Citations

Abstract Background: Optimal early detection and prevention strategies for breast cancer are predicated on our ability to accurately identify women at increased risk for disease. Current breast cancer risk prediction models rely on clinical and epidemiologic features. As demonstrated with other cancers, such as those of the cervix and colon, cancer risk assessment is enhanced when the tissue at risk is examined for evidence of premalignant abnormalities. Here, we present a multivariate model for individualized breast cancer risk prediction that incorporates tissue features identified from biopsies from women with benign breast disease (BBD). Methods: We used our cohort of more than 9000 women diagnosed with BBD at the Mayo Clinic from 1967–1991, and identified a nested case:control series of 377 women who developed cancer (cases) matched with 734 women who did not (controls). We identified a set of variables that either alone or in two-way interactions contributed to a multivariable risk prediction model. We combined this relative risk model with the baseline incidence of breast cancer and the baseline hazard of death from our full BBD cohort to develop a risk prediction tool that computes absolute risk estimates for breast cancer. We calculated 5-year risk predictions for these cases and controls using our model and using the Gail model and compared c-statistics from these risk predictions. We validated our model using an independent set of 378 breast cancer cases and 728 matched controls drawn from our BBD cohort. Results: Cases and controls in the model development data set differed significantly on a number of features when examined individually. Those included in a multivariable relative risk model for breast cancer among women with BBD are shown below. After including interactions between lobular involution, and histologic impression, with age at first live birth/number of children, and degree of involution with sclerosing adenosis, we devised a model that predicts the absolute risk of breast cancer. Predicted five-year risks in the model development series, we observed a c-statistic of 0.66, higher than the c-statistic of 0.61 for the Gail model. With risk prediction estimates from our validation series of cases and matched controls, the c-statistic of our model decreased to 0.59 and the c-statistic for the Gail model was 0.55. Conclusion: We have identified an initial risk prediction model for breast cancer in women with BBD. The identified model includes basic demographic information as well as a number of histologic features of the tissue samples. Its initial performance is promising, providing improved discrimination over the Gail model in our replication data set. Further work is needed to identify features which might provide additional predictive information for breast cancer risk. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-12-03.

Abstract Background: Based upon the association between pathologic response and disease free survival, the neoadjuvant setting is increasingly being used for drug development. NGS has identified unique and recurrent genetic alterations in breast cancer (BC) that are potentially targetable; however, the clinical implications are mostly unknown. We developed a prospective neoadjuvant study (BEAUTY) in high risk BC patients (pts) using weekly T followed by anthracycline-based chemo wherein percutaneous tumor biopsies (PTB) are obtained before/during/after chemo for NGS and PDX. Our goal is to identify novel biomarkers/pathways and develop PDX to test new therapeutic approaches. Methods: Pts underwent PTB at baseline and after 12 wks of T. Response to T was defined based upon 12 week Ki-67: responder (<15%) vs non-responder (≥15%). Pts with histologic response and absence of invasive BC at 12 wks were classified as responders. NGS was performed using PTB/blood DNA (exome) and PTB (RNA seq). MRI response was classified using RECIST criteria. NGS data were used to identify somatic copy number variants (cnvs) and expressed single nucleotide variants (eSNVs). Non-SCID mice (estrogen supplemented) were implanted ≤ 30 minutes with PTB samples. Results: Of the first 78 pts, 44 have completed T. Here we focus on 18 pts with either triple negative or luminal B BC. Clinical characteristics according to Ki-67 response are shown in Table 1. Comparison of genomic alterations in BEAUTY pts with TCGA identified a greater overlap with copy number gains (73%) compared to deletions (40%), along with similar observations of mutations in TP53, PTEN, RYR2, and AKT1 genes. Association analysis of CNVs and eSNVs between responders/non-responders identified 33 genes (predominantly located in chromosomes 1, 8, 13) and 580 eSNVs (corresponding to 497 genes) with a p < 0.05. Differential gene expression (DGE) analysis of responders/non-responders identified 198 genes with a p-value < 0.05. Integrated analysis of 539 genes (CNVs, eSNVs and DGE) identified pathways such as TGF-beta, Jak-Stat, WNT and NOTCH signalling. PDX take rate was 44% [triple negative (6/10); Luminal B (2/8)]. PDX growth rate was significantly associated with clinical baseline Ki-67 (p = 0.00014). Conclusion: This is the first prospective study to demonstrate the feasibility of using PTB to obtain both NGS data and PDX in the neoadjuvant setting. PDX take rate is associated with BC subtype and baseline Ki-67. Studies are ongoing to 1) validate genes/pathways associated with treatment response in subsequent BEAUTY pts; 2) genomically characterize and assess PDX in vivo response to T and 3) Use NGS data to prioritize new drugs/drug combinations in PDX. Funded by Mayo Clinic Center for Individualized Medicine and MC Cancer Center. Clinical CharacteristicsOverallResponders: 12 week Ki-67 < 15% (n = 9)Non-Responders: 12 week Ki-67 ≥ 15% (n = 9)Median Age495345T stage T2/T314 (78%)7 (78%)7 (78%)Node Positive8 (44%)4 (44%)4 (44%)Triple negative10 (56%)6 (67%)4 (44%)Luminal B8 (44%)3 (33%)5 (56%)Ki-67 after 12 Weeks of T Median 5% (0-11%)Median 35% (17-60%)Complete/Partial MRI Response after T 6 (67%)2 (22%) Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P1-08-10.

