Current and prospective pharmacotherapies for the treatment of pleural mesothelioma

Introduction: Mesothelioma is a rare asbestos-linked cancer with an expected incidence peak between 2015–2030. Therapies remain ineffective, thus developing and testing novel treatments is important for both oncologists and researchers. Areas covered: After describing mesothelioma and the shortcomings of current therapies, the article discusses numerous therapies in turn such as immunotherapy (passive and active), gene therapy (such as suicide gene therapy) and targeted therapy such as tyrosine kinase inhibitors. The bases for different therapies and clinical trials at different phases are also described. The article concludes by detailing possible reasons for therapy failure. Expert opinion: Despite the many attempts to uncover new therapeutic options, mesothelioma is still an orphan disease, complicated by factors such as the inflammatory microenvironment and low mutational load. Our opinion is that uncovering the biological mechanisms behind mesothelioma development will assist therapy development. The lack of efficacy of tyrosine kinase inhibitors and modest anti-angiogenic activity indicates a less relevant role for tumor cell proliferation and neoangiogenesis, thus the shortcut of treating mesothelioma with therapies from other cancers may be unsound. Conversely, many lines of evidence indicate that focussing on the survival mechanisms that tumor cells exploit may yield better therapeutics, particularly nutrition and cellular machinery

A Novel Framework for the Comparative Analysis of Biological Networks

Genome sequencing projects provide nearly complete lists of the individual components present in an organism, but reveal little about how they work together. Follow-up initiatives have deciphered thousands of dynamic and context-dependent interrelationships between gene products that need to be analyzed with novel bioinformatics approaches able to capture their complex emerging properties. Here, we present a novel framework for the alignment and comparative analysis of biological networks of arbitrary topology. Our strategy includes the prediction of likely conserved interactions, based on evolutionary distances, to counter the high number of missing interactions in the current interactome networks, and a fast assessment of the statistical significance of individual alignment solutions, which vastly increases its performance with respect to existing tools. Finally, we illustrate the biological significance of the results through the identification of novel complex components and potential cases of cross-talk between pathways and alternative signaling routes

AlignNemo: A Local Network Alignment Method to Integrate Homology and Topology

Local network alignment is an important component of the analysis of protein-protein interaction networks that may lead to the identification of evolutionary related complexes. We present AlignNemo, a new algorithm that, given the networks of two organisms, uncovers subnetworks of proteins that relate in biological function and topology of interactions. The discovered conserved subnetworks have a general topology and need not to correspond to specific interaction patterns, so that they more closely fit the models of functional complexes proposed in the literature. The algorithm is able to handle sparse interaction data with an expansion process that at each step explores the local topology of the networks beyond the proteins directly interacting with the current solution. To assess the performance of AlignNemo, we ran a series of benchmarks using statistical measures as well as biological knowledge. Based on reference datasets of protein complexes, AlignNemo shows better performance than other methods in terms of both precision and recall. We show our solutions to be biologically sound using the concept of semantic similarity applied to Gene Ontology vocabularies. The binaries of AlignNemo and supplementary details about the algorithms and the experiments are available at: sourceforge.net/p/alignnemo

Network Neighbors of Drug Targets Contribute to Drug Side-Effect Similarity

In pharmacology, it is essential to identify the molecular mechanisms of drug action in order to understand adverse side effects. These adverse side effects have been used to infer whether two drugs share a target protein. However, side-effect similarity of drugs could also be caused by their target proteins being close in a molecular network, which as such could cause similar downstream effects. In this study, we investigated the proportion of side-effect similarities that is due to targets that are close in the network compared to shared drug targets. We found that only a minor fraction of side-effect similarities (5.8 %) are caused by drugs targeting proteins close in the network, compared to side-effect similarities caused by overlapping drug targets (64%). Moreover, these targets that cause similar side effects are more often in a linear part of the network, having two or less interactions, than drug targets in general. Based on the examples, we gained novel insight into the molecular mechanisms of side effects associated with several drug targets. Looking forward, such analyses will be extremely useful in the process of drug development to better understand adverse side effects

Maintenance of cross-sector partnerships: the role of frames in sustained collaboration

We examine the framing mechanisms used to maintain a cross-sector partnership (XSP) that was created to address a complex long-term social issue. We study the first eight years of existence of an XSP that aims to create a market for recycled phosphorus, a nutrient that is critical to crop growth but whose natural reserves have dwindled significantly. Drawing on 27 interviews and over 3,000 internal documents, we study the evolution of different frames used by diverse actors in an XSP. We demonstrate the role of framing in helping actors to avoid some of the common pitfalls for an XSP, such as debilitating conflict, and in creating sufficient common ground to sustain collaboration. As opposed to a commonly held assumption in the XSP literature, we find that collaboration in a partnership does not have to result in a unanimous agreement around a single or convergent frame regarding a contentious issue. Rather, successful collaboration between diverse partners can also be achieved by maintaining a productive tension between different frames through ‘optimal’ frame plurality – not excessive frame variety that may prevent agreements from emerging, but the retention of a select few frames and the deletion of others towards achieving a narrowing frame bandwidth. One managerial implication is that resources need not be focussed on reaching a unanimous agreement among all partners on a single mega-frame vis-à-vis a contentious issue, but can instead be used to kindle a sense of unity in diversity that allows sufficient common ground to emerge, despite the variety of actors and their positions

Family Values and Inter-Institutional Governance of Strategic Decision Making in Indian Family Firms

In this paper we use new venture creation in Indian family firms to explore the family firm as an inter-institutional system. We argue that in societies where the traditional family dominates social and economic life, the relationship between the two institutions, the firm and the family, is managed via inter-institutional logics. These inter-institutional logics help reconcile the tensions that often arise in the family firms during strategic decision-making. We use archival and interview data on thirty-six new ventures in eight Indian family firms to identify these logics. Our analysis shows that the interaction between firm and family institutional logics in Indian family firms generates four sub-logics: Economic, Expertise, Reputation and Attachment. These four logics are used to frame and screen new venture opportunities and justify resource allocation