Gail Score Research Articles

Deep learning assessment of senescence-associated nuclear morphologies in mammary tissue from healthy female donors to predict future risk of breast cancer: a retrospective cohort study

Cellular senescence has been associated with cancer as either a barrier mechanism restricting autonomous cell proliferation or a tumour-promoting microenvironmental mechanism that secretes proinflammatory paracrine factors. With most work done in non-human models and the heterogeneous nature of senescence, the precise role of senescent cells in the development of cancer in humans is not well understood. Furthermore, more than 1 million non-malignant breast biopsies are taken every year that could be a major resource for risk stratification. We aimed to explore the clinical relevance for breast cancer development of markers of senescence in mammary tissue from healthy female donors. In this retrospective cohort study, we applied single-cell deep learning senescence predictors, based on nuclear morphology, to histological images of haematoxylin and eosin-stained breast biopsy samples from healthy female donors at the Komen Tissue Bank (KTB) at the Indiana University Simon Cancer Center (Indianapolis, IN, USA). All KTB participants (aged ≥18 years) who underwent core biopsies for research purposes between 2009 and 2019 were eligible for the study. Senescence was predicted in the epithelial (terminal duct lobular units [TDLUs] and non-TDLU epithelium), stromal, and adipose tissue compartments using validated models, previously trained on cells induced to senescence by ionising radiation (IR), replicative exhaustion (or replicative senescence; RS), or antimycin A, atazanavir-ritonavir, and doxorubicin (AAD) exposures. To benchmark our senescence-based cancer prediction results, we generated 5-year Gail scores-the current clinical gold standard for breast cancer risk prediction-for participants aged 35 years and older on the basis of characteristics at the time of tissue donation. The primary outcome was estimated odds of breast cancer via logistic modelling for each tissue compartment based on predicted senescence scores in cases (participants who had been diagnosed with breast cancer as of data cutoff, July 31, 2022) and controls (those who had not been diagnosed with breast cancer). 4382 female donors (median age at donation 45 years [IQR 34-57]) were eligible for the study. As of data cutoff (median follow-up of 10 years [7-11]), 86 (2·0%) had developed breast cancer a mean of 4·8 years (SD 2·84) after date of donation and 4296 (98·0%) had not received a breast cancer diagnosis. Among the 86 cases, we found significant differences in adipose-specific IR and AAD senescence prediction scores compared with controls. Risk analysis showed that individuals in the upper half (above the median) of scores for the adipose tissue IR model had higher odds of developing breast cancer (odds ratio [OR] 1·71 [95% CI 1·10-2·68]; p=0·019), whereas the adipose AAD model revealed a reduced odds of developing breast cancer (OR 0·57 [0·36-0·88]; p=0·013). For the other tissue compartments and the RS model, no significant associations were found (except for stromal tissue via the IR model, had higher odds of developing breast cancer [OR 1·59, 1·03-2·49]). Individuals with both of the adipose risk factors had an OR of 3·32 (1·68-7·03; p=0·0009). Participants with 5-year Gail scores above the median had an OR for development of cancer of 2·33 (1·46-3·82; p=0·0012) compared with those with scores below the median. When combining Gail scores with our adipose AAD risk model, we found that individuals with both of these predictors had an OR of 4·70 (2·29-10·90; p<0·0001). When combining the Gail score with our adipose IR model, we found that individuals with both predictors had an OR of 3·45 (1·77-7·24; p=0·0002). Assessment of senescence-associated nuclear morphologies with deep learning allows prediction of future cancer risk from normal breast biopsy samples. The combination of multiple models improved prediction of future breast cancer compared with the current clinical benchmark, the Gail model. Our results suggest an important role for microscope image-based deep learning models in predicting future cancer development. Such models could be incorporated into current breast cancer risk assessment and screening protocols. Novo Nordisk Foundation, Danish Cancer Society, and the US National Institutes of Health.

Spatial N-glycomics of the normal breast microenvironment reveals fucosylated and high-mannose N-glycan signatures related to BI-RADS density and ancestry.

Higher breast cancer mortality rates continue to disproportionally affect black women (BW) compared to white women (WW). This disparity is largely due to differences in tumor aggressiveness that can be related to distinct ancestry-associated breast tumor microenvironments (TMEs). Yet, characterization of the normal microenvironment (NME) in breast tissue and how they associate with breast cancer risk factors remains unknown. N-glycans, a glucose metabolism-linked post-translational modification, has not been characterized in normal breast tissue. We hypothesized that normal female breast tissue with distinct Breast Imaging and Reporting Data Systems (BI-RADS) categories have unique microenvironments based on N-glycan signatures that varies with genetic ancestries. Profiles of N-glycans were characterized in normal breast tissue from BW (n=20) and WW (n=20) at risk for breast cancer using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). A total of 176 N-glycans (32 core-fucosylated and 144 noncore-fucosylated) were identified in the NME. We found that certain core-fucosylated, outer-arm fucosylated and high-mannose N-glycan structures had specific intensity patterns and histological distributions in the breast NME dependent on BI-RADS densities and ancestry. Normal breast tissue from BW, and not WW, with heterogeneously dense breast densities followed high-mannose patterns as seen in invasive ductal and lobular carcinomas. Lastly, lifestyles factors (e.g. age, menopausal status, Gail score, BMI, BI-RADS) differentially associated with fucosylated and high-mannose N-glycans based on ancestry. This study aims to decipher the molecular signatures in the breast NME from distinct ancestries towards improving the overall disparities in breast cancer burden.

Talking numbers: how women and providers use risk scores during and after risk counseling – a qualitative investigation from the NRG Oncology/NSABP DMP-1 study

ObjectivesLittle research exists on how risk scores are used in counselling. We examined (a) how Breast Cancer Risk Assessment Tool (BCRAT) scores are presented during counselling; (b) how women react...

