Independent component analysis of microarray data in the study of endometrial cancer.

Gene microarray technology is highly effective in screening for differential gene expression and has hence become a popular tool in the molecular investigation of cancer. When applied to tumours, molecular characteristics may be correlated with clinical features such as response to chemotherapy. Exploitation of the huge amount of data generated by microarrays is difficult, however, and constitutes a major challenge in the advancement of this methodology. Independent component analysis (ICA), a modern statistical method, allows us to better understand data in such complex and noisy measurement environments. The technique has the potential to significantly increase the quality of the resulting data and improve the biological validity of subsequent analysis. We performed microarray experiments on 31 postmenopausal endometrial biopsies, comprising 11 benign and 20 malignant samples. We compared ICA to the established methods of principal component analysis (PCA), Cyber-T, and SAM. We show that ICA generated patterns that clearly characterized the malignant samples studied, in contrast to PCA. Moreover, ICA improved the biological validity of the genes identified as differentially expressed in endometrial carcinoma, compared to those found by Cyber-T and SAM. In particular, several genes involved in lipid metabolism that are differentially expressed in endometrial carcinoma were only found using this method. This report highlights the potential of ICA in the analysis of microarray data.

Co-ordination of pathogenicity island expression by the BipA GTPase in enteropathogenic Escherichia coli (EPEC).

BipA is a novel member of the ribosome binding GTPase superfamily and is widely distributed in bacteria and plants. We report here that it regulates -multiple cell surface- and virulence-associated -components in the enteropathogenic Escherichia coli (EPEC) strain E2348/69. The regulated components include bacterial flagella, the espC pathogenicity island and a type III secretion system specified by the locus of enterocyte effacement (LEE). BipA positively regulated the espC and LEE gene clusters through transcriptional control of the LEE-encoded regulator, Ler. Additionally, it affected the pattern of proteolysis of intimin, a key LEE-encoded adhesin specified by the LEE. BipA control of the LEE operated independently of the previously characterized regulators Per, integration host factor and H-NS. In contrast, it negatively regulated the flagella-mediated motility of EPEC and in a Ler-independent manner. Our results indicate that the BipA GTPase functions high up in diverse regulatory cascades to co-ordinate the expression of key pathogenicity islands and other virulence-associated factors in E. coli.