Abstract Objectives: Cellular fibroepithelial lesions (CFELs) are a heterogeneous group of tumors encompassing cellular fibroadenoma (CFA) and phyllodes tumor (PT). Distinction between the two is challenging on core needle biopsy (CNB) specimens. The objective of this study was to evaluate histologic features that can help distinguish PT from CFA on CNB specimens. Methods: Records of all patients diagnosed with CFELs on CNB specimens with follow-up excision between January 2002 and December 2012 were retrieved. Histopathologic stromal features were evaluated on CNB specimens, including mitoses per 10 high-power fields (hpf), overgrowth, increased cellularity, fragmentation, adipose tissue infiltration, heterogeneity, subepithelial condensation, and nuclear pleomorphism. Results: Twenty-seven (42.2%) of 64 were diagnosed as PT (24 benign PTs and three borderline PTs) and 37 (57.8%) as CFA on excision. All features except for increased stromal cellularity were statistically significant. The average number of histologic features seen in PT and CFA was 3.9 and 1.4, respectively (odds ratio [OR], 7.27; 95% confidence interval [CI], 2.44–21.69; P = .0004). The average number of mitoses per 10 hpf was 3.0 for PT compared with 0.8 for CFA (OR, 2.14; 95% CI, 1.18–3.86; P = .01). Conclusions: The presence of mitoses (three or more) and/or total histologic features of three or more on CNB specimens were the most helpful features in predicting PT on excision.

Abstract To reveal biologic mechanisms underlying clinical outcome of high-grade serous (HGS) epithelial ovarian carcinomas (EOC), we evaluated the association between tumor epigenetic changes and time to recurrence (TTR). We assessed methylation at approximately 450,000 genome-wide CpGs in tumors of 337 Mayo Clinic (Rochester, MN) patients. Semi-supervised clustering of discovery (n = 168) and validation (n = 169) sets was used to determine clinically relevant methylation classes. Clustering identified two methylation classes based on 60 informative CpGs, which differed in TTR in the validation set [R vs. L class, P = 2.9 × 10−3, HR = 0.52; 95% confidence interval (CI), 0.34–0.80]. Follow-up analyses considered genome-wide tumor mRNA expression (n = 104) and CD8 T-cell infiltration (n = 89) in patient subsets. Hypomethylation of CpGs located in 6p21.3 in the R class associated with cis upregulation of genes enriched in immune response processes (TAP1, PSMB8, PSMB9, HLA-DQB1, HLA-DQB2, HLA-DMA, and HLA-DOA), increased CD8 T-cell tumor infiltration (P = 7.6 × 10−5), and trans-regulation of genes in immune-related pathways (P = 1.6 × 10−32). This is the most comprehensive assessment of clinical outcomes with regard to epithelial ovarian carcinoma tumor methylation to date. Collectively, these results suggest that an epigenetically mediated immune response is a predictor of recurrence and, possibly, treatment response for HGS EOC. Cancer Res; 74(11); 3084–91. ©2014 AACR.

