, race, education, religion and marital status) were evaluated, and no confounders were found. Therefore, only age-adjusted results are presented. All statistical analyses were completed using Statistical Analysis System 9.0 (SAS Institute, Cary, NC).

Results In single polymorphism analyses, there were a total of seven SNPs showing significant case- control differences at the level p<0.05 from the 52 tested (Table 1). The top three statistically significant SNPs under a dominant model were TERT-07 (rs2736109) with p=0.0004, and TERT-54 (rs3816659) and POT1-03 (rs33964002) with ps=0.01. The ORs were 1.56 (95%CI: 1.22-1.99) for the TERT-07 G-allele, 1.27 (95%CI: 1.05-1.52) for the TERT-54 T-allele and 0.79 (95%CI: 0.67-0.95) for the POT1-03 A-allele. One SNP (TERT-67 rs2853669) was statistically significant at a p value of 0.01 under a recessive model. The OR of the CC genotype was 0.69 (95%CI: 0.69-0.93) compared with one or two copies of the T-allele. However, only one SNP (TERT-07 rs2736109) still retained significance after Bonferroni adjustment for multiple testing at the level of p<0.001 (0.05/52). This finding was strengthened when we restricted the analysis to the subset of women who are Caucasian, who account for 94% of the current study subjects. The OR was 1.60 (95%CI: 1.24-2.05, p=0.0002) for the TERT-07 G- allele. Permutation analysis of 105 random replications showed similar results for the two TERT SNPs (TERT-07 rs2736109 and TERT-54 rs3816659), which achieved a statistically significant level of 0.05 (Figure 1).

Two haplotype blocks were constructed for TERT (Figure 2). Although no statistically significant haplotype was found in block 1, SNP TERT-07 (rs2736109) displayed a strong linkage disequilibrium (D′=0.91) with a functional SNP TERT-67 (rs2853669). Within block 2, a common haplotype containing the TERT-21 G–allele and TERT-54 T-allele showed a significant association with increased breast cancer risk (p=0.001), and 105 repeated permutation analysis confirmed this association with borderline significance (p=0.056). No other inferred haplotypes were associated with breast cancer risk (Figure 2).

Subgroups analyses showed that the ORs of the TERT-07 G-allele, TERT-54 T-allele and TERT-67 CC genotype for pre-menopausal women were, respectively, 1.48 (95%CI: 0.96-2.28), 1.47 (95%CI: 1.06-2.04) and 0.67 (95%CI: 0.42-1.09), which were not statistically significantly different from those for post-menopausal women (1.69 (95%CI: 1.24-2.29), 1.12 (95%CI: 0.89-1.41) and 0.69 (95%CI: 0.47-1.00), respectively). This result indicates that there is no heterogeneity for breast cancer risk by menopausal status (Table 2). The increased breast cancer risk observed for the TERT-07 G-allele among the shortened telomere length subgroup was statistically significant (OR=1.81, 95%CI: 1.25-2.61), but did not reach significance for the subgroup with telomere length above the median (OR=1.36, 95%CI: 0.97-1.92). Therefore, there was no heterogeneity in breast cancer risk by telomere length status (Table 3). Similarly, no effect modifications between those variant alleles and breast cancer risk were observed for subgroups stratified by cigarette smoking, BMI status and family history (data not shown).

ehttp://pupasuite.bioinfo.cipf.es/

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Discussion To the best of our knowledge, this is the largest association study exploring genetic variants NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript in the telomere pathway (52 SNPs among nine genes) and breast cancer risk. Our results provide evidence to support the association of genetic polymorphisms in telomere pathway genes and breast cancer risk. Four SNPs (p≤0.01) in TERT (rs2736109, rs2853669, rs3816659) and POT1 (rs33964002) were significantly related to overall breast cancer risk under dominant or recessive models. One of the SNPs (TERT-07 rs2736109) still retained significance after a 105 repeated permutation tests (p<0.05) and the conservative Bonferroni adjustment for multiple testing at the level of p<0.001. With a moderate sample size (1,067 cases and 1,110 controls) for a genetic association study and the high frequencies (30.5-62.3%) of the four significant variant alleles in the current study, we have reasonable power to determine the main effects of TERT and POT1 variants on breast cancer predisposition.

