Triple-Negative Breast Cancer: An Update on Neoadjuvant Clinical Trials

Triple-negative breast cancer (TNBC) is an aggressive malignancy with a poor prognosis despite the high rates of response to chemotherapy. This scenario highlights the need to develop novel therapies and/or treatment strategies to reduce the mortality associated with TNBC. The neoadjuvant setting provides a model for rapid assessment of treatment efficacy with smaller patient accruals and over shorter periods of time compared to the traditional adjuvant setting. In addition, a clear surrogate endpoint of improved survival, known as pathologic complete response, already exists in this setting. Here, we review current data from completed and ongoing neoadjuvant clinical trials for TNBC

Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples

Abstract Background Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. Methods To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Results Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Conclusions Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor

The Role of Organizational Affiliations and Research Networks in the Diffusion of Breast Cancer Treatment Innovation

The National Institutes of Health (NIH) sees provider-based research networks and other organizational linkages between academic researchers and community practitioners as promising vehicles for accelerating the translation of research into practice. This study examines whether organizational research affiliations and teaching affiliations are associated with accelerated diffusion of sentinel lymph node biopsy (SLNB), an innovation in the treatment of early-stage breast cancer

Race and age disparities in receipt of sentinel lymph node biopsy for early-stage breast cancer

To evaluate differences in use of sentinel lymph node biopsy (SLNB) by age and race in Medicare recipients with early-stage breast cancer, we examined Surveillance, Epidemiology and End Results—Medicare linked data for women undergoing breast conserving surgery for stage I or II breast cancer, including axillary staging, between January 2000 and December 2002. Multivariable generalized linear modeling with generalized estimating equations was used to identify predictors of receiving SLNB versus standard axillary lymph node dissection as the primary axillary staging modality. Women were significantly less likely to receive SLNB as their primary staging procedure if they were African American (OR 0.65), greater than 80 years of age (OR 0.71 vs. age <70), or dually eligible for Medicare and Medicaid (OR 0.61). Tumor characteristics, including well-differentiated histology and stage I disease, were associated with increased likelihood of SLNB, but estrogen receptor status was not a significant predictor. Women treated at an institution affiliated with an NCI cooperative research group had significantly greater likelihood of receiving SLNB (OR 2.31). Likelihood of receiving SLNB increased for women diagnosed in 2001 and 2002 compared with 2000. Significant disparities exist in receipt of SLNB in the Medicare population, with African Americans, the elderly, and economically disadvantaged patients being less likely to receive this innovative and morbidity-sparing procedure. These findings continue a previously observed pattern of reduced access to state of the art breast cancer care among underserved populations

Gene expression in extratumoral microenvironment predicts clinical outcome in breast cancer patients

Abstract Introduction A gene expression signature indicative of activated wound responses is common to more than 90% of non-neoplastic tissues adjacent to breast cancer, but these tissues also exhibit substantial heterogeneity. We hypothesized that gene expression subtypes of breast cancer microenvironment can be defined and that these microenvironment subtypes have clinical relevance. Methods Gene expression was evaluated in 72 patient-derived breast tissue samples adjacent to invasive breast cancer or ductal carcinoma in situ. Unsupervised clustering identified two distinct gene expression subgroups that differed in expression of genes involved in activation of fibrosis, cellular movement, cell adhesion and cell-cell contact. We evaluated the prognostic relevance of extratumoral subtype (comparing the Active group, defined by high expression of fibrosis and cellular movement genes, to the Inactive group, defined by high expression of claudins and other cellular adhesion and cell-cell contact genes) using clinical data. To establish the biological characteristics of these subtypes, gene expression profiles were compared against published and novel tumor and tumor stroma-derived signatures (Twist-related protein 1 (TWIST1) overexpression, transforming growth factor beta (TGF-β)-induced fibroblast activation, breast fibrosis, claudin-low tumor subtype and estrogen response). Histological and immunohistochemical analyses of tissues representing each microenvironment subtype were performed to evaluate protein expression and compositional differences between microenvironment subtypes. Results Extratumoral Active versus Inactive subtypes were not significantly associated with overall survival among all patients (hazard ratio (HR) = 1.4, 95% CI 0.6 to 2.8, P = 0.337), but there was a strong association with overall survival among estrogen receptor (ER) positive patients (HR = 2.5, 95% CI 0.9 to 6.7, P = 0.062) and hormone-treated patients (HR = 2.6, 95% CI 1.0 to 7.0, P = 0.045). The Active subtype of breast microenvironment is correlated with TWIST-overexpression signatures and shares features of claudin-low breast cancers. The Active subtype was also associated with expression of TGF-β induced fibroblast activation signatures, but there was no significant association between Active/Inactive microenvironment and desmoid type fibrosis or estrogen response gene expression signatures. Consistent with the RNA expression profiles, Active cancer-adjacent tissues exhibited higher density of TWIST nuclear staining, predominantly in epithelium, and no evidence of increased fibrosis. Conclusions These results document the presence of two distinct subtypes of microenvironment, with Active versus Inactive cancer-adjacent extratumoral microenvironment influencing the aggressiveness and outcome of ER-positive human breast cancers

