Troester, Melissa A.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Abstract Background: Breast cancers in recently postpartum women may have worse outcomes, but studies examining tumor molecular features by pregnancy recency have shown conflicting results. Methods: This analysis used Carolina Breast Cancer Study data to examine clinical and molecular tumor features among women less than 50 years of age who were recently (≤10 years prior) or remotely (>10 years prior) postpartum, or nulliparous. Prevalence odds ratios (POR) and 95% confidence intervals (CI) were estimated using multivariable models. Results: Recently postpartum women (N = 618) were more frequently lymph node–positive [POR (95% CI): 1.66 (1.26–2.19)], estrogen receptor (ER)-negative [1.37 (1.02–1.83)], and IHC-based triple negative [1.57 (1.00–2.47)] compared with nulliparous (N = 360) women. Some differences were identified between recent versus remotely postpartum; smaller tumor size [0.67 (0.52–0.86)], p53 wildtype [0.53 (0.36–0.77)], and non–basal-like phenotype [0.53 (0.33–0.84)] were more common among recently postpartum. Recently postpartum (vs. nulliparous) had significant enrichment for adaptive immunity, T cells, B cells, CD8 T cells, activated CD8 T cells/natural killer (NK) cells, and T follicular helper (Tfh) cells and higher overall immune cell scores. These differences were attenuated in remotely (compared with recently) postpartum women. Conclusions: These results suggest a dominant effect of parity (vs. nulliparity) and a lesser effect of pregnancy recency on tumor molecular features, although tumor immune microenvironments were altered in association with pregnancy recency. Impact: Our study is unique in examining tumor immune microenvironment and RNA-based markers according to time since last childbirth. Future studies should examine the interplay between tumor features, postdiagnostic treatment, and outcomes among recently postpartum women. See related commentary by McDonald et al., p. 518

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.

Abstract BackgroundCopy 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.ResultsGene 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.ConclusionsThis 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.

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.

Abstract Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer–specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj &gt; 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5–25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06–1.34)]; current versus never smoking [1.37 (1.27–1.47)], high versus low physical activity [0.43 (0.21–0.86)], age ≥30 years versus &lt;20 years at first pregnancy [0.79 (0.72–0.86)]; &gt;0–&lt;5 years versus ≥10 years since last full-term birth [1.31 (1.11–1.55)]; ever versus never use of oral contraceptives [0.91 (0.87–0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen–progestin therapy [0.61 (0.54–0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02–1.21) for current versus never smoking. Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.

Abstract Background: Tumor infiltrating lymphocytes (TILs) play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. Methods: To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling (DSP) of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest (ROIs) in formalin-fixed paraffin embedded tissue sections. 44 antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. Results: In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with Regulatory T cell (Treg) markers (CD4, CD25, FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n=75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. Conclusion: This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with BC subtype, suggesting possible prognostic or targetable differences. Citation Format: Andrea Walens, Linnea T. Olsson, Xiaohua Gao, Alina M. Hamilton, Erin L. Kirk, Stephanie M. Cohen, Bentley R. Midkiff, Yongjuan Xia, Mark E. Sherman, Nana Nikolaishvili-Feinberg, Katherine A. Hoadley, Melissa A. Troester, Benjamin C. Calhoun. Protein-based immune profiles of basal-like vs luminal breast cancers [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-090.

Abstract Background Multigene assays for breast cancer are becoming more commonly used for research, diagnostic, and treatment-selection purposes. These assays are commonly based on a single tumor sample, so this study assesses whether clinically-relevant multigene scores are subject to misclassification due to technical variation or intratumoral heterogeneity. Methods Using FFPE blocks, tumors from 37 patients were sampled at different pathologist-selected spatial locations, targeting regions with distinct histological appearance. A second pathologist assessed mitotic activity and presence of immune infiltration for each specimen. Gene expression was quantified using the PAM50 assay. Samples were classified with respect to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, or Basal-like) and risk of recurrence with proliferation score (ROR-P, high vs. med/low). Euclidean distances between samples were calculated across the 50 genes, and the distribution of Euclidean distances were compared for samples that were concordant vs. discordant for each multigene classifier for PAM50 or ROR-P. Results Of the 37 tumors, 11 had samples with discordant PAM50 subtype and 7 had samples with discordant ROR-P group (75% and 83% agreement, respectively). The Euclidean distance between paired samples with discordant PAM50 intrinsic subtype or ROR-P score was significantly greater than that among concordant tumors. Samples discordant for ROR-P had more heterogeneity in histological characteristics, while discordance of PAM50 subtype call was generally not predicted by heterogeneity of these histological characteristics. Conclusion The concordance of PAM50 subtype calls and ROR-P, despite oversampling of heterogenous-appearing tumor regions, demonstrates reproducibility of the PAM50 classifier for breast cancer tumor intrinsic subtyping. However, assay sampling strategies for histologically heterogeneous tumors merit further consideration. Citation Format: Amber N. Hurson, Alina Hamilton, Linnea T. Olsson, Erin L. Kirk, Benjamin C. Calhoun, Joseph Geradts, Mark E. Sherman, Melissa A. Troester. Intratumoral heterogeneity of prognostic multigene signatures for breast cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-068.

Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Abstract Delayed terminal duct lobular unit (TDLU) involution is associated with elevated mammographic breast density (MD). Both are independent breast cancer risk factors among women with benign breast disease (BBD). Prior digital analyses of normal breast tissues revealed that epithelial nuclear density (END) and TDLU involution are inversely correlated. Accordingly, we examined associations of END, TDLU involution, and MD in BBD clinical biopsies. This study included digitized images of 262 representative image-guided hematoxylin and eosin–stained biopsies from 224 women diagnosed with BBD, enrolled within the cross-sectional BREAST-Stamp project that were visually assessed for TDLU involution (TDLU count/100 mm2, median TDLU span and median acini count per TDLU). A digital algorithm estimated nuclei count per unit epithelial area, or END. Single X-ray absorptiometry of prebiopsy ipsilateral craniocaudal digital mammograms measured global and localized MD surrounding the biopsy region. Adjusted ordinal logistic regression models assessed relationships between tertiles of TDLU and END measures. Analysis of covariance examined mean differences in MD across END tertiles. TDLU measures were positively associated with increasing END tertiles [TDLU count/100 mm2, ORT3vsT1: 3.42, 95% confidence interval (CI), 1.87–6.28; acini count/TDLUT3vsT1, OR: 2.40, 95% CI, 1.39–4.15]. END was significantly associated with localized, but not, global MD. Relationships were most apparent among patients with nonproliferative BBD. These findings suggest that quantitative END reflects different but complementary information to the histologic information captured by visual TDLU and radiologic MD measures and merits continued evaluation in assessing cellularity of breast parenchyma to understand the etiology of BBD.