Background

Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biological mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to inter-individual differences in mammographic density measures.

Methods

We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and non-dense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, body mass index (BMI) and menopausal status.

Results

Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (p=0.00005) and adjusted percent density (p=0.001) whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (p=0.003), but not with adjusted dense area (p=0.07).

Conclusion

We identified two common breast cancer susceptibility variants associated with mammographic measures of radio-dense tissue in the breast gland.

Impact

We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.

Breast density is a strong risk factor for breast cancer; however, no standard assessment method exists. An automated breast density method (ABDM) was modified and compared with a semi-automated user-assisted display method (CM) and the Breast Imaging Reporting and Data System (BI-RADS) four-category tissue composition measure for their ability to predict future breast cancer risk. The three estimation methods were evaluated in a matched breast cancer case (n=372) control (n=713) study at the Mayo Clinic using digitized film mammograms. Mammograms from the craniocaudal (CC) view of the noncancerous breast were acquired on average seven years before diagnosis. Two controls with no prior history of breast cancer from the screening practice were matched to each case on age, number of prior screening mammograms, final screening exam date, menopausal status at this date, interval between earliest and latest available mammograms, and residence. Both Pearson linear correlation (R) and Spearman rank correlation ( r ) coefficients were used for comparing the three methods where appropriate. Conditional logistic regression was used to estimate the risk of breast cancer (odds ratios [ORs] and 95% confidence intervals [CIs]) associated with the quartiles of percent density (ABDM, CM) or BI-RADS category. The area under the receiver operator characteristic curve (AUC) was estimated and used to compare the discriminatory capabilities of each approach. The continuous measures ABDM and CM were highly correlated with each other (R=0.70) but less with BI-RADS (r=0.49 for ABDM and r=0.57 for CM). Risk estimates associated with the lowest to highest quartiles of ABDM were greater in magnitude (ORs: 1.0[ref], 2.3, 3.0, 5.2, p-trend<0.001) than the corresponding quartiles for CM (ORs: 1.0[ref], 1.7, 2.1 and 3.8; p-trend<0.001) and BI-RADS (ORs: 1.0[ref], 1.6, 1.5, 2.6; p-trend<0.001) methods. However, all methods similarly discriminated between case and control status: AUCs were 0.64, 0.63 and 0.61 for ABDM, CM and BI-RADS, respectively. The ABDM is a viable option for quantitatively assessing breast density from digitized film mammograms.

Objective

Awareness of cancer family history is dependent upon communication between family members. Communication of this information and related decision-making could be important factors influencing breast cancer risk reduction and early detection behaviors. Using survey data from 2,328 women (mean age 62.5 years) from 372 families enrolled in the Minnesota breast cancer family study, we explored adult daughter’s reports of breast cancer risk reduction advice received from their mothers.

Methods and Results

Approximately 212 (9%) of respondents reported receiving breast cancer risk reduction advice from their mothers and 130 (89%) reported acting upon such advice. Having a mother or first degree relative (FDR) with a history of breast cancer was significantly correlated with following advice to a higher degree as compared to those not having such family history (p=0.003).

Most frequently reported types of advice were to have mammograms (36%) and to have clinical breast exams (35%). Using multivariable logistic regression and after accounting for non-independence of the sample, significant independent correlates of receiving advice included younger age, having an affected mother, and having a higher perceived breast cancer risk. Receiving advice was also correlated with engaging in a higher number of health promoting behaviors and ever having received a mammogram.

Conclusions

Our preliminary findings are consistent with social influence theory and suggest that mother-daughter communication about reducing risk, especially among those having a FDR with breast cancer, could be a potential pathway through which BC family history is associated with the adoption of breast cancer screening and risk reduction behaviors.

Background

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, 40 years and older, who had a routine mammogram four years or more before their diagnosis. Mammographic density (percent density [PD], 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 performed blinded to the density status. Linear regression models and tests for trend examined the association between pathologic characteristics of the breast tumor (except histology) 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 PD was 29.5% (SD=14.6%). Density was not significantly associated with tumor size (p=0.22), histologic type (p=0.77), estrogen receptor (ER) (p=0.11) or progesterone receptor (PR) (p=0.37) status, mitotic activity (p=0.12) or nuclear pleomorphism (p=0.09) [p-values for PD]. An inverse association was suggested between tumor grade and PD (31.95%, 30.29%, 26.73% for grade I-III; p for trend= 0.06). 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 ER (p=0.009) and PR (p=0.04) were also seen with PD only in this subgroup.

Conclusions

The inverse association between tumor grade and PD in the symptomatic population could inform the biology of the association between mammographic density and breast cancer risk.

Estrogen receptor (ER)-negative breast cancer shows a higher incidence in women of African ancestry compared to women of European ancestry. In search of common risk alleles for ER-negative breast cancer, we combined genome-wide association study (GWAS) data from women of African ancestry (1,004 ER-negative cases and 2,745 controls) and European ancestry (1,718 ER-negative cases and 3,670 controls), with replication testing conducted in an additional 2,292 ER-negative cases and 16,901 controls of European ancestry. We identified a common risk variant for ER-negative breast cancer at the TERT-CLPTM1L locus on chromosome 5p15 (rs10069690: per-allele odds ratio (OR) = 1.18 per allele, P = 1.0 × 10−10). The variant was also significantly associated with triple-negative (ER-negative, progesterone receptor (PR)-negative and human epidermal growth factor-2 (HER2)-negative) breast cancer (OR = 1.25, P = 1.1 × 10−9), particularly in younger women (<50 years of age) (OR = 1.48, P = 1.9 × 10−9). Our results identify a genetic locus associated with estrogen receptor negative breast cancer subtypes in multiple populations.

Mitotic regulatory pathways ensure proper timing of mitotic entry, sister chromatid cohesion and separation, and cytokinesis. Disruption of this process results in inappropriate chromosome segregation and aneuploidy and appears to contribute to cancer. Specifically, disregulation and somatic mutation of mitotic regulators has been observed in human cancers, and overexpression of mitotic regulators is common in aggressive and late stage tumors. However, the role of germline variation in mitotic pathways and risk of cancer is not well understood. We tested 1,084 haplotype-tagging and functional variants from 164 genes in mitotic regulatory pathways in 791 Caucasian women with breast cancer and 843 healthy controls for association with risk of overall and high grade breast cancer. Sixty-one single nucleotide polymorphisms (SNPs) from 40 genes were associated (p<0.05) with risk of breast cancer in a log-additive model. In addition 60 SNPs were associated (p<0.05) with risk of high grade breast cancer. However, none of these associations were significant after Bonferroni correction for multiple testing. In gene-level analyses, CDC25C, SCC1/RAD21, TLK2, and SMC6L1 were associated (p<0.05) with overall breast cancer risk, CDC6, CDC27, SUMO3, RASSF1, KIF2, and CDC14A were associated with high grade breast cancer risk, and EIF3S10 and CDC25A were associated with both. Further investigation in breast and other cancers are needed to understand the influence of inherited variation in mitotic genes on tumor grade and cancer risk.

The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with risk of ovarian cancer. Here we investigated 19p13.1 variation and risk of breast cancer subtypes, defined by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status, using 48,869 breast cancer cases and 49,787 controls from the Breast Cancer Association Consortium (BCAC). Variants from 19p13.1 were not associated with breast cancer overall or with ER-positive breast cancer but were significantly associated with ER-negative breast cancer risk [rs8170 Odds Ratio (OR)=1.10, 95% Confidence Interval (CI) 1.05 – 1.15, p=3.49 × 10-5] and triple negative (TN) (ER, PR and HER2 negative) breast cancer [rs8170 OR=1.22, 95% CI 1.13 – 1.31, p=2.22 × 10-7]. However, rs8170 was no longer associated with ER-negative breast cancer risk when TN cases were excluded [OR=0.98, 95% CI 0.89 – 1.07, p=0.62]. In addition, a combined analysis of TN cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC) (n=3,566) identified a genome-wide significant association between rs8170 and TN breast cancer risk [OR=1.25, 95% CI 1.18 – 1.33, p=3.31 × 10-13]. Thus, 19p13.1 is the first triple negative-specific breast cancer risk locus and the first locus specific to a histological subtype defined by ER, PR, and HER2 to be identified. These findings provide convincing evidence that genetic susceptibility to breast cancer varies by tumor subtype and that triple negative tumors and other subtypes likely arise through distinct etiologic pathways.