Abstract Background: Breast cancer is not a homogeneous disease, but several different and unique subtypes defined by gene expression analysis. Incidence and mortality rates vary by almost 3-fold between Alaska (highest) and the Southwestern tribes (lowest). We hypothesized that these differences may be due to, in part, varying levels of biologic tumor aggressiveness. Methods: A biorepository of the North Central Cancer Treatment Group with 95 cases of American Indian and Alaska Native (AIAN) women with adenocarcinoma of the breast surgically treated from 1990 to 2000 was tested for several biomarkers. Comparison distributions of biomarker values across state of residence using t tests for continuous (p53, MIB-1, cyclin D) and ordinally scaled markers [EGF receptor (EGFR), BCL-2, Her2] and χ2 tests of significance for binary markers [estrogen receptor (ER), progesterone receptor (PR)] were done. Results: Significant regional differences in some biomarker expression levels were seen. No increase was observed in “triple-negative” breast cancer or Her2 overexpression in these cases. Conclusions: Despite a 3-fold difference in breast cancer mortality in Alaska Native versus Southwestern American Indians, standard biomarkers such as ER, PR, and Her2 neu expression did not explain the disparity. Impact: There is a need for research to understand the biologic basis of breast cancer disparities in AIAN women. Potential for a prospective trial will be explored with tribes. See all articles in this CEBP Focus section, “Community Network Program Centers.” Cancer Epidemiol Biomarkers Prev; 23(3); 409–15. ©2014 AACR.

Abstract Atypical hyperplasia is a high-risk premalignant lesion of the breast, but its biology is poorly understood. Many believe that atypical ductal hyperplasia (ADH) is a direct precursor for low-grade ductal breast cancer, whereas atypical lobular hyperplasia (ALH) serves as a risk indicator. These assumptions underlie current clinical recommendations. We tested these assumptions by studying the characteristics of the breast cancers that develop in women with ADH or ALH. Using the Mayo Benign Breast Disease Cohort, we identified all women with ADH or ALH from 1967 to 2001 and followed them for later breast cancers, characterizing side of breast cancer versus side of atypia; time to breast cancer; type, histology, and grade of breast cancer, looking for patterns consistent with precursors versus risk indicators. A total of 698 women with atypical hyperplasia were followed a mean of 12.5 years; 143 developed breast cancer. For both ADH and ALH, there is a 2:1 ratio of ipsilateral to contralateral breast cancer. The ipsilateral predominance is marked in the first 5 years, consistent with a precursor phenotype for both ADH and ALH. For both, there is a predominance of invasive ductal cancers with 69% of moderate or high grade. Twenty-five percent are node positive. Both ADH and ALH portend risk for ductal carcinoma in situ and invasive breast cancers, predominantly ductal, with two thirds moderate or high grade. The ipsilateral breast is at especially high risk for breast cancer in the first 5 years after atypia, with risk remaining elevated in both breasts long term. ADH and ALH behave similarly in terms of later breast cancer endpoints. Cancer Prev Res; 7(2); 211–7. ©2014 AACR.

Abstract Background: Terminal ductal lobular units (TDLUs), the functional units of the breast for lactation, are the structures from which most breast cancers arise. TDLU involution, reflecting atrophy and loss of TDLUs, has been related to lower subsequent breast cancer risk. The predictors of such breast tissue aging, however, are not well defined. Given that estrogens and other hormones play a central role in the etiology of postmenopausal breast cancers, we conducted a study to assess the relationship between four hormones and sex hormone-binding globulin (SHBG) with markers of TDLU involution. Methods: Subjects included healthy women who volunteered between 2009 and 2011 to participate in the Komen Tissue Bank Study. Participants completed a risk factor questionnaire, provided a blood sample, and donated breast tissue for research. Our analysis was restricted to postmenopausal women who were not currently taking menopausal hormones (n=153). A pathologist, masked to patient data, assessed tissue sections for the presence of TDLUs and, among sections containing TDLUs (n=88), measured TDLU diameters for up to ten TDLUs per section. Both presence of TDLUs and TDLU diameter are inversely related to involution. Chemiluminescent immunometric assays were used to measure serum levels of estradiol (E2), SHBG, follicle-stimulating hormone (FSH), and prolactin. Percent free E2 was calculated from measured E2 and SHBG levels. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the presence of TDLUs (none or any) associated with tertiles of serum hormone and SHBG levels. Multivariable ordinal logistic regression was used to calculate ORs, 95% CIs, and p-trend for TDLU diameter categorized as tertiles (≥218.4, 218.4-281, and ≥281 microns) with serum hormone and SHBG levels. All models were adjusted for potential confounding factors. Results: The study population was 87.6% Caucasian with a mean age of 59.5 years, and >2/3 of the women were overweight or obese. Increasing percent free E2 was significantly associated with larger TDLU diameter (OR>2.53 vs. ≥1.99: 5.58, 95% CI: 1.48-21.07; p-trend=0.01), whereas increasing SHBG was associated with smaller TDLU diameter (OR>73nmol/L vs. ≥38 nmol/L: 0.19, 95% CI: 0.05-0.74; p-trend=0.02). Total E2 (p-trend=0.49), FSH (p-trend=0.85), and prolactin (p-trend=0.58) were not associated with TDLU diameter. We did not find significant relationships between the presence of TDLUs and any of the serum levels. Our observed relationships were not modified by age or other breast cancer risk factors, including BMI, years since menopause, and history of bilateral oophorectomy. Conclusion: Based on limited data, these findings suggest that sex hormones may play a role in TDLU involution. Thus, TDLU involution may represent one mechanism by which hormone levels influence breast cancer risk. TDLU measurements may therefore be helpful in assessing breast cancer risk as a marker of breast tissue aging. Analysis of the relationships between hormones and TDLU involution among premenopausal women may provide additional insights into early events in breast carcinogenesis. Citation Format: Zeina G. Khodr, Mark E. Sherman, Ruth M. Pfeiffer, Gretchen L. Gierach, Louise A. Brinton, Roni T. Falk, Deesha Patel, Laura Linville, Susan E. Clare, Daniel Visscher, Carolyn Mies, Stephen Hewitt, Anna Maria Storniolo, Jonine D. Figueroa. Endogenous hormone levels and lobular involution of the breast among healthy, postmenopausal women in the Komen Tissue Bank Study. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr B89.

