Triple-negative breast cancer (TNBC) is clinically defined as the absence of expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). The approximately 15%-20% of breast cancers (BCs) that are triple negative represent an aggressive subtype that is more likely to have a poor prognosis. Highly heterogeneous, the TNBC collective comprises multiple independent molecular subtypes, underpinned by unique biologic pathways. The chief TNBC subtyping systems are briefly outlined in Figure 1. Among these, the widely accepted Lehmann molecular classification categorizes TNBC into: basal-like (BL1 and BL2), immunomodulatory, luminal androgen receptor (LAR), mesenchymal, and mesenchymal stem-like.3 The subtypes also respond differently to available therapies. For example, the LAR tumors have a low proliferation rate and are less sensitive to standard chemotherapy, whereas the basal type is characterized by high proliferation and greater sensitivity to chemotherapy. Lumped with TNBC is the highly recalcitrant quadruple-negative breast cancer (QNBC), simplistically designated as a TNBC subset that lacks androgen receptor (AR) expression. In fact, 70%-80% of TNBCs are veritably QNBCs (ie, are AR negative).

Targeted cancer therapeutics are promised to have a major impact on cancer treatment and survival. Successful application of these novel treatments requires a molecular definition of a patient's disease typically achieved through the use of tissue biopsies. Alternatively, allowing longitudinal monitoring, biomarkers derived from blood, isolated either from circulating tumor cell derived DNA (ctcDNA) or circulating cell-free tumor DNA (ccfDNA) may be evaluated. In order to use blood derived templates for mutational profiling in clinical decisions, it is essential to understand the different template qualities and how they compare to biopsy derived template DNA as both blood-based templates are rare and distinct from the gold-standard. Using a next generation re-sequencing strategy, concordance of the mutational spectrum was evaluated in 32 patient-matched ctcDNA and ccfDNA templates with comparison to tissue biopsy derived DNA template. Different CTC antibody capture systems for DNA isolation from patient blood samples were also compared. Significant overlap was observed between ctcDNA, ccfDNA and tissue derived templates. Interestingly, if the results of ctcDNA and ccfDNA template sequencing were combined, productive samples showed similar detection frequency (56% vs 58%), were temporally flexible, and were complementary both to each other and the gold standard. These observations justify the use of a multiple template approach to the liquid biopsy, where germline, ctcDNA, and ccfDNA templates are employed for clinical diagnostic purposes and open a path to comprehensive blood derived biomarker access.

Background Crown-like structures in breast adipose tissue (CLS-B), composed of necrotic adipocytes encircled by macrophages, are associated with obesity and hypothesized to worsen breast cancer prognosis; however, data are sparse, particularly in multi-racial populations. Methods We assessed specimens for CLS-B from 174 African-American and 168 White women with stage I–III breast cancer treated by mastectomy. Benign breast tissue from an uninvolved quadrant was immunohistochemically stained for CD68 to determine CLS-B presence and density (per cm2 of adipose tissue). Demographic and lifestyle factors, collected via medical record review, were analyzed for associations with CLS-B using logistic regression. Multivariable Cox proportional hazards models were used to compute hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between CLS-B and overall (OS) or progression-free (PFS) survival. Results Detection of any CLS-B was similar between African-American (32%) and White (29%) patients with no evidence of an association between race and CLS-B in multivariable models (OR = 0.82, 95% CI = 0.49–1.36). Detection of CLS-B was associated with obesity (OR = 4.73, 95% CI = 2.48–9.01) and age ≥ 60 years at diagnosis (OR = 1.78, 95% CI = 0.99–3.21). There was some evidence of associations with parity and current smoking status. Detection of CLS-B was not associated with OS (HR = 1.02, 95% CI = 0.55–1.87) or PFS (HR = 0.99, 95% CI = 0.59–1.67). Conclusions Our results show a strong, positive association between BMI and CLS-B in non-tumor tissue similar to previous findings. Detection of CLS-B did not vary by race and was not associated with worse OS or PFS.

Among women diagnosed with stage I–IIIa, node-negative, hormone receptor (HR)-positive breast cancer (BC), Oncotype DX recurrence scores (ODX RS) inform chemotherapy treatment decisions. Differences in recurrence scores or testing may contribute to racial disparities in BC mortality among women with HR+ tumors. We identified 12,081 non-Hispanic White (NHW) and non-Hispanic Black (NHB) BC patients in Georgia (2010–2014), eligible to receive an ODX RS. Logistic regression was used to estimate the odds of chemotherapy receipt by race and ODX RS. Cox proportional hazard regression was used to calculate the hazard ratios (HRs) comparing BC mortality rates by race and recurrence score. Receipt of Oncotype testing was consistent between NHB and NHW women. Receipt of chemotherapy was generally comparable within strata of ODX RS—although NHB women with low scores were slightly more likely to receive chemotherapy (OR = 1.16, 95% CI 0.77, 1.75), and NHB women with high scores less likely to receive chemotherapy (OR = 0.77, 95% CI 0.48, 1.24), than NHW counterparts. NHB women with a low recurrence score had the largest hazard of BC mortality (HR = 2.47 95% CI 1.22, 4.99) compared to NHW women. Our data suggest that additional tumor heterogeneity, or other downstream treatment factors, not captured by ODX, may be drivers of racial disparities in HR+ BC.

