Subtype-specific Breast Research Articles

Exploring the epigenetic profile of ID4 in breast cancer: bioinformatic insights into methylation patterns and chromatin accessibility dynamics.

Inhibitor of differentiation 4 (ID4) is a dominant-negative regulator of basic helix-loop-helix (bHLH) transcription factors. The expression of ID4 is dysregulated in various breast cancer subtypes, indicating a potential role for ID4 in subtype-specific breast cancer development. This study aims to elucidate the epigenetic regulation of ID4 within breast cancer subtypes, with a particular focus on DNA methylation and chromatin accessibility. Bioinformatic analyses were conducted to assess DNA methylation and chromatin accessibility in ID4 regulatory regions across breast cancer subtypes. Gene Set Enrichment Analysis (GSEA) was conducted to identify related gene sets. Transcription factor binding within ID4 enhancer and promoter regions was explored. In vitro experiments involved ER+ breast cancer cell lines treated with estradiol (E2) and Tamoxifen. Distinct epigenetic profiles of ID4 were observed, revealing increased methylation and reduced chromatin accessibility in luminal subtypes compared to the basal subtype. Gene Set Enrichment Analysis (GSEA) implicated estrogen-related pathways, suggesting a potential link between estrogen signaling and the regulation of ID4 expression. Transcription factor analysis identified ER and FOXA1 as regulators of ID4 enhancer regions. In vitro experiments confirmed the role of ER, demonstrating reduced ID4 expression and increased methylation with estradiol treatment. Conversely, Tamoxifen treatment increased ID4 expression, indicating the potential involvement of ER signaling through ERα in the epigenetic regulation of ID4 in breast cancer cells. This study shows the intricate epigenetic regulation of ID4 in breast cancer, highlighting subtype-specific differences in DNA methylation and chromatin accessibility.

Abstract 4332: Isoform-level transcriptome-wide analyses identify extensive genetic mechanisms for breast cancer risk undetectable on the gene-level

Abstract Genome-wide association studies (GWAS) have identified over 170 genetic variants associated with breast cancer risk. Integrative methods, like colocalization and transcriptome-wide association studies (TWAS), can identify potential biological mediators for genetic associations but, to date, have only contextualized a fraction of GWAS loci. This reduced discovery is due to an overreliance on reference transcriptomic panels of total gene expression, which ignore widespread alternative splicing that gives rise to multiple transcript-isoforms of the same gene with differing effects on tumorigenesis and progression. However, integrating highly correlated transcript-isoforms with phenotypic associations from genome-wide association studies (GWAS) requires methodological innovations.Here, we first introduce isoTWAS, a multivariate, machine learning method to integrate genetics, isoform-level expression, and phenotypic associations in a step-wise testing framework, and present its advantages over traditional gene-level methods.We then apply isoTWAS to multiomic data from non-cancerous breast samples from the Genotype-Tissue Expression Project (GTEx) and breast cancer risk GWAS summary statistics from the Breast Cancer Association Consortium. In total, we generated strong predictive models for 70,816 isoforms across 12,103 genes and estimated isoform associations for overall and subtype-specific breast cancer risk. We observed 570 associated isoforms across 384 unique genes (compared to 141 associated genes out of 14,613 genes tested in a gene-level TWAS with the same GWAS) at FDR and FWER-corrected P < 0.05. Critically, isoTWAS prioritized isoform associations within 1 Megabase of 66 independent GWAS-significant loci compared to 22 from gene-level TWAS. Of these isoforms within 1 Megabase of a GWAS locus, 19 associated isoforms had a significantly associated risk variant within the gene body. Of note, we find a negative association between the ESR1 isoform ENST00000488573 and overall breast cancer risk (P = 3.35 x 10-9). Previous studies using breast tissue have not prioritized ESR1 expression as a potential mediator, despite strong SNP associations at this locus. We are currently updating transcriptomic annotations using long-read RNA-sequencing data to improve the precision and specificity of GTEx isoform-level quantifications. We will then expand our isoTWAS analysis to other related tissues (connective, adipose, and immune-related tissues) to identify causal susceptibility transcripts for overall and subtype-specific risk. Our study underscores the wealth of information remaining in bulk RNA-seq datasets that sophisticated methods like isoTWAS can leverage to identify genetic risk mechanisms for breast cancer that is missed with traditional gene-centric measurements and methods. Citation Format: Arjun Bhattacharya, Yung-Han Chang, Bogdan Pasaniuc, Sara Lindstroem. Isoform-level transcriptome-wide analyses identify extensive genetic mechanisms for breast cancer risk undetectable on the gene-level [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4332.

