Basal-like phenotype is not associated with patient survival in estrogen-receptor-negative breast cancers

INTRODUCTION: Basal-phenotype or basal-like breast cancers are characterized by basal epithelium cytokeratin (CK5/14/17) expression, negative estrogen receptor (ER) status and distinct gene expression signature. We studied the clinical and biological features of the basal-phenotype tumors determined by immunohistochemistry (IHC) and cDNA microarrays especially within the ER-negative subgroup. METHODS: IHC was used to evaluate the CK5/14 status of 445 stage II breast cancers. The gene expression signature of the CK5/14 immunopositive tumors was investigated within a subset (100) of the breast tumors (including 50 ER-negative tumors) with a cDNA microarray. Survival for basal-phenotype tumors as determined by CK5/14 IHC and gene expression signature was assessed. RESULTS: From the 375 analyzable tumor specimens, 48 (13%) were immunohistochemically positive for CK5/14. We found adverse distant disease-free survival for the CK5/14-positive tumors during the first years (3 years hazard ratio (HR) 2.23, 95% confidence interval (CI) 1.17 to 4.24, p = 0.01; 5 years HR 1.80, 95% CI 1.02 to 3.15, p = 0.04) but the significance was lost at the end of the follow-up period (10 years HR 1.43, 95% CI 0.84 to 2.43, p = 0.19). Gene expression profiles of immunohistochemically determined CK5/14-positive tumors within the ER-negative tumor group implicated 1,713 differently expressed genes (p < 0.05). Hierarchical clustering analysis with the top 500 of these genes formed one basal-like and a non-basal-like cluster also within the ER-negative tumor entity. A highly concordant classification could be constructed with a published gene set (Sorlie's intrinsic gene set, concordance 90%). Both gene sets identified a basal-like cluster that included most of the CK5/14-positive tumors, but also immunohistochemically CK5/14-negative tumors. Within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification. CONCLUSION: Basal cytokeratin-positive tumors have a biologically distinct gene expression signature from other ER-negative tumors. Even if basal cytokeratin expression predicts early relapse among non-selected tumors, the clinical outcome of basal tumors is similar to non-basal ER-negative tumors. Immunohistochemically basal cytokeratin-positive tumors almost always belong to the basal-like gene expression profile, but this cluster also includes few basal cytokeratin-negative tumors

Mediator complex (MED) 7: a biomarker associated with good prognosis in invasive breast cancer, especially ER+ luminal subtypes

Background: Mediator complex (MED) proteins have a key role in transcriptional regulation, some interacting with the oestrogen receptor (ER). Interrogation of the METABRIC cohort suggested that MED7 may regulate lymphovascular invasion (LVI). Thus MED7 expression was assessed in large breast cancer (BC) cohorts to determine clinicopathological significance. Methods: MED7 gene expression was investigated in the METABRIC cohort (n = 1980) and externally validated using bc-GenExMiner v4.0. Immunohistochemical expression was assessed in the Nottingham primary BC series (n = 1280). Associations with clinicopathological variables and patient outcome were evaluated. Results: High MED7 mRNA and protein expression was associated with good prognostic factors: low grade, smaller tumour size, good NPI, positive hormone receptor status (p < 0.001), and negative LVI (p = 0.04) status. Higher MED7 protein expression was associated with improved BC-specific survival within the whole cohort and ER+/luminal subgroup. Pooled MED7 gene expression data in the external validation cohort confirmed association with better survival, corroborating with the protein expression. On multivariate analysis, MED7 protein was independently predictive of longer BC-specific survival in the whole cohort and Luminal A subtype (p < 0.001). Conclusions: MED7 is an important prognostic marker in BC, particularly in ER+luminal subtypes, associated with improved survival and warrants future functional analysis

Studying the Effect of Decentralized Battery Storage to Smooth the Generated Power of a Grid Integrated Wind Energy Conversion System

This work investigates the technical possibility of using battery storage in order to smooth the power generated from a grid connected wind energy converter unit. Wind energy has gained much credit in the past two decades as a sustainable energy resource. The penetration of wind energy generators into the electric utility grids is expected to increase to about 203.5 GW within the present decade. Due to the intermittent nature of the wind and the limited reliability of the wind prognoses there have been serious concerns about reliability and operation of the utility power grids. Battery storage is suggested to compensate wind power fluctuations and smooth the power flow to the utility grids. The battery storage in such applications has dynamic operating conditions and is subjected to different degradation mechanisms which stimulate the capacity losses and hence influence the feasibility of their implementation. In this paper, the real behavior, the technical feasibility of the battery and its effect on wind power fed to the utility grid will be judged. The investigated system is simulated using real measurement data of a 600 kW rated power wind turbine. The simulation results of different battery capacities show that the integration of the battery storage has compensated the fluctuations of the generated wind power to match the forecasting value, which smoothed the power fed to the utility grid and allows better grid operation. Moreover, the battery aging model has generated very important information about the battery degradation and available capacity (in this case of about 85%) after one year of operation. Therefore, further investigations with different battery technologies (e.g. Li-Ion and NiMH) and development of intelligent system operation strategy have to be investigated