Infrared absorption spectra, radiative efficiencies, and global warming potentials of perfluorocarbons: Comparison between experiment and theory

Experimentally and theoretically determined infrared spectra are reported for a series of straight-chain perfluorocarbons: C2F6, C3F8, C4F10, C5F12, C6F14, and C8F18. Theoretical spectra were determined using both density functional (DFT) and ab initio methods. Radiative efficiencies (REs) were determined using the method of Pinnock et al. (1995) and combined with atmospheric lifetimes from the literature to determine global warming potentials (GWPs). Theoretically determined absorption cross sections were within 10% of experimentally determined values. Despite being much less computationally expensive, DFT calculations were generally found to perform better than ab initio methods. There is a strong wavenumber dependence of radiative forcing in the region of the fundamental C-F vibration, and small differences in wavelength between band positions determined by theory and experiment have a significant impact on the REs. We apply an empirical correction to the theoretical spectra and then test this correction on a number of branched chain and cyclic perfluoroalkanes. We then compute absorption cross sections, REs, and GWPs for an additional set of perfluoroalkenes

Advanced optical imaging in living embryos

Developmental biology investigations have evolved from static studies of embryo anatomy and into dynamic studies of the genetic and cellular mechanisms responsible for shaping the embryo anatomy. With the advancement of fluorescent protein fusions, the ability to visualize and comprehend how thousands to millions of cells interact with one another to form tissues and organs in three dimensions (xyz) over time (t) is just beginning to be realized and exploited. In this review, we explore recent advances utilizing confocal and multi-photon time-lapse microscopy to capture gene expression, cell behavior, and embryo development. From choosing the appropriate fluorophore, to labeling strategy, to experimental set-up, and data pipeline handling, this review covers the various aspects related to acquiring and analyzing multi-dimensional data sets. These innovative techniques in multi-dimensional imaging and analysis can be applied across a number of fields in time and space including protein dynamics to cell biology to morphogenesis

Role of HGF in epithelial-stromal cell interactions during progression from benign breast disease to ductal carcinoma in situ

Abstract Introduction Basal-like and luminal breast cancers have distinct stromal–epithelial interactions, which play a role in progression to invasive cancer. However, little is known about how stromal–epithelial interactions evolve in benign and pre-invasive lesions. Methods To study epithelial–stromal interactions in basal-like breast cancer progression, we cocultured reduction mammoplasty fibroblasts with the isogenic MCF10 series of cell lines (representing benign/normal, atypical hyperplasia, and ductal carcinoma in situ). We used gene expression microarrays to identify pathways induced by coculture in premalignant cells (MCF10DCIS) compared with normal and benign cells (MCF10A and MCF10AT1). Relevant pathways were then evaluated in vivo for associations with basal-like subtype and were targeted in vitro to evaluate effects on morphogenesis. Results Our results show that premalignant MCF10DCIS cells express characteristic gene expression patterns of invasive basal-like microenvironments. Furthermore, while hepatocyte growth factor (HGF) secretion is upregulated (relative to normal, MCF10A levels) when fibroblasts are cocultured with either atypical (MCF10AT1) or premalignant (MCF10DCIS) cells, only MCF10DCIS cells upregulated the HGF receptor MET. In three-dimensional cultures, upregulation of HGF/MET in MCF10DCIS cells induced morphological changes suggestive of invasive potential, and these changes were reversed by antibody-based blocking of HGF signaling. These results are relevant to in vivo progression because high expression of a novel MCF10DCIS-derived HGF signature was correlated with the basal-like subtype, with approximately 86% of basal-like cancers highly expressing the HGF signature, and because high expression of HGF signature was associated with poor survival. Conclusions Coordinated and complementary changes in HGF/MET expression occur in epithelium and stroma during progression of pre-invasive basal-like lesions. These results suggest that targeting stroma-derived HGF signaling in early carcinogenesis may block progression of basal-like precursor lesions

Surgical Patterns of Care in Patients with Invasive Breast Cancer Treated with Neoadjuvant Systemic Therapy and Breast Magnetic Resonance Imaging: Results of a Secondary Analysis of TBCRC 017

Neoadjuvant chemotherapy (NCT) down-stages advanced primary tumors, with magnetic resonance imaging (MRI) being the most sensitive imaging predictor of response. However, the impact of MRI evaluation on surgical treatment decisions in the neoadjuvant setting has not been well described. We report surgical patterns of care across 8 National Cancer Institute comprehensive cancer centers in women receiving both NCT and MRI to evaluate the impact of MRI findings on surgical planning

Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples

Abstract Background Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. Methods To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Results Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Conclusions Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor