Citations

Abstract Allergen-induced respiratory inflammation facilitates and/or elicits the extravasation of proinflammatory leukocytes by well-understood mechanisms that mediate the movement of multiple cell types. The nonspecific character of these pathways led us to hypothesize that circulating cancer cells use similar mechanisms, promoting secondary tumor formation at distal sites. To test this hypothesis, the frequency of metastasis to the lung as a function of allergic pulmonary inflammation was assessed following the i.v. injection of B16-F10 melanoma cells in mice. These studies showed that allergen-induced pulmonary inflammation resulted in a >3-fold increase in lung metastases. This increase was dependent on CD4+ T-cell activities; however, it occurred independent of the induced eosinophilia associated with allergen provocation. Interventional strategies showed that existing therapeutic modalities for asthma, such as inhaled corticosteroids, were sufficient to block the enhanced pulmonary recruitment of cancer cells from circulation. Additional mechanistic studies further suggested that the ability of circulating cancer cells to extravasate to surrounding lung tissues was linked to the activation of the vascular endothelium via one or more Gαi-coupled receptors. Interestingly, a survey of a clinical breast cancer surgical database showed that the incidence of asthma was higher among patients with lung metastases. Thus, our data show that allergic respiratory inflammation may represent a risk factor for the development of lung metastases and suggest that amelioration of the pulmonary inflammation associated with asthma will have a direct and immediate benefit to the 7% to 8% of breast cancer patients with this lung disease. [Cancer Res 2008;68(20):8582–9]

Purpose An accurate estimate of a woman's breast cancer risk is essential for optimal patient counseling and management. Women with biopsy-confirmed atypical hyperplasia of the breast (atypia) are at high risk for breast cancer. The Gail model is widely used in these women, but has not been validated in them. Patients and Methods Women with atypia were identified from the Mayo Benign Breast Disease (BBD) cohort (1967 to 1991). Their risk factors for breast cancer were obtained, and the Gail model was used to predict 5-year–and follow-up–specific risks for each woman. The predicted and observed numbers of breast cancers were compared, and the concordance between individual risk levels and outcomes was computed. Results Of the 9,376 women in the BBD cohort, 331 women had atypia (3.5%). At a mean follow-up of 13.7 years, 58 of 331 (17.5%) patients had developed invasive breast cancer, 1.66 times more than the 34.9 predicted by the Gail model (95% CI, 1.29 to 2.15; P < .001). For individual women, the concordance between predicted and observed outcomes was low, with a concordance statistic of 0.50 (95% CI, 0.44 to 0.55). Conclusion The Gail model significantly underestimates the risk of breast cancer in women with atypia. Its ability to discriminate women with atypia into those who did and did not develop breast cancer is limited. Health care professionals should be cautious when using the Gail model to counsel individual patients with atypia.

AbstractAberrant Wnt/β-catenin signaling leading to nuclear accumulation of the oncogene product β-catenin is observed in a wide spectrum of human malignancies. The destruction complex in the Wnt/β-catenin pathway is critical for regulating the level of β-catenin in the cytoplasm and in the nucleus. Here, we report a comprehensive study of the contribution of genetic variation in six genes encoding the β-catenin destruction complex (APC, AXIN1, AXIN2, CSNK1D, CSNK1E, and GSK3B) to breast cancer using a Mayo Clinic Breast Cancer Case-Control Study. A total of 79 candidate functional and tagging single nucleotide polymorphisms (SNP) were genotyped in 798 invasive cases and 843 unaffected controls. Of these, rs454886 in the APC tumor suppressor gene was associated with increased breast cancer risk (per allele odds ratio, 1.23; 95% confidence intervals, 1.05-1.43; Ptrend = 0.01). In addition, five SNPs in AXIN2 were associated with increased risk of breast cancer (Ptrend &lt; 0.05). Haplotype-based tests identified significant associations between specific haplotypes in APC and AXIN2 (P ≤ 0.03) and breast cancer risk. Further characterization of the APC and AXIN2 variants suggested that AXIN2 rs4791171 was significantly associated with risk in premenopausal (Ptrend = 0.0002) but not in postmenopausal women. The combination of our findings and numerous genetic and functional studies showing that APC and AXIN2 perform crucial tumor suppressor functions suggest that further investigation of the contribution of AXIN2 and APC SNPs to breast cancer risk are needed. (Cancer Epidemiol Biomarkers Prev 2008;17(8):2101–8)

