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Derald H. Ruttenberg Cancer Center, Mt. Sinai School of Medicine. New York, New York 10029 [H. F., C. B. A.]; Department of Epidemiology, School of Public Health [R. C. M., M. D. G.], Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599 [R. C. M., M. D. G., L. G. D.]; Department of Pathology, Roswell Park Cancer Institute, Buffalo, New York 14263 [J. G.]; and School of Public Health, Queensland University of Technology, Brisbane, QLD 4059, Australia [B. N.]
| Abstract |
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| Introduction |
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Laboratory studies indicate that both tobacco smoke carcinogens and ionizing radiation cause DNA damage, potentially increasing cancer risk if such mutations occur in critical regions of growth control genes, such as the tumor suppressor gene p53. p53 regulates cellular proliferation and apoptosis and may contribute to cancer when inactivated or altered by mutations or other mechanisms (17) . Mutational spectra analyses in lung tumors reveal associations between benzo(a)pyrene in tobacco smoke and signature p53 mutations, in particular G to T transversions at codons 157, 158, 248, and 273 (18, 19, 20) . Radiation exposure is associated with deletion and missense mutations (G to T transversions) in p53 in studies of lung tumors (21 , 22) and with impaired p53-mediated response to DNA damage in ataxia telangiectasia mutation carriers in breast cancer (23 , 24) .
The prevalence of p53 mutations in breast cancer is
30% (18
, 25) . The mutational spectra of breast cancer is similar to that of lung cancer in that they both exhibit high proportions of missense mutations, but the distribution and position of transversion and transition mutations differ (26)
. Conway et al. (27)
described recently the prevalence and spectrum of p53 mutations among a subset of cases from the CBCS3
(n = 456). A higher proportion of G to T transversion mutations were found in the breast tumors of current smokers compared with those of former and never smokers. Accumulation of the p53 protein is detected in
45% of breast cancers, suggesting that p53 function can be altered by mechanisms other than mutation (28
, 29)
. It is also possible for p53 mutations to occur outside of the sequenced region, which IHC protein staining will detect if the mutation results in stabilization (18)
. IHC detection of the p53 protein is more practical for large-scale epidemiological studies and may be useful in identifying factors that operate through a p53 pathway to influence breast cancer risk.
Subdividing breast cancers by p53 status may elucidate associations among smoking, low-dose ionizing radiation, and breast cancer risk (30) . Only two population-based, case-control studies of breast cancer have examined p53 protein expression in breast tumors with respect to etiology, and both focused on younger women (31 , 32) . The present analysis evaluated whether associations between environmental exposures such as cigarette smoking and low-dose ionizing radiation exposure differed for p53+ and p53- breast cancer in relation to controls in the CBCS, a large population-based study (n = 683) that included a diverse population 2074 years of age.
| Materials and Methods |
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Data were collected by trained nurse interviewers who administered a questionnaire at the participants home, took body size measurements, and drew a 30-ml blood sample. The questionnaire included assessment of each participants menstrual, reproductive, and contraceptive histories, first-degree family history of breast cancer, occupational history, exposure to occupational and medical ionizing radiation, and other lifestyle factors. Interviews were completed on 77% (n = 861) of eligible and locatable cases and 68% (n = 790) of eligible and locatable controls (36) . In the parent study, risk factors associated with slight increased risk of breast cancer included younger age at menarche, oral contraceptive use, history of breast or ovarian cancer in first-degree relatives, higher education level, former smoking status, and long-term smoking and low-dose ionizing radiation exposures. Ever having a full-term pregnancy, lactation among parous women, and higher body mass index were inversely associated with breast cancer overall; minor differences were observed when participants were stratified by race and/or menopausal status (7 , 37, 38, 39, 40) .
