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Epidemiology and Prevention |
Departments of 1 Environmental Health Sciences and 2 Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
Requests for reprints: Jing Shen, Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, 630 West 168th Street, P&S 19-418, New York, NY 10032. Phone: 212-305-8158; Fax: 212-305-5328; E-mail: js2182{at}columbia.edu.
| Abstract |
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| Introduction |
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Several studies examining telomere length in humans using Southern blot telomere restriction fragment (TRF) analysis found that breast carcinomas had shorter telomeres than normal breast tissue; high grade (grade III of III) invasive carcinomas had shorter telomeres than low grade (grade I of III) invasive carcinomas (19, 20). Dysfunctional telomeres are considered an early initiating event in breast cancer development, inducing chromosomal instability (18, 21). However, results are mixed with respect to associations between tumor telomere length and clinicopathologic features, such as histologic grade, tumor size, lymph node status, or hormone receptor status (19, 22, 23). Only two studies suggested that short telomeres are associated with smoking-related cancer risk (3, 17). Thus far, the relationship between telomere length and breast cancer susceptibility has not been reported. We hypothesized that individuals with shorter telomeres have a higher susceptibility for developing breast cancer.
| Materials and Methods |
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45 years; (d) any male with breast cancer; and (e) a known BRCA mutation. Epidemiology and family history questionnaires were administered to each consenting, participating family member on recruitment into the Registry and collected information on demographics, ethnicity, history of all cancers, smoking and alcohol consumption, reproductive history, hormone use, weight, height, and physical activity. A self-administered dietary questionnaire was also provided with return by mail. In addition, a sample of peripheral blood was collected from participants. The present study included 268 family sets (287 breast cancer cases and 350 sister controls) from families in the MNYR with at least two sisters discordant for breast cancer. Laboratory methods. Genomic DNA was extracted from white blood cells by the salting out procedure. White blood cells were lysed with SDS (final concentration 0.66% SDS) in a nuclei lysis buffer and treated with RNase A (final 133 µg/mL) and RNase T1 (final 20 units/mL) to remove RNA. Proteins were coprecipitation with NaCl (330 µL of saturated NaCl added per 1 mL solution) by centrifugation. Genomic DNA was recovered from the supernatant by precipitation with 100% ethanol, washed in 70% ethanol, and dissolved in the Tris-EDTA buffer. Telomere length quantification was done with the quantitative PCR (Q-PCR) method described by Cawthon (25). Telomere length measurement by the Q-PCR assay involved determining the relative ratio of telomere (T) repeat copy number to a single copy gene (S) copy number (T/S ratio) in experimental samples using standard curves. This ratio is proportional to the average telomere length. Then, the ratio for each sample was normalized to a reference DNA to standardize between different runs. 36B4, encoding acidic ribosomal phosphoprotein P0 was used as the single copy gene. Telomere and 36B4 gene PCRs were always done in separate 96 wells with each sample run in duplicate. Further modifications to the protocol were as follows: two master mixes of PCR reagents were prepared, one with telomere primer pairs (Tel-1, 5'-GGTTTTTGAGGGTGAGGGTGAGGGTGAGGGTGAGGGT-3'; Tel-2, 5'-TCCCGACTATCCCTATCCCTATCCCTATCCCTATCCCTA-3') and the other with 36B4 primer pairs (36B4u, 5'-CAGCAAGTGGGAAGGTGTAATCC-3'; 36B4d, 5'-CCCATTCTATCATCAACGGGTACAA-3') with the same final concentration (2.4 nmol/L). An aliquot of 25 ng (5 µL) template DNA was added to each reaction containing 12.5 µL SYBR Green PCR Master Mix (Applied Biosystems) and 7.5 µL primers mixture. The DNA quantity standards were serial dilutions of a reference DNA sample (a mixture of several unknown DNAs) to produce five final concentrations (0.4, 0.8, 1.2, 1.6, and 2.0 ng/µL). In each run, a standard curve and a negative control (water) were included. The PCR was done on a real-time PCR instrument (ABI 7500, Applied Biosystems). The thermal cycling profile for the telomere amplification was 95°C for 10 min followed by 30 cycles of 95°C for 15 s and 54°C for 2 min and for the 36B4 amplification was 95°C for 10 min followed by 40 cycles of 95°C for 15 s and 60°C for 1 min. Following amplification, a dissociation curve was done to confirm the specificity of the reaction. Standard and dissociation curves were generated with the ABI Prism 7500 SDS software. R2 for each standard curve was >0.98. The assay was done with the laboratory personnel blinded to the subject's case-control status. Evaluation of the variation of the Q-PCR method among 40 duplicated samples indicated that most of the data varied within the 95% confidence intervals (95% CI) of the mean (data not shown). The Pearson and Spearman correlation coefficients were 0.50 (P < 0.001) and 0.47 (P < 0.002), respectively. The intrabatch and interbatch variability [coefficient of variation (CV)] in present study was 19% and 28%, respectively.
