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DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.

Basal-like breast cancers (BBC) exhibit subtype-specific phenotypic and transcriptional responses to stroma, but little research has addressed how stromal-epithelial interactions evolve during early BBC carcinogenesis. It is also unclear how common genetic defects, such as p53 mutations, modify these stromal-epithelial interactions. To address these knowledge gaps, we leveraged the MCF10 progression series of breast cell lines (MCF10A, MCF10AT1, and MCF10DCIS) to develop a longitudinal, tissue-contextualized model of p53-deficient, pre-malignant breast. Acinus asphericity, a morphogenetic correlate of cell invasive potential, was quantified with optical coherence tomography imaging, and gene expression microarrays were performed to identify transcriptional changes associated with p53 depletion and stromal context. Co-culture with stromal fibroblasts significantly increased the asphericity of acini derived from all three p53-deficient, but not p53-sufficient, cell lines, and was associated with the upregulation of 38 genes. When considered as a multigene score, these genes were upregulated in co-culture models of invasive BBC with increasing stromal content, as well as in basal-like relative to luminal breast cancers in two large human datasets. Taken together, stromal-epithelial interactions during early BBC carcinogenesis are dependent upon epithelial p53 status, and may play important roles in the acquisition of an invasive morphologic phenotype.

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort (N= 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size (N=359 and 130) and a small published dataset (N=12). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString's commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses.

Tumor-infiltrating lymphocytes 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. To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx�� (NanoString) platform to perform digital spatial profiling 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 in formalin-fixed paraffin embedded tissue sections. Forty-four antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. 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, and 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. 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 breast cancer subtype, suggesting possible prognostic, or targetable differences.

Background: African American women have the highest risk of breast cancer mortality compared to other racial groups. Differences in tumor characteristics have been implicated as a possible cause; however, the tumor microenvironment may also contribute to this disparity in mortality. Hepatocyte growth factor (HGF) is a stroma-derived marker of the tumor microenvironment that may affect tumor progression differentially by race. Objective: To examine whether an HGF gene expression signature is differentially expressed by race and tumor characteristics. Methods: Invasive breast tumors from 1957 patients were assessed for a 38-gene RNA-based HGF gene expression signature. Participants were black (n = 1033) and non-black (n = 924) women from the population-based Carolina Breast Cancer Study (1993���2013). Generalized linear models were used to estimate the relative frequency differences (RFD) in HGF status by race, clinical, and demographic factors. Results: Thirty-two percent of tumors were positive for the HGF signature. Black women were more likely [42% vs. 21%; RFD = + 19.93% (95% CI 16.00, 23.87)] to have HGF-positive tumors compared to non-black women. Triple-negative patients had a higher frequency of HGF positivity [82% vs. 13% in non-triple-negative; RFD = + 65.85% (95% CI 61.71, 69.98)], and HGF positivity was a defining feature of basal-like subtype [92% vs. 8% in non-basal; RFD = + 81.84% (95% CI 78.84, 84.83)]. HGF positivity was associated with younger age, stage, higher grade, and high genomic risk of recurrence (ROR-PT) score. Conclusion: HGF expression is a defining feature of basal-like tumors, and its association with black race and young women suggests it may be a candidate pathway for understanding breast cancer disparities.