RANK and RANKL Expression in Tumors of Patients with Early Breast Cancer

AbstractThe receptor activator of nuclear factor-κB (RANK) pathway was associated with the pathogenesis of breast cancer. Several studies attempted to link the RANK/RANKL pathway to prognosis; however, with inconsistent outcomes. We aimed to further contribute to the knowledge about RANK/RANKL as prognostic factors in breast cancer. Within this study, protein expression of RANK and its ligand, RANKL, in the tumor tissue was analyzed in association with disease-free survival (DFS) and overall survival (OS) in a study cohort of patients with early breast cancer.607 samples of female primary and early breast cancer patients from the Bavarian Breast Cancer Cases and Controls Study were analyzed to correlate the RANK and RANKL expression with DFS and OS. Therefore, expression was quantified using immunohistochemical staining of a tissue microarray. H-scores were determined with the cut-off value of 8.5 for RANK and 0 for RANKL expression, respectively.RANK and RANKL immunohistochemistry were assessed by H-score. Both biomarkers did not correlate (ρ = −0.04). According to molecular subtypes, triple-negative tumors and HER2-positive tumors showed a higher number of RANK-positive tumors (H-score ≥ 8.5), however, no subtype-specific expression of RANKL could be detected. Higher RANKL expression tended to correlate with a better prognosis. However, RANK and RANKL expression could not be identified as statistically significant prognostic factors within the study cohort.Tumor-specific RANK and RANKL expressions are not applicable as prognostic factors for DFS and OS, but might be associated with subtype-specific breast cancer progression.

RANK and RANKL Expression in Tumors of Patients with Early Breast Cancer

AbstractThe receptor activator of nuclear factor-κB (RANK) pathway was associated with the pathogenesis of breast cancer. Several studies attempted to link the RANK/RANKL pathway to prognosis; however, with inconsistent outcomes. We aimed to further contribute to the knowledge about RANK/RANKL as prognostic factors in breast cancer. Within this study, protein expression of RANK and its ligand, RANKL, in the tumor tissue was analyzed in association with disease-free survival (DFS) and overall survival (OS) in a study cohort of patients with early breast cancer.607 samples of female primary and early breast cancer patients from the Bavarian Breast Cancer Cases and Controls Study were analyzed to correlate the RANK and RANKL expression with DFS and OS. Therefore, expression was quantified using immunohistochemical staining of a tissue microarray. H-scores were determined with the cut-off value of 8.5 for RANK and 0 for RANKL expression, respectively.RANK and RANKL immunohistochemistry were assessed by H-score. Both biomarkers did not correlate (ρ = −0.04). According to molecular subtypes, triple-negative tumors and HER2-positive tumors showed a higher number of RANK-positive tumors (H-score ≥ 8.5), however, no subtype-specific expression of RANKL could be detected. Higher RANKL expression tended to correlate with a better prognosis. However, RANK and RANKL expression could not be identified as statistically significant prognostic factors within the study cohort.Tumor-specific RANK and RANKL expressions are not applicable as prognostic factors for DFS and OS, but might be associated with subtype-specific breast cancer progression.

Structure learning for gene regulatory networks.

Inference of biological network structures is often performed on high-dimensional data, yet is hindered by the limited sample size of high throughput "omics" data typically available. To overcome this challenge, often referred to as the "small n, large p problem," we exploit known organizing principles of biological networks that are sparse, modular, and likely share a large portion of their underlying architecture. We present SHINE-Structure Learning for Hierarchical Networks-a framework for defining data-driven structural constraints and incorporating a shared learning paradigm for efficiently learning multiple Markov networks from high-dimensional data at large p/n ratios not previously feasible. We evaluated SHINE on Pan-Cancer data comprising 23 tumor types, and found that learned tumor-specific networks exhibit expected graph properties of real biological networks, recapture previously validated interactions, and recapitulate findings in literature. Application of SHINE to the analysis of subtype-specific breast cancer networks identified key genes and biological processes for tumor maintenance and survival as well as potential therapeutic targets for modulating known breast cancer disease genes.

