HER2 Phosphorylation Is Maintained by a PKB Negative Feedback Loop in Response to Anti-HER2 Herceptin in Breast Cancer

A feedback loop maintains HER2 receptor signalling and cell survival in response to Herceptin treatment in HER2-positive breast cancers, but this Herceptin resistance may be bypassed by pan-HER inhibitors

Regulation of ErbB2 Receptor Status by the Proteasomal DUB POH1

Understanding the factors, which control ErbB2 and EGF receptor (EGFR) status in cells is likely to inform future therapeutic approaches directed at these potent oncogenes. ErbB2 is resistant to stimulus-induced degradation and high levels of over-expression can inhibit EGF receptor down-regulation. We now show that for HeLa cells expressing similar numbers of EGFR and ErbB2, EGFR down-regulation is efficient and insensitive to reduction of ErbB2 levels. Deubiquitinating enzymes (DUBs) may extend protein half-lives by rescuing ubiquitinated substrates from proteasomal degradation or from ubiquitin-dependent lysosomal sorting. Using a siRNA library directed at the full complement of human DUBs, we identified POH1 (also known as Rpn11 or PSMD14), a component of the proteasome lid, as a critical DUB controlling the apparent ErbB2 levels. Moreover, the effects on ErbB2 levels can be reproduced by administration of proteasomal inhibitors such as epoxomicin used at maximally tolerated doses. However, the extent of this apparent loss and specificity for ErbB2 versus EGFR could not be accounted for by changes in transcription or degradation rate. Further investigation revealed that cell surface ErbB2 levels are only mildly affected by POH1 knock-down and that the apparent loss can at least partially be explained by the accumulation of higher molecular weight ubiquitinated forms of ErbB2 that are detectable with an extracellular but not intracellular domain directed antibody. We propose that POH1 may deubiquitinate ErbB2 and that this activity is not necessarily coupled to proteasomal degradation

Monte Carlo Simulations of HIV Capsid Protein Homodimer

Capsid protein (CA) is the building block of virus coats. To help understand how the HIV CA proteins self-organize into large assemblies of various shapes, we aim to computationally evaluate the binding affinity and interfaces in a CA homodimer. We model the N- and C-terminal domains (NTD and CTD) of the CA as rigid bodies and treat the five-residue loop between the two domains as a flexible linker. We adopt a transferrable residue-level coarse-grained energy function to describe the interactions between the protein domains. In seven extensive Monte Carlo simulations with different volumes, a large number of binding/unbinding transitions between the two CA proteins are observed, thus allowing a reliable estimation of the equilibrium probabilities for the dimeric vs monomeric forms. The obtained dissociation constant for the CA homodimer from our simulations, 20–25 μM, is in reasonable agreement with experimental measurement. A wide range of binding interfaces, primarily between the NTDs, are identified in the simulations. Although some observed bound structures here closely resemble the major binding interfaces in the capsid assembly, they are statistically insignificant in our simulation trajectories. Our results suggest that although the general purpose energy functions adopted here could reasonably reproduce the overall binding affinity for the CA homodimer, further adjustment would be needed to accurately represent the relative strength of individual binding interfaces

Synthetic spatially graded Rac activation drives directed cell polarization and locomotion

Migrating cells possess intracellular gradients of Rho GTPases, but it is unknown whether these shallow gradients themselves can induce motility. Here we describe a new method to present cells with induced linear gradients of active, endogenous Rac without receptor activation. Gradients as low as 15% were sufficient to not only trigger cell migration up the synthetic gradient, but also to induce both cell polarization and repolarization. Response kinetics were inversely proportional to Rac gradient values, in agreement with a new mathematical model, suggesting a role for natural input gradient amplification upstream of Rac. Increases in Rac levels beyond a well-defined threshold dramatically augmented polarization and decreased sensitivity to the gradient value. The threshold was governed by initial cell polarity and PI3K activity, supporting a role for both in defining responsiveness to natural or synthetic Rac activation. Our methodology suggests a general way to investigate processes regulated by intracellular signaling gradients

Connexin 43 mediated gap junctional communication enhances breast tumor cell diapedesis in culture

INTRODUCTION: Metastasis involves the emigration of tumor cells through the vascular endothelium, a process also known as diapedesis. The molecular mechanisms regulating tumor cell diapedesis are poorly understood, but may involve heterocellular gap junctional intercellular communication (GJIC) between tumor cells and endothelial cells. METHOD: To test this hypothesis we expressed connexin 43 (Cx43) in GJIC-deficient mammary epithelial tumor cells (HBL100) and examined their ability to form gap junctions, establish heterocellular GJIC and migrate through monolayers of human microvascular endothelial cells (HMVEC) grown on matrigel-coated coverslips. RESULTS: HBL100 cells expressing Cx43 formed functional heterocellular gap junctions with HMVEC monolayers within 30 minutes. In addition, immunocytochemistry revealed Cx43 localized to contact sites between Cx43 expressing tumor cells and endothelial cells. Quantitative analysis of diapedesis revealed a two-fold increase in diapedesis of Cx43 expressing cells compared to empty vector control cells. The expression of a functionally inactive Cx43 chimeric protein in HBL100 cells failed to increase migration efficiency, suggesting that the observed up-regulation of diapedesis in Cx43 expressing cells required heterocellular GJIC. This finding is further supported by the observation that blocking homocellular and heterocellular GJIC with carbenoxolone in co-cultures also reduced diapedesis of Cx43 expressing HBL100 tumor cells. CONCLUSION: Collectively, our results suggest that heterocellular GJIC between breast tumor cells and endothelial cells may be an important regulatory step during metastasis

Gefitinib (IRESSA) sensitive lung cancer cell lines show phosphorylation of Akt without ligand stimulation

