Pancreatic cancer is typically detected at an advanced stage, and is refractory to most forms of treatment, contributing to poor survival outcomes. The incidence of pancreatic cancer is gradually increasing, linked to an aging population and increasing rates of obesity and pancreatitis, which are risk factors for this cancer. Sources of risk include adipokine signaling from fat cells throughout the body, elevated levels of intrapancreatic intrapancreatic adipocytes (IPAs), inflammatory signals arising from pancreas-infiltrating immune cells and a fibrotic environment induced by recurring cycles of pancreatic obstruction and acinar cell lysis. Once cancers become established, reorganization of pancreatic tissue typically excludes IPAs from the tumor microenvironment, which instead consists of cancer cells embedded in a specialized microenvironment derived from cancer-associated fibroblasts (CAFs). While cancer cell interactions with CAFs and immune cells have been the topic of much investigation, mechanistic studies of the source and function of IPAs in the pre-cancerous niche are much less developed. Intriguingly, an extensive review of studies addressing the accumulation and activity of IPAs in the pancreas reveals that unexpectedly diverse group of factors cause replacement of acinar tissue with IPAs, particularly in the mouse models that are essential tools for research into pancreatic cancer. Genes implicated in regulation of IPA accumulation include KRAS, MYC, TGF-β, periostin, HNF1, and regulators of ductal ciliation and ER stress, among others. These findings emphasize the importance of studying pancreas-damaging factors in the pre-cancerous environment, and have significant implications for the interpretation of data from mouse models for pancreatic cancer.

While many novel associations predicted by two-hybrid library screens reflect actual biological associations of two proteins in vivo, at times the functional co-relevance of two proteins scored as interacting in the two-hybrid system is unlikely. The reason for this positive score remains obscure, which leads to designating such clones as false positives. After investigating the effect of overexpressing a series of putative false positives in yeast, we determined that expression of some of these clones induces an array of biological effects in yeast, including altered growth rate and cell permeability, that bias perceived activity of LacZ reporters. Based on these observations, we identify four simple strategies that can assist in determining whether a protein is likely to have been selected in a two-hybrid screen because of indirect metabolic effects.

Two-hybrid systems have become favored tools for detection and analysis of protein interactions because of their low cost and ease of use compared to biochemical or biophysical interaction technologies. It is possible to augment the utility of two-hybrid systems and derivative systems such as dual-bait two-hybrid systems by adapting strategies that speed the analysis of the relative strength of a series of protein-protein associations. This report describes two simple techniques that employ either a flatbed scanner or a plate reader to quantitate the activity of colorimetric reporters such as LacZ or GusA commonly used in two-hybrid approaches.

The clinical treatment of cancer is in the process of a great leap forward, with the use of microarray-based technologies holding the promise to derive previously unobtainable insights into many aspects of disease pathogenesis. In surveying the past five years of progress, it is apparent that use of microarrays to query tumor samples and matching model systems can provide useful information concerning tumor classification, prognosis, and response to drug treatment. Further uses of microarrays in cancer biology have been proposed, with particular interest in prospects of this technology to elucidate cancer etiology and identify critical signal transduction pathways relevant to cancer drug development. In this review, we summarize the status of these fields and use insights gleaned from the extensive use of microarrays in studies of gene function versus gene expression profiles in model organisms such as yeast to identify critical issues for ongoing application development.

The goal of drug discovery is to develop novel small-molecule compounds that ameliorate, cure, and (optimal-ly) prevent clinically significant diseases. It has been much asserted that the resources of genome and proteome projects will contribute significantly towards this goal. The volume of information generated through these projects is by any objective standard impressive and overwhelming, providing a great impetus to the development of a bioinformatics community that will be able to make sense of the data onslaught (issues discussed in References 12 and 13). From an intellectual perspective, this work has the potential to add a new level of rigorous mathematical modeling to the common conceptions of cell, tissue, and organism over the next decade or so. However, from a pragmatic perspective focused on drug discovery over the window of the next three to five years, an essential topic of debate is how best to garner information from “-omics” resources as they become available and how to exploit this information to generate useful compounds. In this context, one idea has been to develop novel drugs that have improved specificity of action, and reduced undesirable side effects, by targeting specific proteins or protein-protein interactions (PPIs). The purpose of this review is to discuss what such a strategy entails, how screening for such targeted agents might be practically accomplished, and to raise issues concerning the validation of results.

In 1983, while investigators had identified a few human proteins as important regulators of specific biological outcomes, how these proteins acted in the cell was essentially unknown in almost all cases. Twenty-five years later, our knowledge of the mechanistic basis of protein action has been transformed by our increasingly detailed understanding of protein-protein interactions, which have allowed us to define cellular machines. The advent of the yeast two-hybrid (Y2H) system in 1989 marked a milestone in the field of proteomics. Exploiting the modular nature of transcription factors, the Y2H system allows facile measurement of the activation of reporter genes based on interactions between two chimeric or “hybrid” proteins of interest. After a decade of service as a leading platform for individual investigators to use in exploring the interaction properties of interesting target proteins, the Y2H system has increasingly been applied in high-throughput applications intended to map genome-scale protein-protein interactions for model organisms and humans. Although some significant technical limitations apply, Y2H has made a great contribution to our general understanding of the topology of cellular signaling networks.