Abstract P5-03-06: Effect of Sleep Traits on Subtype Specific Breast Cancer Survival: a Mendelian Randomization Analysis

Abstract Background There is increasing interest in the relationship between sleep traits and both quality of life and survival in breast cancer. Recent work has found that oestrogen receptor positive (ER+) tumour cells are more likely to spread, via the circulation, at night than in the morning, providing support for a potential role of sleep characteristics influencing metastasis and therefore survival from breast cancer. The aim of this study was to investigate causal effects of sleep traits on subtype-specific breast cancer survival. Methods Single-nucleotide polymorphisms (SNPs) identified from GWAS associated with sleep traits with were used as a genetic instruments for Chronotype (N=697,828), Insomnia (N=1,331,010), Sleep Duration (N=446,118), Napping (N=452,633), Daytime sleepiness(N=452,071) and Ease of Getting up (N=461,658). All instruments were identified in data from UK Biobank, except chronotype and insomnia, which were identified in meta-analyses of UK Biobank and 23andme. For all instruments female-specific effect estimates were used. For these SNPs, summary statistics of their association with breast cancer survival were obtained from GWAS meta-analyses of European women from the Breast Cancer Association Consortium (BCAC), (N=91,686, with 7531 breast cancer specific deaths over a median follow-up of 8.1 years). To estimate the causal effect of the sleep traits on breast cancer survival, we applied two-sample MR for both overall and subtype-specific breast cancer (Luminal A-like, Luminal B-like, Human Epidermal Growth Factor 2 (Her2) positive, Her2 negative and triple negative (TNBC)). Further stratification by tumour characteristics at diagnosis and treatment received was also used. Sensitivity analyses were used to assess the robustness of main analyses to MR assumptions. Results For every hour increase in sleep duration, we observed worsening 5-year breast cancer specific survival in patients with ER+ tumours who received endocrine therapy (HR: 2.55, 95% CI: 1.10, 5,82) and for all patients receiving aromatase inhibitors (HR: 9.57, 95% CI: 1.61, 57.10). Conversely, improved 5-year survival was observed in patients with ER- tumours who received chemotherapy (HR: 0.30, 95% CI: 0.10, 0.87) and all patients receiving taxanes (HR: 0.23, 95% CI: 0.05, 0.98). We also observed that an increase in daytime sleepiness improved 15-year survival in patients both overall (HR: 0.34, 95% CI: 0.14, 0.80) and with lymph node negative tumours at diagnosis (HR: 0.12, 95% CI: 0.02, 0.64). Detailed sensitivity analyses are ongoing. Conclusions The current study uses a causal approach to identify potential effects between sleep patterns and breast cancer survival and confirms the previously observed relationships with increased sleep duration and worse survival in ER+ breast cancer. The reasons for opposite effects seen in those with ER- and those receiving taxanes needs further mechanistic work. Although the improved survival in relation to increased daytime sleepiness appears to be in-keeping with previous findings, this may largely reflect shorter sleep duration. Further work accurately characterising sleep quality, rather than duration in those with breast cancer, examining the effects on quality of life and survival and establishing mechanisms are needed. Citation Format: Bryony Hayes, Richard Martin, Deborah Lawlor, Rebecca Richmond, Tim Robinson. Effect of Sleep Traits on Subtype Specific Breast Cancer Survival: a Mendelian Randomization Analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-03-06.

Integrating multi-type aberrations from DNA and RNA through dynamic mapping gene space for subtype-specific breast cancer driver discovery.

Driver event discovery is a crucial demand for breast cancer diagnosis and therapy. In particular, discovering subtype-specificity of drivers can prompt the personalized biomarker discovery and precision treatment of cancer patients. Still, most of the existing computational driver discovery studies mainly exploit the information from DNA aberrations and gene interactions. Notably, cancer driver events would occur due to not only DNA aberrations but also RNA alternations, but integrating multi-type aberrations from both DNA and RNA is still a challenging task for breast cancer drivers. On the one hand, the data formats of different aberration types also differ from each other, known as data format incompatibility. On the other hand, different types of aberrations demonstrate distinct patterns across samples, known as aberration type heterogeneity. To promote the integrated analysis of subtype-specific breast cancer drivers, we design a "splicing-and-fusing" framework to address the issues of data format incompatibility and aberration type heterogeneity simultaneously. To overcome the data format incompatibility, the "splicing-step" employs a knowledge graph structure to connect multi-type aberrations from the DNA and RNA data into a unified formation. To tackle the aberration type heterogeneity, the "fusing-step" adopts a dynamic mapping gene space integration approach to represent the multi-type information by vectorized profiles. The experiments also demonstrate the advantages of our approach in both the integration of multi-type aberrations from DNA and RNA and the discovery of subtype-specific breast cancer drivers. In summary, our "splicing-and-fusing" framework with knowledge graph connection and dynamic mapping gene space fusion of multi-type aberrations data from DNA and RNA can successfully discover potential breast cancer drivers with subtype-specificity indication.

Postmenopausal overweight and breast cancer risk; results from the KARMA cohort

PurposeTo study the risk of incident breast cancer and subtype-specific breast cancer in relation to excess body weight in a contemporary Swedish prospective cohort study, The Karolinska Mammography Project for Risk Prediction of Breast Cancer, KARMA.MethodsA total of 35,412 postmenopausal women attending mammography and included in the KARMA study provided baseline data on body mass index (BMI) and potential confounders. During eight years of follow-up, 822 incident invasive breast cancer cases were identified.ResultsWomen with overweight (BMI ≥ 25–< 30 kg/m2) constituting 34% of the study cohort had an increased risk of incident breast cancer with an adjusted Hazard Ratio (HRadj) 1.19 (95% CI 1.01–1.4). A similar, however, non-significant, association was found for women with obesity (BMI ≥ 30 kg/m2) conferring 13% of the cohort, with a HRadj of 1.19 (95% CI 0.94–1.5). Overweight was associated with risk of node-negative disease (HRadj 1.29, 95% CI 1.06–1.58), whereas obesity was associated with node-positive disease (HRadj 1.64, 95% CI 1.09–2.48). Both overweight and obesity were associated with risk of estrogen receptor positive (ER+) disease (HRadj 1.20, 95% CI 1.00–1.44 and HRadj 1.33, 95% CI 1.03–1.71, respectively), and low-grade tumors (HRadj 1.25, 95% CI 1.02–1.54, and HRadj 1.40, 95% CI 1.05–1.86, respectively). Finally, obesity was associated with ER+HER2 negative disease (HRadj 1.37, 95% CI 1.05–1.78) and similarly luminal A tumors (HRadj 1.43, 95% CI 1.02–2.01).ConclusionOverweight and obesity are associated with an increased risk of developing breast cancer, specifically ER+, low-grade, and for obesity, node-positive, high-risk breast cancer indicating a further need for risk communication and preventive programs.

Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry.

Simple SummaryGenetic variants explaining approximately 40% of familial breast cancer risk have been identified, thus leaving a significant fraction of the heritability of this disease still unexplained. The exact nature of this missing fraction is unknown; more extensive sequencing efforts could potentially identify new moderate-penetrance breast cancer risk alleles. The aim of this study was to perform a large-scale whole-exome sequencing study, followed by a targeted validation, in breast cancer patients and healthy women of European descent. We identified 20 novel genes with modest evidence of association (p-value < 0.05) for either overall or subtype-specific breast cancer; however, much larger studies are needed to confirm the exact role of these genes in susceptibility to breast cancer.Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.

Abstract 3670: Systematic literature review of risk factor associations with breast cancer subtypes in women of African, Asian, Hispanic, and European descents

Abstract Background: Studies have reported differences in associations between breast cancer risk factors and subtypes defined by hormone receptor status, particularly estrogen receptor (ER) positive versus ER negative tumors. Most studies have been conducted in women of European descent, and an expanding body of literature in other populations suggests differences by race/ethnicity. Clarifying whether associations between risk factors and disease subtypes are consistent across racial/ethnic populations has important implications for understanding disease etiology and for improving risk prediction models. To address this question, we conducted a qualitative literature review to investigate the consistency in associations between multiple breast cancer risk factors and risk of tumor subtypes in women of African, Asian, Hispanic, and European descent. Methods: We searched PubMed for publications between January 1, 1990 and June 8, 2021 that reported associations between breast cancer risk factors and risk of subtypes of the disease. We evaluated 19 risk factors, including reproductive, anthropometric, lifestyle, and diet factors, as well as medical history and use of menopausal hormone therapy (MHT). Subtypes were defined as ER positive or negative (specifically triple negative when available). We prioritized review studies (i.e., meta-analyses, systematic reviews, and pooled analyses) and included individual studies with populations not included in the reviews. The number of publications per risk factor ranged from 3 for calcium intake to 28 for parity, with up to 7 reviews per risk factor. Most publications reported estimates for women of European descent, followed by Asian, African, and Hispanic. Evidence of subtype heterogeneity was determined by expert review. Results: There was strong evidence of association between reproductive factors and MHT with risk of ER positive but not ER negative disease. Parity, younger age at first birth and older age at menarche were associated with lower risk of ER positive disease, while MHT use was associated with higher risk of ER positive disease. For these risk factors, we did not find evidence that risk associations or etiologic heterogeneity varied by race/ethnicity. For the other risk factors, there was limited or no evidence of heterogeneity in risk associations by subtype, which was consistent across racial/ethnic groups. Few publications, however, specifically studied women of non-European ancestry. Conclusion: For most breast cancer risk factors, evidence is insufficient to evaluate differences in ER-specific risk associations by race/ethnicity. More studies are needed to evaluate subtype-specific breast cancer risk factors in diverse populations, which will be important for informing the development of multi-ethnic/racial BC risk prediction models that account for subtype heterogeneity. Citation Format: Amber N. Hurson, Thomas U. Ahearn, Renske Keeman, Mustapha Abubakar, Audrey Y. Jung, Pooja Middha Kapoor, Hela Koka, Xiaohong R. Yang, Jenny Chang-Claude, Elena Martínez, Rulla M. Tamimi, Melissa A. Troester, Elisa V. Bandera, Marjanka K. Schmidt, Montserrat Garcia-Closas. Systematic literature review of risk factor associations with breast cancer subtypes in women of African, Asian, Hispanic, and European descents [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3670.

Association between Ancestry-Specific 6q25 Variants and Breast Cancer Subtypes in Peruvian Women.

Breast cancer incidence in the United States is lower in Hispanic/Latina (H/L) compared with African American/Black or Non-Hispanic White women. An Indigenous American breast cancer-protective germline variant (rs140068132) has been reported near the estrogen receptor 1 gene. This study tests the association of rs140068132 and other polymorphisms in the 6q25 region with subtype-specific breast cancer risk in H/Ls of high Indigenous American ancestry. Genotypes were obtained for 5,094 Peruvian women with (1,755) and without (3,337) breast cancer. Associations between genotype and overall and subtype-specific risk for the protective variant were tested using logistic regression models and conditional analyses, including other risk-associated polymorphisms in the region. We replicated the reported association between rs140068132 and breast cancer risk overall [odds ratio (OR), 0.53; 95% confidence interval (CI), 0.47-0.59], as well as the lower odds of developing hormone receptor negative (HR-) versus HR+ disease (OR, 0.77; 95% CI, 0.61-0.97). Models, including HER2, showed further heterogeneity with reduced odds for HR+HER2+ (OR, 0.68; 95% CI, 0.51-0.92), HR-HER2+ (OR, 0.63; 95% CI, 0.44-0.90) and HR-HER2- (OR, 0.77; 95% CI, 0.56-1.05) compared with HR+HER2-. Inclusion of other risk-associated variants did not change these observations. The rs140068132 polymorphism is associated with decreased risk of breast cancer in Peruvians and is more protective against HR- and HER2+ diseases independently of other breast cancer-associated variants in the 6q25 region. These results could inform functional analyses to understand the mechanism by which rs140068132-G reduces risk of breast cancer development in a subtype-specific manner. They also illustrate the importance of including diverse individuals in genetic studies.

Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach.

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Development and validation of polygenic risk scores for prediction of breast cancer and breast cancer subtypes in Chinese women

BackgroundStudies investigating breast cancer polygenic risk score (PRS) in Chinese women are scarce. The objectives of this study were to develop and validate PRSs that could be used to stratify risk for overall and subtype-specific breast cancer in Chinese women, and to evaluate the performance of a newly proposed Artificial Neural Network (ANN) based approach for PRS construction.MethodsThe PRSs were constructed using the dataset from a genome-wide association study (GWAS) and validated in an independent case-control study. Three approaches, including repeated logistic regression (RLR), logistic ridge regression (LRR) and ANN based approach, were used to build the PRSs for overall and subtype-specific breast cancer based on 24 selected single nucleotide polymorphisms (SNPs). Predictive performance and calibration of the PRSs were evaluated unadjusted and adjusted for Gail-2 model 5-year risk or classical breast cancer risk factors.ResultsThe primary PRSANN and PRSLRR both showed modest predictive ability for overall breast cancer (odds ratio per interquartile range increase of the PRS in controls [IQ-OR] 1.76 vs 1.58; area under the receiver operator characteristic curve [AUC] 0.601 vs 0.598) and remained to be predictive after adjustment. Although estrogen receptor negative (ER−) breast cancer was poorly predicted by the primary PRSs, the ER− PRSs trained solely on ER− breast cancer cases saw a substantial improvement in predictions of ER− breast cancer.ConclusionsThe 24 SNPs based PRSs can provide additional risk information to help breast cancer risk stratification in the general population of China. The newly proposed ANN approach for PRS construction has potential to replace the traditional approaches, but more studies are needed to validate and investigate its performance.

Association of Genetic Ancestry With Terminal Duct Lobular Unit Involution Among Healthy Women.

Reduced age-related terminal duct lobular unit (TDLU) involution has been linked to increased breast cancer risk and triple-negative breast cancer. Associations of TDLU involution levels with race and ethnicity remain incompletely explored. Herein, we examined the association between genetic ancestry and TDLU involution in normal breast tissue donated by 2014 healthy women in the United States. Women of African ancestry were more likely than European women to have increased TDLU counts (odds ratio [OR]trend = 1.36, 95% confidence interval [CI] = 1.07 to 1.74), acini counts per TDLU (OR = 1.47, 95% CI = 1.06 to 2.03), and median TDLU span (ORtrend = 1.44, 95% CI = 1.08 to 1.91), indicating lower involution, whereas East Asian descendants were associated with decreased TDLU counts (ORtrend = 0.52, 95% CI = 0.35 to 0.78) after controlling for potential confounders. These associations are consistent with the racial variations in incidence rates of triple-negative breast cancer in the United States and suggest opportunities for future work examining whether TDLU involution may mediate the racial differences in subtype-specific breast cancer risk.

Rare germline copy number variants (CNVs) and breast cancer risk

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E−18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

Detection of subtype-specific breast cancer surface protein biomarkers via a novel transcriptomics approach.

Background: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patients with breast cancer, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed ‘SURFACER’.Methods: Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA versus normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2 and Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity.Results: Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of five BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms.Conclusions: BRCA patients can be stratified into five surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.

Sugar-Sweetened Beverages, Artificially Sweetened Beverages, and Breast Cancer Risk: Results From 2 Prospective US Cohorts

BackgroundWhether consumption of sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) is associated with the risk of breast cancer is of public health interest. ObjectivesWe sought to evaluate associations between consumption of SSBs and ASBs and risks of total and subtype-specific breast cancer. MethodsWe followed 82,713 women from the Nurses’ Health Study (1980 to 2016) and 93,085 women from the Nurses’ Health Study II (1991 to 2017). Cumulatively averaged intakes of SSBs and ASBs from FFQs were tested for associations with incident breast cancer cases and subtypes using Cox regression models. We also evaluated the associations stratified by menopausal status, physical activity, BMI, and alcohol intake. ResultsWe documented 11,379 breast cancer cases during 4,655,153 person-years of follow-up. Consumption of SSBs or ASBs was not associated with total breast cancer risk: pooled HRs comparing extreme categories (≥1/day compared with <1/month) were 1.03 (95% CI, 0.95–1.12) and 0.96 (95% CI, 0.91–1.02), respectively. We observed a suggestive interaction by BMI using pooled data (P-interaction = 0.08), where a modestly higher risk of breast cancer with each serving per day increment of SSBs was found in lean women (HR, 1.06; 95% CI, 1.01–1.11) but not among overweight or obese women (HR, 1.00; 95% CI, 0.95–1.06). Moreover, in the pooled, fully adjusted analysis, compared to infrequent consumers (<1/month), those who consumed ≥1 serving of ASBs per day had a lower risk of luminal A breast tumors (HR, 0.90; 95% CI, 0.80–1.01; P-trend = 0.02). ConclusionsAlthough no significant associations were observed overall, consumption of SSBs was associated with a slightly higher risk of breast cancer among lean women. This finding could have occurred by chance and needs confirmation. Our findings also suggest no substantial increase in the risk of breast cancer with consumption of ASBs.

