Altered expression of p120catenin predicts poor outcome in invasive breast cancer.

PURPOSE: The study focuses on p120catenin, a regulator of cell adhesion, which has previously been described in many malignancies and suggested with a role in invasion and metastatic behaviour. In this study, we investigate the role of altered immunoexpression of p120catenin isoforms in the prognosis of invasive breast cancer (n = 351). METHODS: We used cDNA microarrays to screen differences in gene expression in invasive breast cancer in general, and between local and metastasized disease particularly. On this basis, we performed p120catenin immunohistochemistry in order to confirm the prognostic value of p120catenin isoforms on tissue microarrays comprising 341 patients from the era of mammographic screening, directed to modern surgical and oncological treatments, and followed-up for maximum of 20 years. RESULTS: In cDNA microarray analysis, p120catenin was discovered down-regulated along with E-cadherin and alpha-catenin. In addition, p120catenin distinguished metastasized breast cancer from local disease. Immunohistochemistry confirmed the value of p120catenin as an independent prognosticator of breast cancer survival. In our results, p120catenin was associated with 3.7-fold risk of breast cancer death in multivariate Cox's regression analyses adjusted for the established prognosticators of breast cancer (p = 0.039). Particularly, the long isoform of p120catenin predicted metastatic disease (p = 0.029). CONCLUSION: The present paper is the first report on p120catenin in invasive breast cancer based on a well-characterized patient material with long-term follow-up. We observed altered expression of p120catenin isoforms in invasive breast cancer and, in our material, the decrease in p120 immunoexpression was significantly associated with poor outcome of disease.

A human ImmunoChip cDNA microarray provides a comprehensive tool to study immune responses.

DNA microarray technology has developed rapidly in recent years and has become an essential tool, providing novel approaches to biomedical research. In this paper, we describe a self-designed ImmunoChip cDNA array for immunological research. With a comprehensive selection of genes of interest, we can focus on key signalling pathways and molecular mechanisms at relatively low cost compared to commercial platforms which are usually targeted at global screening of gene expression. To validate the efficiency of the ImmunoChip, we studied T helper cell polarization to functionally distinct subsets (Th1 and Th2). We also developed a tool for quality control of cDNA microarrays that assesses the technical quality of an ImmunoChip. The information produced with the quality control tool is shown to be valuable for extracting correct information from cDNA microarrays. Gene expression measurements with ImmunoChip are in agreement with the results obtained using oligonucleotide microarrays and with published quantitative RT-PCR data. The ImmunoChip provides reliable measurements and gives new insights into various aspects of human immune responses.

Geometrical distortions in two-dimensional gels: applicable correction methods.

Two-dimensional electrophoresis (2-DE) provides a rapid means for separating thousands of proteins from cell and tissue samples in one run. Although this powerful research tool has been enthusiastically applied in many fields of biomedical research, accurate analysis and interpretation of the data have provided many challenges. Several analysis steps are needed to convert the large amount of noisy data obtained with 2-DE into reliable and interpretable biological information. The goals of such analysis steps include accurate protein detection and quantification, as well as the identification of differentially expressed proteins between samples run on different gels. To achieve these goals, systematic errors such as geometric distortions between the gels must be corrected by using computer-assisted methods. A wide range of computer software has been developed, but no general consensus exists as standard for 2-DE data analysis protocol. The choice of analysis approach is an important element depending both on the data and on the goals of the experiment. Therefore, basic understanding of the algorithms behind the software is required for optimal results. This review highlights some of the common themes in 2-DE data analysis, including protein spot detection and geometric image warping using both spot- and pixel-based approaches. Several computational strategies are overviewed and their relative merits and potential pitfalls discussed. Finally, we offer our own personal view of future trends and developments in large-scale proteome research.