Most studies of Aurora A (AurA) describe it as a mitotic centrosomal kinase. However, we and others have recently identified AurA functions as diverse as control of ciliary resorption, cell differentiation, and cell polarity control in interphase cells. In these activities, AurA is transiently activated by noncanonical signals, including Ca2+-dependent calmodulin binding. These and other observations suggested that AurA might be involved in pathological conditions, such as polycystic kidney disease (PKD). In this paper, we show that AurA is abundant in normal kidney tissue but is also abnormally expressed and activated in cells lining PKD-associated renal cysts. PKD arises from mutations in the PKD1 or PKD2 genes, encoding polycystins 1 and 2 (PC1 and PC2). AurA binds, phosphorylates, and reduces the activity of PC2, a Ca2+-permeable nonselective cation channel and, thus, limits the amplitude of Ca2+ release from the endoplasmic reticulum. These and other findings suggest AurA may be a relevant new biomarker or target in the therapy of PKD.

The multi-functional adaptor protein NEDD9/HEF1/Cas-L regulates cell motility, invasion and cell cycle progression, and plays key roles in cancer progression and metastasis. NEDD9 is localized to the centrosome and is required for activation of Aurora A kinase in mitosis. Here we demonstrate that the HECT-WW protein Smurf2 physically associates with NEDD9 and is required for the stability of NEDD9 protein. Smurf2 depletion results in a marked decrease in NEDD9 protein levels, by facilitating polyubiquitination and proteasomal degradation of NEDD9. Conversely, forced overexpression of Smurf2 results in upregulation of endogenous NEDD9 protein, confirming the role for Smurf2 in NEDD9 stability. Cells with Smurf2 depletion fail to activate Aurora A at the G2/M boundary, leading to a marked delay in mitotic entry. These observations suggest that the stable complex of Smurf2 and NEDD9 is required for timely entry into mitosis via Aurora A activation.

The Cas scaffolding proteins (NEDD9/HEF1/CAS-L, BCAR1/p130Cas, EFSSIN, and HEPL/CASS4) regulate cell migration, division and survival, and are often deregulated in cancer. High BCAR1 expression is linked to poor prognosis in breast cancer patients, while upregulation of NEDD9 contributes to the metastatic behavior of melanoma and glioblastoma cells. Our recent work knocking out the single Drosophila Cas protein, Dcas, identified a genetic interaction with E-cadherin. As E-cadherin is often downregulated during epithelial-mesenchymal transition (EMT) prior to metastasis, if such an activity was conserved in mammals it might partially explain how Cas proteins promote aggressive tumor behavior. We here establish that Cas proteins negatively regulate E-cadherin expression in human mammary cells. Cas proteins do not affect E-cadherin transcription, but rather, BCAR1 and NEDD9 signal through SRC to promote E-cadherin removal from the cell membrane and lysosomal degradation. We also find mammary tumors arising in MMTV-polyoma virus T-antigen mice have enhanced junctional E-cadherin in a Nedd9−/− background. Cumulatively, these results suggest a new role for Cas proteins in cell-cell adhesion signaling in cancer.

Polycystic liver disease (PLD) occurs in 75–90% of patients affected by autosomal dominant polycystic kidney disease (ADPKD), which affects 1∶400–1,000 adults and arises from inherited mutations in the PKD1 or PKD2 genes. PLD can lead to bile duct obstructions, infected or bleeding cysts, and hepatomegaly, which can diminish quality of life. At present, no effective, approved therapy exists for ADPKD or PLD. We recently showed that inhibition of the molecular chaperone heat shock protein 90 (HSP90) with a small molecule inhibitor, STA-2842, induced the degradation of multiple HSP90-dependent client proteins that contribute to ADPKD pathogenesis and slowed the progression of renal cystogenesis in mice with conditional deletion of Pkd1. Here, we analyzed the effects of STA-2842 on liver size and cystic burden in Pkd-/- mice with established PLD. Using magnetic resonance imaging over time, we demonstrate that ten weeks of STA-2842 treatment significantly reduced both liver mass and cystic index suggesting selective elimination of cystic tissue. Pre-treatment cystic epithelia contain abundant HSP90; the degree of reduction in cysts was accompanied by inhibition of proliferation-associated signaling proteins EGFR and others, and induced cleavage of caspase 8 and PARP1, and correlated with degree of HSP90 inhibition and with inactivation of ERK1/2. Our results suggest that HSP90 inhibition is worth further evaluation as a therapeutic approach for patients with PLD.