With informed patient consent, 738 tumor blocks containing invasive breast cancer (86%) were received from pathology departments from participating hospitals and processed by the CBCS. Hospital slides were retrieved for an additional 69 cases (8%), leaving 54 cases for whom no clinical specimen was obtained (6%). Blocks were sectioned according to the defined study protocol (41) , and case slides were assayed within 4 weeks of being sectioned. A total of 683 case slides (79%) were assayed for p53 protein expression using an IHC technique that uses an antibody with high sensitivity in paraffin-embedded tissues (DO7; DAKO, Glostrup, Denmark). Positive and negative control slides were included with each batch. Formalin-fixed, paraffin-embedded tissue sections were placed on coated slides and baked at 60°C for 1 h, deparaffinized in xylene, hydrated in descending alcohols, placed in an antigen retrieval Citra buffer (pH 6.0), and heated in a microwave oven to subboiling for 10 min. Normal horse serum blocking solution was subsequently applied to the cooled slides to block the sites to which the secondary antibody was expected to bind. The primary p53 mouse monoclonal antibody clone DO7 was applied to all of the slides and incubated in a humidity chamber for 1 h. Negative antibody control slides were incubated with nonspecific IgE under identical conditions. A secondary biotinylated antibody (horse, antimouse) application followed. An avidin-biotin complex application sought out the biotin from the secondary antibody and prepared the slides for the color deposit. The chromagen 3,3'-diaminobenzidine was used, and finally the slides were counterstained with hematoxylin.
Slides were read by the study pathologist (J. G.) who recorded detailed information on the intensity, localization and distribution of the protein stain. Cases were considered p53+ if dark nuclear protein staining was present in 10% or more of the invasive tumor cells; cases with <10% cells of dark, nuclear staining were considered p53-.
Race was classified according to self-report. Fewer than 2% of women described themselves as races other than African-American or white and were classified as white. Women were considered postmenopausal if they had undergone natural menopause, bilateral oophorectomy, or if they were 50 years and older and had ceased menstruating or were taking hormone replacement therapy. Participants were classified as smokers if they reporting smoking >100 cigarettes in their lifetime. Living with a smoker was regarded as passive smoking exposure. Exposure to low-dose ionizing radiation was captured by several variables including: chest X-ray before age 20 (yes/no), medical treatment-related radiation (yes/no for exposure anywhere in the body to monitor or treat a condition other than breast cancer such as scoliosis, chest fluoroscopy for tuberculosis, or kidney stones), and occupational exposure to ionizing radiation (based on participants report of two longest held jobs since age 18). The International Commission of Radiological Protection classification was used to classify jobs with potential exposure and included registered nurses, licensed practical nurses, medical doctors, and radiological technicians (40 , 42) .
2 statistics were used to test differences in proportions, using SAS 6.0 (43)
. Unconditional logistic regression was used to calculate ORs and 95% CIs for p53+ breast cancer cases and p53- breast cancer cases as compared with controls in relation to cigarette smoking and low-dose ionizing radiation exposure. PROC GENMOD was used to adjust for age (as an 11-level ordinal variable reflecting 5-year age categories), race (African-American or white), and to incorporate offset terms derived from sampling fractions used to identify eligible participants. Multivariable logistic regression models were used to adjust for potential confounding factors, although ORs were not altered significantly after adjustment for additional covariates. Therefore, ORs shown are adjusted only for design variables (age and race) and sampling fractions.
Tumor stage and hormone receptor status information was abstracted from the medical records of the cases. Tumor stage was evaluated as a multilevel variable based on the American Joint Classification of Cancer categories (44) . ER status was abstracted from medical records for the majority of the cases. For 11% of the cases, ER status was determined in our IHC laboratory using a positive cutpoint of 5% (45) . Case-case analyses (p53+ cases versus p53- cases) provided information about the magnitude of the degree of heterogeneity between the two disease subgroups (p53+ and p53- breast cancers) and permitted adjustment for tumor characteristics in the models (46) .
| Results |
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50% of premenopausal African-American and white cases had p53+ breast cancer, whereas
40% of postmenopausal cases were p53+.
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20 years to nonsmokers was 1.5 (95% CI, 1.12.1), whereas the corresponding OR for p53+ breast cancer was somewhat similar, although not statistically significant (1.3; 95% CI, 0.91.8). No dose-response patterns were noted across levels of smoking duration (total years smoked) or dose (packs/day). Accounting for passive smoking exposure did not reveal significant breast cancer heterogeneity by p53 status; ORs were similar for both case groups.