Human telomerase reverse transcriptase (TERT) is an important catalytic subunit of telomerase and determines telomerase activity (40-42). TERT, located at 5p15.33, includes 16 exons with at least 508 known SNPs. Two functional SNPs (TERT-08 rs2735940 and TERT-67 rs2853669) have been found within the promoter region (T/C transitions at 1381bp and 244bp upstream of the transcription-starting site ATG) (22;23). The TERT-08 CC genotype had lower telomerase activity and was associated with shorter telomere length among healthy Japanese and coronary artery disease patients compared with T-allele carriers (22;43). However, this association was not observed in a Swedish population study (25). A previous study among Polish women observed that carrying the TERT-08 TT genotype has no overall relationship with breast cancer risk (OR=0.98, 95%CI: 0.83-1.15), but a decreased risk was observed for individuals with a family history of breast cancer (OR=0.73, 95%CI: 0.53-1.00) (26). Our data did not show any significant genotype-breast cancer association for this SNP, and also no genotype-family history interaction was observed. In a recent study of 66 non- small cell lung cancer tissues, telomerase activity was significantly decreased in carriers of the TERT-67 CC genotype compared to those with the TT genotype (p=0.03), while telomere length was longer in those with the CC compared to TT genotype, but it did not reach statistical significance (p=0.06) (23). Our results for this SNP indicated that the CC genotype was correlated with a significant decreased breast cancer risk (OR=0.69, 95%CI: 0.69-0.93), but this association was not modified by breast cancer family history as found by a previous study (26). It is consistent with a recent observation that TERT-67 CC genotype was significantly associated with decreased breast cancer risk (OR=0.65, 95%CI: 0.46-0.92) in a Swedish population (44). This result is supported by bioinformatics functional analysis (PupaSuite), which indicates that the TERT-67 variant allele disrupts transcription factor binding sites, presumably altering the activity of telomerase.

Until now, no experimental functional data have been reported for TERT-07 (rs2736109) and TERT-54 (rs3816659) that had significant positive associations with increased breast cancer risk under a dominant model in the current study. Bioinformatics PupaSuite exploration also did not indicate any potential functions. TERT-07, with the most significant p-value in mono- variable analysis, is sited within the gene's promoter region and located in the same haplotype block as TERT-67, a known functional SNP. A strong linkage disequilibrium (D′=0.91) was observed between TERT-07 and TERT-67 (Figure 2), indicating a potentially functional complementation on modification of telomerase function and breast cancer risk. A recent GWA study including 29,603 cancer cases and 45,846 controls found TERT-01 SNP (rs2736098) was significantly associated with increased risks for basal cell carcinoma, bladder, lung and prostate cancers (ORs ranged from 1.13-1.21, p<1.3×10-4) (45). Other GWA studies observed that a TERT-69 SNP (rs2736100) was significantly related with increased risks for lung cancer (OR=1.18, 95%CI: 1.10-1.26, p=4×10-6) (46), glioma (OR=1.27, 95%CI: 1.19–1.37, p=1.5×10-17) (47) and lung fibrosis (OR=2.11, 95%CI: 1.61-2.78, p=2.9×10-8) (48). Because

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the most significant SNP (TERT-07) found in the current study has no available genotyping data in the HapMap project, it is difficult to obtain the direct linkage disequilibrium parameters

NIH-PA Author Manuscript NIH-PA Author Manuscriptfor this NIH-PA Author Manuscript SNP and the SNPs (TERT-01 and TERT-69) showing significance in GWA studies. We downloaded a Caucasian dataset (22 subjects) from the website of Genome Variation Serverf that contains the three SNPs to estimate the LD parameters. A strong linkage disequilibrium was found between TERT-07 and TERT-01 (D′=0.87, r2=0.57), but not for TERT-69. Whether these SNPs located within this narrow genomic region (about 11kb) have a similar etiologic role in breast tumorigenesis needs further evaluation.

That no significant interplay for the TERT-07 variant allele and telomere length on breast cancer risk was noted in the current study suggests that this variant allele is less likely to influence breast cancer risk by directly impacting telomere length. It is biologically plausible that when rapid shortening of telomere length is truly caused by this variant allele, the response of proliferating cells leads to immediate initiation of a feedback mechanism to increase telomerase activity, and sustain telomere function by extending telomere length (49;50). Therefore, an association between the TERT variant allele and shortened telomere length may be shielded, and unable to be detected easily. This is consistent with our observation of a detectable genotype-outcome (breast cancer) association, but without a genotype-phenotype (telomere length) connection. However, the exact underlying mechanisms require further laboratory functional validation or determination of combined biomarkers in the telomere pathway (global or chromosome-specific telomere lengths, activities of telomerase components and telomere- proteins expression) to clarify.