Study of ductal lavage cytology in women at high risk for breast carcinoma

Background: Ductal lavage (DL) involves cannulating the nipple aspirate fluid (NAF)-producing ducts with a microcatheter and lavaging with saline to retrieve cells for cytological and molecular analysis. This method improves upon NAF and fine-needle aspiration and can provide important data on cellular yield and molecular markers in DL fluid. Aims and Objectives: This aimed to study the cytology of DL in women at risk of/clinicoradiological possibility of breast carcinoma and to correlate the cytology of DL with Gail risk score and with histopathology (wherever available). Materials and Methods: The present study, conducted at Hindu Rao Hospital, Delhi, between 2012 and 2014, examined 36 patients with nipple discharge. Nipple aspiration and DL were performed, and the results were analyzed and compared. The present study also looked at the correlation between DL results and the patient’s Gail score and correlated histopathology with DL cytology. Results: The present study enrolled 36 women and studied 50 ducts from 46 breasts. Nipple fluid was aspirated from 34 patients, with inadequate cellular material for diagnosis in 24 breasts, benign in 18, atypia in 2, and no malignancy found. The correlation of DL with Gail score was statistically significant, as was the correlation between epithelial cells in DL and NAF samples. The correlation between DL and histopathological findings was statistically insignificant. Conclusion: DL samples may miss atypical cells, and have higher epithelial cell count than NAF. Higher Gail score correlates with mild atypical cells in DL (P=0.003).

Abstract A071: Deciphering the normal breast microenvironment in Black women and White women

Abstract Despite having similar incidence of breast cancer, black women (BW) are typically diagnosed with more aggressive subtypes of breast cancer compared to white women (WW). One mediator contributing to the disparity in breast cancer mortality rates is the distinct tumor microenvironments (TME) associated with BW and WW. Yet, characterization of the normal microenvironment (NME) in breast tissue and how they may associate with breast cancer risk factors remains unknown. Contemporary literature reports that TMEs from BW and WW with breast cancer are characterized with higher densities of pro-tumorigenic macrophages (M2) and cancer-associated adipocytes have been observed in BW compared to WW, and typically associated with worse breast cancer prognosis. While the TME has been shown to be critical for breast cancer progression, the lack of characterization of the NME is a limiting factor towards understanding the molecular differences between a normal and cancerous breast microenvironment. We hypothesize that characterizing the tissue compositions in the breast NME could elucidate unique molecular signatures that may be contributing to distinct alterations that are driving the disparity in breast cancer aggressiveness in BW. The cohorts consisted of normal breast tissue from BW (n=20) and WW (n=20) with breast cancer risk determined by Gail score. The Gail model is a well-established tool used to assess the 5-year risk of developing invasive breast cancer based on demographic and clinical data. All tissues were obtained from the Susan G. Komen tissue bank and used with institutional permission. Profiles of N-glycans, a glucose metabolism-linked post-translational modification, were characterized in normal breast tissue from BW and WW at risk for breast cancer using matrix assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). Tissue from both cohorts were characterized based on their tissue compositions including areas rich in stroma, adipocytes, and crown like structures (CLSs), a pro-inflammatory process consisting of dying adipocytes surrounded by stroma and macrophages. Nearly 70 N-glycans were identified in the NME from both BW and WW. When comparing N-glycan peaks between premenopausal and postmenopausal women, one N-glycan peak (m/z 1905.633) was significantly higher in the premenopausal group (p&amp;lt;0.0001) regardless of genetic ancestry. However, when comparing peak m/z 1905.633 based on genetic ancestry, premenopausal and postmenopausal BW had significantly higher peak intensities compared to premenopausal and postmenopausal WW (premenopausal BW vs WW, p = 0.024; postmenopausal BW vs WW, p = 0.028). Overall, the data suggests that there may be distinct N-glycan structures associated with premenopausal and postmenopausal women based on genetic ancestry. Characterizing the NME from BW and WW at risk for breast cancer may help towards understanding potential breast stroma priming molecular signatures contributing to differences in breast cancer aggressiveness observed in BW compared to WW. Citation Format: Denys Rujchanarong, Anand Mehta, Richard R. Drake, Marvella E. Ford, Peggi M. Angel. Deciphering the normal breast microenvironment in Black women and White women [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A071.

Outcomes of Abbreviated MRI (Ab-MRI) for Women of any Breast Cancer Risk and Breast Density in a Community Academic Setting.

Abbreviated magnetic resonance imaging (Ab-MRI) has been evaluated for elevated breast cancer risk or dense breasts but has not been evaluated across all risk profiles. Patients selected underwent Ab-MRI from February 2020 to September 2021. Women were older than aged 30 years, up to date with screening mammography, and paid $299 cash. A total of 93 patients were identified with a mean age of 52 years; 92.5% were Caucasian, 0% black, and 97.9% were from high socioeconomic status. Mean Gail score was 14.2, and 83.3% had a lifetime risk of breast cancer <20%. Reasons for Ab-MRI: dense breasts (36.6%); family history (24.7%); palpable mass (12.9%). Providers ordering: OBGYN (49.5%); breast surgeon (39.1%); primary care (6.6%). Thirteen biopsies (14%) detected one breast cancer. 31.1% had a change in follow-up screening: 58.6% 6-month MRI, 20.7% 6-month mammogram, and 10.3% 6-month ultrasound. Negative predictive value was 100% (95% confidence interval [CI]: 95-100%, p < 0.0001). Sensitivity was 100% (95% CI: 2.5-100%, p < 0.0001), and specificity was 87% (95% CI: 78.3-93.1%, p < 0.0001) compared with 77.6% and 98.8% for mammography. Only one cancer was detected: cost of $27,807 plus cost of 13 MRI or ultrasound (US)-guided biopsies and additional follow-up imaging. Historically 20% of abnormalities detected on full MRI are malignant; however, 7.7% of ab-MRI abnormalities were malignant CONCLUSIONS: One third of women were recommended a change in follow-up, which predominantly included a 6-month MRI. Ab-MRI may introduce average risk women to unnecessary follow-up and increased biopsies with a lower cancer detection rate. Ab-MRI should be evaluated closely before implementation.

Metabolic Links to Socioeconomic Stresses Uniquely Affecting Ancestry in Normal Breast Tissue at Risk for Breast Cancer.

A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and they are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. One hypothesis is that chronic social and economic stressors result in ancestry-dependent molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue. Altered regulation of N-glycosylation of proteins, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, has been associated with two strong independent risk factors for breast cancer: increased breast density and body mass index (BMI). Interestingly, high body mass index (BMI) levels have been reported to associate with increases of cancer-associated N-glycan signatures. In this study, we used matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) to investigate molecular pattern changes of N-glycosylation in ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation was tested against social stressors including marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (BW=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. One specific N-glycan (2158 m/z) appeared dependent on ancestry with high sensitivity and specificity (AUC 0.77, Brown/Wilson p-value<0.0001). Application of a linear regression model with ancestry as group variable and socioeconomic covariates as predictors identified a specific N-glycan signature associated with different socioeconomic stresses. For WW, household income was strongly associated to certain N-glycans, while for BW, marital status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk.