Statistical methods. Telomere length was analyzed as a continuous variable and a categorical variable. ANOVA was used to determine the differences in telomere length as a continuous variable by case-control status, age group at blood donation (<40, 4049, 5059, and
60 years old), body mass index (BMI; <25 and
25), smoking history (never and ever), cigarette smoking per day (<10 and
10), and smoking pack-years (<7 and
7). Medians in controls were used to categorize the intervals of BMI, cigarettes per day, and pack-years. As a categorical variable, short telomeres were defined as less than the median (0.70) telomere length in controls, and
2 tests were used to assess case-control differences in frequencies of short telomeres. Quartiles of telomere length, based on control values (Q1,
0.96; Q2, 0.700.95; Q3, 0.490.69; and Q4, <0.49), were used to evaluate the dose-response. Because age might modify the association between telomere length and breast cancer risk, we further analyzed telomere-breast cancer relationships separately in two subgroups stratified by menopausal status. All analyses were stratified by family sets through conditional logistic regression with SAS version 9.0 (SAS Institute) to estimate the strength of the associations as odds ratios (OR) and corresponding 95% CI. All models were adjusted by age of blood donation and smoking status.
| Results |
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0.96) as the referent group, the percentage of subjects in quartiles Q2, Q3, and Q4 were, respectively, 24.4%, 25.4%, and 28.6% in cases and 25.3%, 24.8%, and 24.8% in controls. The adjusted ORs for breast cancer increased from 1.35 (95% CI, 0.792.29) to 1.47 (95% CI, 0.862.52) to 1.55 (95% CI, 0.882.73) as telomere length shortened from 0.96 to <0.49, but no statistically significant dose-response was observed (Ptrend = 0.14). The relationships between telomere length and breast cancer in subgroups categorized by menopausal status are shown in Table 4
. Increased breast cancer risk for shorter telomeres was noted only in premenopausal women, although the association did not reach statistical significance. The adjusted OR in premenopausal women was 1.37 (95% CI, 0.702.71), similar to the nonsignificant OR observed among all women (1.26). The dose-response effect of shortened telomere length for increased breast cancer risk was more pronounced in premenopausal women. The adjusted ORs were, respectively, 1.65, 1.59, and 2.09 for Q2, Q3, and Q4 but still did not reach statistical significance (Ptrend = 0.17).
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| Discussion |
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Our results are biologically plausible and consistent with most previous studies exploring the relationship between telomere length and genomic instability or tumorigenesis using in vivo or in vitro experiments with highly sensitive cell lines or animals. The most important function of telomeres is maintaining genomic integrity and stability (2, 21). When telomeres are shortened to a critical length, the result is telomere dysfunction with no further cell division (30). Recently, Lin et al. (31) reviewed the dynamics of telomere length in different cancers. In tumor cells, telomere length has a wide range of variability, and its equilibrium depends on the balance between telomere shortening from cell division and telomere elongation that results from telomerase activity (32). Many previous experiments showed that tumor cells have extremely short and stable telomeres, and their stability is achieved by the activation of telomerase (33, 34). Other studies on telomere length and carcinogenesis indicated that telomere dysfunction (caused by telomere shortening) is a very early and prevalent genetic alteration acquired in the multistep process of malignant transformation (10, 18), and telomere shortening leads to increased frequencies of chromosome instability (35, 36). Animal studies have shown that mice with shorter telomeres have an increased incidence of tumors and enhanced risk of epithelial cancers due to the formation of complex nonreciprocal translocations (35, 37). Clinical observations of tumor tissues showed that telomere length in colorectal carcinoma patients is shorter than in normal controls and subjects with colonic polyps (38). Maruyama et al. (39) observed that telomere length in intestinal metaplasia cases is statistically significantly shorter than in normal controls, but the telomere length in gastric carcinoma cases has no significant difference compared with controls. Sommerfeld et al. (40) measured telomere length in matched samples of normal benign prostatic hyperplasia (BPH) and prostate cancer tissues taken from radical prostatectomies. The telomeres from prostate cancer tissues were significantly and consistently shorter than the telomeres from cells in either the adjacent normal or BPH tissues. These results can be explained by the two outcomes of telomere dysfunction in somatic cells, depending on the integrity of checkpoint mechanisms (21, 4143). On the one hand, when telomeres shorten to below a critical length due to cell division, cell division ceases and the cell undergoes either replicative senescence or apoptosis (44). On the other hand, if these two processes are bypassed, the cell continues to proliferate through activation of telomerase and genomic instability is initiated. The accumulated mutations, genetic lesions, and inactivated tumor suppressor checkpoints will ultimately result in cancer (1, 45). These data suggest that telomere shortening may be either a biomarker of susceptibility or resistance to cancer, depending on the balance of cellular checkpoint functions.
