High throughput analysis of protein-protein interactions is an important sector of hypothesis-generating research. Using an improved and automated version of the yeast two-hybrid system, we completed a large interaction screening project with a focus on nuclear receptors and their cofactors. A total of 425 independent yeast twohybrid cDNA library screens resulted in 6425 potential interacting protein fragments involved in 1613 different interaction pairs. We show that simple statistical parameters can be used to narrow down the data set to a high confidence set of 377 interaction pairs where validated interactions are enriched to 61% of all pairs. Within the high confidence set, there are 64 novel proteins potentially binding to nuclear receptors or their cofactors. We discuss several examples of high interest, and we expect that communication of this huge data set will help to complement our knowledge of the protein interaction repertoire of this family of transcription factors and instigate the characterization of the various novel candidate interactors. Molecular & Cellular Proteomics 4:205-213, 2005.Nuclear receptors are a family of transcription factors involved in the control of many physiological processes including development, sexual differentiation, inflammation, and metabolism (1, 2). They can bind to DNA directly or via interaction with other proteins. Nuclear receptor activity is regulated by the binding of small molecule ligands to the receptor and/or by posttranslational modifications. Activation of nuclear receptors involves a change in conformation that affects the interaction of the receptor with other proteins, which in turn brings about the effect of the receptor on gene expression (3, 4). Knowledge about the ligand-dependent binding of nuclear receptors to their cofactors is central to the understanding of their physiological function and their use as targets for drug discovery (5). However, the available knowledge is highly biased toward a few intensively studied receptors, and little is known for the potential interaction patterns of the rest of the family (6).The elucidation of protein-protein interaction patterns provides an important basic data set in the functional analysis of the proteome. In the past, large data sets on protein interactions have been reported for model organisms such as yeast (7), fly (8), and worm (9). Here we present a protein interaction data set focusing on the family of human nuclear receptors generated by automated yeast two-hybrid (Y2H) 1 library screening. Application of statistical selection methods led to the generation of a high confidence subset of interaction pairs. EXPERIMENTAL PROCEDURESYeast Two-hybrid Screening-"Bait" is the protein or protein fragment for which we tried to find interacting proteins in a cDNA library using the yeast two-hybrid method. The bait is always a fusion with the DNA binding domain of the GAL4 transcription factor. "Prey" is a protein or protein fragment isolated from a cDNA library in a yeast two-hybrid screen as potentially...

Abstract.Background: Glioblastomas are the most common and most malignant brain tumors in adults. A small subgroup of glioblastomas contains areas with histological features of oligodendroglial differentiation (GBMO). Our objective was to genetically characterize the oligodendroglial and the astrocytic parts of GBMOs and correlate morphologic and genetic features with clinical data.Methods: The oligodendroglial and the "classic" glioblastoma parts of 13 GBMO were analyzed separately by interphase fluorescence in situ hybridization (FISH) on paraffin sections using a custom probe set (regions 1p, 1q, 7q, 10q, 17p, 19q, cen18, 21q) and by comparative genomic hybridization (CGH) of microdissected paraffin embedded tumor tissue.Results: We identified four distinct genetic subtypes in 13 GBMOs: an "astrocytic" subtype (9/13) characterized by +7/−10; an "oligodendroglial" subtype with −1p/−19q (1/13); an "intermediate" subtype showing +7/−1p (1/13), and an "other" subtype having none of the former aberrations typical for gliomas (2/13). The different histological tumor parts of GBMO revealed common genetic changes in all tumors and showed additional aberrations specific for each part.Conclusion: Our findings demonstrate the monoclonal origin of GBMO followed by the development of the astrocytic and oligodendroglial components. The diagnostic determination of the genetic signatures may allow for a better prognostication of the patients.

Our findings demonstrate the monoclonal origin of GBMO followed by the development of the astrocytic and oligodendroglial components. The diagnostic determination of the genetic signatures may allow for a better prognostication of the patients.