Abstract P3-14-13: Metabolic links to socioeconomic stresses uniquely affecting race in normal breast tissue at risk for breast cancer

Abstract A primary difference between black women (BW) and white women (WW) diagnosed with breast cancer is not incidence, but aggressiveness of the tumor. Black women have higher mortalities with similar incidence of breast cancer compared to other race/ethnicities, and are diagnosed at a younger age with more advanced tumors with double the rate of lethal, triple negative breast cancers. There is ongoing debate regarding whether the underlying cause of higher mortality is related to healthcare inequalities or due to ancestry dependent molecular features found in normal breast tissue that facilitate the aggressive phenotype found in black women. One hypothesis is that chronic social and economic stressors result in molecular responses that create a tumor permissive tissue microenvironment in normal breast tissue, and these chronic stresses differ by race/ethnicity. In this study, we investigate molecular pattern changes in tissue N-glycosylation in a cohort of ancestry defined normal breast tissue from BW and WW with significant 5-year risk of breast cancer by Gail score. N-glycosylation, a glucose metabolism-linked post-translational modification attached to an asparagine (N) residue, was tested against social stressors. Social stresses included marital status, single, education, economic status (income), personal reproductive history, the risk factors BMI and age. Normal breast tissue microarrays from the Susan G. Komen tissue bank (WB=43; WW= 43) were used to evaluate glycosylation against socioeconomic stress and risk factors. There was no significant difference in age (Median age BW 42.5, 95% CI [40.0, 45.0]; WW 42.0, 95% CI [39.7, 44.3]). A subgroup of women had similar BMI (BW, n=24 Median BMI 29.5, 95% CI [27.6, 32.3]; WW, n=24 28.3, 95% CI [23.5, 31.6]. BW women had an overall lower median risk by 5-year Gail score, which, (BW 9.4, 95% CI [8.9, 9.9]; WW 10.4, 95% CI [8.1, 12.6]). Area under the receiver operating curve (AUC) ≥0.70, Brown/Wilson p-value &amp;lt;0.001 was used to assess for individual glycosylation differences in normal breast tissue at risk for breast cancer. Out of 55 N-glycans profiled in normal breast by glycomics mass spectrometry, one N-glycan appeared dependent on ancestry with high sensitivity and specificity (AUC 0.788, Brown/Wilson p-value&amp;lt;0.0001). For women of the same BMI, a total of 12 N-glycans could report potential ancestry-dependent differences. Interestingly, when we fit a linear regression model with ancestry as group variable and socioeconomic covariates as predictors, different N-glycans associated with different socioeconomic stresses. Five N-glycans in particular linked to different socioeconomic stresses for both BW and WW. For white women, household income was strongly associated to certain N-glycans, while for black women, marriage status (married and single) was strongly associated with the same N-glycan signature. Current work focuses on understanding if combined N-glycan biosignatures can further help understand normal breast tissue at risk. The data suggests that metabolic patterns linked to socioeconomic stresses may contribute to breast cancer risk dependent on ancestry. This study lays the foundation for understanding the complexities linking socioeconomic stresses and molecular factors to their role in ancestry dependent breast cancer risk and aggressiveness in black women. Citation Format: Peggi M Angel, Yeonhee Park, Danielle A Scott, Denys Rujchanarong, Sean Brown, Richard R Drake, George E Sandusky, Harikrishna Nakshatri. Metabolic links to socioeconomic stresses uniquely affecting race in normal breast tissue at risk for breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-14-13.

The effect of the use of the Gail model on breast cancer diagnosis in BIRADs 4a cases.

The BI-RADS classification system and the Gail Model are the scoring systems that contribute to the diagnosis of breast cancer. The aim of the study was to determine the contribution of Gail Model to the diagnosis of breast lesions that were radiologically categorized as BI-RADS 4A. We retrospectively examined the medical records of 320 patients between January 2011 and December 2020 whose lesions had been categorized as BI-RADS 4A. Radiological parameters of breast lesions and clinical parameters according to the Gail Model were collected. The relationship between malignant BI-RADS 4A lesions and radiological and clinical parameters was evaluated. In addition, the effect of the Gail Model on diagnosis in malignant BI-RADS 4A lesions was evaluated. Among radiological features, there were significant differences between lesion size, contour, microcalcification content, echogenicity, and presence of ectasia with respect to the pathological diagnosis (p <0.05). No significant difference was found between the lesions' pathological diagnosis and the patients' Gail score (p> 0.05). An analysis of the features of the Gail model revealed that there was no significant difference between the age of menarche, age at first live birth, presence of a first-degree relative with breast cancer, and a history of breast biopsy and the pathological diagnosis (p> 0.05). As a conclusion Gail Model does not contribute to the diagnosis of BC, especially in patients with BI-RADS 4A lesions.

906Can mammographic density add value to the Gail model in risk-stratifying women in BreastScreen Australia?

Abstract Background There is significant interest in personalised, risk-based breast cancer screening. This requires high quality risk assessment. The ‘Gail model’ risk assessment tool has been validated on over 40,000 BreastScreen Australia participants. We assess whether adding mammographic density (MD) information improves risk stratification on that cohort. Methods We used questionnaire data, baseline MD readings (using AutoDensity) and linked screening and cancer registry records from 40,158 BreastScreen Australia participants aged 50–69 years (via the lifepool cohort). We investigated incident invasive breast cancer rates by quintiles of Gail model scores, MD, and combinations of Gail and MD. Results Gail scores and MD values were weakly correlated (r≤0.02). Gail and MD were each strong predictors of incident breast cancer, but stronger predictors when used in combination. For example, the odds ratio for incident invasive breast cancer was 3.6 (95%CI 2.5-6.3) for the 17% of women in the upper two quintiles of both Gail and MD scores compared to the 17% of women in the lower two quintiles of both scores. In comparison, the odds ratio for breast cancer between same-size (each 17%) upper and lower groups for Gail score alone was 2.5 (95%CI 1.8-3.4), and for MD 1.9 (95%CI 1.2-2.9). Conclusions Combining Gail and MD categories improves risk stratification on BreastScreen Australia participants, compared to using Gail or MD alone. Key messages While questionnaire data and MD measures are each strong predictors of future invasive breast cancer among BreastScreen Australia participants, risk prediction is stronger when questionnaire and MD measures are combined.