Overall, we did not observe significant relationships between telomere length and age at blood donation, BMI, smoking status, and smoking levels (cigarette per day and pack-years) either in cases or controls (Table 2), except for a marginally significant shortening of telomere length in controls with increasing age at blood donation. This result indicates a partial contribution of age at blood donation to telomere length, consistent with previous observations (46, 47). Valdes et al. reported a significant reverse dose-dependent relationship of telomere length with smoking pack-years among 1,122 White women ages 18 to 76 years. Another study found that cigarette smoking was associated with lower telomerase reverse transcriptase (hTERT) mRNA expression but had no detectable effect on telomere length (46). We did not observe inverse relationships between telomere length and cigarettes per day or pack-years, perhaps due to the small sample size with few heavy smokers 25% of the women smoked 20 or more pack-years. However, the different patterns for the telomere length-breast cancer relationship observed in never and ever smokers suggest that smoking may play a role in the process of telomere shortening.
The most widely used method to measure telomere length is TRF analysis. However, it suffers from several major drawbacks and is not high throughput, reducing its utility in epidemiologic studies. The Q-PCR assay, developed by Cawthon and used in present study, has the advantages of high throughput (96-well plates used) and high sensitivity (nanogram quantities of DNA can be analyzed). It also has relatively little variation because the measurement of telomeres by Q-PCR does not include the subtelomeric region, which is highly variable between individuals, from 2.5 to 6 kb (31). In addition, it is less affected by short telomeres and DNA quality (can be applied to degraded or fixed material; ref. 48). The means of telomere length and SEs in the present study are consistent with a prior study, but the CVs are higher than previously reported (47). This suggests that the Q-PCR method is reasonably reliable and useful in large-scale epidemiologic studies, although considerable variability exists, especially among different batches. To obtain more accurate and stable results in the future, triplicate or even quadruplicate assays might be useful for improving Q-PCR measurement of telomere length.
Measurement error may have occurred in categorizing subjects' telomere length by the Q-PCR assay because of the methodologic variability, but it should have randomly and equally affected cases and controls. Because sisters in the same family were assayed randomly, and the laboratory personnel were blinded to case-control status, any measurement error in the laboratory assay would be nondifferential and therefore likely bias the associations toward the null. The nondifferential measurement error cannot explain the positive trends we have observed here. Even if this bias was present, it should be of limited importance due to the increased ORs observed in those with much shorter telomere length (Q3 and Q4). Undiagnosed breast cancer cases might be included in controls, especially among the younger control sisters, and would produce misclassification of disease. This misclassification bias might underestimate the potential association between shorter telomere length and breast cancer risk. Although we have adjusted for age at blood donation and smoking status, potential confounders, in the analytic models, we cannot exclude residual confounding caused by unconsidered factors related to both the dynamics of telomere length and breast cancer risk in the present study. These factors, including oxidative stress, chronic inflammation, epigenetic modifications, and genetic polymorphisms in telomere-related genes, should be investigated in future studies to better understand the relationship between telomere length and breast cancer risk.
Compared with previous studies, our study has several advantages. One strength was the family-based design using sisters from the same families as cases and controls, which may be an efficient design in an association study compared with unrelated population controls (49). Any potential confounding related to population admixture was reduced, and some of the confounding due to differences in genetic susceptibility as well as behavioral and lifestyle factors that cluster within families was reduced. A major limitation is the case-control study design with telomere length measured in bloods collected after diagnosis of cancer eliminating our ability to determine the etiologic temporal sequence between telomere shortening and breast cancer risk. Previous reports, with small numbers of samples, are inconsistent on the role of chemotherapy or radiation treatment on telomere length (5052). Our results indicated that telomere length in cases who donated blood before diagnosis was not significantly different from that of cases who donated blood after diagnosis (P = 0.34), but their age of cancer diagnosis was not comparable (44.1 versus 51.6 years, respectively). Therefore, we cannot exclude the possible effect of treatment (chemotherapy or radiation) on telomere length based on the present data. Further investigation focused on this issue in a well-designed follow-up study is needed.
In conclusion, our data provided modest evidence that short telomere length is associated with increased breast cancer risk and that this relationship may be more pronounce in premenopausal women. However, because of the large uncertainty surrounding our point estimates, further studies using large cohorts are needed.
| Acknowledgments |
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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.
| Footnotes |
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Received 9/21/06. Revised 1/18/07. Accepted 3/27/07.
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