1 Department of Epidemiology, Yale University School of Public Health, New Haven, CT
2 Yale Cancer Center, Yale University, New Haven, CT.
3 Department of Environmental Health, Colorado State University, Fort Collins, CO.
4 Division of Epidemiology and Statistics, European Institute of Oncology, Milan, Italy.
5 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD.
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ABSTRACT |
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breast neoplasms; case-control studies; polychlorinated biphenyls; women's health
Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio; PCBs, polychlorinated biphenyls; ppb, parts per billion
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INTRODUCTION |
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The rationale for examining the association by specific congeners is evident from experimental studies. Studies show that both hormonal and nonhormonal effects of PCBs are structure dependent (1520
). For example, as summarized by Safe (17
) and Wolff and Toniolo (18
), nonplanar PCB congeners with chlorine substitutions in orthopositions (two and six substitutions) were shown to have estrogenic activity such as increasing uterine weight, causing precocious puberty in rats, and enhancing proliferation of MCF-7 breast tumor cells. Some highly substituted PCBs (with both two and four substitutions) are also considered to have weak estrogenic activity.
On the other hand, coplanar congeners whose orthopositions have no (or only one or two) chlorine substitutions are structurally similar to 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD or dioxin). These congeners are thought to bind to the aryl hydrocarbon receptor, thus eliciting dioxinlike properties such as antiestrogenic activity (17, 18
). The antiestrogenic effects of these congeners could thus counteract some estrogenic effects induced by the estrogenic PCB congeners.
Studies also suggest that PCBs have different enzyme inducibility. PCB congeners that are sterically similar to dioxin induce CYP1A1 and CYP1A2 activities by binding with the aryl hydrocarbon receptor, thus potentially reducing the risk of breast cancer (17, 19
). Congeners with at least two para- (4,4') and two orthosubstitutions exhibit phenobarbital-like effects that mainly induce CYP2B1 and CYP2B2 activities (17
20
). Clearly, this complex array of potential PCB effects could be missed by evaluating the total level of PCBs only instead of individual congeners.
Here, we report the results of a case-control study of breast cancer in Connecticut. The study was designed to evaluate whether breast adipose tissue levels of PCBs are associated with the risk of breast cancer and whether the risk varies by specific congeners and/or congener groups.
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MATERIALS AND METHODS |
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Breast adipose tissue and chemical analysis
Breast adipose tissue not needed for diagnostic purposes was collected and was placed in a glass bottle on ice, which was then coded and frozen within 30 minutes of biopsy. Samples were stored at -84°C until sent in batches to the study laboratory at Colorado State University, where they were stored frozen until analysis. Tissue samples were analyzed in batches of 12, and each batch contained samples for approximately six cases, four controls, and four quality controls. Samples were batched and coded at Yale; therefore, laboratory personnel did not know their case-control status.
Nine PCB congeners known to be abundant in human adipose tissue were measured in this study, including International Union of Pure and Applied Chemists (IUPAC) congeners 74, 118, 138, 153, 156, 170, 180, 183, and 187. As summarized by McFarland and Clarke (19), although major differences exist in the PCB composition of humans, wildlife, and fish, congeners 138, 153, and 180 appear most frequently in all analytes. The laboratory method for analyzing PCB congeners in breast adipose tissue has been described elsewhere (22
). The method involves extracting the compounds of interest in hexane, separating the organochlorine pesticides from the PCBs and purifying the sample by using Florisil chromatography (U.S. Silica Company, Berkeley Springs, West Virginia), and identifying and/or quantifying the compounds by using gas chromatography. The quantitation limits of this method were 7.5, 12.5, 10, 25, 25, 20, 12.5, 10, and 12.5 parts per billion (ppb) for PCB congeners 74, 118, 138, 153, 156, 170, 180, 183, and 187, respectively. In this study, total PCBs was defined as the sum of the nine measured PCB congeners. About 98.1 percent of the subjects who participated in this study had quantified levels of PCBs.
Strict quality control and assessment procedures were followed throughout sample analysis, including method spikes, reagent blanks, and establishment of quality control windows. Quality control spike recoveries for the PCB congeners during sample analyses ranged from 82 to 96 percent, with a coefficient of variation of 1025 percent. Adipose tissue levels of PCB congeners were reported as ppb, which is equivalent to nanograms of PCB congener per gram of lipid. The amount of lipid in the sample was quantified gravimetrically.