Purpose: Improved risk stratification and predictive biomarkers of treatment response are needed for non-muscle-invasive bladder cancer (NMIBC). Here we assessed the clinical utility of targeted RNA and DNA molecular profiling in NMIBC. Experimental Design: Gene expression in NMIBC samples was profiled by NanoString nCounter, an RNA quantification platform, from two independent cohorts (n = 28, n = 50); targeted panel sequencing was performed in a subgroup (n = 50). Gene signatures were externally validated using two RNA sequencing datasets of NMIBC tumors (n = 438, n = 73). Established molecular subtype classifiers and novel gene expression signatures were assessed for associations with clinicopathologic characteristics, somatic tumor mutations, and treatment outcomes. Results: Molecular subtypes distinguished between low-grade Ta tumors with FGFR3 mutations and overexpression (UROMOL-class 1) and tumors with more aggressive clinicopathologic characteristics (UROMOL-classes 2 and 3), which were significantly enriched with TERT promoter mutations. However, UROMOL subclasses were not associated with recurrence after bacillus Calmette-Guérin (BCG) immunotherapy in two independent cohorts. In contrast, a novel expression signature of an inflamed tumor microenvironment (TME) was associated with improved recurrence-free survival after BCG. Expression of immune checkpoint genes (PD-L1/PD-1/CTLA-4) was associated with an inflamed TME, but not with higher recurrence rates after BCG. FGFR3 mutations and overexpression were both associated with low immune signatures. Conclusions: Assessment of the immune TME, rather than molecular subtypes, is a promising predictive biomarker of BCG response. Modulating the TME in an immunologically “cold” tumor warrants further investigation. Integrated transcriptomic and exome sequencing should improve treatment selection in NMIBC.

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.

Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade.Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype(1-3). To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 x 10(-8)), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade.Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype(1-3). To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 x 10(-8)), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes., This work was supported by the European Union’s Horizon 2020 Research and Innovation Programme under Marie Sklodowska-Curie grant agreement number 656144. Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project (funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the ‘Ministère de l’Économie de la Science et de l’Innovation du Québec’ (through Genome Québec) and the Quebec Breast Cancer Foundation); the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118, C8197/A16565 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec (grant PSR-SIIRI-701). Combining of the GWAS data was supported in part by NIH Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE; part of the GAME-ON initiative).

Background: Some breast tumors expressing greater than 1% and less than 10% estrogen receptor (ER) positivity (ER-borderline) are clinically aggressive; others exhibit luminal biology. Prior ER-borderline studies included few black participants. Methods: Using the Carolina Breast Cancer Study (phase I: 1993-1996; 2: 1996-2001; 3: 2008-2013), a population-based study that oversampled black women, we compared ER-borderline (n = 217) to ER-positive (n = 1885) and ER-negative (n = 757) tumors. PAM50 subtype and risk of recurrence score (ROR-PT, incorporates subtype, proliferation, tumor size) were measured. Relative frequency differences (RFD) were estimated using multivariable linear regression. Disease-free interval (DFI) was evaluated by ER category and endocrine therapy receipt, overall and by race, using Kaplan Meier and Cox models. Statistical tests were two-sided. Results: ER-borderlines were more frequently basal-like (RFD = +37.7%, 95% confidence interval [CI] = 27.1% to 48.4%) and high ROR-PT (RFD = +52.4%, 95% CI = 36.8% to 68.0%) relative to ER-positives. Having a high ROR-PT ER-borderline tumor was statistically significantly associated with black race (RFD = +26.2%, 95% CI = 9.0% to 43.3%). Compared to ER-positives, DFI of ER-borderlines treated with endocrine therapy was poorer but not statistically significantly different (hazard ratio [HR] = 2.03, 95% CI = 0.89% to 4.65%), whereas DFI was statistically significantly worse for ER-borderlines without endocrine therapy (HR = 3.33, 95% CI = 1.84% to 6.02%). However, black women with ER-borderline had worse DFI compared to ER-positives, even when treated with endocrine therapy (HR = 2.77, 95% CI = 1.09% to 7.04%). Conclusions: ER-borderline tumors were genomically heterogeneous, with survival outcomes that differed by endocrine therapy receipt and race. Black race predicted high-risk ER-borderlines and may be associated with poorer endocrine therapy response.