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3628 breast cancer cases and 5190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of SNPs were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using ten different cut-offs for the most significant density SNPs (1-10% representing 5,222-50,899 SNPs). Permutation analysis was also performed across all 10 cut-offs. The association between risk score and breast cancer was significant for all cut-offs from 3-10% of top density SNPs, being most significant for the 6% (2-sided P=0.002) to 10% (P=0.001) cut-offs (overall permutation P=0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR= 1.31 (95%CI 1.08-1.59)] compared to women in the bottom 10%. Together, our results demonstrate that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.

Objective

Our goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0.

Methods

Various QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets.

Results

For Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed.

Conclusions

Using our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h).

Background

Investigations of breast carcinogenesis often rely upon comparisons between cancer tissue and nonmalignant breast tissue. It is unclear how well common reference sources of nonmalignant breast tissues reflect normal breast tissue.

Methods

Breast tissue samples were evaluated from three sources: 1) normal donor tissues in the Susan G. Komen for the Cure® Tissue Bank at Indiana University Simon Cancer Center (KTB), 2) women who underwent reduction mammaplasty (RM) at Mayo Clinic Rochester, and 3) the Mayo Clinic Benign Breast Disease Cohort Study (BBD). Samples were examined histologically and assessed for proliferative disease and degree of lobular involution. Univariate comparisons were performed among the study groups, and multivariate analyses were performed with logistic regression to assess the association between study group and the presence of epithelial proliferative disease and complete lobular involution.

Results

Histologic data were collected for 455 KTB samples, 259 RM samples, and 319 BBD samples. Histologic findings and the frequency of epithelial proliferation were significantly different among the groups. Histologic abnormalities were seen in a minority of the KTB samples (35%), whereas an abnormality was present in 88% of RM tissues and 97.5% of BBD samples. The presence of proliferative disease (with or without atypical hyperplasia) was present in 3.3% of normal donors (3.3%), 17% of RM samples, and 34.9% of BBD samples, (p<0.0001 for each comparison). Multivariate analyses confirmed that these differences remained significant and also showed higher likelihood of complete lobular involution in the normal donor samples compared to RM and BBD tissues.

Conclusion

Compared to benign breast disease tissues and reduction mammaplasty tissues, breast tissue samples from normal donors have significantly fewer histologic abnormalities and a higher frequency of more complete lobular involution. Breast tissue samples from normal donors represent a unique tissue resource with histologic features consistent with lower breast cancer risk.

Triple negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiological factors which promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome wide association studies (GWAS) display heterogeneity of effect among breast cancer subtypes as defined by estrogen receptor (ER) and progesterone receptor (PR) status. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple negative breast cancer and 4,978 healthy controls. We identified six single nucleotide polymorphisms (SNPs) significantly associated with risk of triple negative breast cancer, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.11) and rs8100241 (19p13.11). Together, our results provide convincing evidence of genetic susceptibility for triple negative breast cancer.

Purpose

Aspirin and other non-aspirin non-steroidal anti-inflammatory drugs (NSAIDs) can inhibit aromatase activity and thus could selectively lower incidence of hormone receptor positive tumors. We assessed whether the association of aspirin and other NSAIDs with postmenopausal breast cancer risk differs by estrogen and progesterone receptor (ER, PR) status of the tumor.

Methods

A population-based cohort of 26,580 postmenopausal women was linked to a SEER Cancer Registry to identify incident breast cancers. Regular use of aspirin and other NSAIDs was reported on a self-administered questionnaire mailed in 1992. Cox proportional hazards models were used to estimate multivariate relative risks (RRs) and 95% confidence intervals (CIs) of breast cancer incidence overall and by ER and PR status, adjusting for multiple breast cancer risk factors.

Results

Through 2005, 1,581 incident breast cancer cases were observed. Compared to aspirin never users, women who regularly consumed aspirin had a lower risk of breast cancer (RR=0.80; 95% CI: 0.71–0.90), and there was evidence for lower risk with increasing frequency of use (RR=0.71 for aspirin use 6 or more times/week versus never use; p-trend=0.00001). Inverse associations for regular aspirin use were observed for ER+ (RR=0.77; 95% CI 0.67–0.89), ER− (RR=0.78; 95% CI 0.56–1.08), PR+ (RR=0.79; 95% CI 0.68–0.92), and PR− (RR=0.73; 95% CI 0.56–0.95) breast cancers. In contrast, use of other NSAIDs was not associated with breast cancer incidence overall (RR=0.95, 95% CI: 0.85–1.07), or by ER or PR status.

Conclusions

Aspirin, but not other NSAID use, was associated with about 20% lower risk of postmenopausal breast cancer and did not vary by ER or PR status of the tumor, suggesting that the hypothesized protective effects of aspirin may either be through cellular pathways independent of estrogen or progesterone signaling, or on tumor microenvironment.

Introduction

Increased mammographic breast density is one of the strongest risk factors for breast cancer. While two-thirds of the variation in mammographic density appears to be genetically influenced, few variants have been identified. We examined the association of inherited variation in genes from pathways that mediate cell division with percent mammographic density (PMD) adjusted for age, body mass index (BMI) and postmenopausal hormones, in two studies of healthy postmenopausal women.

Methods

We investigated 2,058 single nucleotide polymorphisms (SNPs) in 378 genes involved in regulation of mitosis for associations with adjusted PMD among 484 unaffected postmenopausal controls (without breast cancer) from the Mayo Clinic Breast Cancer Study (MCBCS) and replicated the findings in postmenopausal controls (n = 726) from the Singapore and Sweden Breast Cancer Study (SASBAC) study. PMD was assessed in both studies by a computer-thresholding method (Cumulus) and linear regression approaches were used to assess the association of SNPs and PMD, adjusted for age, BMI and postmenopausal hormones. A P-value threshold of 4.2 × 10-5 based on a Bonferroni correction of effective number of independent tests was used for statistical significance. Further, a pathway-level analysis was conducted of all 378 genes using the self-contained gene-set analysis method GLOSSI.

Results

A variant in PRPF4, rs10733604, was significantly associated with adjusted PMD in the MCBCS (P = 2.7 × 10-7), otherwise, no single SNP was associated with PMD. Additionally, the pathway analysis provided no evidence of enrichment in the number of associations observed between SNPs in the mitotic genes and PMD (P = 0.60). We evaluated rs10733604 (PRPF4), and 73 other SNPs at P < 0.05 from 51 genes in the SASBAC study. There was no evidence of an association of rs10733604 (PRPF4) with adjusted PMD in SASBAC (P = 0.23). There were, however, consistent associations (P < 0.05) of variants at the putative locus, LOC375190, Aurora B kinase (AURKB), and Mini-chromosome maintenance complex component 3 (MCM3) with adjusted PMD, although these were not statistically significant.

Conclusions

Our findings do not support a role of inherited variation in genes involved in regulation of cell division and adjusted percent mammographic density in postmenopausal women.

Mammographic breast density is one of the strongest risk factors for breast cancer. Unfortunately, the biologic basis underlying this association is unknown. This study compared aromatase expression or immunoreactivity (IR) in core biopsies from mammographically dense versus non-dense regions of the breast to examine whether estrogen synthesis in the breast is associated with mammographic breast density (MBD) and one possible mechanism through which it may influence breast cancer. Eligible participants were 40+ yrs, had a screening mammogram with visible MBD and no prior cancer or current endocrine therapy. Mammograms were used to identify dense and non-dense regions and ultrasound-guided core biopsies were performed to obtain tissue from these regions. Immunostaining for aromatase employed the streptavidin-biotin amplification method and #677 mouse monoclonal antibody. Aromatase IR was scored in terms of extent and intensity of staining for each cell type (stroma, epithelium, adipocytes) on the histologic section. A modified histological (H)-score provided quantitation of aromatase IR in each cell type and overall. Repeated measures analyses evaluated average differences (βH) in H-score in dense versus non-dense tissue within and across cell types. Forty nine women mean age 50 yrs (range: 40 to 82), participated. Aromatase IR was increased in dense (vs. non-dense) tissue in both the stroma (βH =0.58) and epithelium (βH =0.12) (p<0.01). Adipocytes from non-dense tissue, however, had a greater IR compared to those from dense tissue (βH =-0.24, p<0.01). An overall H-score which integrated results from all cell types demonstrated that aromatase IR was twice as great for dense (mean H-score=0.90, SD=0.53) vs. non-dense (mean H-score=0.45, SD=0.39) breast tissue (βH =0.45; p<0.001). Overall, aromatase IR was greater for mammographically dense vs. non-dense tissue and may partly explain how MBD influences breast cancer.