Another functional genetic variation in TERT has been found (MNS16A), which is a 23bp (or 26bp) tandem repeat sequence TCC TCT TAT (cat) CTC CCA GTC TCA TC in the putative promoter region of the anti-sense RNA transcript (24). The short (S) allele of MNS16A has been associated with increased expression of hTERT mRNA in telomerase positive cell lines and primary lung cancer tissues (24). A recent study observed that carrying the variant S allele was associated with significantly increased breast cancer risk (OR= 1.50, 95%CI: 1.15–1.96) among Chinese women (51). We found no significant relationship between the S allele and breast cancer predisposition (OR=1.05, 95%CI: 0.89-1.25), and a more diversified distribution of MNS16A genotypes (9 alleles) in the current study. This is consistent with a report on a Caucasian case-control study of malignant gliomas (10 alleles) (52), but different from a breast cancer study in Chinese women (only 4 alleles) (51). These data indicate that the ethnic background might have a significant influence on the association of telomere genetic variation and breast cancer.

Little is known about the impact of POT1 genetic variation on telomere function and cancer risk. Although POT1 might function as a negative regulator of telomere length by directly inhibiting telomerase activity or controlling telomeric DNA substrate access to telomerase in human cells (53;54), two previous population studies did not observe any association between POT1 polymorphisms and breast or lung cancer (26;55). Our study, for the first time, provides some evidence that several POT1 polymorphisms (rs7794637, rs33964002, rs7784168 and rs10250202) might have main effects on breast cancer risk. However, data on these SNPs did not reach statistical significance for the 105 permutation analysis or a more conservative Bonferroni multiple testing. Functional evaluation using PupaSuite also did not note any functionality. Therefore, these findings should be interpreted with caution until laboratory functional validation or independent replication in a population study is obtained.

The strengths of current study include the population-based study design with a relatively large sample size; a moderate number of SNPs within the same pathway examined and an

fhttp://gvs.gs.washington.edu/GVS/

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intermediate phenotype marker (telomere length) used. The extensive information on known breast cancer risk factors and other co-variables obtained from questionnaires allowed us to

NIH-PA Author Manuscript NIH-PA Author Manuscriptcontrol NIH-PA Author Manuscript for potential confounders and evaluate effect modifications in the data analysis. By analyzing SNPs in telomere pathway genes, we identified one promising candidate gene (TERT) whose role should be confirmed in further independent replication studies. At the same time, a fine mapping study with high-density SNPs within the target region also would be helpful in identifying the causal variants for sporadic breast cancer. In addition to genetic variants, epigenetic alterations, especially telomere specific gene hypermethylation and hypomethylation in subtelomeric regions, are also involved in the regulation of telomerase activity and telomere length maintenance. Our inability to evaluate these potential genetic- epigenetic modifications during breast cancer development is one of the limitations of the current study. Furthermore, we had no data on telomerase activity that might impact breast cancer risk by modifying telomere length or genetic variants. Due to the multiple comparisons in our data analysis, and the lack of an independent study to provide additional supportive evidence, we also could not completely rule out the possibility of false positive findings. However, using the Bonferroni adjustment and permutation analyses whenever feasible, we should have minimized this possibility.

In conclusion, our study identified a few promising SNPs in telomere pathway genes that are potentially associated with breast cancer risk, although the OR for each SNP was modest in magnitude. These findings provide additional data to support the hypothesis that breast cancer is a polygenic trait with multiple pathway abnormalities. If replicated by additional population studies, it will delineate a comprehensive picture on the etiological role of telomere pathway genes in breast cancer predisposition, and has significant clinical applications in identifying high-risk individuals and improving early diagnosis.

Supplementary Material Refer to Web version on PubMed Central for supplementary material.

Acknowledgments

Grant support: National Cancer Institute and National Institute of Environmental Health Sciences grants R03CA125768, U01CA/ES66572, P30ES009089 and P30ES10126; and awards from the Breast Cancer Research Foundation, and Women At Risk (WAR).