Background: An understanding of how the mammary gland responds to toxicant and drug exposures can shed light on mechanisms of breast cancer initiation/progression and therapeutic effectiveness, respectively. In this study, we employed noninvasive, label-free and high-throughput optical coherence tomography speckle fluctuation spectroscopy (OCT-SFS) to track exposure-response relationships in three-dimensional (3D) mammary epithelial organoid models. Methods: OCT-SFS is sensitive to relatively high speed (~0.16-8 μm/min) motions of subcellular light scattering components occurring over short (~2-114 s) time scales, termed "intracellular motility." In this study, OCT speckle fluctuation spectra are quantified by two metrics: the intracellular motility amplitude, M, and frequency-dependent motility roll-off, α. OCT-SFS was performed on human mammary organoid models comprised of pre-malignant MCF10DCIS.com cells or MCF7 adenocarcinoma cells over 6 days of exposure to either a microtubule inhibitor (Paclitaxel, Taxol) or a myosin II inhibitor (Blebbistatin). Raw values of a and M were normalized to a dynamic range corresponding to fixed (0%) and live/homeostatic (100%) organoids for each cell line. Results: In this work, we observed a significant decrease in both M and a of MCF10DCIS.com organoids after 24 hours of exposure to Taxol (P

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44–1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.

Background: After controlling for baseline disease factors, researchers have found that black women have worse breast cancer survival, and this suggests that treatment differences may contribute to poorer outcomes. Delays in initiating and completing treatment are one proposed mechanism. Methods: Phase 3 of the Carolina Breast Cancer Study involved a large, population-based cohort of women with incident breast cancer. For this analysis, we included black women (n = 1328) and white women (n = 1331) with stage I to III disease whose treatment included surgery with or without adjuvant therapies. A novel treatment pathway grouping was used to benchmark the treatment duration (surgery only, surgery plus chemotherapy, surgery plus radiation, or all 3). Models controlled for the treatment pathway, age, and tumor characteristics and for demographic factors related to health care access. Exploratory analyses of the association between delays and cancer recurrence were performed. Results: In fully adjusted analyses, blacks had 1.73 times higher odds of treatment initiation more than 60 days after their diagnosis in comparison with whites (odds ratio [OR], 1.73; 95% confidence interval [CI], 1.04-2.90). Black race was also associated with a longer treatment duration. Blacks were also more likely to be in the highest quartile of treatment duration (OR, 1.69; 95% CI, 1.41-2.02), even after adjustments for demographic and tumor characteristics (OR, 1.31; 95% CI, 1.04-1.64). A nonsignificant trend toward a higher recurrence risk was observed for patients with delayed initiation (hazard ratio, 1.44; 95% CI, 0.89-2.33) or the longest duration (hazard ratio, 1.17; 95% CI, 0.87-1.59). Conclusions: Black women more often had delayed treatment initiation and a longer duration than whites receiving similar treatment. Interventions that target access barriers may be needed to improve timely delivery of care.

Background: The dominant invasive breast cancer histologic subtype, ductal carcinoma, shows intrinsic subtype diversity. However, lobular breast cancers are predominantly Luminal A. Both histologic subtypes show distinct relationships with patient and tumor characteristics, but it is unclear if these associations remain after accounting for intrinsic subtype. Methods: Generalized linear models were used to estimate relative frequency differences (RFDs) and 95% confidence intervals (95% CIs) for the associations between age, race, tumor characteristics, immunohistochemistry (IHC) and RNA-based intrinsic subtype, TP53 status, and histologic subtype in the Carolina Breast Cancer Study (CBCS, n = 3,182) and The Cancer Genome Atlas (TCGA, n = 808). Results: Relative to ductal tumors, lobular tumors were significantly more likely to be Luminal A [CBCS RNA RFD: 44.9%, 95% CI (39.6, 50.1); TCGA: RFD: 50.5%, 95% CI (43.9, 57.1)], were less frequent among young (��� 50 years) and black women, were larger in size, low grade, less frequently had TP53 pathway defects, and were diagnosed at later stages. These associations persisted among Luminal A tumors (n = 242). Conclusions: While histology is strongly associated with molecular characteristics, histologic associations with age, race, size, grade, and stage persisted after restricting to Luminal A subtype. Histology may continue to be clinically relevant among Luminal A breast cancers.

Background In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. Methods We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. Results All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 × 10–4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 × 10–4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 × 10–19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 × 10–6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. Conclusions We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.