The efforts to personalize treatment for patients with breast cancer have led to a focus on the deeper characterization of genotypic and phenotypic heterogeneity among breast cancers. Traditional pathology utilizes microscopy to profile the morphologic features and organizational architecture of tumor tissue for predicting the course of disease, and is the first-line set of guiding tools for customizing treatment decision-making. Currently, clinicians use this information, combined with the disease stage, to predict patient prognosis to some extent. However, tumoral heterogeneity stubbornly persists among patient subgroups delineated by these clinicopathologic characteristics, as currently used methodologies in diagnostic pathology lack the capability to discern deeper genotypic and subtler phenotypic differences among individual patients. Recent advancements in molecular pathology, however, are poised to change this by joining forces with multiple-omics technologies (genomics, transcriptomics, epigenomics, proteomics, and metabolomics) that provide a wealth of data about the precise molecular complement of each patient’s tumor. In addition, these technologies inform the drivers of disease aggressiveness, the determinants of therapeutic response, and new treatment targets in the individual patient. The tumor architecture information can be integrated with the knowledge of the detailed mutational, transcriptional, and proteomic phenotypes of cancer cells within individual tumors to derive a new level of biologic insight that enables powerful, data-driven patient stratification and customization of treatment for each patient, at each stage of the disease. This review summarizes the prognostic and predictive insights provided by commercially available gene expression-based tests and other multivariate or clinical -omics-based prognostic/predictive models currently under development, and proposes a more inclusive multiplatform approach to tackling the challenging heterogeneity of breast cancer to individualize its management. “The future is already here—it’s just not very evenly distributed.”-William Ford Gibson.

The number of patients with breast cancer diagnosed with sleep disturbance has grown substantially within the United States over the past 20 years. Meanwhile, there have been significant improvements in the psychological treatment of sleep disturbance in patients with breast cancer. More specifically, cognitive behavioral therapy for insomnia (CBT-I), mindfulness, and yoga have shown to be 3 promising treatments with varying degrees of benefit, supporting data, and inherent limitations. In this article, we will outline the treatment approach for sleep disturbance in patients with breast cancer and conduct a comprehensive review of CBT-I, mindfulness, and yoga as they pertain to this patient population.

Introduction While type 2 diabetes (T2D) has been associated with increased all-cause mortality among women diagnosed with breast cancer (BC), the association between T2D and breast cancer-specific (BCS) mortality is unresolved. The goal of this study was to examine the association between T2D and BCS mortality and examine the influence of metformin treatment on mortality rates. Methods A retrospective cohort study was conducted between 2002 and 2008 at Emory University Hospitals among non-Hispanic black and white women who had confirmed diagnosis of stage I-III BC and known diabetes status (T2D: n = 73; non-T2D: n = 514). Cox proportional hazard models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI). Results Compared to non-T2D patients, T2D women had almost a 2-fold increase in BCS mortality after adjusting for covariates (HR = 2.01; 95%CI = 1.02–3.98). Though attenuated, the increased hazard of death was also observed for all-cause mortality (HR = 1.74; 95%CI = 1.06–2.87). T2D patients who were not on metformin had substantially higher hazard of BCS mortality compared to non-diabetic patients (HR = 4.54; 95%CI = 1.98–10.44), whereas the association among T2D patients treated with metformin was weak (HR = 1.20; 95%CI = 0.36–3.97) and included the null. Conclusions Among women with BC, T2D is associated with increased BCS mortality. Metformin treatment for T2D during the initial diagnosis of BC may improve outcomes.

© The Author(s) 2019. Published by Oxford University Press. Background: Racial disparities in breast cancer (BC) outcomes persist where non-Hispanic black (NHB) women are more likely to die from BC than non-Hispanic white (NHW) women, and the extent of this disparity varies geographically. We evaluated tumor, treatment, and patient characteristics that contribute to racial differences in BC mortality in Atlanta, Georgia, where the disparity was previously characterized as especially large. Methods: We identified 4943 NHW and 3580 NHB women in the Georgia Cancer Registry with stage I-IV BC diagnoses in Atlanta (2010-2014). We used Cox proportional hazard regression to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) comparing NHB vs NHW BC mortality by tumor, treatment, and patient characteristics on the additive and multiplicative scales. We additionally estimated the mediating effects of these characteristics on the association between race and BC mortality. Results: At diagnosis, NHB women were younger-with higher stage, node-positive, and triple-negative tumors relative to NHW women. In age-adjusted models, NHB women with luminal A disease had a 2.43 times higher rate of BC mortality compared to their NHW counterparts (95% CI = 1.99 to 2.97). High socioeconomic status (SES) NHB women had more than twice the mortality rates than their white counterparts (HR = 2.67, 95% CI = 1.65 to 4.33). Racial disparities among women without insurance, in the lowest SES index, or diagnosed with triple-negative BC were less pronounced. Conclusions: In Atlanta, the largest racial disparities are observed in luminal tumors and most pronounced among women of high SES. More research is needed to understand drivers of disparities within these treatable features.