Summary

Monoclonal B-cell lymphocytosis (MBL) is an asymptomatic haematological condition characterized by low absolute levels of B-cell clones with a surface immunophenotype similar to that of chronic lymphocytic leukaemia (CLL). In the general population, MBL increases with age with a prevalence of 5–9% in individuals over age 60 years. It has been reported to be higher among first-degree relatives from CLL families. We report results of multi-parameter flow cytometry among 505 first-degree relatives with no personal history of lymphoproliferative disease from 140 families having at least two cases of CLL. Seventeen percent of relatives had MBL. Age was the most important determinant where the probability for developing MBL by age 90 years was 61%. MBL clustered in certain families but clustering was independent of the number of known CLL cases in a family. As is the case with CLL, males had a significantly higher risk for MBL than did females (p=0.04). MBL patients had significantly higher mean absolute lymphocyte counts (2.4 × 109/l) and B-cell counts (0.53 × 109/l) than those with a normal B-cell immunophenotype. Our findings show that MBL occurs at a very high rate in high risk CLL families. Both the age and gender distribution of MBL are parallel to CLL, implying a shared inherited risk.

High percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer. We conducted a meta-analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P=9×6·10−10). This finding might partly explain the underlying biology of the recently discovered association between common variants in ZNF365 and breast cancer risk.

Purpose

Mammographic density and lobular involution are both significant risk factors for breast cancer, but whether these reflect the same biology is unknown. We examined the involution and density association in a large benign breast disease (BBD) cohort.

Patients and Methods

Women in the Mayo Clinic BBD cohort who had a mammogram within 6 months of BBD diagnosis were eligible. The proportion of normal lobules that were involuted was categorized by an expert pathologist as no (0%), partial (1% to 74%), or complete involution (≥ 75%). Mammographic density was estimated as the four-category parenchymal pattern. Statistical analyses adjusted for potential confounders and evaluated modification by parity and age. We corroborated findings in a sample of women with BBD from the Mayo Mammography Health Study (MMHS) with quantitative percent density (PD) and absolute dense and nondense area estimates.

Results

Women in the Mayo BBD cohort (n = 2,667) with no (odds ratio, 1.7; 95% CI, 1.2 to 2.3) or partial (odds ratio, 1.3; 95% CI, 1.0 to 1.6) involution had greater odds of high density (DY pattern) than those with complete involution (P trend < .01). There was no evidence for effect modification by age or parity. Among 317 women with BBD in the MMHS study, there was an inverse association between involution and PD (mean PD, 22.4%, 21.6%, 17.2%, for no, partial, and complete, respectively; P trend = .04) and a strong positive association of involution with nondense area (P trend < .01). No association was seen between involution and dense area (P trend = .56).

Conclusion

We present evidence of an inverse association between involution and mammographic density.

Background

There is strong and consistent evidence that a genetic component contributes to the etiology of chronic lymphocytic leukemia (CLL). A recent genome-wide association study (GWAS) of CLL identified 7 genetic variants that increased the risk of CLL within a European population.

Methods

We evaluated the association of these variants, or variants in linkage disequilibrium (LD) with these variants, with CLL risk in an independent sample of 438 CLL cases and 328 controls.

Results

Of these 7 SNPs, 6 had p-trend < 0.05 and had estimated odds ratios (ORs) that were strikingly comparable to those of the previous study. Associations were seen for rs9378805 (OR = 1.47, 95% CI: 1.19, 1.80, p-trend = 0.0003) near IRF4 and rs735665 near GRAMD1B (OR= 1.47; 95% CI: 1.14, 1.89; p-trend = 0.003). However, no associations (P> 0.05) were found for rs11083846, nor were any found for any SNPs in LD with rs11083846.

Conclusions

Our results confirm the previous findings and further support the role of a genetic basis in the etiology of CLL; however, more research is needed to elucidate the causal SNP(s) and the potential manner in which these SNPs or linked SNPs function in CLL pathogenesis.

