Figueroa, Jonine D.

AbstractAutomated methods are needed to facilitate high‐throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large‐scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37–0.87) and study (kappa range = 0.39–0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p‐value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000–4,500 cells: kappa = 0.78) than those with lower counts (50–500 cells: kappa = 0.41; p‐value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre‐ and post‐analytical quality control procedures are necessary in order to ensure satisfactory performance.

Abstract Purpose: Breast biopsies with benign findings (benign breast disease [BBD]) outnumber biopsies revealing in-situ or invasive cancer 4:1, providing an opportunity to identify histopathological features that predict breast cancer risk. Greater degrees of involution of terminal duct lobular units (TDLUs), the structures within the breast that produce milk and the primary source of breast cancer precursors, have been inversely associated with breast cancer risk among women with BBD. We recently developed measures to quantitate levels of TDLU involution, which demonstrate high inter/intra pathologist reproducibility. Here we assessed whether TDLU counts/100mm2 and median TDLU span (microns), two measures inversely related to degree of TDLU involution, are associated with subsequent breast cancer risk among women with BBD. Methods: From the Mayo BBD cohort (n = 9,376), we evaluated benign biopsies from 99 women who later developed breast cancer (cases) and 145 age-matched controls who did not develop breast cancer. Digitized images of biopsy sections were reviewed to enumerate TDLUs/mm2 and measure median TDLU span (microns) for up to ten normal TDLUs. Breast cancer risk factors were available from questionnaires or medical records. To assess associations with breast cancer risk, subjects were categorized into quartile levels of TDLU counts and median TDLU spans, based on data from controls. Odds ratios (ORs) and 95% confidence intervals (CI) were estimated using multivariable conditional logistic regression models, adjusted for histologic type of BBD, family history of breast cancer and menopausal hormone use. Results: Compared to controls, women who developed breast cancer had higher median number of TDLU counts/100mm2 (28 vs 20, p = 0.03) and larger TDLU spans (300 vs 267 microns, p = 0.14). In multivariable models higher TDLU counts (quartile4 vs. quartile1, OR = 2.44, 95%CI = 0.96-6.19, ptrend = 0.02) and larger TDLU span measures (quartile4 vs. quartile1, OR = 2.83, 95%CI = 1.13-7.06, ptrend = 0.03) were associated with subsequent diagnosis of breast cancer. Combinatorial metrics of TDLU counts with median TDLU span measures identified women at higher risk; specifically, women above the median for both TDLU span and TDLU counts had an OR = 3.75 (95%CI = 1.40-10.00, ptrend = 0.008), compared with women below the median for TDLU span and TDLU counts. Conclusion: These data show that lack of TDLU involution, as measured by increased persistence of TDLU counts, larger median TDLU spans and cross-classification using these measures was associated with increased breast cancer risk among women with BBD, extending prior work in this cohort based on other TDLU involution metrics. Future studies to identify determinants of TDLU involution, its association with breast cancer risk and its potential as an intermediate endpoint in prevention studies warrant consideration. Citation Format: Jonine D. Figueroa, Ruth Pfeiffer, Maya Palakal, Amy C. Degnim, Derek Radisky, Lynn C. Hartmann, Marlene Frost, Melody L. Stallings Mann, Louise A. Brinton, Daphne Papathomas, Daniel Visscher, Mark E. Sherman. Standardized measures of lobular involution and subsequent breast cancer risk among women with benign breast disease. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4682. doi:10.1158/1538-7445.AM2015-4682

AbstractBreast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.

Abstract Background: Terminal duct lobular units (TDLU) are the predominant source of breast cancers. Lesser degrees of age-related TDLU involution have been associated with increased breast cancer risk, but factors that influence involution are largely unknown. We assessed whether circulating hormones, implicated in breast cancer risk, are associated with levels of TDLU involution using data from the Susan G. Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center (2009–2011). Methods: We evaluated three highly reproducible measures of TDLU involution, using normal breast tissue samples from the KTB (n = 390): TDLU counts, median TDLU span, and median acini counts per TDLU. RRs (for continuous measures), ORs (for categorical measures), 95% confidence intervals (95% CI), and Ptrends were calculated to assess the association between tertiles of estradiol, testosterone, sex hormone–binding globulin (SHBG), progesterone, and prolactin with TDLU measures. All models were stratified by menopausal status and adjusted for confounders. Results: Among premenopausal women, higher prolactin levels were associated with higher TDLU counts (RRT3vsT1:1.18; 95% CI: 1.07–1.31; Ptrend = 0.0005), but higher progesterone was associated with lower TDLU counts (RRT3vsT1: 0.80; 95% CI: 0.72–0.89; Ptrend < 0.0001). Among postmenopausal women, higher levels of estradiol (RRT3vsT1:1.61; 95% CI: 1.32–1.97; Ptrend < 0.0001) and testosterone (RRT3vsT1: 1.32; 95% CI: 1.09–1.59; Ptrend = 0.0043) were associated with higher TDLU counts. Conclusions: These data suggest that select hormones may influence breast cancer risk potentially through delaying TDLU involution. Impact: Increased understanding of the relationship between circulating markers and TDLU involution may offer new insights into breast carcinogenesis. Cancer Epidemiol Biomarkers Prev; 23(12); 2765–73. ©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.