Background More than 1.5 million women per year have a benign breast biopsy resulting in concern about their future breast cancer (BC) risk. This study examined the performance of 2 BC risk models that integrate clinical and histologic findings in this population. Methods The BC risk at 5 and 10 years was estimated with the Breast Cancer Surveillance Consortium (BCSC) and Benign Breast Disease to Breast Cancer (BBD‐BC) models for women diagnosed with benign breast disease (BBD) at the Mayo Clinic from 1997 to 2001. Women with BBD were eligible for the BBD‐BC model, but the BCSC model also required a screening mammogram. Calibration and discrimination were assessed. Results Fifty‐six cases of BC were diagnosed among the 2142 women with BBD (median age, 50 years) within 5 years (118 were diagnosed within 10 years). The BBD‐BC model had slightly better calibration at 5 years (0.89; 95% confidence interval [CI], 0.71‐1.21) versus 10 years (0.81; 95% CI, 0.70‐1.00) but similar discrimination in the 2 time periods: 0.68 (95% CI, 0.60‐0.75) and 0.66 (95% CI, 0.60‐0.71), respectively. In contrast, among the 1089 women with screening mammograms (98 cases of BC within 10 years), the BCSC model had better calibration (0.94; 95% CI, 0.85‐1.43) and discrimination (0.63; 95% CI, 0.56‐0.71) at 10 years versus 5 years (calibration, 1.31; 95% CI, 0.94‐2.25; discrimination, 0.59; 95% CI, 0.46‐0.71) where discrimination was not different from chance. Conclusions The BCSC and BBD‐BC models were validated in the Mayo BBD cohort, although their performance differed by 5‐year risk versus 10‐year risk. Further enhancement of these models is needed to provide accurate BC risk estimates for women with BBD.
Model for Predicting Breast Cancer Risk in Women With Atypical Hyperplasia
Purpose Women with atypical hyperplasia (AH) on breast biopsy have an aggregate increased risk of breast cancer (BC), but existing risk prediction models do not provide accurate individualized estimates of risk in this subset of high-risk women. Here, we used the Mayo benign breast disease cohort to develop and validate a model of BC risk prediction that is specifically for women with AH, which we have designated as AH-BC. Patients and Methods Retrospective cohorts of women age 18 to 85 years with pathologically confirmed benign AH from Rochester, MN, and Nashville, TN, were used for model development and external validation, respectively. Clinical risk factors and histologic features of the tissue biopsy were selected using L1-penalized Cox proportional hazards regression. Identified features were included in a Fine and Gray regression model to estimate BC risk, with death as a competing risk. Model discrimination and calibration were assessed in the model-building set and an external validation set. Results The model-building set consisted of 699 women with AH, 142 of whom developed BC (median follow-up, 8.1 years), and the external validation set consisted of 461 women with 114 later BC events (median follow-up, 11.4 years). The final AH-BC model included three covariates: age at biopsy, age at biopsy squared, and number of foci of AH. At 10 years, the AH-BC model demonstrated good discrimination (0.63 [95% CI, 0.57 to 0.70]) and calibration (0.87 [95% CI, 0.66 to 1.24]). In the external validation set, the model showed acceptable discrimination (0.59 [95% CI, 0.51 to 0.67]) and calibration (0.91 [95% CI, 0.65 to 1.42]). Conclusion We have created a new model with which to refine BC risk prediction for women with AH. The AH-BC model demonstrates good discrimination and calibration, and it validates in an external data set.
A Soft Microenvironment Protects from Failure of Midbody Abscission and Multinucleation Downstream of the EMT-Promoting Transcription Factor Snail
Mechanical forces are increasingly recognized to regulate morphogenesis, but how this is accomplished in the context of the multiple tissue types present within a developing organ remains unclear. Here we use bioengineered “microfluidic chest cavities” to precisely control the mechanical environment of the fetal lung. We show that transmural pressure controls airway branching morphogenesis, the frequency of airway smooth muscle contraction, and the rate of developmental maturation of the lungs, as assessed by transcriptional analyses. Timelapse imaging reveals that branching events are synchronized across distant locations within the lung, and are preceded by long-duration waves of airway smooth muscle contraction. Higher transmural pressure decreases the interval between systemic smooth muscle contractions and increases the rate of morphogenesis of the airway epithelium. These data reveal that the mechanical properties of the microenvironment instruct crosstalk between different tissues to control the development of the embryonic lung.
Macrophagic “Crown-like Structures” Are Associated with an Increased Risk of Breast Cancer in Benign Breast Disease
Abstract Metabolic reprogramming plays a critical role in carcinogenesis, in part due its ability to promote immune suppressive properties within tumors. Agents that specifically target crucial metabolic enzymes utilized by cancer are been actively investigated. However, it is unclear whether inhibition of fatty acid metabolism in tumors affects their immunogenicity. Here, we show for the first time that inhibition of stearoyl-CoA desaturase 1 (SCD1), a key enzyme involved in fatty-acid synthesis and a potential prognostic marker for human cancers, increases the immunogenicity of poorly immunogenic tumors. The enhanced immune activation is accompanied by upregulated endoplasmic reticulum (ER) stress and is dependent on the translocation of ER protein calreticulin to the tumor cell surface. Inhibition of SCD1 increased both recruitment and activation of immune cells in vivo, which when combined with PD-1 blockade resulted in potent and durable anti-tumor T cell responses. Together, our results indicate that inhibition of tumorigenic de novo lipogenesis represents a novel approach to enhance T cell based cancer immunotherapy. Citation Format: Christina Anna Elizabeth Von Roemeling, Thomas Caulfield, Yaqing Qie, Derek C. Radisky, Xiujie Liu, Yuanxin Chen, Joshua Knight, John Copland, Betty Kim. Blockade of stearoyl CoA desaturase 1 promotes immunogenic clearance of tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-189. doi:10.1158/1538-7445.AM2017-LB-189
Abstract 4253: Expression profiling of paired benign and breast cancer lesions in African American women
Abstract Benign breast disease, a known risk factor for subsequent breast cancer, includes a histological spectrum of lesions that can be subdivided based on the overall impression into non-proliferative lesions, proliferative lesions without atypia, and atypical hyperplasia. Yet little is known about the molecular characteristics of benign breast tissue from African American women, who suffer from disproportionately high breast cancer mortality rates. 72 breast samples from African American women were obtained. RNA was extracted from archival formalin-fixed, paraffin-embedded (FFPE) blocks. Gene expression profiling was performed on these samples using the Affymetrix HTA2.0 exon array chip. A fit linear model using generalized least squares identified probe sets with differential expression in benign-in situ and benign-invasive breast cancer paired lesions. 36 benign and 36 breast cancer paired lesions were included in the study. In the benign-in situ set (n=20), 978 probe sets were differentially expressed (threshold: fold-change, 1.50; p < 0.05). Probe sets mapped to 125 annotated genes, of which 69 (55.2%) were involved in cancer. The benign-invasive set (n=52) identified 351 differentially expressed probe sets that mapped to 84 annotated genes, of which 61 (72.6%) had known cancer significance. Genes involved in cellular growth and proliferation were significantly over-expressed in both benign-in situ and benign-invasive lesions (p-values < 0.0104). In the population of 36 paired samples, differentially expressed genes were found to regulate the estrogen receptor (ESR1) through distinct network associations. Many genes are differentially expressed by benign and breast cancer lesions, and in situ/invasive histology contribute to the distinct molecular characteristics and pathways of breast malignancy. Our findings highlight the first study to assess expression profiling of paired benign and breast cancer lesions among African American women. Citation Format: Andreana Natalie Holowatyj, Julie J. Ruterbusch, Rouba Ali-Fehmi, Sudeshna Bandyopadhyay, Christine Mehner, Melody Stallings Mann, Gregory Dyson, Derek Radisky, Michele L. Cote. Expression profiling of paired benign and breast cancer lesions in African American women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4253. doi:10.1158/1538-7445.AM2017-4253
Abstract 5299: Validation of the BCSC model within the Mayo Benign Breast Disease Cohort
Abstract Background: The Breast Cancer Surveillance Consortium (BCSC) model predicts invasive breast cancer risk in women with Benign Breast Disease (BBD), and recently incorporated BBD histology into the model. The BCSC has been validated in the Mayo Mammography Health Study, but has yet to be examined in Mayo Clinic’s BBD cohort. The Benign Breast Disease to Breast Cancer (BBD-BC) model predicts risk of both invasive and in situ breast cancer. Here we compare the performance of the BCSC and BBD-BC in Mayo Clinic’s BBD cohort. Methods: Eligible women underwent a breast biopsy with benign findings at the Mayo Clinic between years 1997-2001 and had a 4-view screening mammogram within six months of biopsy. Clinical BI-RADS density assessments using the 4th edition American College of Radiology were available on all mammograms, and were coded as almost entirely fat, scattered fibroglandular densities, heterogeneously dense, and extremely dense. Risk at 5 and 10 years of invasive cancer only (BCSC model) or both invasive and in situ cancer (BBD-BC model) were estimated. In situ cancers were censored at time of diagnosis for both models. Concordance statistics, i.e. model discrimination (higher is better), for each model were calculated using a Cox proportional hazards model with predicted risk as the sole predictor, and were compared using permutation tests. The ratio of total predicted (sum of predicted risk) to observed number of invasive breast cancers was used to assess model calibration. Calibration was not formally compared across models due to differences in how DCIS was treated in the development of each (BCSC censored; BBD-BC event). Results: 999 women met inclusion criteria. BI-RADS density was categorized as fatty in 46 (4.6%), scattered densities in 372 (37.2%), heterogeneously dense in 423 (42.3%), and extremely dense in 158 (15.8%). 62 invasive cancers occurred over a median 13.3yrs of follow-up, with 16 (25.8%) and 48 (77.4%) of the cancers occurring with-in 5 and 10 years. The concordance of the BCSC at 5 years was 0.550 (95% CI 0.409—0.691), compared to 0.719 (95% CI 0.578—0.860) for the BBD-BC (p-value=0.005). At 10 years the BCSC concordance was not significantly different from the BBD-BC, at 0.624 (95% CI 0.542—0.706) and 0.662 (95% CI 0.580—0.744), respectively (p-value=0.306). The BCSC over predicted the number invasive cancers in the BBD cohort at 5 years (predicted-to-observed=1.54; 95% CI 1.01—2.70), but was well calibrated at 10 years (1.06; 95% CI 0.83, 1.47). Conclusions: The BCSC model performed reasonably well in the BBD Cohort 10 years post-biopsy, but overestimated risk at 5 years. Additional study is needed to improve models for prediction of breast cancer risk among women with BBD. Citation Format: Ryan D. Frank, Celine M. Vachon, Stacey J. Winham, Robert A. Vierkant, Marlene H. Frost, Derek C. Radisky, Daniel W. Visscher, Amy C. Degnim. Validation of the BCSC model within the Mayo Benign Breast Disease Cohort [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5299. doi:10.1158/1538-7445.AM2017-5299