Recent studies on gene molecular profiling using cDNA microarray in a relatively small series of breast cancer have identified biologically distinct groups with apparent clinical and prognostic relevance. The validation of such new taxonomies should be confirmed on larger series of cases prior to acceptance in clinical practice. The development of tissue microarray (TMA) technology provides methodology for high-throughput concomitant analyses of multiple proteins on large numbers of archival tumour samples. In our study, we have used immunohistochemistry techniques applied to TMA preparations of 1,076 cases of invasive breast cancer to study the combined protein expression profiles of a large panel of well-characterized commercially available biomarkers related to epithelial cell lineage, differentiation, hormone and growth factor receptors and gene products known to be altered in some forms of breast cancer. Using hierarchical clustering methodology, 5 groups with distinct patterns of protein expression were identified. A sixth group of only 4 cases was also identified but deemed too small for further detailed assessment. Further analysis of these clusters was performed using multiple layer perceptron (MLP)-artificial neural network (ANN) with a back propagation algorithm to identify key biomarkers driving the membership of each group. We have identified 2 large groups by their expression of luminal epithelial cell phenotypic characteristics, hormone receptors positivity, absence of basal epithelial phenotype characteristics and lack of c-erbB-2 protein overexpression. Two additional groups were characterized by high c-erbB-2 positivity and negative or weak hormone receptors expression but showed differences in MUC1 and E-cadherin expression. The final group was characterized by strong basal epithelial characteristics, p53 positivity, absent hormone receptors and weak to low luminal epithelial cytokeratin expression. In addition, we have identified significant differences between clusters identified in this series with respect to established prognostic factors including tumour grade, size and histologic tumour type as well as differences in patient outcomes. The different protein expression profiles identified in our study confirm the biologic heterogeneity of breast cancer and demonstrate the clinical relevance of classification in this manner. These observations could form the basis of revision of existing traditional classification systems for breast cancer. ' 2005 Wiley-Liss, Inc.Key words: breast cancer; classification; protein expression; tissue microarray Routine clinical management of breast cancer relies on traditional histopathologic classification including tumour grade, histologic tumour type, carcinoma size and lymph node stage. Despite the overall association of these variables with prognosis and outcome, 1 these systems remain relatively weakly predictive of behaviour in some circumstances. Tumours of apparently homogenous morphologic character vary in response to therapy and have divergent outc...

Introduction Breast cancer is a heterogeneous disease encompassing a number of phenotypically diverse tumours. Expression levels of the oestrogen, progesterone and HER2/ neu receptors which characterize clinically distinct breast tumours have been shown to change during disease progression and in response to systemic therapies. Mi(cro)RNAs play critical roles in diverse biological processes and are aberrantly expressed in several human neoplasms including breast cancer, where they function as regulators of tumour behaviour and progression. The aims of this study were to identify miRNA signatures that accurately predict the oestrogen receptor (ER), progesterone receptor (PR) and HER2/neu receptor status of breast cancer patients to provide insight into the regulation of breast cancer phenotypes and progression.

Post-translational histone modifications are known to be altered in cancer cells, and loss of selected histone acetylation and methylation marks has recently been shown to predict patient outcome in human carcinoma. Immunohistochemistry was used to detect a series of histone lysine acetylation (H3K9ac, H3K18ac, H4K12ac, and H4K16ac), lysine methylation (H3K4me2 and H4K20me3), and arginine methylation (H4R3me2) marks in a well-characterized series of human breast carcinomas (n = 880). Tissue staining intensities were assessed using blinded semiquantitative scoring. Validation studies were done using immunofluorescence staining and Western blotting. Our analyses revealed low or absent H4K16ac in the majority of breast cancer cases (78.9%), suggesting that this alteration may represent an early sign of breast cancer. There was a highly significant correlation between histone modifications status, tumor biomarker phenotype, and clinical outcome, where high relative levels of global histone acetylation and methylation were associated with a favorable prognosis and detected almost exclusively in luminal-like breast tumors (93%). Moderate to low levels of lysine acetylation (H3K9ac, H3K18ac, and H4K12ac), lysine (H3K4me2 and H4K20me3), and arginine methylation (H4R3me2) were observed in carcinomas of poorer prognostic subtypes, including basal carcinomas and HER-2-positive tumors. Clustering analysis identified three groups of histone displaying distinct pattern in breast cancer, which have distinct relationships to known prognostic factors and clinical outcome. This study identifies the presence of variations in global levels of histone marks in different grades, morphologic types, and phenotype classes of invasive breast cancer and shows that these differences have clinical significance. [Cancer Res 2009;69(9):3802-9]

Due to the well-defined role of β-alanine as a substrate of carnosine (a major contributor to H+ buffering during high-intensity exercise), β-alanine is fast becoming a popular ergogenic aid to sports performance. There have been several recent qualitative review articles published on the topic, and here we present a preliminary quantitative review of the literature through a meta-analysis. A comprehensive search of the literature was employed to identify all studies suitable for inclusion in the analysis; strict exclusion criteria were also applied. Fifteen published manuscripts were included in the analysis, which reported the results of 57 measures within 23 exercise tests, using 18 supplementation regimes and a total of 360 participants [174, β-alanine supplementation group (BA) and 186, placebo supplementation group (Pla)]. BA improved (P = 0.002) the outcome of exercise measures to a greater extent than Pla [median effect size (IQR): BA 0.374 (0.140–0.747), Pla 0.108 (−0.019 to 0.487)]. Some of that effect might be explained by the improvement (P = 0.013) in exercise capacity with BA compared to Pla; no improvement was seen for exercise performance (P = 0.204). In line with the purported mechanisms for an ergogenic effect of β-alanine supplementation, exercise lasting 60–240 s was improved (P = 0.001) in BA compared to Pla, as was exercise of >240 s (P = 0.046). In contrast, there was no benefit of β-alanine on exercise lasting <60 s (P = 0.312). The median effect of β-alanine supplementation is a 2.85% (−0.37 to 10.49%) improvement in the outcome of an exercise measure, when a median total of 179 g of β-alanine is supplemented.

Carotenoids represent some of the most important secondary metabolites in the human diet, and tomato (Solanum lycopersicum) is a rich source of these health-promoting compounds. In this work, a novel and fruit-related regulator of pigment accumulation in tomato has been identified by artificial neural network inference analysis and its function validated in transgenic plants. A tomato fruit gene regulatory network was generated using artificial neural network inference analysis and transcription factor gene expression profiles derived from fruits sampled at various points during development and ripening. One of the transcription factor gene expression profiles with a sequence related to an Arabidopsis (Arabidopsis thaliana) ARABIDOPSIS PSEUDO RESPONSE REGULATOR2-LIKE gene (APRR2-Like) was up-regulated at the breaker stage in wild-type tomato fruits and, when overexpressed in transgenic lines, increased plastid number, area, and pigment content, enhancing the levels of chlorophyll in immature unripe fruits and carotenoids in red ripe fruits. Analysis of the transcriptome of transgenic lines overexpressing the tomato APPR2-Like gene revealed up-regulation of several ripening-related genes in the overexpression lines, providing a link between the expression of this tomato gene and the ripening process. A putative ortholog of the tomato APPR2-Like gene in sweet pepper (Capsicum annuum) was associated with pigment accumulation in fruit tissues. We conclude that the function of this gene is conserved across taxa and that it encodes a protein that has an important role in ripening.