45 research outputs found
Evaluation of CA 19-9, a predictive biomarker of response and survival in patients undergoing chemotherapy for metastatic pancreatic ductal adenocarcinoma
BAP1 and YY1 regulate expression of death receptors in malignant pleural mesothelioma
Malignant pleural mesothelioma (MPM) is a rare, aggressive, and incurable cancer arising from the mesothelial lining of the pleura, with few available treatment options. We recently reported loss of function of the nuclear deubiquitinase BRCA1-associated protein 1 (BAP1), a frequent event in MPM, is associated with sensitivity to tumour necrosis factor-related apoptosis-inducing ligand (TRAIL)-mediated apoptosis. As a potential underlying mechanism, here we report that BAP1 negatively regulates the expression of TRAIL receptors: death receptors 4 (DR4) and 5 (DR5). Using tissue microarrays (TMAs) of tumour samples from MPM patients, we found a strong inverse correlation between BAP1 and TRAIL receptor expression. BAP1 knockdown increased DR4 and DR5 expression, whereas overexpression of BAP1 had the opposite effect. Reporter assays confirmed wild-type BAP1, but not catalytically-inactive mutant BAP1, reduced promoter activities of DR4 and DR5, suggesting deubiquitinase activity is required for the regulation of gene expression. Co-IP studies demonstrated direct binding of BAP1 to the transcription factor Ying Yang 1 (YY1), and ChIP assays revealed BAP1 and YY1 to be enriched in the promoter regions of DR4 and DR5. Knockdown of YY1 also increased DR4 and DR5 expression and sensitivity to TRAIL. These results suggest that BAP1 and YY1 cooperatively repress transcription of TRAIL receptors. Our finding that BAP1 directly regulates the extrinsic apoptotic pathway will provide new insights into the role of BAP1 in the development of MPM and other cancers with frequent BAP1 mutations
Utilizing linked open data for web service selection and composition to support e-commerce transactions
© Springer International Publishing Switzerland 2016. Web Services (WS) have emerged during the past decades as a means for loosely coupled distributed systems to interact and communicate. Nevertheless, the abundance of services that can be retrieved online, often providing similar functionalities, can raise questions regarding the selection of the optimal service to be included in a value added composition. We propose a framework for the selection and composition of WS utilizing Linked open Data (LoD). The proposed method is based on RDF triples describing the functional and non-functional characteristics of WS. We aim at the optimal composition of services as a result of specific SPARQL queries and personalized weights for QoS criteria. Finally we utilize an approach based on the particle swarm optimization (PSO) method for the ranking of returned services
Service workload patterns for QoS-driven cloud resource management
Cloud service providers negotiate SLAs for customer services they offer based on the reliability of performance and availability of their lower-level platform infrastructure. While availability management is more mature, performance management is less reliable. In order to support a continuous approach that supports the initial static infrastructure configuration as well as dynamic reconfiguration and auto-scaling, an accurate and efficient solution is required. We propose a prediction technique that combines a workload pattern mining approach with a traditional collaborative filtering solution to meet the accuracy and efficiency requirements. Service workload patterns abstract common infrastructure workloads from monitoring logs and act as a part of a first-stage high-performant configuration mechanism before more complex traditional methods are considered. This enhances current reactive rule-based scalability approaches and basic prediction techniques by a hybrid prediction solution. Uncertainty and noise are additional challenges that emerge in multi-layered, often federated cloud architectures. We specifically add log smoothing combined with a fuzzy logic approach to make the prediction solution more robust in the context of these challenges
Acute immune signatures and their legacies in severe acute respiratory syndrome coronavirus-2 infected cancer patients
Given the immune system’s importance for cancer surveillance and treatment, we have investigated how it
may be affected by SARS-CoV-2 infection of cancer patients. Across some heterogeneity in tumor type,
stage, and treatment, virus-exposed solid cancer patients display a dominant impact of SARS-CoV-2,
apparent from the resemblance of their immune signatures to those for COVID-19+ non-cancer patients.
This is not the case for hematological malignancies, with virus-exposed patients collectively displaying heterogeneous humoral responses, an exhausted T cell phenotype and a high prevalence of prolonged virus
shedding. Furthermore, while recovered solid cancer patients’ immunophenotypes resemble those of nonvirus-exposed cancer patients, recovered hematological cancer patients display distinct, lingering immunological legacies. Thus, while solid cancer patients, including those with advanced disease, seem no more at
risk of SARS-CoV-2-associated immune dysregulation than the general population, hematological cancer
patients show complex immunological consequences of SARS-CoV-2 exposure that might usefully inform
their care
A theoretical model of inflammation- and mechanotransduction- driven asthmatic airway remodelling
Inflammation, airway hyper-responsiveness and airway remodelling are well-established hallmarks of asthma, but their inter-relationships remain elusive. In order to obtain a better understanding of their inter-dependence, we develop a mechanochemical morphoelastic model of the airway wall accounting for local volume changes in airway smooth muscle (ASM) and extracellular matrix in response to transient inflammatory or contractile agonist challenges. We use constrained mixture theory, together with a multiplicative decomposition of growth from the elastic deformation, to model the airway wall as a nonlinear fibre-reinforced elastic cylinder. Local contractile agonist drives ASM cell contraction, generating mechanical stresses in the tissue that drive further release of mitogenic mediators and contractile agonists via underlying mechanotransductive signalling pathways. Our model predictions are consistent with previously described inflammation-induced remodelling within an axisymmetric airway geometry. Additionally, our simulations reveal novel mechanotransductive feedback by which hyper-responsive airways exhibit increased remodelling, for example, via stress-induced release of pro-mitogenic and procontractile cytokines. Simulation results also reveal emergence of a persistent contractile tone observed in asthmatics, via either a pathological mechanotransductive feedback loop, a failure to clear agonists from the tissue, or a combination of both. Furthermore, we identify various parameter combinations that may contribute to the existence of different asthma phenotypes, and we illustrate a combination of factors which may predispose severe asthmatics to fatal bronchospasms