Abstract PS8-02: Influence of a breast cancer polygenic risk score on adherence to preventive endocrine therapy in high risk women at 1 and 2 year follow-up: The genetic risk estimate (GENRE) trial

Abstract Background: Preventive endocrine therapy (ET) has been proven extensively to decrease breast cancer (BC) risk by 50-65%. Despite this significant reduction, a small proportion of high risk women take ET, due to attitudes toward medications, inaccurate risk perception and drug side-effects. The addition of a polygenic risk score (PRS), comprised of 77 BC genetic susceptibility loci (Single Nucleotide Polymorphisms (SNP)), to the standard risk calculator estimates, can be used to improve BC risk estimation. We previously reported on the influence of the PRS-adjusted BC risk estimates on the intent to use ET (Abstract, SABCS, 2019). Here we report on the influence of PRS-adjusted BC risk estimates on ET adherence at 1 and 2 year follow –up. We also report on ET side effects over this same time period. Methods: Women older than age 35 were eligible if they were deemed at high risk for BC by either a 5 year Gail Model risk of ≥3% or 10 year Tyrer-Cuzick risk (IBIS) of ≥5%. We excluded women with a personal history of BC or hereditary BC syndromes. At baseline, participants were counseled on their BC risk using standard risk calculators: Gail and IBIS risk scores (5 yr, 10 yr, &amp; lifetime) and ET options were discussed, including benefits and risks. Blood samples were obtained and genotyped for 77 SNPs, and an updated BC -PRS risk report was shared with study participants that reflected the IBIS and Gail risk predictions for 5 yr, 10 yr, &amp; lifetime BC risk with and without the PRS. A baseline self-reported questionnaire assessed understanding of BC risk and decision to take ET. Follow-up questionnaires at 1 and 2 years assessed self-reported ET adherence and ET side effects (vasomotor symptoms, vaginal symptoms, sexual dysfunction, weight gain, GI symptoms, headaches, breast sensitivity, mood changes, and joint pain). Adherence to ET at 1 and 2 year follow-up was stratified by three categories of lifetime PRS-BC risk: 0-20%; 20-40%; 40-100%. Results: 151 women at Mayo Clinic Rochester and CancerCare Manitoba were enrolled in the study from 2016 to 2017. Of the 149 participants with evaluable data at 1 and 2 year follow-up, 57 (38%) started on ET therapy, all within 1 year of the baseline visit; 43 (29%) were taking ET at 1 year and 33 (22%) were taking ET at 2 year follow-up, representing a discontinuation rate of 26% at 1 year and 42% at 2 year follow-up. Adherence to ET use at 1 year and 2 year follow-ups correlated significantly with the category of PRS-BC risk estimation: at 1 year follow up, 17% of those in the lowest PRS-IBIS risk category, 23% in the middle risk category and 50% of those in the highest risk category were taking ET (p=0.001). At 2 year follow up, 12% of those in the lowest PRS-IBIS risk category, 18% in the middle risk category and 38% of those in the highest risk category were taking ET (p=0.008). At 1 year follow up, participants taking ET reported significantly more bothersome symptoms of vaginal itching (p=0.010), weight gain (p=0.015) and joint pain (p=0.044), compared with those not on ET. There was a trend towards increased irritability and mood swings on those taking ET (p=0.059). At year 2 there was no significant difference in side effects between those taking and not taking ET. Conclusion: Adherence to ET in a population of women at high risk for BC decreased overtime and strongly correlated with the level of risk, with 38% of those at highest risk of breast cancer taking ET at 2 year follow up. Side effects of vaginal itching, weight gain and body aches were more common on those taking ET versus not taking ET at the 1 year follow-up, but did not differ at 2 year follow-up, possibly due to the fact that those with the most bothersome symptoms have discontinued ET by the 2 year follow up. Citation Format: Daniela Stan, Julian Kim, Daniel Schaid, Erin Carlson, Andrew Cooke, Christina A. Kim, Benjamin Goldenberg, Jason Sinnwell, Debjani Grenier, Amy Degnim, Fergus Couch, Celine Vachon, Sandhya Pruthi. Influence of a breast cancer polygenic risk score on adherence to preventive endocrine therapy in high risk women at 1 and 2 year follow-up: The genetic risk estimate (GENRE) trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-02.

Abstract PS11-14: Advanced precision health resources in the Susan G Komen tissue bank at the IU simon comprehensive cancer center

