MiT/TFE factors control ER-phagy via transcriptional regulation of FAM134B.

Lysosomal degradation of the endoplasmic reticulum (ER) via autophagy (ER-phagy) is emerging as a critical regulator of cell homeostasis and function. The recent identification of ER-phagy receptors has shed light on the molecular mechanisms underlining this process. However, the signaling pathways regulating ER-phagy in response to cellular needs are still largely unknown. We found that the nutrient responsive transcription factors TFEB and TFE3-master regulators of lysosomal biogenesis and autophagy-control ER-phagy by inducing the expression of the ER-phagy receptor FAM134B. The TFEB/TFE3-FAM134B axis promotes ER-phagy activation upon prolonged starvation. In addition, this pathway is activated in chondrocytes by FGF signaling, a critical regulator of skeletal growth. FGF signaling induces JNK-dependent proteasomal degradation of the insulin receptor substrate 1 (IRS1), which in turn inhibits the PI3K-PKB/Akt-mTORC1 pathway and promotes TFEB/TFE3 nuclear translocation and enhances FAM134B transcription. Notably, FAM134B is required for protein secretion in chondrocytes, and cartilage growth and bone mineralization in medaka fish. This study identifies a new signaling pathway that allows ER-phagy to respond to both metabolic and developmental cues.

The Cyclin-dependent kinase 1: more than a cell cycle regulator.

The Cyclin-dependent kinase 1, as a serine/threonine protein kinase, is more than a cell cycle regulator as it was originally identified. During the last decade, it has been shown to carry out versatile functions during the last decade. From cell cycle control to gene expression regulation and apoptosis, CDK1 is intimately involved in many cellular events that are vital for cell survival. Here, we provide a comprehensive catalogue of the CDK1 upstream regulators and substrates, describing how this kinase is implicated in the control of key 'cell cycle-unrelated' biological processes. Finally, we describe how deregulation of CDK1 expression and activation has been closely associated with cancer progression and drug resistance.

Integration of NMR Spectroscopy in an Analytical Workflow to Evaluate the Effects of Oxidative Stress on Abituzumab: Beyond the Fingerprint of mAbs.

The assessment of the higher-order structure (HOS) by NMR is a powerful methodology to characterize the structural features of biologics. Forced oxidative stress studies are used to investigate the stability profile, to develop pharmaceutical formulations and analytical methods. Here, the effects of forced oxidative stress by H2O2 on the monoclonal antibody Abituzumab have been characterized by a multianalytical approach combining NMR spectroscopy, mass spectrometry, differential scanning calorimetry, surface plasmon resonance, computational tools, and bioassays. This integrated strategy has provided qualitative and semiquantitative characterization of the samples and information at residue level of the effects that oxidation has on the HOS of Abituzumab, correlating them to the loss of the biological activity.

Epitope Mapping and Binding Assessment by Solid-State NMR Provide a Way for the Development of Biologics under the Quality by Design Paradigm.

Multispecific biologics are an emerging class of drugs, in which antibodies and/or proteins designed to bind pharmacological targets are covalently linked or expressed as fusion proteins to increase both therapeutic efficacy and safety. Epitope mapping on the target proteins provides key information to improve the affinity and also to monitor the manufacturing process and drug stability. Solid-state NMR has been here used to identify the pattern of the residues of the programmed cell death ligand 1 (PD-L1) ectodomain that are involved in the interaction with a new multispecific biological drug. This is possible because the large size and the intrinsic flexibility of the complexes are not limiting factors for solid-state NMR.

Reactions with Proteins of Three Novel Anticancer Platinum(II) Complexes Bearing N-Heterocyclic Ligands.

Three novel platinum(II) complexes bearing N-heterocyclic ligands, i.e., Pt2c, Pt-IV and Pt-VIII, were previously prepared and characterized. They manifested promising in vitro anticancer properties associated with non-conventional modes of action. To gain further mechanistic insight, we have explored here the reactions of these Pt compounds with a few model proteins, i.e., hen egg white lysozyme (HEWL), bovine pancreatic ribonuclease (RNase A), horse heart cytochrome c (Cyt-c) and human serum albumin (HSA), primarily through ESI MS analysis. Characteristic and variegate patterns of reactivity were highlighted in the various cases that appear to depend both on the nature of the Pt complex and of the interacting protein. The protein-bound Pt fragments were identified. In the case of the complex Pt2c, the adducts formed upon reaction with HEWL and RNase A were further characterized by solving the respective crystal structures: this allowed us to determine the exact location of the various Pt binding sites. The implications of the obtained results are discussed in relation to the possible mechanisms of action of these innovative anticancer Pt complexes.