BACKGROUND: Phase III trials evaluating the efficacy of gefitinib (IRESSA) in non-small cell lung cancer (NSCLC) lend support to the need for improved patient selection in terms of gefitinib use. Mutation of the epidermal growth factor receptor (EGFR) gene is reported to be associated with clinical responsiveness to gefitinib. However, gefitinib-sensitive and prolonged stable-disease-defined tumors without EGFR gene mutation have also been reported. METHODS: To identify other key factors involved in gefitinib sensitivity, we analyzed the protein expression of molecules within the EGFR family, PI3K-Akt and Ras/MEK/Erk pathways and examined the sensitivity to gefitinib using the MTT cell proliferation assay in 23 lung cancer cell lines. RESULTS: We identified one highly sensitive cell line (PC9), eight cell lines displaying intermediate-sensitivity, and 14 resistant cell lines. Only PC9 and PC14 (intermediate-sensitivity) displayed an EGFR gene mutation including amplification. Eight out of the nine cell lines showing sensitivity had Akt phosphorylation without ligand stimulation, while only three out of the 14 resistant lines displayed this characteristic (P = 0.0059). Furthermore, the ratio of phosphor-Akt/total Akt in sensitive cells was higher than that observed in resistant cells (P = 0.0016). Akt phosphorylation was partially inhibited by gefitinib in all sensitive cell lines. CONCLUSION: These results suggest that Akt phosphorylation without ligand stimulation may play a key signaling role in gefitinib sensitivity, especially intermediate-sensitivity. In addition, expression analyses of the EGFR family, EGFR gene mutation, and FISH (fluorescence in situ hybridization) analyses showed that the phosphorylated state of EGFR and Akt might be a useful clinical marker of Akt activation without ligand stimulation, in addition to EGFR gene mutation and amplification, particularly in adenocarcinomas

Efficient Production of HIV-1 Virus-Like Particles from a Mammalian Expression Vector Requires the N-Terminal Capsid Domain

It is now well accepted that the structural protein Pr55Gag is sufficient by itself to produce HIV-1 virus-like particles (VLPs). This polyprotein precursor contains different domains including matrix, capsid, SP1, nucleocapsid, SP2 and p6. In the present study, we wanted to determine by mutagenesis which region(s) is essential to the production of VLPs when Pr55Gag is inserted in a mammalian expression vector, which allows studying the protein of interest in the absence of other viral proteins. To do so, we first studied a minimal Pr55Gag sequence called Gag min that was used previously. We found that Gag min fails to produce VLPs when expressed in an expression vector instead of within a molecular clone. This failure occurs early in the cell at the assembly of viral proteins. We then generated a series of deletion and substitution mutants, and examined their ability to produce VLPs by combining biochemical and microscopic approaches. We demonstrate that the matrix region is not necessary, but that the efficiency of VLP production depends strongly on the presence of its basic region. Moreover, the presence of the N-terminal domain of capsid is required for VLP production when Gag is expressed alone. These findings, combined with previous observations indicating that HIV-1 Pr55Gag-derived VLPs act as potent stimulators of innate and acquired immunity, make the use of this strategy worth considering for vaccine development

Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1 protease, resulting in non-functional virus particles. Nevertheless, there exist mutations in this region leading to resistance against Bevirimat. Highly specific and accurate tools to predict resistance to maturation inhibitors can help to identify patients, who might benefit from the usage of these new drugs.</p> <p>Results</p> <p>We tested several methods to improve Bevirimat resistance prediction in HIV-1. It turned out that combining structural and sequence-based information in classifier ensembles led to accurate and reliable predictions. Moreover, we were able to identify the most crucial regions for Bevirimat resistance computationally, which are in line with experimental results from other studies.</p> <p>Conclusions</p> <p>Our analysis demonstrated the use of machine learning techniques to predict HIV-1 resistance against maturation inhibitors such as Bevirimat. New maturation inhibitors are already under development and might enlarge the arsenal of antiretroviral drugs in the future. Thus, accurate prediction tools are very useful to enable a personalized therapy.</p

Predicting Bevirimat resistance of HIV-1 from genotype

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors are a new class of antiretroviral drugs. Bevirimat (BVM) was the first substance in this class of inhibitors entering clinical trials. While the inhibitory function of BVM is well established, the molecular mechanisms of action and resistance are not well understood. It is known that mutations in the regions CS p24/p2 and p2 can cause phenotypic resistance to BVM. We have investigated a set of p24/p2 sequences of HIV-1 of known phenotypic resistance to BVM to test whether BVM resistance can be predicted from sequence, and to identify possible molecular mechanisms of BVM resistance in HIV-1.</p> <p>Results</p> <p>We used artificial neural networks and random forests with different descriptors for the prediction of BVM resistance. Random forests with hydrophobicity as descriptor performed best and classified the sequences with an area under the Receiver Operating Characteristics (ROC) curve of 0.93 ± 0.001. For the collected data we find that p2 sequence positions 369 to 376 have the highest impact on resistance, with positions 370 and 372 being particularly important. These findings are in partial agreement with other recent studies. Apart from the complex machine learning models we derived a number of simple rules that predict BVM resistance from sequence with surprising accuracy. According to computational predictions based on the data set used, cleavage sites are usually not shifted by resistance mutations. However, we found that resistance mutations could shorten and weaken the <it>α</it>-helix in p2, which hints at a possible resistance mechanism.</p> <p>Conclusions</p> <p>We found that BVM resistance of HIV-1 can be predicted well from the sequence of the p2 peptide, which may prove useful for personalized therapy if maturation inhibitors reach clinical practice. Results of secondary structure analysis are compatible with a possible route to BVM resistance in which mutations weaken a six-helix bundle discovered in recent experiments, and thus ease Gag cleavage by the retroviral protease.</p