Interview
Information on major confounding factors, including reproductive history, lactation history, medical history, occupation, and demographics, was collected through an in-person interview by using a standardized, structured questionnaire. After approval by the subjects' physicians, potential participants were approached by letter and then by telephone. Those who consented were interviewed in person, generally in their homes or another convenient location. The dietary information was collected with a scannable semiquantitative food frequency questionnaire developed by the Fred Hutchinson Cancer Research Center (Seattle, Washington) to optimize estimation of fat intake. Each subject was asked to characterize her usual diet in the year before her biopsy. The entire interview took about 6090 minutes to complete.
Data analysis
Statistical analyses were based on lipid-adjusted adipose tissue levels of PCBs. Tertiles of adipose tissue levels of total and individual PCB congeners were formed based on the frequency distribution of these congeners in controls. Unconditional logistic regression modeling was used to estimate the exposure and/or disease association and to adjust for potential confounders. Odds ratios and 95 percent confidence intervals were calculated by using SAS statistical software and the PROC GENMOD procedure (23). In addition, we used a test of linear trend in which the actual level of total PCBs or group or individual congener is included in the model.
Since breast cancer risk may vary based on menopausal, parity, or lactation status, we evaluated the risk for nulliparous and parous women, with or without a history of lactation. We also analyzed the data based on body mass index (BMI; <21, 2124, or 25 kg/m2), since an increased risk of breast cancer was associated with body size and PCBs are known to be lipophilic and to accumulate in fat tissue. In addition to assessing the risk associated with total PCBs and individual congeners, we also combined individual congeners on the basis of their hormonal and nonhormonal activities, as proposed by Wolff et al. (24
), into the following three groups: group 1, potentially estrogenic and weak phenobarbital inducer, including congener 187; group 2, potentially antiestrogenic and dioxinlike, including congeners 74, 118, 138, 156, and 170; and group 3, phenobarbital, CYP1A and CYP2B inducers, including congeners 153, 180, and 183. Risk of breast cancer was examined within each of the congener groups and was mutually adjusted for each other.
We used both continuous variables (other than race and family breast cancer history) and categorical variables to adjust for potential confounders, reaching the same conclusion. This paper presents the results adjusted for confounders by using continuous variables only; included were age (years), BMI (kg/m2), lifetime months of lactation, age at menarche (years), age at first full-term pregnancy (years), fat consumption (grams/day), income 10 years before disease diagnosis or interview (adjusted for the number of people in the family at that time), race, and family breast cancer history. In this study, some weak confounders (such as family breast cancer history, age at menarche, and age at first full-term pregnancy) were included in the final model; because our primary purpose was to estimate the association between PCBs and breast cancer risk, we wanted to be certain that the known risk factors included in our adjusted analyses did not confound the estimates.
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RESULTS |
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DISCUSSION |
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When our results are interpreted, several potential limitations related to the study design should be considered. First, while our study did not support a positive association between adipose tissue levels of PCB congeners and breast cancer, this conclusion was based on the nine congeners we analyzed. These congeners are predominant and among those most commonly found in the environment and in human tissue (19). However, still other less-common PCB congeners have been found in the environment and in human tissue. Some have shown both hormonal and nonhormonal activities, so they can be associated either positively or negatively with breast cancer risk (18
). For example, congener 77, not measured in this study, has been shown to significantly (p < 0.01) attenuate 17ß-estrodial- and Aroclor-induced uterine weight increase in rats (16
). The dose required to produce these antiestrogenic effects was only 4080 times higher than that previously shown for dioxin. On the other hand, a small case-control study found that congener 99, also not measured in this study, was associated with an increased risk of breast cancer (7
).
A recent study by Moysich et al. (9) reported a significantly increased risk of breast cancer associated with serum levels of moderately chlorinated PCBs for postmenopausal parous women who had never breastfed an infant. An odds ratio of 3.6 (95 percent CI: 1.1, 8.6) was reported for moderately chlorinated PCBs when the third tertile was compared with the lowest based on data from 46 cases and 61 controls. Seven of our measured congeners would be classified as moderately chlorinated PCBs according to the classification system of Moysich et al. While chance cannot be ruled out as a potential explanation for the reported association in their study, another possibility is that some of the congeners included in their study, but not in ours, may be associated with an increased risk of breast cancer.