Combining Phosphoproteomics Datasets and Literature Information to Reveal the Functional Connections in a Cell Phosphorylation Network.

Protein phosphorylation modulates many biological processes. However, the characterization of the complex regulatory circuits underlying cell response to external and internal stimuli is still limited by our inability to describe the phosphorylation network on a global scale. Modern MS-based phosphoproteomics allows monitoring tens of thousands of phosphorylation sites in multiple conditions, making the approach ideal to explore signaling pathways mediated by phosphorylation. Here, we review recent advances in phosphoproteomics and discuss some of the computational approaches developed to facilitate extraction of signaling information from these datasets. Finally, this review focuses on approaches that integrate prior literature information with unbiased phosphoproteomics experiments.

IKAP: A heuristic framework for inference of kinase activities from Phosphoproteomics data.

MOTIVATION: Phosphoproteomics measurements are widely applied in cellular biology to detect changes in signalling dynamics. However, due to the inherent complexity of phosphorylation patterns and the lack of knowledge on how phosphorylations are related to functions, it is often not possible to directly deduce protein activities from those measurements. Here, we present a heuristic machine learning algorithm that infers the activities of kinases from Phosphoproteomics data using kinase-target information from the PhosphoSitePlus database. By comparing the estimated kinase activity profiles to the measured phosphosite profiles, it is furthermore possible to derive the kinases that are most likely to phosphorylate the respective phosphosite. RESULTS: We apply our approach to published datasets of the human cell cycle generated from HeLaS3 cells, and insulin signalling dynamics in mouse hepatocytes. In the first case, we estimate the activities of 118 at six cell cycle stages and derive 94 new kinase-phosphosite links that can be validated through either database or motif information. In the second case, the activities of 143 kinases at eight time points are estimated and 49 new kinase-target links are derived. AVAILABILITY AND IMPLEMENTATION: The algorithm is implemented in Matlab and be downloaded from github. It makes use of the Optimization and Statistics toolboxes. https://github.com/marcel-mischnik/IKAP.git. CONTACT: marcel.mischnik@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Acoustic reflex patterns in amyotrophic lateral sclerosis.

The aim of the study is to investigate acoustic reflex testing in amyotrophic lateral sclerosis patients. Amplitude, latency, and rise time of stapedial reflex were recorded for 500 and 1000 Hz contralateral stimulus. Statistical analysis was performed by the Wilcoxon test and the level of significance was set at 5 %. Fifty-one amyotrophic lateral sclerosis patients and ten sex- and age-matched control subjects were studied. Patients were further divided in two groups: amyotrophic lateral sclerosis-bulbar (38 cases, with bulbar signs at evaluation) and amyotrophic lateral sclerosis-spinal (13 cases, without bulbar signs at evaluation). Stapedial reflex was present in all patients. There was a statistically significant difference in the mean amplitude, latency, and rise time between the amyotrophic lateral sclerosis patients as compared with the controls. Amplitude was lower in both the amyotrophic lateral sclerosis-bulbar and the amyotrophic lateral sclerosis-spinal patients than in the controls (p < 0.05) and rise time was longer in both patient groups compared with the controls (p < 0.05). These results confirm the presence of abnormal acoustic reflex patterns in amyotrophic lateral sclerosis cases with bulbar signs and, moreover, suggesting a possible subclinical involvement of the stapedial motor neuron even in amyotrophic lateral sclerosis-spinal patients. Amplitude and rise time seem to be good sensitive parameters for investigating subclinical bulbar involvement.

The cell-autonomous mechanisms underlying the activity of metformin as an anticancer drug.

The biguanide drug metformin profoundly affects cell metabolism, causing an impairment of the cell energy balance and triggering a plethora of pleiotropic effects that vary depending on the cellular or environmental context. