Sherman, Mark E.

Abstract Purpose: Expression of the tumor suppressor gene E-cadherin is diminished in lobular breast cancers and has been implicated in epithelial mesenchymal transition. We assessed risk factor associations for breast cancer stratified by low vs. high E-cadherin protein expression in a pooled analysis within the Breast Cancer Association Consortium (BCAC) studies. Methods: E-cadherin tumor tissue staining was performed centrally at the NCI on formalin-fixed paraffin-embedded tissue microarray (TMA) sections representing 6,010 breast cancer patients from 12 US and European BCAC studies. TMAs were digitally scanned and scored using the SlidePath Digital Image Hub (Leica Biosystems, Wetzlar, Germany). For 5,896 cancers with evaluable tumors, E-cadherin was visually scored as estimated percent of positive cells times stain intensity (0, 1+, 2+, 3+) (score range 0-300). E-cadherin low was defined as tumors with a score < 100. Risk factor associations for low vs. high E-cadherin expressing tumors were evaluated by logistic regression, adjusted for age and study site, and stratified by ER status and histologic subtype. To assess the consistency in results by study, meta-analyses were performed using the random-effects model. All statistical tests were two-sided. Results: E-cadherin low cancers comprised 20% of tumors and were associated with lobular histology, well/moderately differentiated cancers, > 2cm in size, and HER2-negative status (χ2, P < 0.003 for all factors). E-cadherin low status was associated with family history of breast cancer (FH) (OR = 1.32, 95% CI = 1.09-1.60, P-het = 0.005) and ever use of menopausal hormones (OR = 1.26, 95% CI = 1.02-1.56, P-het = 0.03). Study specific meta-plots showed consistent effects across studies for menopausal hormone therapy (I2 = 0.0%, p = 0.64); however, E-cadherin loss by FH did show evidence of heterogeneity by study (I2 = 54%, P = 0.03). Differences in E-cadherin expression remained significant for FH, and menopausal hormone use when further adjusted for ER (P < 0.05). We also found relationships with E-cadherin loss to vary by BMI, number of live births, age at first birth, and oral contraceptive use in stratified analysis by ER status and histologic subtype. Conclusion: This large pooled analysis shows that breast cancer risk factor associations may differ by E-cadherin expression independent of ER status, suggesting that it may represent a marker of etiologic heterogeneity. Citation Format: Hisani N. Horne, Hannah Oh, Mark E. Sherman, Maya Palakal, Stephen H. Hewitt, Marjanka Schmidt, Javier Benitez, Roger Milne, Hermann Brenner, Heli Nevanlinna, Arto Mannermaa, Georgia Chenevix-Trench, Fergus Couch, Peter Devilee, Diana Eccles, Maartje Hooning, Anthony J. Swerdlow, Nick Orr, Melissa A. Troester, Renata Cora, Paul D. Pharoah, Montserrat Garcia-Closas, Jonine D. Figueroa. Breast cancer risk factor associations by loss of E-cadherin tumor tissue expression: A pooled analysis of 5,896 cases in 12 studies from the Breast Cancer Association Consortium (BCAC). [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3451.

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.

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.

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes‐type shrinkage estimator. Six SNPs showed interactions with associated p ‐values ( p int ) <1.1 × 10 −3 . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER‐negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER‐negative BC risk in women <160 cm (OR = 0.83, p = 0.039, p int = 1.9 × 10 −4 ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10 −4 ), and absent in women who had had just one (OR = 0.96, p = 0.19, p int = 6.1 × 10 −4 ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10 −5 ), but no association was observed in current smokers (OR = 1.07, p = 0.14, p int = 3.4 × 10 −4 ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.

Abstract Background: Endometrial cancers account for over 46,000 cases and 8,100 deaths annually in the U.S. Endometrial cancers that are confined to the uterus portend an excellent prognosis, suggesting that development of early detection methods for these tumors could reduce mortality. To identify and validate markers with potential utility in early detection of endometrial cancers, we compared DNA methylation profiling data for endometrial cancer tissues collected in a population-based epidemiological study and a comparison set of benign endometrial tissues, and replicated promising candidates in a separate clinical study. Methods: We used the Illumina Golden Gate platform to profile DNA methylation of CpGs at 1536 sites (807 genes) using fixed tissues from 148 endometrial cancers included in the population-based Polish Endometrial Cancer Study (cases) and 23 benign endometrial tissues collected at Magee Women's Hospital (controls). Tissue cores (1.0-mm) removed from target-rich areas of blocks were used for DNA extraction, bisulfite treatment and profiling. We replicated top candidate markers by applying pyrosequencing assays to endometrial brushings performed prior to hysterectomy among 38 women with endometrial cancer and 37 with benign gynecological diseases treated at the Mayo Clinic and calculated odds ratios comparing the highest tertile of methylation values in controls for each marker with middle and low tertiles. In addition, we assessed discrimination across the whole range of cutoffs using Receiver Operator Characteristics (ROC) curves. Results: Methylation profiling identified 114 CpG sites with differential methylation levels between cases and controls (P≤10-7). Eight genes (ADCYAP1, ASCL2, HS3ST2, HTR1B, MME, NPY, and SOX1) which showed large case-control differences in methylation levels (≥ 0.4), and low values in controls (&lt;0.2) were chosen for replication by pyrosequencing in pre-hysterectomy patients. In the replication study, higher methylation levels were found for 7 of 8 genes in endometrial brush samples from women with cancer as compared to women without cancer. In the replication study, odds ratios for association of methylation markers with endometrial cancer ranged from 3.6 (95%-CI: 1.35-9.47) for HTR1B to 10.9 (95%-CI: 3.23-36.91) for ASCL2. Discrimination of cases and controls was best for ADCYAP1 (area under ROC curve=0.89; 95% CI: 0.80-0.97), CDH13 (0.87; 95% CI: 0.80-0.97), and MME (0.87; 95% CI: 0.78-0.97). Conclusions: Analysis of DNA methylation markers in endometrial brushings is strongly associated with prevalent endometrial cancer at hysterectomy. Development and validation of a robust early detection marker panel for endometrial cancers, including non-endometrioid cancers and precursor lesions is ongoing. Citation Format: Nicolas A. Wentzensen, Jamie Bakkum, Keith Killian, Viji Shridhar, Lisa Adams, Richard Guido, Lori D'Ambrosio, Patricia Luhn, Joshua Sampson, Hannah Yang, Louise Brinton, Jolanta Lissowska, Karl Podratz, Mark Sherman. Discovery and validation of methylation markers for early detection of endometrial cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3477. doi:10.1158/1538-7445.AM2013-3477

Abstract The 19p13.1 breast cancer susceptibility locus is a modifier of breast cancer risk in BRCA1 mutation carriers and is also associated with the 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 OR, 1.10; 95% confidence interval (CI), 1.05–1.15; P = 3.49 × 10−5] and triple-negative (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 triple-negative cases were excluded (OR, 0.98; 95% CI, 0.89–1.07; P = 0.62). In addition, a combined analysis of triple-negative cases from BCAC and the Triple Negative Breast Cancer Consortium (TNBCC; N = 3,566) identified a genome-wide significant association between rs8170 and triple-negative 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 histologic 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. Cancer Res; 72(7); 1795–803. ©2012 AACR.

Abstract Background: The single-nucleotide polymorphism (SNP) 5p12-rs10941679 has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium. Methods: Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS), and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression. Results: For white Europeans, the per-allele OR associated with 5p12-rs10941679 was 1.11 (95% CI = 1.08–1.14, P = 7 × 10−18) for invasive breast cancer and 1.10 (95% CI = 1.01–1.21, P = 0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR = 1.07, 95%CI = 0.99–1.15, P = 0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR = 1.16, 95% CI = 1.12–1.20, P = 1 × 10−18 vs. OR = 1.03, 95% CI = 0.99–1.07, P = 0.2 for PR-negative disease; Pheterogeneity = 2 × 10−7); heterogeneity by ER status was not observed (P = 0.2) once PR status was accounted for. The association was also stronger for lower grade tumors [per-allele OR (95% CI) = 1.20 (1.14–1.25), 1.13 (1.09–1.16), and 1.04 (0.99–1.08) for grade 1, 2, and 3/4, respectively; Ptrend = 5 × 10−7]. Conclusion: 5p12 is a breast cancer susceptibility locus for PR-positive, lower grade breast cancer. Impact: Multicenter fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants. Cancer Epidemiol Biomarkers Prev; 20(10); 2222–31. ©2011 AACR.