Breast cancers detected after a negative breast screening examination and prior to the next screening are referred to as interval cancers. These cancers generally have poor clinical characteristics compared with screen-detected cancers, but associations between interval cancer and genomic cancer characteristics are not well understood. Mammographically screened women diagnosed with primary invasive breast cancer from 1993 to 2013 (n �� 370) were identified by linking the Carolina Breast Cancer Study and the Carolina Mammography Registry. Among women with a registry-identified screening mammogram 0 to 24 months before diagnosis, cancers were classified as screen-detected (N �� 165) or interval-detected (N �� 205). Using logistic regression, we examined the association of mode of detection with cancer characteristics (clinical, IHC, and genomic), overall, and in analyses stratified on mammographic density and race. Interval cancer was associated with large tumors [>2 cm; OR, 2.3; 95% confidence interval (CI), 1.5���3.7], positive nodal status (OR, 1.8; 95% CI, 1.1���2.8), and triple-negative subtype (OR, 2.5; 95% CI, 1.1���5.5). Interval cancers were more likely to have non-Luminal A subtype (OR, 2.9; 95% CI, 1.5���5.7), whereas screen-detected cancers tended to be more indolent (96% had low risk of recurrence genomic scores; 71% were PAM50 Luminal A). When stratifying by mammographic density and race, associations between interval detection and poor prognostic features were similar by race and density status. Strong associations between interval cancers and poor-prognosis genomic features (non-Luminal A subtype and high risk of recurrence score) suggest that aggressive tumor biology is an important contributor to interval cancer rates.

Background: Invasive lobular breast tumors display unique reproductive risk factor profiles. Lobular tumors are predominantly Luminal A subtype, and it is unclear whether reported risk factor associations are independent of molecular subtype. Methods: Polytomous logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) for the associations between risk factors and histologic subtype [ductal (n = 2,856), lobular (n = 326), and mixed ductal���lobular (n = 473)] in the Carolina Breast Cancer Study (1993���2013). Three-marker immunohistochemical clinical subtypes were defined as Luminal A (ER+ or PR+/HER2-), Luminal B (ER+ or PR+/HER2+), Triple Negative (ER���/PR���/HER2-), and HER2+ (ER���/PR���/HER2+). Results: In case���case analyses compared to ductal, lobular tumors were significantly associated with lactation duration > 12 months [OR 1.86, 95% CI (1.33���2.60)], age at first birth ��� 26 years [OR: 1.35, 95% CI: (1.03���1.78)], and current oral contraceptive use [OR: 1.86, 95% CI: (1.08���3.20)]. Differences in risk factor associations between ductal and lobular tumors persisted after restricting to Luminal A subtype. Conclusions: Lobular tumors were associated with older age at first birth, increased lactation duration, and current oral contraceptive use. Etiologic heterogeneity by histology persisted after restricting to Luminal A subtype, suggesting both tumor histology and intrinsic subtype play integral parts in breast cancer risk.

Mutations in tumor suppressor TP53 have been inconsistently linked to breast cancer risk factors and survival. Immunohistochemistry (IHC) staining, a primary clinical means of TP53 mutation determination, only detects mutations that facilitate protein accumulation (e.g., missense mutations). RNA-based pathway methods capture functional status and may aid in understanding the role of TP53 function in racial disparities of breast cancer. TP53 status was assessed among invasive breast cancer cases from the Carolina Breast Cancer Study (CBCS) (2008���2013) using IHC and an established RNA-based TP53 signature (CBCS and The Cancer Genome Atlas (TCGA)). Frequency of TP53 status (IHC, RNA-based) was estimated in association with tumor characteristics, PAM50 intrinsic subtype, age, and race using relative frequency differences (RFDs) and 95% confidence intervals (95% CI) as the measure of association. Approximately 60% of basal-like tumors were TP53 protein positive (IHC), while nearly 100% were TP53 mutant-like (RNA). Luminal A tumors had low frequency of TP53 positivity (IHC: 7.9%) and mutant-like status (RNA: 1.7%). Mutant-like TP53 (RNA) was strongly associated with age ���50 years, high tumor grade, advanced stage of disease, large tumor size, and basal-like and HER2 intrinsic subtypes. Black race was strongly associated with TP53 mutant-like status (RNA) (RFD: 24.8%, 95% CI: 20.5, 29.0) even after adjusting for age, grade, stage (RFD: 11.3%; 95% CI: 7.6, 15.0). Associations were attenuated and non-significant when measured by IHC. IHC-based TP53 status is an insensitive measurement of TP53 functional status. RNA-based methods suggest a role for TP53 in tumor prognostic features and racial disparities.

The ability to assess toxicant exposures of 3D in vitro mammary models that recapitulate the tissue microenvironment can aid in our understanding of environmental exposure risk over time. Longitudinal studies of 3D model systems, however, are cumbersome and suffer from a lack of high-throughput toxicological assays. In this study, we establish a noninvasive and label-free optical coherence tomography (OCT)-based imaging platform for tracking exposure-response relationships in 3D human mammary epithelial organoid models. The OCT-based assay includes metrics that quantify organoid intracellular kinetic energy and cross-sectional area (CSA). We compare the results to those obtained using the 3-(4,5-dimethylthiazol-2- yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) mitochondrial dye conversion assay. Both estrogen receptor (ER)-positive (MCF7) and ER-negative (MCF10DCIS.com) breast cell lines were studied, beginning one hour after exposure and continuing for several days. Six days of exposure to 17b-estradiol or the selective ER modulator 4-hydroxytamoxifen respectively increased or decreased MCF7 organoid CSA (p < .01), consistent with the role of estrogen signaling in ER-positive mammary epithelial cell proliferation. We also observed a significant decrease in the intracellular kinetic energy of MCF10DCIS.com organoids after 24 h of exposure to doxorubicin, a cytotoxic intercalating agent that causes DNA double-strand breaks (p < .01). MTT-based metabolic activity of MCF10DCIS.com organoids after 48 h of doxorubicin exposure decreased with dose in a similar manner as OCT-based energy metrics. These results demonstrate the feasibility of an OCT-based assay to quantify mammary epithelial cell toxicant response in vitro, noninvasively, longitudinally, and in the context of tissue microenvironments, providing a new high-throughput screening tool for toxicological studies.

RNA-based, multi-gene molecular assays are available and widely used for patients with ER-positive/HER2-negative breast cancers. However, RNA-based genomic tests can be costly and are not available in many countries. Methods for inferring molecular subtype from histologic images may identify patients most likely to benefit from further genomic testing. To identify patients who could benefit from molecular testing based on H&E stained histologic images, we developed an image analysis approach using deep learning. A training set of 571 breast tumors was used to create image-based classifiers for tumor grade, ER status, PAM50 intrinsic subtype, histologic subtype, and risk of recurrence score (ROR-PT). The resulting classifiers were applied to an independent test set (n = 288), and accuracy, sensitivity, and specificity of each was assessed on the test set. Histologic image analysis with deep learning distinguished low-intermediate vs. high tumor grade (82% accuracy), ER status (84% accuracy), Basal-like vs. non-Basal-like (77% accuracy), Ductal vs. Lobular (94% accuracy), and high vs. low-medium ROR-PT score (75% accuracy). Sampling considerations in the training set minimized bias in the test set. Incorrect classification of ER status was significantly more common for Luminal B tumors. These data provide proof of principle that molecular marker status, including a critical clinical biomarker (i.e., ER status), can be predicted with accuracy >75% based on H&E features. Image-based methods could be promising for identifying patients with a greater need for further genomic testing, or in place of classically scored variables typically accomplished using human-based scoring.

Background: African American breast cancer patients have lower frequency of hormone receptor-positive (HR+)/human epidermal growth factor receptor 2 (HER2)-negative disease and higher subtype-specific mortality. Racial differences in molecular subtype within clinically defined subgroups are not well understood. Methods: Using data and biospecimens from the population-based Carolina Breast Cancer Study (CBCS) Phase 3 (2008-2013), we classified 980 invasive breast cancers using RNA expression-based PAM50 subtype and recurrence (ROR) score that reflects proliferation and tumor size. Molecular subtypes (Luminal A, Luminal B, HER2-enriched, and Basal-like) and ROR scores (high vs low/medium) were compared by race (blacks vs whites) and age (���50 years vs���50 years) using chi-square tests and analysis of variance tests. Results: Black women of all ages had a statistically significantly lower frequency of Luminal A breast cancer (25.4% and 33.6% in blacks vs 42.8% and 52.1% in whites; younger and older, respectively). All other subtype frequencies were higher in black women (case-only odds ratio [OR] = 3.11, 95% confidence interval [CI] = 2.22 to 4.37, for Basal-like; OR=1.45, 95% CI=1.02 to 2.06, for Luminal B; OR=2.04, 95% CI=1.33 to 3.13, for HER2-enriched). Among clinically HR+/HER2- cases, Luminal A subtype was less common and ROR scores were statistically significantly higher among black women. Conclusions: Multigene assays highlight racial disparities in tumor subtype distribution that persist even in clinically defined subgroups. Differences in tumor biology (eg, HER2-enriched status) may be targetable to reduce disparities among clinically ER+/HER2- cases.

Background: Heterogeneity of muscle-invasive bladder cancer (MIBC) has been characterized using whole-genome mRNA expression data, showing distinct molecular and clinicopathological characteristics by subtypes. However, associations between risk factors and molecular subtypes have not been reported. Methods: Four previously published schemes were used to categorize molecular subtypes in 372 MIBC patients from the Cancer Genome Atlas (TCGA). Data on gene expression (RNA-seq), demographic, and clinicopathological characteristics were retrieved through TCGA data portal. Polytomous logistic regression was used to estimate the associations of subtypes by different schemes with age at diagnosis, obesity, and smoking. Results: While some quantitative variation was evident, distinct molecular subtype schemes showed considerable consistency in the association with the risk factors. Generally, compared to patients with luminal-like tumors, patients with basal-like subtypes were more likely to be older (OR75 + yrs vs.

Colorectal cancer is the third most common cancer in men and women in the US, with over 95,000 new cases expected in 2016. Many preclinical, epidemiological, and clinical studies have shown that regular aspirin (acetylsalicylic acid) use, even in low-doses, prevents the development of colorectal neoplasia. In 2015, the US Preventative Services Task Force acknowledged the value of low-dose aspirin in primary prevention of colorectal cancer in adults aged 50–59 years. Despite this wealth of evidence, how aspirin reduces colorectal cancer risk is not fully understood. Many mechanisms have been proposed, but the most commonly cited is aspirin’s inhibition of PTGS2 (COX-2), a known mediator of inflammation and immunosuppression that is overexpressed in many colorectal neoplasms.

Background: In the USA, the breast cancer mortality rate is 41% higher for African-American women than non-Hispanic White women. While numerous gene expression studies have classified biological features that vary by race and may contribute to poorer outcomes, few studies have experimentally tested these associations. CRYβB2 gene expression has drawn particular interest because of its association with overall survival and African-American ethnicity in multiple cancers. Several reports indicate that overexpression of the CRYβB2 pseudogene, CRYβB2P1, and not CRYβB2 is linked with race and poor outcome. It remains unclear whether either or both genes are linked to breast cancer outcomes. This study investigates CRYβB2 and CRYβB2P1 expression in human breast cancers and breast cancer cell line models, with the goal of elucidating the mechanistic contribution of CRYβB2 and CRYβB2P1 to racial disparities. Methods: Custom scripts for CRYβB2 or CRYβB2P1 were generated and used to identify reads that uniquely aligned to either gene. Gene expression according to race and tumor subtype were assessed using all available TCGA breast cancer RNA sequencing alignment samples (n = 1221). In addition, triple-negative breast cancer models engineered to have each gene overexpressed or knocked out were developed and evaluated by in vitro, biochemical, and in vivo assays to identify biological functions. Results: We provide evidence that CRYβB2P1 is expressed at higher levels in breast tumors compared to CRYβB2, but only CRYβB2P1 is significantly increased in African-American tumors relative to White American tumors. We show that independent of CRYβB2, CRYβB2P1 enhances tumorigenesis in vivo via promoting cell proliferation. Our data also reveal that CRYβB2P1 may function as a non-coding RNA to regulate CRYβB2 expression. A key observation is that the combined overexpression of both genes was found to suppress cell growth. CRYβB2 overexpression in triple-negative breast cancers increases invasive cellular behaviors, tumor growth, IL6 production, immune cell chemoattraction, and the expression of metastasis-associated genes. These data underscore that both CRYβB2 and CRYβB2P1 promote tumor growth, but their mechanisms for tumor promotion are likely distinct. Conclusions: Our findings provide novel data emphasizing the need to distinguish and study the biological effects of both CRYβB2 and CRYβB2P1 as both genes independently promote tumor progression. Our data demonstrate novel molecular mechanisms of two understudied, disparity-linked molecules.

Purpose Invasive breast cancers are thought to arise from in situ lesions, but some ductal carcinoma in situ (DCIS) are indolent with low likelihood of progressing to invasive carcinoma. Comparison of risk factor associations between DCIS and invasive disease may elucidate which factors influence early versus late stages of carcinogenesis. Therefore, we determined whether there were differences in risk factor profiles for screen-detected DCIS and invasive breast cancer among Luminal A lesions. Methods We conducted a case-control analysis using data from the Carolina Breast Cancer Study (1993-2001). Analyses were restricted to Luminal A tumors and screen-detected tumors among mammography-eligible women, to limit confounding by mode of detection (N = 108 DCIS; N = 203 invasive). Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between risk factors and lesion type. Results In stratified analyses, we observed qualitative differences in the direction of association for ever smoking, obese BMI, high waist-To-hip-ratio (WHR), and ?10 years of oral contraceptive use between DCIS and invasive disease. Breastfeeding was inversely associated with invasive disease and was not associated with DCIS. Interaction tests for risk factor associations between Luminal A DCIS and invasive breast cancer were not statistically significant (p>0.05). Conclusions Among Luminal A tumors, established breast cancer risk factors may exert stronger effects on progression of early lesions to invasive disease, with lesser effects on risk of DCIS.

Purpose: Female breast cancer demonstrates bimodal age frequency distribution patterns at diagnosis, interpretable as two main etiologic subtypes or groupings of tumors with shared risk factors. While RNA-based methods including PAM50 have identified well-established clinical subtypes, age distribution patterns at diagnosis as a proxy for etiologic subtype are not established for molecular and genomic tumor classifications. Methods: We evaluated smoothed age frequency distributions at diagnosis for Carolina Breast Cancer Study cases within immunohistochemistry-based and RNA-based expression categories. Akaike information criterion (AIC) values compared the fit of single density versus two-component mixture models. Two-component mixture models estimated the proportion of early-onset and late-onset categories by immunohistochemistry-based ER (n = 2860), and by RNA-based ESR1 and PAM50 subtype (n = 1965). PAM50 findings were validated using pooled publicly available data (n = 8103). Results: Breast cancers were best characterized by bimodal age distribution at diagnosis with incidence peaks near 45 and 65 years, regardless of molecular characteristics. However, proportional composition of early-onset and late-onset age distributions varied by molecular and genomic characteristics. Higher ER-protein and ESR1-RNA categories showed a greater proportion of late age-at-onset. Similarly, PAM50 subtypes showed a shifting age-at-onset distribution, with most pronounced early-onset and late-onset peaks found in Basal-like and Luminal A, respectively. Conclusions: Bimodal age distribution at diagnosis was detected in the Carolina Breast Cancer Study, similar to national cancer registry data. Our data support two fundamental age-defined etiologic breast cancer subtypes that persist across molecular and genomic characteristics. Better criteria to distinguish etiologic subtypes could improve understanding of breast cancer etiology and contribute to prevention efforts.