Abstract Background: Terminal duct lobular units (TDLUs) are the anatomical source of most breast cancers. TDLU involution, manifested as atrophy and loss of TDLUs, is associated with reduced breast cancer risk. We hypothesize that breast cancer susceptibility loci are associated with TDLU involution. Accordingly, we evaluated relationships between 25 established breast cancer susceptibility markers and their association with TDLU involution in the Susan G. Komen for the Cure® Tissue Bank (KTB). Methods: Subjects were women ages 18-84 (N=680), who had no personal history of any cancer, were not currently taking menopausal hormones, completed a risk factor questionnaire, provided an Oragene® saliva sample, and donated a 10-guage needle tissue core from the upper outer breast quadrant for research. We genotyped 25 known single nucleotide polymorphisms (SNPs) associated with breast cancer risk using TaqMan® assays. Pathologists masked to risk data classified three features inversely related to TDLU involution using one histological section of breast tissue/subject: number of TDLUs per section (TDLU density), TDLU diameters and number of acini per TDLU. SNPS were compared to metrics of TDLU involution categorized in tertiles: TDLU density (0-1, 2-8, 9+), mean TDLU diameter (53-291, 292-415, 416-1143 microns), and mean number of acini per TDLU (2-10, 11-20, 21+). We estimated age-adjusted per-allele odds ratios (ORs) and 95% confidence intervals (CIs) using ordinal logistic regression models with TDLU measures as the outcome and SNPs as the explanatory variables. Associations with TDLU density were based on up to 680 women with genotype data, while associations with diameter and acini measures were based on up to 469 women with observed TDLUs. Results: The rs3803662 (TOX3/TNRC9) SNP risk allele showed an association with increased TDLU density, larger TDLUs, and more acini in TDLUs (TDLU density per-allele OR=1.29 95%CI=1.04-1.60; TDLU diameter OR=1.32 95%CI=1.00-1.74; and TDLU acini OR=1.34 95%CI=1.02-1.77), consistent with previous observations of significant associations seen for this SNP with mammographic density (a well-established risk factor for breast cancer), breast cancer risk, and survival of breast cancer. In addition, we observed associations for four other SNPs with TDLU density (rs311499, rs10483813, rs2981582, rs3817198), for one other SNP with mean TDLU diameter (rs11249433), and for three other SNPs with mean TDLU acini number (rs704010, rs10941679, rs11249433). Conclusion: These data suggest that breast cancer susceptibility SNPs may be associated with TDLU involution levels, and could represent a mechanism by which they influence breast cancer risk. These findings warrant replication in other studies and provide support for the concept that levels of TDLU involution represent an intermediate marker of breast cancer risk. Citation Format: Jonine D. Figueroa, Gretchen L. Gierach, Ruth Pfeiffer, Stephen Chanock, Louise Brinton, Deesha A. Patel, Daniel Visscher, Carolyn Mies, Stephen Hewitt, Susan Clare, Anna Maria Storniolo, Mark Sherman. Associations between breast cancer susceptibility markers and terminal duct lobular unit involution in normal breast tissues among women from the Susan G. Komen for the Cure® Tissue Bank. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 58.