Vacuole membrane protein 1 (Vmp1) is described as a cancer-relevant cell cycle modulator, but the function of this protein and its mode of action in tumor progression are still unknown. In this study, we show that the VMP1 mRNA level is significantly reduced in kidney cancer metastases as compared to primary tumors. Further, VMP1 expression is also decreased in the invasive breast cancer cell lines HCC1954 and MDA-MB-231 as compared to the non-invasive cell lines MCF-12A, T-47D and MCF-7. We show for the first time that Vmp1 is a plasma membrane protein and an essential component of initial cell-cell contacts and tight junction formation. It interacts with the tight junction protein Zonula Occludens-1 and colocalizes in spots between neighboring HEK293 cells. Downregulation of VMP1 by RNAi results in loss of cell adherence, and increases the invasion capacity of the non-invasive kidney cancer cell line Caki-2. In conclusion, our findings establish Vmp1 to be a novel cell-cell adhesion protein and that its expression level determines the invasion and metastatic potential of cancer cells.

As several model genomes have been sequenced, the elucidation of protein function is the next challenge toward the understanding of biological processes in health and disease. We have generated a human ORFeome resource and established a functional genomics and proteomics analysis pipeline to address the major topics in the post-genome-sequencing era: the identification of human genes and splice forms, and the determination of protein localization, activity, and interaction. Combined with the understanding of when and where gene products are expressed in normal and diseased conditions, we create information that is essential for understanding the interplay of genes and proteins in the complex biological network. We have implemented bioinformatics tools and databases that are suitable to store, analyze, and integrate the different types of data from high-throughput experiments and to include further annotation that is based on external information. All information is presented in a Web database (http://www.dkfz.de/LIFEdb). It is exploited for the identification of disease-relevant genes and proteins for diagnosis and therapy

Cancer transcription microarray studies commonly deliver long lists of ''candidate'' genes that are putatively associated with the respective disease. For many of these genes, no functional information, even less their relevance in pathologic conditions, is established as they were identified in large-scale genomics approaches. Strategies and tools are thus needed to distinguish genes and proteins with mere tumor association from those causally related to cancer. Here, we describe a functional profiling approach, where we analyzed 103 previously uncharacterized genes in cancer relevant assays that probed their effects on DNA replication (cell proliferation). The genes had previously been identified as differentially expressed in genome-wide microarray studies of tumors. Using an automated high-throughput assay with single-cell resolution, we discovered seven activators and nine repressors of DNA replication. These were further characterized for effects on extracellular signalregulated kinase 1/2 (ERK1/2) signaling (G 1 -S transition) and anchorage-independent growth (tumorigenicity). One activator and one inhibitor protein of ERK1/2 activation and three repressors of anchorage-independent growth were identified. Data from tumor and functional profiling make these proteins novel prime candidates for further in-depth study of their roles in cancer development and progression. We have established a novel functional profiling strategy that links genomics to cell biology and showed its potential for discerning cancer relevant modulators of the cell cycle in the candidate lists from microarray studies. (Cancer Res 2005; 65(17): 7733-42)

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Software for high-throughput cytometry assays

A software tool for the analysis of high-throughput cell-based assays is presented.