ORs were slightly higher for p53+ breast cancer than for p53- breast cancer with respect to exposure to certain sources of low-dose ionizing radiation. As shown in Table 3
, having a chest X-ray before the age of 20 was slightly associated with p53+ breast cancer but not p53- breast cancer. No association was observed for medical treatment-related ionizing radiation exposure and p53+ or p53- breast cancer, whereas occupational exposure to ionizing radiation was associated with ORs of 1.9 for both p53+ and p53- breast cancer. A variable representing whether participants had none, one, or two or more types of low-dose radiation exposure was constructed and examined in relation to p53 breast cancer subtypes. ORs were slightly higher for p53+ breast cancer than p53- breast cancer with respect to the number of sources of low-dose ionizing radiation exposure [p53+ ORs, 1.2 (95% CI, 0.91.7) for one source and 1.5 (95% CI, 0.82.6) for two or more sources; p53- ORs, 1.0 (95% CI, 0.81.3) and 1.3 (95% CI, 0.72.2), respectively]. Because this variable did not distinguish between sources of exposure, further analyses were conducted to determine the contributions of medical treatment-related, chest X-ray, and occupational radiation exposures. Exposure to both chest X-ray and occupational radiation was more strongly associated with p53+ than p53- breast cancer relative to no exposure (p53+ OR, 2.2; 95% CI, 1.05.3; and p53- OR, 1.3; 95% CI, 0.53.4). The combination of medical treatment-related ionizing radiation and occupational exposure resulted in ORs for p53+ breast cancer that were higher in magnitude (OR, 3.7; 95% CI, 0.816.8) than for p53- breast cancer (OR, 1.7; 95% CI, 0.310.5) also. This pattern did not persist when medical treatment-related radiation and chest X-rays were evaluated together. Adjustment for stage and ER status did not substantially alter any of the risk estimates for smoking or low-dose radiation exposure in case-only analyses.
| Discussion |
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The relationship between low-dose ionizing radiation exposure and p53+ and p53- breast cancers has not been reported previously. High-dose radiation exposure, such as that endured by Hiroshima survivors, is associated with increased risk of breast cancer (16) . Evidence also exists to indicate a higher breast cancer incidence and mortality among women who underwent diagnostic or therapeutic irradiation for a variety of conditions including benign breast disease, enlarged thymus, scoliosis, and postpartum mastitis, especially during adolescence (50, 51, 52, 53, 54) . It is possible that the elevated ORs for p53+ breast cancer associated with low-dose ionizing radiation exposure is identifying carriers of ataxia telangiectasia mutations who are extremely radiosensitive or individuals who have inefficient DNA repair capabilities.
The ionizing radiation variables that were evaluated in this population-based study included those deriving from medical procedures (such as chest X-rays), medical treatment (such as irradiation for an enlarged thymus), and those obtained while on the job. In addition, we evaluated whether multiple sources of radiation exposure influenced development of p53+ and p53- breast cancer. Admittedly, sample sizes diminished quickly, and confidence intervals were wide and overlapping; results therefore are regarded as preliminary. Nevertheless, it is possible that low-dose ionizing radiation influences breast cancer risk by adversely affecting the p53 gene, and OR patterns are generally supportive of this idea.
Because the breast is hypothesized to be especially susceptible to DNA damage during puberty when cells are rapidly dividing (16 , 55) , we examined whether exposure to chest X-rays before the age of 20 increased risk for p53+ or p53- breast cancer. The proportion of cases reporting a chest X-ray before age 20 was higher among p53+ cases than p53- cases and controls, resulting in a slight positive association. However, the reference group was heterogeneous, consisting of those never exposed to a chest X-ray and those who reported having a chest X-ray sometime after age 20. If radiation exposure exerts a deleterious effect on the p53 gene, it is possible that the OR for p53+ breast cancer is underestimated because the reference group contains women with the exposure.
Occupational exposure to radiation was associated with a doubling of risk for both p53+ and p53- breast cancer. When occupational exposure was combined with medical treatment-related radiation exposure or chest X-ray exposure, higher ORs were observed for p53+ breast cancer. This pattern was not seen when chest X-rays and medical treatment radiation were combined. The basis for this apparent cumulative effect is not clear, and because of the relatively small numbers in key strata, it is not possible to analyze this interaction further. Moreover, for most comparisons, confidence intervals overlap, and hence the radiation from medical sources may not be increasing risk of p53+ breast cancer beyond that experienced from occupational exposure.