Experimental studies have suggested that some PCB congeners have estrogenic activity while others have antiestrogenic activity (17, 18
). The antiestrogenic effects of some congeners theoretically could counteract the estrogenic effects induced by other PCB congeners. The correlation between the individual congeners, however, may have hampered our ability to separate the effects of each individual congener or group of congeners, as reported in tables 5 and 6. Further methodological work is in progress to explore possible independent effects of the various congeners in the presence of colinearity.
Another concern related to the study design is use of patients with benign breast disease as controls. If PCBs and benign breast disease were associated, the true relative risk would be underestimated. However, it does not seem likely that use of benign breast disease patients as controls entirely explains the lack of an association of PCBs with breast cancer, since the hypothesis that environmental exposure to organochlorine compounds increases female breast cancer risk came from two studies that used patients with benign breast diseases as controls (7, 8
). In the present study, the geometric mean adipose tissue level of PCBs (table 2) for the breast cancer cases (478.6 ppb) was not significantly different (p = 0.70) from that for the 91 controls with proliferative benign breast diseases (495.6 ppb) or the 95 controls with nonproliferative benign breast diseases or normal tissue (490.1 ppb).
One possible limitation originates from our method of selecting potential cases and controls, which was based on the availability of 0.4 g of residual adipose tissue and is discussed elsewhere (21). At Yale-New Haven Hospital, many women undergo fine needle biopsy; these women would not have been eligible for our study since fine-needle biopsy specimens are typically very small and therefore insufficient for PCB quantification. Cases, but not controls, would be more likely to undergo subsequent surgical procedures. Therefore, more cases than controls would be considered potentially eligible for this study. This possible selection bias would influence the results only if the decision to use fine-needle biopsy for diagnostic purposes were related to body burden of PCBs, which is very unlikely. Also, subject selection in this study was dictated by the study population definition and availability of sufficient adipose tissue. Tissue levels of PCBs were measured after we completed the interviews, and no subjects were excluded from the study because of their past exposure experience or PCB tissue levels.
Another potential concern is the study sample size, particularly when data were stratified further by menopausal status, parity, lactation status, and body size. However, stratification by these variables seems mandatory since recent studies have suggested that PCB effects may vary by disease type (7) or by population groups (9
). The relatively small sample size also may be partly responsible for the lack of significant association found for some of the established breast cancer risk factors observed in this study and other recently published studies with similar sample sizes that also investigated the relation between organochlorine compounds and breast cancer risk (9
, 11
13
). In our study, use of women with benign breast disease as controls may partially account for the lack of association between family breast cancer history and breast cancer risk; however, benign breast disease was not associated with tissue levels of PCBs (table 2).
Our study also offers several advantages that may enhance interpretation of the results. First, PCBs are lipophilic, metabolically resistant, and preferentially stored in adipose tissue. Therefore, tissue samples would provide a good medium for assessing body burden for lifetime exposures. Second, adipose tissue levels of PCBs are unlikely to be affected by recent exposures, such as recent intakes. Finally, we collected detailed information on major confounders, such as menstrual and reproductive factors. Absent or inadequate control for known breast cancer risk factors has been suggested to be partly responsible for the inconsistency of previous studies (9).
In summary, our results do not support the hypothesis that environmental exposure to PCBs has a substantial impact on breast cancer risk. These results are consistent with those from more recent epidemiologic studies. However, we cannot rule out the possibility that PCB congeners not included in our study may increase the risk of breast cancer, and the results by individual or groups of congeners may be affected by the correlation between the individual or group of congeners.
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ACKNOWLEDGMENTS |
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The authors thank study interviewers Donna Carrano, Melita Bosnyak, Heather Hutson, and Sylvia Ullman for their high-quality interviewing; the Colorado State University's Analytical Laboratory for their state-of-the-art chemical analyses of adipose tissue contaminants; and Drs. Leticia DeDios and Christine Howe at Yale Cancer Center Shared Resources for their assistance in collecting study materials. Special thanks are also given to Drs. Kumiko Iwamoto, Gwen Collman, and G. Iris Obrams at the National Institutes of Health for their support and guidance of the study.
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NOTES |
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REFERENCES |
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