Purpose

Accurate, individualized risk prediction for breast cancer is lacking. Tissue-based features may help to stratify women into different risk levels. Breast lobules are the anatomic sites of origin of breast cancer. As women age, these lobular structures should regress, which results in reduced breast cancer risk. However, this does not occur in all women.

Methods

We have quantified the extent of lobule regression on a benign breast biopsy in 85 patients who developed breast cancer and 142 age-matched controls from the Mayo Benign Breast Disease Cohort, by determining number of acini per lobule and lobular area. We also calculated Gail model 5-year predicted risks for these women.

Results

There is a step-wise increase in breast cancer risk with increasing numbers of acini per lobule (P = .0004). Adjusting for Gail model score, parity, histology, and family history did not attenuate this association. Lobular area was similarly associated with risk. The Gail model estimates were associated with risk of breast cancer (P = .03). We examined the individual accuracy of these measures using the concordance (c) statistic. The Gail model c statistic was 0.60 (95% CI, 0.50 to 0.70); the acinar count c statistic was 0.65 (95% CI, 0.54 to 0.75). Combining acinar count and lobular area, the c statistic was 0.68 (95% CI, 0.58 to 0.78). Adding the Gail model to these measures did not improve the c statistic.

Conclusion

Novel, tissue-based features that reflect the status of a woman's normal breast lobules are associated with breast cancer risk. These features may offer a novel strategy for risk prediction.

Background

Lobular involution, or age-related atrophy of breast lobules, is inversely associated with breast cancer risk, and mammographic breast density (MBD) is positively associated with breast cancer risk.

Methods

To evaluate whether lobular involution and MBD are independently associated with breast cancer risk in women with benign breast disease, we performed a nested cohort study among women (n = 2666) with benign breast disease diagnosed at Mayo Clinic between January 1, 1985, and December 31, 1991 and a mammogram available within 6 months of the diagnosis. Women were followed up for an average of 13.3 years to document any breast cancer incidence. Lobular involution was categorized as none, partial, or complete; parenchymal pattern was classified using the Wolfe classification as N1 (nondense), P1, P2 (ductal prominence occupying <25%, or >25% of the breast, respectively), or DY (extremely dense). Hazard ratios (HRs) and 95% confidence intervals (CIs) to assess associations of lobular involution and MBD with breast cancer risk were estimated using adjusted Cox proportional hazards model. All tests of statistical significance were two-sided.

Results

After adjustment for MBD, having no or partial lobular involution was associated with a higher risk of breast cancer than having complete involution (none: HR of breast cancer incidence = 2.62, 95% CI = 1.39 to 4.94; partial: HR of breast cancer incidence = 1.61, 95% CI = 1.03 to 2.53; Ptrend = .002). Similarly, after adjustment for involution, having dense breasts was associated with higher risk of breast cancer than having nondense breasts (for DY: HR of breast cancer incidence = 1.67, 95% CI = 1.03 to 2.73; for P2: HR of breast cancer incidence = 1.96, 95% CI = 1.20 to 3.21; for P1: HR of breast cancer incidence = 1.23, 95% CI = 0.67 to 2.26; Ptrend = .02). Having a combination of no involution and dense breasts was associated with higher risk of breast cancer than having complete involution and nondense breasts (HR of breast cancer incidence = 4.08, 95% CI = 1.72 to 9.68; P = .006).

Conclusion

Lobular involution and MBD are independently associated with breast cancer incidence; combined, they are associated with an even greater risk for breast cancer.

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 non-specific 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 intravenous injection of B16-F10 melanoma cells in mice. These studies demonstrated 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 demonstrate that allergic respiratory inflammation may represent a risk factor for the development of lung metastases and suggests that amelioration of the pulmonary inflammation associated with asthma will have a direct and immediate benefit to the 7–8% of breast cancer patients with this lung disease.

Background

Numerous studies point to a positive relationship between elevated levels of estrogens and increased risk of breast. Androgens are converted to estrogens by the aromatase enzyme, which is encoded by the CYP19 gene. We recently published resequencing data on 88 polymorphisms identified in that gene. The hypothesis tested in this study was that polymorphisms, or haplotypes, in CYP19 are related to risk of breast cancer.