Abstract Background: Understanding how hereditary, lifestyle and demographic risk factors influence the development of breast cancer is critical for its prevention and treatment. For this purpose, the Susan G. Komen Tissue Bank at the IU Simon Comprehensive Cancer Center (KTB) serves as the world’s primary repository for normal breast tissue and blood samples from healthy women (~5,500 tissue + blood donors and ~4,500 blood-only donors). In addition, KTB has received mammograms, H&amp;E images and additional longitudinal health and wellness data from its donors via ongoing annual surveys. Whole genome sequencing has also recently been completed on a subset of 500 donors, including ~125 initially healthy donors who later went on to develop breast cancer. To make these disparate, multi-modal data accessible to the larger research community and add advanced precision health analytics capabilities to the KTB database, LifeOmic's Precision Health Cloud (PHC), a secure healthcare-compliant cloud platform, was chosen to host the KTB data moving forward. The PHC provides browsing and querying capabilities across all data including genomic, demographic, histology, donor surveys, and scanned images. Data from donors can be viewed individually as well as analyzed across cohorts of interest. Computation resources, such as informatics workflows and machine learning infrastructure, are available on the same secure environment to leverage the power of cloud computing without having to download large files. This is in addition to visual and custom analytics using Jupyter Notebooks accessible to collaborators. Methods: We loaded all available KTB data from ~10,000 donors into the PHC. Donor-reported data collected at the time of donation and subsequent follow-up questionnaire responses were loaded as FHIR Observations and Medications in the PHC. Additional imaging and genomic data loaded into the PHC include approximately 12,000 mammogram images, 5,000 H&amp;E images, 5,000 ancestry-informative genotypes and 500 VCF and BAM files from whole genome sequencing. A timeline view of each donor shows data collected from each donation and follow-up surveys. All genetic variants were annotated upon ingestion into the PHC with functional effect on genes, population allele frequency, ClinVar clinical significance and in silico predictions for functional impact. Results: To demonstrate the utility of KTB data hosted in the PHC, we will show how the PHC can be used to directly analyze genomic and donor-reported data, specifically focusing on the recent whole genome sequencing data from 500 donors. Whole genome sequencing data will be used to calculate the genetic ancestry of each donor compared to their self-reported ancestry and previously predicted ancestry from a 41-SNP ancestry panel. Additionally, we will calculate genomewide breast cancer polygenic risk scores and compare these with the survey-based Tyrer-Cuzick and Gail score risk measures. We will assess how the polygenic risk score further stratifies the donors that have germline pathogenic variants in a known breast cancer gene. For the ~125 sequenced donors that went on to develop breast cancer we will also investigate correlations between family history of cancer, age of diagnosis, prior gynecological history and lifestyle differences. All generated results will remain in the PHC for access by future KTB collaborators to continue to build the utility and value of the KTB data. Conclusions: We have shown how hosting KTB data in the PHC opens new opportunities for advanced precision health research for breast cancer researchers worldwide. As more specimens and diverse data sets including genomic, longitudinal and imaging information are being tracked and deposited into KTB, this resource will continue to grow to enable diverse research needs. Citation Format: Steven M Bray, Swee Seong Wong, Baiju G Parikh, Kevin C Wood, Samuel T Rysdyk, Jill E Henry, Natascia Marino, Milan Radovich, Anna Maria V Storniolo. Advanced precision health resources in the Susan G Komen tissue bank at the IU simon comprehensive cancer center [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS11-14.

Effects of Raloxifene Combined with Low-dose Conjugated Estrogen on the Endometrium in Menopausal Women at High Risk for Breast Cancer

OBJECTIVES:To compare the effects of low-dose conjugated estrogen (CE), raloxifene, and the combination thereof on the endometrium of postmenopausal women.METHODS:Postmenopausal women between 45 and 60 years of age, with Gail score≥1.67 and no endometrial disorders, were randomly assigned to receive low-dose CE (0.3 mg), raloxifene (60 mg), or combined therapy for 1 year. Transvaginal ultrasound was performed at baseline and every 3 months; the Kupperman Index was assessed at baseline and every 6 months. Endometrial biopsies were performed if endometrial thickness (ET) was ≥5 mm or if vaginal bleeding occurred. The primary outcome was the occurrence of ET≥5 mm over the one-year period.RESULTS:Seventy-three women were randomly assigned and analyzed on an intent-to-treat basis. Eight, three, and four women in the CE, raloxifene, and combination groups, respectively, exhibited ET≥5 mm. No genital bleeding was reported in the combination group. Endometrial biopsy revealed atrophy or polyps in all groups, with one patient in the CE group exhibiting a proliferative endometrium without atypia. At 6 months, there was a progressive increase in mean ET in the CE group, but not in the other two groups, with statistically significant differences at 6, 9, and 12 months. Mean scores for vasomotor symptoms and Kupperman Index favored the CE and combination groups over raloxifene.CONCLUSION:Combined raloxifene and low-dose CE decreased the severity of menopausal symptoms to a similar extent as CE alone and had similar effects as raloxifene alone on the endometrium.

A risk-associated Active transcriptome phenotype expressed by histologically normal human breast tissue and linked to a pro-tumorigenic adipocyte population

BackgroundPrevious studies have identified and validated a risk-associated Active transcriptome phenotype commonly expressed in the cancer-adjacent and histologically normal epithelium, stroma, and adipose containing peritumor microenvironment of clinically established invasive breast cancers, conferring a 2.5- to 3-fold later risk of dying from recurrent breast cancer. Expression of this Active transcriptome phenotype has not yet been evaluated in normal breast tissue samples unassociated with any benign or malignant lesions; however, it has been associated with increased peritumor adipocyte composition.MethodsDetailed histologic and transcriptomic (RNAseq) analyses were performed on normal breast biopsy samples from 151 healthy, parous, non-obese (mean BMI = 29.60 ± 7.92) women, ages 27–66 who donated core breast biopsy samples to the Komen Tissue Bank, and whose average breast cancer risk estimate (Gail score) at the time of biopsy (1.27 ± 1.34) would not qualify them for endocrine prevention therapy.ResultsFull genome RNA sequencing (RNAseq) identified 52% (78/151) of these normal breast samples as expressing the Active breast phenotype. While Active signature genes were found to be most variably expressed in mammary adipocytes, donors with the Active phenotype had no difference in BMI but significantly higher Gail scores (1.46 vs. 1.18; p = 0.007). Active breast samples possessed 1.6-fold more (~ 80%) adipocyte nuclei, larger cross-sectional adipocyte areas (p < 0.01), and 0.5-fold fewer stromal and epithelial cell nuclei (p < 1e−6). Infrequent low-level expression of cancer gene hotspot mutations was detected but not enriched in the Active breast samples. Active samples were enriched in gene sets associated with adipogenesis and fat metabolism (FDR q ≤ 10%), higher signature scores for cAMP-dependent lipolysis known to drive breast cancer progression, white adipose tissue browning (Wilcoxon p < 0.01), and genes associated with adipocyte activation (leptin, adiponectin) and remodeling (CAV1, BNIP3), adipokine growth factors (IGF-1, FGF2), and pro-inflammatory fat signaling (IKBKG, CCL13).ConclusionsThe risk-associated Active transcriptome phenotype first identified in cancer-adjacent breast tissues also occurs commonly in healthy women without breast disease who do not qualify for breast cancer chemoprevention, and independently of breast expressed cancer-associated mutations. The risk-associated Active phenotype appears driven by a pro-tumorigenic adipocyte microenvironment that can predate breast cancer development.

Abstract P3-08-20: The normal breast Active transcriptome associated with future breast cancer risk is driven by a dysregulated adipocyte microenvironment

Abstract Background: Previous studies of breast samples from cosmetic surgeries, benign biopsies associated with abnormal mammograms or cancer-adjacent tissue have identified at least two different transcriptional phenotypes of “normal” human breast tissue (Troester, 2009; Haakensen, 2011), including an “Active” phenotype linked to increased risk of later breast cancer mortality (Roman-Perez, 2012; Troester, 2016). This study compares breast histology and transcriptional phenotypes from healthy parous women with no prior history of breast disease who donated breast core biopsies for research and supplied reproductive histories enabling breast cancer risk calculation. Since the Active transcriptome phenotype was recently associated with increased mammary adipocyte content, we focused on the possibility that adipocyte activation contributes to the Active transcriptome and drives breast cancer risk. Methods: RNA from paraffin-embedded tissue sections sufficient for RNAseq analysis (~100ng) was extracted from 151/200 core biopsies donated to the Komen Tissue Bank by healthy, parous white women (age range: 27-66, median = 45) with no history of breast cancer. Questionnaire data enabled breast cancer risk (Gail) score calculation; and digitized H&amp;E images were used for histologic analyses. A previously validated classifying signature was used in unsupervised hierarchical clustering to identify samples with Active (78/151) vs. Inactive (73/151) transcriptome phenotypes for comparison with donor risk factors, breast tissue composition, and expression of candidate genes and gene signatures. Results: Mean (+/-SD) BMI and Gail score values were 29.60 (+/-7.92) and 1.27 (+/- 1.34), respectively; BMI scores were not significantly different by phenotype, but Gail scores were significantly higher for donors with an Active phenotype (1.46 vs. 1.18; p=0.007, Wilcoxon rank-sum). Active normal breast tissue samples possessed significantly more (%) adipocyte nuclei (p=3.9e-11) and greater adipocyte size (p&amp;lt;0.01), with fewer (%) stromal (p=4.3e-7) and (%) epithelial (p=1.2e-10) nuclei. Differentially expressed genes between the Active and Inactive phenotypes were significantly enriched for gene sets (GSEA) involved in fat differentiation and metabolism (14% at FDR q≤10%). Signature scores for cAMP-dependent lipolysis (known to drive breast cancer progression), as well as white adipose tissue “browning,” were significantly higher (Wilcoxon p&amp;lt;0.01) for the Active samples, as were specific genes reflecting adipocyte activation (leptin, adiponectin), remodeling (CAV1, BNIP3), adipokine growth factors (IGF-1, FGF2), and pro-inflammatory fat signaling (IKBKG, CCL13). Conclusion: In this cohort of predominantly non-obese women without breast disease, ~50% express an Active transcriptome phenotype previously linked to later-life breast cancer mortality. While &amp;gt;80% of this donor cohort would not qualify for breast cancer chemoprevention, those with Active transcriptomes had significantly higher Gail scores supporting their increased future risk for breast cancer development. The Active breast transcriptome is strongly associated with increased adipocyte content, size, and overexpression of signatures and genes (including those previously linked to breast cancer progression) indicating a differentially activated adipocyte population. This dysregulated mammary adipocyte microenvironment not only appears to underlie the Active transcriptome phenotype but also precedes and potentially predicts the future histologic development of breast cancer. Citation Format: Christopher C Benz, Taekyu Kang, Christina Yau, Chris Wong, Yulia Newton, Charlie Vaske, Stephen C Benz, Gregor Krings, Roman Camarda, Jill E Henry, Josh Stuart, Mark Powell. The normal breast Active transcriptome associated with future breast cancer risk is driven by a dysregulated adipocyte microenvironment [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-08-20.

Abstract P5-08-01: Breast cancer risk thresholds as a predictor of chemoprevention uptake in the Athena Breast Health Network

Abstract Background: Large-scale chemoprevention trials validated endocrine risk reduction strategies to lower breast cancer risk. We sought to understand the risk at which women are likely to adopt chemoprevention. A 5-year Gail risk of 1.67% or above is considered elevated risk, and the FDA indication for prescribing chemoprevention. We examined chemoprevention use in the Athena Breast Health Network (Athena), which includes approximately 100,000 women who are screened by mammography at Sanford Health, UC Davis, UC Irvine, UC Los Angeles, UC San Diego, and UC San Francisco. Methods: We calculated the Gail risk score for women who had completed an Athena online intake survey distributed before being seen at screening centers; this survey included questions about chemoprevention usage. First, we analyzed 16,518 surveys of 9,318 unique women without breast cancer or DCIS who received breast cancer screening at UCSF from 2011- 2018 and who consented to research. These women also self-reported use of chemoprevention. We stratified Gail risk scores by a threshold of 1.67%, and by percentiles to identify those women in the top 2.5% by age. We compared current chemoprevention use in these different breast cancer risk strata, and factors associated with its use. An analysis including all 100,000 women in the Athena Network will be presented at SABCS. Results: Overall, at UCSF, 48 of 9,318 women (0.51%) reported current chemoprevention use. The 5-year Gail risk was greater than 1.66% in 3,675 of 9,318 women (39%), of whom 205 (2.2%) were in the top 2.5% of risk by age. Chemoprevention use was reported by 13 of 205 (6.3%) women in the top 2.5% of risk by age (mean Gail risk 5.6%), as compared to 41 of 3,675 (1.1%) who were at Gail above 1.66% (mean Gail = 3.9%). Women in the top 2.5% and those with Gail risk &amp;gt;1.66% were significantly more likely to be using chemoprevention p&amp;lt; 0.01 for each respectively). Chemoprevention uptake was correlated with the joint effect of the top 2.5% of risk by age and increasing Gail score (OR = 10.25; P = 0.009). Preliminary results were consistent among the 100,000 women in the Athena registry (analysis ongoing). In addition, chemoprevention use was more likely in older women (OR = 1.10; P &amp;lt; 0.01, for every year of age) and in those women with Ashkenazi ancestry on both sides of the family compared to none (OR = 2.32; P = 0.02). Race and education were not associated with use of chemoprevention. Discussion: Women with higher Gail scores in the top 2.5% of risk by age are positively associated with current chemoprevention use (6.34%). Importantly, this analysis presents a risk-stratified, population-level risk reduction strategy, using the top 2.5% risk threshold by age. It provides an opportunity to specifically target chemoprevention to women at highest need to reduce their breast cancer risk. In the WISDOM Study (NCT02620852), we are prospectively testing active outreach based on breast cancer risk in the top 2.5% of risk by age, and have developed a breast health decisions aid to standardize communication of risk-reducing options. Citation Format: Yash S Huilgol, Holly Keane, Yiwey Shieh, Jeffrey Tice, Elad Ziv, Lisa Madlensky, Leah Sabacan, Irene Acerbi, Mandy Che, Allison Stover Fiscalini, Hoda Anton-Culver, Alexander D Borowsky, Sharon Hunt, Arash Naeim, Barbara Parker, Laura J van 't Veer, Athena Breast Health Network Investigators and Advocate Partners and Laura J Esserman. Breast cancer risk thresholds as a predictor of chemoprevention uptake in the Athena Breast Health Network [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-08-01.

Abstract PD3-03: Impact of the breast cancer polygenic risk score on preventive endocrine therapy adherence and endocrine therapy usage on quality of life - The Genetic Risk Estimate (GENRE) trial

Abstract Background: Studies demonstrate breast cancer risk reduction of 50-65% with the use of endocrine therapy (ET) and yet drug uptake and adherence in this setting is suboptimal even among high risk women. A Polygenic Risk Score (PRS) comprised of 77 BC genetic susceptibility loci (Single Nucleotide Polymorphisms (SNP)) can provide a personalized risk assessment and potentially influence ET adherence. We assessed ET adherence at 1 year comparing women whose risk estimate increased due to PRS versus women whose risk estimate decreased due to PRS. The effect of ET use on quality of life (hot flashes, night sweats, vaginal dryness, weight gain, joint pain) was evaluated. Methods: Eligible women required either a 5 year Gail Model risk of ≥3% or 10 year IBIS ( International Breast Intervention Study or Tyrer-Cuzick model) of ≥5%. Women with a history of breast cancer (BC) or hereditary BC syndrome were excluded. High risk women were counseled at baseline using their Gail and IBIS risk scores and ET options were discussed including benefits and risks. Participants completed a self-reported questionnaire at baseline to assess their understanding of breast cancer risk and decision to take preventive ET. Blood samples were obtained and genotyped for 77 SNPs, and the odds ratio from the SNPs were used to modify the IBIS and Gail risk estimates. The BC -PRS risk estimate information was shared with study participants that reflected the IBIS and Gail risk estimates for 5 year, 10 year, &amp; lifetime BC risk with and without the PRS. Follow up questionnaires at year 1 were administered to assess drug adherence and ET usage on quality of life. Results: 151 women were enrolled at Mayo Clinic Rochester and CancerCare Manitoba from 2016 to 2017. The median age was 56.1 (range 36-76.4), 35.6% were premenopausal, 98.7% were Caucasian and 64.7% had&amp;gt;1 family member with BC. Median 5yr, 10yr, &amp; lifetime IBIS- PRS risk estimates were 3.8% (2.0-11.5), 7.9% (5.0-23.1), and 25.3% (5.5 to 92.2). At year 1 (n=112 women) 46 % of those with an increase in risk when considering the BC-PRS score and 16 % with a decrease in risk were taking ET ( p&amp;lt; 0.001). Types of ET taken: tamoxifen-18, raloxifene- 3, exemestane -14 and missing-1. Women taking ET reported weight gain ( 19.4% vs 6.7%, p=0.04) and more joint pain ( 27.8 % vs 12%, p=0.04) when compared to women not taking ET. Conclusion: In high risk women, BC-PRS risk estimates in addition to standard BC risk calculators had a significant impact on preventive ET adherence. ET use was associated with weight gain and joint pain. Citation Format: Sandhya Pruthi, Julian O Kim, Daniel Schaid, Andrew Cooke, Christina Kim, Benjamin Goldenberg, Jason Sinnwell, Debjani Grenier, Fergus Couch, Celine Vachon. Impact of the breast cancer polygenic risk score on preventive endocrine therapy adherence and endocrine therapy usage on quality of life - The Genetic Risk Estimate (GENRE) trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD3-03.

Abstract P2-10-05: A breast cancer multi-racial/ethnic polygenic risk score for improved personalized breast cancer screening

Abstract Background: Polygenic risk scores (PRS) integrate risk information from breast cancer associated SNPs (single nucleotide polymorphism). The risk scores have mostly been developed in populations of European ancestry, and have been shown to improve risk prediction over standard breast cancer risk models in these populations. The ability of the PRS to personalize screening is currently being studied. We included PRS as a component of breast cancer risk assessment in the WISDOM Study, a trial of personalized vs. annual breast cancer screening. In order to account for race/ethnicity in PRS risk assessment, we developed a race/ethnicity calibrated and inclusive PRS risk score that we incorporated here into the Gail model to determine impact on risk stratification. Methods: We constructed two different PRS for each race/ethnicity: For Caucasian populations, we constructed two PRS based on SNPs discovered in European-ancestry populations. One PRS was based on 167 SNPs (PRS-167) and the other based on 313 SNPs (PRS-313) from the Breast Cancer Association Consortium studies as previously published. For each of the Asian-, Hispanic- and African-ancestry populations we added additional ancestry specific SNPs to the PRS-167 or the PRS-313, that were literature curated or our own identified race/ethnicity SNPs that we validated to provide independent risk prediction for their ancestry group: Asian added 10 or 4 additional SNPs, Hispanic 2 SNPs, and African 8 and 12 SNPs, respectively to each model. We tested this approach using datasets from several case-control studies of multiple racial/ethnic populations and compared discrimination of the models using area under the receiver operating characteristic curve (AUROC). Furthermore, we applied our multi-racial/ethnic PRS-313 in a sample of ~3000 multi-racial/ethnic women from the Athena Breast Screening Registry, case-control sampled by Gail score to be at elevated (Gail &amp;gt;1.67) or average (Gail≤1.67) risk, to evaluate the impact of our multi-ethnic adjustment on risk stratification. Results: A multi-race/ethnicity adjusted PRS-313 and PRS-167 plus ethnicity specific SNPs has moderate-high discriminatory power with AUROCs of 0.65 and 0.64, respectively. The specificity of our PRS-167 in the different race/ethnicity ancestries performs relatively well in Asian (AUROC 0.59) and Hispanic (AUROC 0.63) populations, but less so in African-ancestry (AUROC 0.56). Incorporating multi-race/ethnicity PRS into Gail model selected women, resulted in 20% of average-risk women transitioning to risk above 1.67%, and conversely, 38% of elevated risk patients were reclassified to average risk. Conclusion: We constructed a PRS risk score that can be applied to multi-ethnic populations and found moderate-high discrimination. Additional work is needed for the African-ancestry population. The addition of a multi-race/ethnicity SNP model to risk classification based on the Gail model significantly changes risk stratification and clinical care recommendations due to down- or up-reclassification of women at average versus elevated risk. Citation Format: Sarah Theiner, Donglei Hu, Scott Huntsman, Yiwey Shieh, Laura Fejerman, Irene Acerbi, Sarah D Sawyer, Paige Kendall, Wei Zheng, Dezheng Huo, Olufunmilayo I Olopade, Christopher Haiman, Karla Kerlikowske, Steven Cummings, Ester John, Gabriela Torres-Mejia, Lawrence H Kushi, Denise Wolf, Jeffery A Tice, David A Pearce, Laura Esserman, Athena Breast Health Network Investigators and Advocate Partners, Laura J van ‘t Veer, Elad Ziv. A breast cancer multi-racial/ethnic polygenic risk score for improved personalized breast cancer screening [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-10-05.