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Figure 1. Results from 105 permutation tests for 4 promising SNPs of TERT. Two SNPs (TERT-07 rs2736109 and TERT-54 rs3816659) showed statistically significant associations with breast cancer risk (permutation p<0.05).

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Figure 2. A. TERT gene haplotype blocks. Two haplotype blocks were constructed for TERT. Within block 1, SNP TERT-07 (rs2736109), with the most significant p-value in mono-variable analysis, showed a strong linkage disequilibrium (D′=0.91) with a functional SNP TERT-67 (rs2853669). Two SNPs of TERT-01 (rs2736098) and TERT-69 (rs2736100) significantly related with several cancer risks in recent GWA studies, were located near the haplotype block 1 (1,263 to 8,833bp away). B. TERT common haplotypes and breast cancer risk after 105 permutation tests. Haplotype GT within block 2 showed a borderline significant permutation p value.

Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1. Shen et al. Page 14 0.04 0.01 0.02 0.01 0.05 0.01 -value 0.0004 p NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript * 1.0 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) OR (95%CI) 0.83 (0.70-0.99) 0.79 (0.67-0.95) 0.82 (0.69-0.97) 1.56 (1.22-1.99) 1.27 (1.05-1.52) 1.29 (1.00-1.65) 0.69 (0.52-0.93) <0.05), Long Island Breast Cancer Study Project, p Controls 460 (43.9) 587 (56.1) 460 (43.3) 603 (56.7) 467 (43.8) 599 (56.2) 194 (18.4) 860 (81.6) 395 (37.3) 663 (62.7) 939 (87.5) 134 (12.5) 954 (88.2) 128 (11.8) Table 1 Cases 86 (8.3) 470 (48.0) 510 (52.0) 482 (48.5) 511 (51.5) 482 (48.4) 515 (51.6) 125 (12.7) 858 (87.3) 317 (32.1) 670 (67.9) 849 (84.7) 153 (15.3) 948 (91.7) CC CC GG GG AA AA GG CT/TT TT/TC TT/TG GA/AA GA/AA AG/GG AG/GG Genotype rs # rs7794637 rs7784168 rs2736109 rs3816659 rs2853669 rs33964002 rs10250202 †

‡ Gene TERT TERT POT1 POT1 Dominant model Recessive model Age adjusted OR Under dominant model if the ORs for heterozygous and homozygous genotypes were in same direction. Under recessive model if the ORs for heterozygous and homozygous genotypes were in opposite direction. 1996-1997 Overall effect for single SNP of telomere pathway genes on breast cancer risk (only showing with * † ‡

Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1. Shen et al. Page 15 0.09 0.07 0.06 0.08 0.02 0.44 0.10 0.36 0.11 0.28 -value 0.001 p NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript * 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) OR (95%CI) 0.77 (0.56-1.04) 0.76 (0.56-1.03) 0.74 (0.54-1.01) 1.48 (0.96-2.28) 1.47 (1.06-2.04) 1.19 (0.77-1.83) 0.67 (0.42-1.09) 0.90 (0.72-1.13) 0.84 (0.67-1.04) 0.89 (0.71-1.10) 1.69 (1.24-2.29) 62 (17.4) 49 (13.5) 49 (13.4) 158 (44.9) 194 (55.1) 157 (44.2) 198 (55.8) 158 (44.4) 198 (55.6) 293 (82.5) 137 (38.5) 219 (61.5) 313 (86.5) 317 (86.6) 284 (43.7) 366 (56.3) 284 (42.8) 379 (57.2) 291 (43.8) 374 (56.2) 127 (19.4) 527 (80.6) 240 (36.5) Controls N (%) Table 2 32 (9.6) 42 (13.4) 95 (30.4) 49 (15.4) 80 (12.4) 160 (51.6) 150 (48.4) 162 (51.3) 154 (48.7) 164 (51.9) 152 (48.1) 272 (86.6) 218 (69.6) 269 (84.6) 300 (90.4) 296 (45.8) 351 (54.2) 306 (46.8) 348 (53.2) 304 (46.2) 354 (53.8) 567 (87.6) 220 (33.9) Cases N (%) CC CC CC GG GG AA AA GG GG GG AA AA CT/TT TT/TC TT/TG GA/AA GA/AA AG/GG AG/GG GA/AA GA/AA AG/GG AG/GG Genotype Recessive model Dominant model Dominant model rs # rs7794637 rs7784168 rs2736109 rs3816659 rs2853669 rs7794637 rs7784168 rs2736109 rs3816659 rs33964002 rs10250202 rs33964002 Gene TERT TERT TERT POT1 POT1 POT1 Pre-menopausal Women Post-menopausal Women Effect of single SNP in telomere pathway genes on breast cancer risk by menopausal status, Long Island Breast Cancer Study Project, 1996-1997

Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1. Shen et al. Page 16 0.32 0.10 0.05 -value p NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript * 1.00 (ref) 1.00 (ref) OR (95%CI) 1.12 (0.89-1.41) 1.31 (0.95-1.79) 0.69 (0.47-1.00) 82 (12.3) 74 (11.1) 417 (63.5) 585 (87.7) 596 (88.9) Controls N (%) 52 (7.7) 430 (66.1) 560 (84.9) 100 (15.1) 625 (92.3) Cases N (%) CC GG CT/TT TT/TC TT/TG Genotype Recessive model rs # rs2853669 rs10250202 Gene TERT POT1 Age adjusted OR *

Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1. Shen et al. Page 17 0.30 0.09 0.13 0.08 0.10 0.09 0.14 0.07 0.06 0.10 -value 0.002 p NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript * 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) 1.00 (ref) OR (95%CI) 0.88 (0.68-1.13) 0.80 (0.62-1.03) 0.83 (0.64-1.06) 1.36 (0.97-1.92) 1.25 (0.96-1.62) 1.37 (0.95-1.98) 0.74 (0.49-1.11) 0.80 (0.62-1.02) 0.78 (0.61-1.01) 0.81 (0.63-1.04) 1.81 (1.25-2.61) 95 (18.5) 62 (11.8) 64 (12.0) 93 (18.2) 221 (43.2) 290 (56.8) 221 (42.2) 303 (57.8) 223 (42.6) 301 (57.4) 420 (81.5) 200 (38.9) 314 (61.1) 461 (88.2) 470 (88.0) 227 (44.7) 281 (55.3) 227 (44.5) 283 (55.5) 232 (45.3) 280 (54.7) 418 (81.8) 183 (35.4) Controls N (%) Table 3 47 (9.2) 71 (14.6) 76 (15.4) 52 (11.0) 220 (45.7) 261 (54.3) 228 (46.7) 260 (53.3) 229 (46.5) 263 (53.5) 414 (85.4) 166 (34.1) 321 (65.9) 418 (84.6) 464 (90.8) 239 (50.3) 236 (49.7) 243 (50.5) 238 (49.5) 242 (50.4) 238 (49.6) 423 (89.0) 144 (30.2) Cases N (%) CC CC CC GG GG AA AA GG GG GG AA AA CT/TT TT/TC TT/TG GA/AA GA/AA AG/GG AG/GG GA/AA GA/AA AG/GG AG/GG Genotype Recessive model Dominant model Dominant model rs # rs7794637 rs7784168 rs2736109 rs3816659 rs2853669 rs7794637 rs7784168 rs2736109 rs3816659 rs33964002 rs10250202 rs33964002 median ≥ Gene TERT TERT TERT POT1 POT1 POT1 Telomere length Telomere length < median Effect of single SNP in telomere pathway genes on breast cancer risk by length status, Long Island Breast Cancer Study Project, 1996-1997

Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1. Shen et al. Page 18 0.08 0.38 0.02 -value p NIH-PA Author Manuscript NIH-PA Author Manuscript NIH-PA Author Manuscript * 1.00 (ref) 1.00 (ref) OR (95%CI) 1.27 (0.97-1.65) 1.17 (0.82-1.68) 0.60 (0.39-0.92) 68 (13.0) 62 (11.8) 334 (64.6) 453 (87.0) 464 (88.2) Controls N (%) 37 (7.4) 72 (14.9) 333 (69.8) 411 (85.1) 465 (92.6) Cases N (%) CC GG CT/TT TT/TC TT/TG Genotype Recessive model rs # rs2853669 rs10250202 Gene TERT POT1 Age adjusted OR *

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