Methods

Incident cases of breast cancer were identified through the Division of Medical Oncology at the Mayo Clinic in Rochester, MN. Controls were patients visiting Mayo for an annual medical examination. Controls were frequency matched to cases based on age and region of residence. Tag-polymorphisms were selected using 2 methods: 1) 12 variants using the tag-selection method of Carlson et al [1]; and 2) 12 variants using the haplotype method of Stram [2]. Six SNPs were selected by both methods. Genotyping was conducted using SNPStream, TaqMan and RFLP analyses. Logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI). Analyses were conducted among all cases and controls, or stratified by estrogen receptor alpha (ER) status and/or menopausal status.

Results

A total of 750 cases (60% postmenopausal) and 732 controls (75% postmenopausal) were included. No association with breast cancer risk was detected for individual variants, selected tagSNPs or hap-tag SNPs despite 80% power to detect odds ratios as low as 1.49 for MAF of 0.10. Similarly, stratified analyses based on ER status or menopausal status failed to detect any association with breast cancer risk.

Conclusion

These analyses suggest that variants of CYP19 are not associated with risk of breast cancer.

Purpose

Immunotherapeutic modalities are commonly used for treatment of patients with melanoma. The therapeutic success in pre-clinical models has not yielded the expected clinical results. To understand this discrepancy, we attempted to define immune homeostasis of 209 patients with melanoma across stages of disease relative to normal controls.

Patients and Methods

PBMC and plasma were collected from patients and healthy donors. PBMC were analyzed for frequencies of natural killer, dendritic, and T-cells, and their functional status. Matched plasma samples were analyzed for the concentrations of 27 cytokines, chemokines, and growth factors. RNA was isolated from 24 metastatic melanoma tumor biopsies and profiled by microarray analysis.

Results

The frequency of NK, T-cells, and DC in patients does not significantly change across stages of melanoma. However, plasma concentrations of Th2 cytokines (IL-4, IL-5, IL-10 and IL-13) in tumor bearing patients were significantly higher than those with resected melanoma. Expression array analysis of metastatic melanoma revealed that the malignant melanocytes were not the source of the Th2 cytokines, but did highly up-regulate VEGF transcripts, consistent with plasma VEGF concentrations. In vitro VEGF exposure of normal PBMC lead to re-polarization from Th1 to Th2 emulating the state of metastatic melanoma.

Conclusions

Patients with metastatic melanoma exist in a state of Th2 mediated “chronic inflammation” as a result of at least VEGF overproduction by malignant tumors. These data support prior observations regarding the impact of VEGF on immune cell function and suggests consideration of VEGF inhibitors in future cancer immunotherapy clinical studies in metastatic melanoma.

Mammographic percent density (PD) is a strong risk factor for breast cancer, but there has been relatively little systematic evaluation of other features in mammographic images that might additionally predict breast cancer risk. We evaluated the association of a large number of image texture features with risk of breast cancer using a clinic-based case-control study of digitized film mammograms, all with screening mammograms prior to breast cancer diagnosis. The sample was split into training (123 cases, 258 controls) and validation (123 cases, 264 controls) datasets. Age and body mass index (BMI)-adjusted Odds Ratios (ORs) per standard deviation change in the feature, 95% confidence intervals, and the area under the receiver operator characteristic curve (AUC) were obtained using logistic regression. A bootstrap approach was used to identify the strongest features in the training dataset, and results for features that validated in the second half of the sample were reported using the full dataset. The mean age at mammography was 64.0 ± 10.2 years, and the mean time from mammography to breast cancer was 3.7 ± 1.0 (range 2.0-5.9 years). PD was associated with breast cancer risk (OR=1.49; 1.25-1.78). The strongest features that validated from each of several classes (Markovian, run-length, Laws, wavelet and Fourier) showed similar ORs as PD and predicted breast cancer at a similar magnitude (AUC=0.58-0.60) as PD (AUC=0.58). All of these features were automatically calculated (unlike PD), and measure texture at a coarse scale. These features were moderately correlated with PD (r = 0.39-0.64), and after adjustment for PD, each of the features attenuated only slightly and retained statistical significance. However, simultaneous inclusion of these features in a model with PD did not significantly improve the ability to predict breast cancer.