Abstract 3314: Normal breast tissue at risk for cancer development: A breast cancer initiating role for mammary adipocytes

Abstract Adipocytes are the predominant cell population in the normal breast and while recent attention has pointed to adipocyte-tumor cell crosstalk as a driver of breast cancer biology there have been few reports on the potential role of adipocytes in driving breast cancer initiation. Because normal breast tissue studies have invariably used reduction mammoplasty, benign biopsy or cancer-adjacent tissues, we studied random breast core biopsy samples donated by 145 healthy, parous, non-obese, white women (median age = 45, range 27-66 y) without any history of breast cancer. Using questionnaire data to calculate future breast cancer risk (Gail scores), we compared digitized microscopic breast tissue (H&amp;E) images with whole genome transcriptome profiling (RNAseq) from FFPE-extracted RNA. We used unsupervised hierarchical clustering of 1487 genes (normalized, median centered, log2-scaled RSEM values) to identify 32% of normal samples with an “Active” (vs. 68% “Inactive”) transcriptome phenotype previously associated with later-life risk of death from breast cancer. Despite slightly lower BMI values, donors with the Active transcriptome phenotype showed significantly higher Gail scores as well as higher mammary adipocyte nuclei counts (median 80% vs. 60%, p=2.3e-6). Tissue resident leukocytes were uncommon but Active transcriptome tissues expressed significantly altered immune modules enriched in TGFβ, interferon and macrophage gene signatures (including single gene increase in CD68) and depleted (relative to Inactive samples) of CD8+ T-cell and serum response/inflammation/wound healing signatures. Active samples were not enriched in cell senescence, SASP or DNA damage response gene signatures but were enriched in an autophagy-to-senescence-transition (AST) signature with increased CAV1 (caveolin-1, p=2.7e-12) and BNIP3 (Bcl2 interacting protein-3, p=4.7e-05) expression, genes that also regulate lipoprotein digestion/mobilization and adipocyte remodeling. Strongest among significant associations linking Active with adipocyte-enriched normal breast samples were increases in two adipokine growth factors, IGF-1 (p=2.2e-16) and FGF2 (p=3.0e-11), the adipokine (resistin) receptor CAP1 (p=0.04) recently linked to poor breast cancer outcomes, and a cAMP-dependent pro-lipolytic signature (p=0.01) known to drive breast cancer progression which, in these samples, correlated positively with average adipocyte area values. Altogether, the collective histologic and molecular features characterizing the normal breast tissue of &amp;gt;30% of healthy parous and non-obese women with increased predicted breast cancer risk seem to implicate a dysregulated mammary adipocyte microenvironment similar to but distinct from that associated with established breast tumors, that precedes microscopic and clinical evidence of breast tumorigenesis. Citation Format: Taekyu Kang, Christina Yau, Stephen Benz, Gregor Krings, Roman Camarda, Jill E. Henry, Mark Powell, Christopher C. Benz. Normal breast tissue at risk for cancer development: A breast cancer initiating role for mammary adipocytes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3314.

Impact of a breast cancer (BC) polygenic risk score (PRS) on the decision to take preventive endocrine therapy (ET): The Genetic Risk Estimate (GENRE) trial.

1501 Background: Despite BC risk reduction of 50-65% by preventive endocrine therapy (ET), very few at-risk women choose to take them. A woman’s perceived BC risk correlates with uptake of ET. A PRS comprised of 77 BC genetic susceptibility loci (Single Nucleotide Polymorphisms (SNP) improves the accuracy of risk prediction for BC. We examined the impact of the addition of individualized PRS BC risk prediction to standard risk calculator estimates on intent to take BC prevention medication. Methods: Eligible women had ≥5% 10 yr BC Tyrer-Cuzick risk (IBIS) or 5 year Gail score ≥3%, with no history of BC or hereditary BC syndrome. Standard BC risk estimates (IBIS or Gail) were incorporated into the counselling on BC preventive ET. A self-reported questionnaire at baseline quantified intention to take ET and explored factors associated with this decision. Blood samples were obtained and genotyped for 77 SNPs, individualized PRS were calculated then incorporated into IBIS and Gail predictions for 5 yr, 10 yr, &amp; lifetime BC risk. At a second visit, PRS risk &amp; prevention recommendations were revisited. Post visit questionnaires assessed change in intent to take ET. Multivariable linear regression was performed to assess impact of baseline variables on change in intent to take medication. Results: From 2016 to 2017, 151 women in Canada &amp; USA were enrolled, median age: 56.1 (range 36-76.4), 35.6% were premenopausal, 98.7% were Caucasian. Median 5yr, 10yr, &amp; lifetime IBIS risk estimates were 3.8% (2.0-11.5), 7.9% (5.0-23.1), and 25.3% (5.5 to 92.2). PRS increased BC risk estimates in 84 (55.6%) and reduced BC risk estimates in 67 (44%) women. After PRS risk counselling, intention to take ET significantly changed (p&lt;0.001): 41.9% of those with increased PRS were more inclined, and 46.7% of women with decreased PRS were less inclined to take ET. On multivariable regression, increase in PRS (p&lt;0.0001) and less concern about ET side effects (p&lt;0.0001) were associated with greater intent to take ET. Conclusions: In high risk women, PRS significantly changed BC risk estimates &amp; intent to take preventive ET. Further assessments of the impact of PRS scores on compliance with ET are warranted. Clinical trial information: NCT02517593.