Objective: Mother-daughter communication may be a potential pathway between family history and cancer prevention behavior. We examined the degree to which mothers reported providing advice on breast cancer prevention to their daughters, the content of such advice, and correlates of providing such advice. Methods: Data were collected via a mailed questionnaire to 1773 women from 355 families in the Minnesota Breast Cancer Family Study. Women were asked whether or not they had provided advice to their daughters on what they should do to prevent breast cancer. An additional open-ended question asked them to describe the types of advice they had provided. Results: Nine hundred seventy-six (55%) of the women reported providing breast cancer prevention advice to their daughters. The most frequent types of advice were to have a mammogram (51%), perform breast self-examination (BSE) (39%), have a clinical breast examination (CBE) (30%), and maintain a healthy lifestyle (21%). From multivariate logistic regression, older age ( p < 0.001), having a personal history of breast cancer ( p < 0.001), higher degree of breast cancer worry/concern ( p < 0.001), engaging in a higher number of health-promoting behaviors ( p < 0.001), and ever performing a BSE ( p = 0.04) were factors independently associated with the provision of advice. Analyses accounting for sample nonindependence did not change our results. Conclusions: Breast cancer prevention behaviors were associated with providing advice. By better understanding the pathways through which breast cancer family history is associated with screening mammography and other prevention behaviors, researchers can develop more effective, tailored prevention interventions at the family level.

AbstractBackground: Limited studies have examined the associations between mammographic density and subsequent breast tumor characteristics.Methods: Eligible women were part of a case-control study of postmenopausal breast cancer, were 40 years or older and had a routine mammogram 4 years or more before their diagnosis. Mammographic density (percent density, dense area, and nondense area) was estimated using a computer-assisted thresholding program. At the time of cancer diagnosis, cases were classified as asymptomatic or symptomatic based on medical record review and breast imaging workup. Pathologic review was done blinded to the density status. Linear regression models and tests for trend examined the association between pathologic characteristics of the breast tumor and the components of density for all participants, and stratified by symptom status at diagnosis.Results: Of the 286 eligible cases, 77% were 60 years or older and mean percent density was 29.5% (SD, 14.6%). Density was not significantly associated with tumor size (P = 0.22), histologic type (P = 0.77), estrogen receptor (P = 0.11) or progesterone receptor (P = 0.37) status, mitotic activity (P = 0.12), or nuclear pleomorphism (P = 0.09; P values for percent density). An inverse association was suggested between tumor grade and percent density (32.0%, 30.3%, 26.7% for grades 1-3; P = 0.06 for trend). The inverse association with tumor grade and its components (nuclear pleomorphism and tubular differentiation) was only evident among the 97 symptomatic women; positive associations of estrogen receptor (P = 0.009) and progesterone receptor (P = 0.04) were also seen with percent density only in this subgroup.Conclusions: The inverse association between tumor grade and percent density in the symptomatic population could inform the biology of the association between mammographic density and breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(4):872–9)

Abstract Background: Early adolescent weight may affect the risk of postmenopausal breast cancer, and this association may be modified by a family history of breast or ovarian cancer in a first-degree relative, and/or estrogen (ER) and progesterone (PR) receptor status of the disease. Methods: Relative weight at age 12 years (above, below, or average weight compared with peers) and family history were ascertained using a mailed questionnaire in 1986, in the Iowa Women's Health Study, a prospective cohort study of postmenopausal women. Incident breast cancer cases (including ER and PR status) were identified using the Iowa Surveillance, Epidemiology, and End Results Cancer Registry. Relative risks (RR) and 95% confidence intervals (95% CI) were estimated using Cox proportional hazards regression, and were adjusted for breast cancer risk factors, including body mass index at age 18 years and body mass index at study baseline. Results: Through 2003, 2,503 cases of postmenopausal breast cancer were identified among 35,941 women in the analytic cohort. Compared with women with average weight at age 12 years, there was no association of below average weight with risk of breast cancer (RR, 1.02; 95% CI, 0.92-1.13), whereas women with above average weight had a lower risk (RR, 0.85; 95% CI, 0.74-0.98). There was no evidence of an interaction between weight at age 12 years and family history (P = 0.44). The inverse association of above average weight with risk of breast cancer was strongest for PR− tumors (RR, 0.62; 95% CI, 0.43-0.89), intermediate for ER+ (RR, 0.80; 95% CI, 0.67-0.96) and ER− (RR, 0.77; 95% CI, 0.50-1.19) tumors, and weakest for PR+ tumors (RR, 0.90; 95% CI, 0.74-1.09). These associations were not modified by a family history (all P &gt; 0.18). In a joint ER/PR analyses, the strongest inverse association with above average weight at age 12 years was seen for ER+/PR− (RR, 0.49; 95% CI, 0.29-0.85). Conclusion: Above average weight at age 12 years was inversely associated with risk of postmenopausal breast cancer, and was not modified by a family history of the disease. The inverse association was strongest for ER+/PR− tumors. (Cancer Epidemiol Biomarkers Prev 2008;17(2):374–8)

Abstract Increased mammographic density (MD), the proportion of dense tissue visible on a mammogram, is a strong risk factor for breast cancer, common in the population and clusters in families. We conducted the first genome-wide linkage scan to identify genes influencing MD. DNA was obtained from 889 relatives (756 women, 133 men) from 89 families. Percent MD was estimated on 618 (82%) female family members using a validated computer-assisted thresholding method. The genome-wide scan included 403 microsatellite DNA markers with an average spacing of 9 cM. Fine mapping of a region of chromosome 5p (5p13.1-5p15.1) was done using 21 additional closely spaced DNA markers. Linkage analyses were conducted to quantify the evidence for a gene responsible for MD across the genome. The maximum log odds for linkage (LOD) score from the genome-wide scan was on chromosome 5p (LOD = 2.9, supporting linkage by a factor of 102.9 or 794 to 1) with a 1-LOD interval spanning 28.6 cM. Two suggestive regions for linkage were also identified on chromosome 12 (LOD = 2.6, 1-LOD interval of 14.8 cM; and LOD = 2.5, 1-LOD interval of 17.2 cM). Finer mapping of the region surrounding the maximum LOD on chromosome 5p resulted in stronger and statistically significant evidence for linkage (LOD = 4.2) and a narrowed 1-LOD interval (13.4 cM). The putative locus on chromosome 5p is likely to account for up to 22% of variation in MD. Hence, 1 or more of the 45 candidate genes in this region could explain a large proportion of MD and, potentially, breast cancer. [Cancer Res 2007;67(17):8412–8]

Abstract Background: Mammographic density is a strong risk factor for breast cancer. However, whether changes in mammographic density are associated with risk remains unclear. Materials and Methods: A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Controls were matched on age, exam date, residence, menopause, interval between, and number of mammograms. All serial craniocaudal mammograms 10 years before ascertainment were digitized, and quantitative measures of percent density (PD) were estimated using a thresholding method. Data on potential confounders were abstracted from medical records. Logistic regression models with generalized estimating equations were used to evaluate the interactions among PD at earliest mammogram, time from earliest to each serial mammogram, and absolute change in PD between the earliest and subsequent mammograms. Analyses were done separately for PD measures from the ipsilateral and contralateral breast and also by use of hormone therapy (HT). Results: Subjects had an average of five mammograms available, were primarily postmenopausal (83%), and averaged 61 years at the earliest mammogram. Mean PD at earliest mammogram was higher for cases (31%) than controls (27%; ipsilateral side). There was no evidence of an association between change in PD and breast cancer risk by time. Compared with no change, an overall reduction of 10% PD (lowest quartile of change) was associated with an odds ratio of 0.9997 and an increase of 6.5% PD (highest quartile of change) with an odds ratio of 1.002. The same results held within the group of 220 cases and 340 controls never using HT. Among the 124 cases and 337 controls known to use HT during the interval, there was a statistically significant interaction between change in PD and time since the earliest mammogram (P = 0.01). However, in all groups, the risk associated with the earliest PD remained a stronger predictor of risk than change in PD. Conclusion: We observed no association between change in PD with breast cancer risk among all women and those never using HT. However, the interaction between change in PD and time should be evaluated in other populations. (Cancer Epidemiol Biomarkers Prev 2007;16(5):921–8)

Abstract Mammographic breast density is a strong risk factor for breast cancer but whether breast density is a general marker of susceptibility or is specific to the location of the eventual cancer is unknown. A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Mammograms on average 7 years before breast cancer were digitized, and quantitative measures of percentage density and dense area from each side and view were estimated. A regional density estimate accounting for overall percentage density was calculated from both mammogram views. Location of breast cancer and potential confounders were abstracted from medical records. Conditional logistic regression was used to estimate associations, and C-statistics were used to evaluate the strength of risk prediction. There were increasing trends in breast cancer risk with increasing quartiles of percentage density and dense area, irrespective of the side of the breast with cancer (Ptrends &lt; 0.001). Percentage density from the ipsilateral side [craniocaudal (CC): odds ratios (ORs), 1.0 (ref), 1.7, 3.1, and 3.1; mediolateral oblique (MLO): ORs, 1.0 (ref), 1.5, 2.2, and 2.8] and the contralateral side [CC: ORs, 1.0 (ref), 1.8, 2.2, and 3.7; MLO: ORs, 1.0 (ref), 1.6, 1.9, and 2.5] similarly predicted case-control status (C-statistics, 0.64-65). Accounting for overall percentage density, density in the region where the cancer subsequently developed was not a significant risk factor [CC: 1.0 (ref), 1.3, 1.0, and 1.2; MLO: 1.0 (ref), 1.1, 1.0, and 1.1 for increasing quartiles]. Results did not change when examining mammograms 3 years on average before the cancer. Overall mammographic density seems to represent a general marker of breast cancer risk that is not specific to breast side or location of the eventual cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(1):43–9)