Failure patterns and survival outcomes in triple negative breast cancer (TNBC): a 15 year comparison of 448 non-Hispanic black and white women

Purpose: Triple negative breast cancer (TNBC) is a distinct subtype of breast cancer with unique pathologic, molecular and clinical behavior. It occurs more frequently in young blacks and has been reported to have a shorter disease-free interval. We undertook this study to analyze the demographic characteristics, failure patterns, and survival outcomes in this disease. Methods: A total of 448 non-Hispanic black and white women were identified over a 15 year period from 1996 to 2011. Demographic and clinical information including age, race, menopausal status, stage, tumor characteristics, and treatments were collected. Fisher’s exact test and multivariable Cox regression were used to compare failure patterns and survival outcomes between races. Results: 49 % (n = 223) were black. 59 % patients were between 41 and 60 years, with 18 % ≤40 years. 57 % were premenopausal and 89 % had grade 3 tumors. Stage II (47 %) was most frequent stage at diagnosis followed by stage III (28 %). 32 % had lymphovascular invasion. Adjusting for age, stage, and grade, there was no difference in survival outcomes (OS, DFS, LFFS, and DFFS) between the two races. 62 (14 %) patients failed locally either in ipsilateral breast or chest wall, and 19 (4 %) failed in the regional lymphatics. Lung (18 %) was the most frequent distant failure site with <12 % each failing in brain, liver and bones. Conclusion: Failure patterns and survival outcomes did not differ by race in this large collection of TNBC cases. Lung was the predominate site of distant failure followed by brain, bone, and liver. Few patients failed in the regional lymphatics

Molecular Subtype Classification Is a Determinant of Non-Sentinel Lymph Node Metastasis in Breast Cancer Patients with Positive Sentinel Lymph Nodes

Background: Previous studies suggested that the molecular subtypes were strongly associated with sentinel lymph node (SLN) status. The purpose of this study was to determine whether molecular subtype classification was associated with nonsentinel lymph nodes (NSLN) metastasis in patients with a positive SLN. Methodology and Principal Findings: Between January 2001 and March 2011, a total of 130 patients with a positive SLN were recruited. All these patients underwent a complete axillary lymph node dissection. The univariate and multivariate analyses of NSLN metastasis were performed. In univariate and multivariate analyses, large tumor size, macrometastasis and high tumor grade were all significant risk factors of NSLN metastasis in patients with a positive SLN. In univariate analysis, luminal B subgroup showed higher rate of NSLN metastasis than other subgroup (P = 0.027). When other variables were adjusted in multivariate analysis, the molecular subtype classification was a determinant of NSLN metastasis. Relative to triple negative subgroup, both luminal A (P = 0.047) and luminal B (P = 0.010) subgroups showed a higher risk of NSLN metastasis. Otherwise, HER2 over-expression subgroup did not have a higher risk than triple negative subgroup (P = 0.183). The area under the curve (AUC) value was 0.8095 for the Cambridge model. When molecular subtype classification was added to the Cambridge model, the AUC value was 0.8475. Conclusions: Except for other factors, molecular subtype classification was a determinant of NSLN metastasis in patient

Gene signatures of breast cancer progression and metastasis

Breast cancer is a heterogeneous disease. Patient outcome varies significantly, depending on prognostic features of patients and their tumors, including patient age, menopausal status, tumor size and histology, nodal status, and so on. Response to treatment also depends on a series of predictive factors, such as hormone receptor and HER2 status. Current treatment guidelines use these features to determine treatment. However, these guidelines are imperfect, and do not always predict response to treatment or survival. Evolving technologies are permitting increasingly large amounts of molecular data to be obtained from tumors, which may enable more personalized treatment decisions to be made. The challenge is to learn what information leads to improved prognostic accuracy and treatment outcome for individual patients

High-throughput quantitative analysis with cell growth kinetic curves for low copy number mutant cells

The mutation rate in cells induced by environmental genotoxic hazards is very low and difficult to detect using traditional cell counting assays. The established genetic toxicity tests currently recognized by regulatory authorities, such as conventional Ames and hypoxanthine guanine phosphoribosyl-transferase (HPRT) assays, are not well suited for higher-throughput screening as they require large amounts of test compounds and are very time consuming. In this study, we developed a novel cell-based assay for quantitative analysis of low numbers of cell copies with HPRT mutation induced by an environmental mutagen. The HPRT gene mutant cells induced by the mutagen were selected by 6-thioguanine (6-TG) and the cell\u2019s kinetic growth curve monitored by a real-time cell electronic sensor (RT-CES) system. When a threshold is set at a certain cell index (CI) level, samples with different initial mutant cell copies take different amounts of time in order for their growth (or CI accumulation) to cross this threshold. The more cells that are initially seeded in the test well, the faster the cell accumulation and therefore the shorter the time required to cross this threshold. Therefore, the culture time period required to cross the threshold of each sample corresponds to the original number of cells in the sample. A mutant cell growth time threshold (MT) value of each sample can be calculated to predict the number of original mutant cells. For mutagenesis determination, the RT-CES assay displayed an equal sensitivity (p\u2009>\u20090.05) and coefficients of variation values with good correlation to conventional HPRT mutagenic assays. Most importantly, the RT-CES mutation assay has a higher throughput than conventional cellular assays.Peer reviewed: YesNRC publication: Ye