Healthful and Unhealthful Plant-Based Diets and Risk of Breast Cancer in U.S. Women: Results from the Nurses' Health Studies.

Plant-based diets have been associated with lower risk of various diseases, including type 2 diabetes, cardiovascular disease, and other cardiometabolic risk factors. However, the association between plant-based diet quality and breast cancer remains unclear. We prospectively followed 76,690 women from the Nurses' Health Study (NHS, 1984-2016) and 93,295 women from the NHSII (1991-2017). Adherence to an overall plant-based diet index (PDI), a healthful PDI (hPDI), and an unhealthful PDI (uPDI) was assessed using previously developed indices. Cox proportional hazards models were used to estimate HR and 95% confidence intervals (CI) for incident invasive breast cancer. Over 4,841,083 person-years of follow-up, we documented 12,482 incident invasive breast cancer cases. Women with greater adherence to PDI and hPDI were at modestly lower risk of breast cancer [(HRQ5 vs. Q1, 0.89; 95% CI, 0.84-0.95); (HRQ5 vs. Q1, 0.89; 95% CI, 0.83-0.94)]. We observed significant heterogeneity by estrogen receptor (ER) status, with the strongest inverse association between hPDI and breast cancer observed with ER-negative tumors [HRQ5 vs. Q1, 0.77; 95% CI, 0.65-0.90; P trend < 0.01]. We also found an inverse association between extreme quintiles of healthy plant foods and ER-negative breast cancer [HR, 0.74; 95% CI, 0.61-0.88; P trend < 0.01]. This study provides evidence that adherence to a healthful plant-based diet may reduce the risk of breast cancer, especially those that are more likely to be aggressive tumors. This is the first prospective study investigating the relation between healthful and unhealthful plant-based dietary indices and risk of total and subtype-specific breast cancer.

Sugar-Sweetened Beverages, Artificially Sweetened Beverages, and Breast Cancer Risk: Results From Two Prospective US Cohorts

Abstract Objectives Whether consumption of sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) is associated with risk of breast cancer is of public health interest. Therefore, we aimed to evaluate associations between consumption of SSBs and ASBs with risk of total and subtype-specific breast cancer. Methods We followed 80,677 women from the Nurses’ Health Study (NHS; 1980 to 2016) and 86,115 women from the Nurses’ Health Study II (NHSII; 1991 to 2017) who were free from breast cancer at baseline. Multivariable Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results We documented 10,248 breast cancer cases during 3,990,008 person-years of follow-up. Consumption of SSBs or ASBs were not associated with total breast cancer risk; pooled HR (95% CI) comparing extreme categories were 1.05 (0.97, 1.15) and 0.97 (0.91, 1.03), respectively. In cohort-specific analysis, SSBs were associated with a higher risk of breast cancer in NHS (HR ≥1/day vs. &amp;lt; 1/month 1.12; 95% CI 1.00, 1.24; P-trend = 0.03). We observed a significant interaction by BMI (P-interaction = 0.02), where a modestly higher risk of breast cancer with each serving per day increment of SSBs was found in lean women (BMI &amp;lt; 25 kg/m2) (HR, 1.06, 95% CI, 1.01, 1.12), but not among overweight or obese women (BMI ≥ 25 kg/m2) (HR, 0.98, 95% CI, 0.93, 1.04). Moreover, in the pooled, fully adjusted analysis, compared to infrequent consumers (&amp;lt;1/month), those who consumed ≥ 1 serving of ASBs per day had a lower risk of luminal A breast tumors (HR, 0.88; 95% CI, 0.78, 0.99; P-trend = 0.01). Conclusions Although no significant associations were observed overall, consumption of SSBs was associated with a modest higher risk of breast cancer among lean women. This finding could have occurred by chance and needs confirmation. Our findings also suggest no substantial increase in risk of breast cancer with consumption of ASBs. Funding Sources This study was supported by grants from the National Institutes of Health, and the Breast Cancer Research Foundation. ARN was supported by a fellowship from the Spanish Association Against Cancer Scientific Foundation (FC AECC). The funding sources did not participate in the design or conduct of the study; collection, management, analysis or interpretation of the data; or preparation, review, or approval of the manuscript.

Abstract PS7-36: Subtype-dependent locoregional recurrence patterns in different subtypes of breast cancer: A retrospective analysis of 16,505 patients over 10 years of follow-up

Abstract Background While numerous studies have consistently reported that the molecular subtypes of breast cancer are associated with different patterns of distant metastasis, the impact of molecular subtypes on the locoregional recurrence has not been thoroughly investigated. Currently, major guidelines in breast cancer recommend annual mammography for locoregional surveillance. In the present study, we investigated the patterns of locoregional recurrence in a large cohort of breast cancer patients who underwent standardized treatment at a single institution. Methods We retrospectively reviewed the clinical records of all patients who underwent breast cancer surgery for stage I-III diseases between January 2000 and December 2018. The patients with ductal carcinoma in situ who underwent standard treatment were also included. The events were classified into ipsilateral breast cancer recurrence (IBTR), locoregional recurrence (LRR) and contralateral breast cancer (CBC). All IBTR events were included in the LRR events. The patients with initial stage IV breast cancer, with recurrence breast cancer previously treated at elsewhere, or patients with insufficient follow-up period were excluded. Results A total of 16,505 patients were identified and included in the analysis. For all patients, the rate of IBTR, LRR, and CBC at 10 year was 2.6%, 4.9% and 1.9%, retrospectively. There was no significant association between the IHC-based molecular subtype and tumor recurrences in the 1,535 patients with ductal carcinoma in situ. For 14,970 patients with invasive disease, we observed significant differences in IBTR, LRR, and CBC between different molecular subtypes. For all events, HR-/HER2+ subtype and HR-/HER2- subtype showed worst recurrence-free survival compared to other subtypes (p&amp;lt;0.001). However, when each event-types was separately analyzed, we observed a unique subtype-specific outcome differences according to different types of events. For IBTR, HR-/HER2- subtype showed significantly worse outcome compared to HR+ tumors (p&amp;lt;0.001) but HR-/HER2+ subtype showed significantly higher number of events even compared to HR-/HER2- (p=0.026). For LRR, HR-/HER2+ and HR-/HER2- subtypes showed similar degree of worsening outcome compared to other subtypes (p&amp;lt;0.001). For CBC, HR+/HER2- subtype showed significantly better outcome compared to other subtypes (p&amp;lt;0.001). Interestingly, while the risk of development of LRR in HR+ subtypes was steady over time, the HR- subtypes showed increased risk of developing LRR during the first three years of follow-up. After that, all subtypes showed constant risk of developing LRR. In HR-/HER2+ subtype and HR-/HER- subtype, 68.2% and 75.5% of LRR events were manifested during the first three years, respectively. In contrast, HR+/HER2- and HR+/HER2+ subtypes had 43.5% and 56.5% of LRR events during the same period. In terms of CBC, all subtypes showed consistent annual risk of developing CBC during the follow-up period. The HR-/HER2- showed significantly increased risk of developing CBC compared to HR+/HER2- subtype until seven years of follow-up. Conclusions We propose a subtype-specific locoregional and contralateral breast recurrence patterns in operable breast cancer patients by using a large cohort of breast cancer patients with sufficient long-term follow-up. These findings suggest a subtype-based tailored approach for locoregional and contralateral breast recurrences after curative treatment Citation Format: Jong Ho Cheun, Han-Byoel Lee, Wonshink Han, Dong-Young Noh, Hyeong-Gon Moon. Subtype-dependent locoregional recurrence patterns in different subtypes of breast cancer: A retrospective analysis of 16,505 patients over 10 years of follow-up [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 PS7-36.