Two previous studies examined the relationship between smoking and breast cancer by p53 expression status. Our findings differ from Gammon et al. (32)
, who noted a positive association between current smoking and p53+ breast cancer in their study of breast cancer among women <45 years (p53+ OR, 1.29; 95% CI, 0.792.11; p53- OR, 0.66; 95% CI, 0.411.06; ratio of the ORs, 1.96; 95% CI, 1.103.52). van der Kooy et al. (31)
also reported an elevated OR for p53+ breast cancer for current smokers (p53+ OR, 1.4; 95% CI, 0.92.2; p53- OR, 0.9; 95% CI, 0.61.4) in their population-based study of younger women. Our results also differ from the conclusions of Conway et al. (27)
, who evaluated the prevalence and mutational spectrum of p53 mutations in relation to smoking exposure in a subset of cases used in this analysis. They reported a higher prevalence of G
T transversion mutations in p53 in the breast tumors of current smokers (5.9%) compared with never smokers (0.9%), with little difference for other types of mutations.
It is not clear why our results differ from the previous studies. Despite similar p53+ prevalences and even when analyses were restricted to younger women, no associations between smoking and p53+ breast cancer were observed in our study. It is possible that genetic differences in metabolism and detoxification of tobacco smoke carcinogens between study populations contribute to the disparate findings. However, as noted by Gammon et al., it is also possible their results were attributable to chance because no dose-response relationships were observed. The results of van der Kooy et al. (32) are even less convincing of a difference between p53+ and p53- breast cancer (31) . A potential explanation for the discordance between our findings and those of Conway et al. (27) is the low prevalence of the transversion mutations and the lack of specificity of the IHC technique. Only 5.9% (5 of 85) of the cases who were current smokers in Conways study revealed G to T transversion mutations in p53, whereas in this study, 17.7% (56/317) of the cases who were current smokers were classified as p53+ using IHC. Thus, the cases whose tumors stained positive for p53 as a result of other molecular mechanisms than mutation may be obscuring the association noted by Conway et al. (27) .
Our findings should be interpreted in light of the studys limitations. Although size of the CBCS was nearly twice as large as either of the other studies, sample sizes were diminished after stratification of cases by p53 status and across multiple levels of exposure. This resulted in wide confidence limits for some variables. Additionally, p53 data were not available for all of the cases who contributed questionnaire information. However, it is unlikely that nonresponse to the study was related to p53 status; cases missing p53 information differed little from those with information.
Limitations resulting from IHC classification of p53 status must be acknowledged. Only one tumor slide was assayed per case, which may not adequately capture tumor tissue heterogeneity (56)
. Additionally, tumor specimens were retrieved from 26 participating hospitals, where potential variation in quality of fixation could have affected p53 staining results, probably lowering the proportion of p53+ tumors. However, the proportion of p53+ cases was similar to that of previous studies. Most importantly, IHC will not detect p53mutations that are so severe that no protein is made (18)
. An example of such a mutation is a deletion. Because
7% of the CBCS cases had tumors containing deletion mutations in p53, the potential for misclassification by IHC is high in this group (27)
. Ionizing radiation exposure is associated with point mutations as well as p53 deletions, which might result in misclassification among exposed cases. Cases with deletions were likely classified as p53- (because no protein is made), despite having an abnormality in the gene. This type of misclassification error may have attenuated the ORs for p53+ breast cancer and elevated associations for p53- breast cancer.
Strengths of this study include its population-based design with representation of younger and older women and the comprehensive questionnaire that included low-dose ionizing radiation exposure assessment. The tumor block acquisition rates were high, and immunostaining of p53 status enabled a larger sample size of cases to be evaluated with respect to several exposures.
In conclusion, the results from this study provide little evidence for breast cancer heterogeneity as classified by p53 expression status in relation to environmental exposures. Our findings of increased risk of p53+ breast cancer among women exposed to multiple sources of low-dose ionizing radiation exposure should be evaluated further. To elucidate specific mechanisms behind exposures believed to adversely affect the p53 gene, analyses involving genetic sequencing could be performed.
| Acknowledgments |
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| Footnotes |
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1 This study was supported by funding for a Specialized Program of Research Excellence in Breast Cancer Grant NCI P50-CA 58223. ![]()
2 To whom requests for reprints should be addressed, at Derald H. Ruttenberg Cancer Center, Mt. Sinai School of Medicine, One Gustave L. Levy Place, Box 1130, New York, NY 10029-6574. Phone: (212) 659-5523; Fax: (212) 849-2564. ![]()
3 The abbreviations used are: CBCS, Carolina Breast Cancer Study; OR, odds ratio; CI, confidence interval; IHC, immunohistochemistry; ER, estrogen receptor. ![]()
Received 12/31/01; revised 5/31/02; accepted 6/ 5/02.
| References |
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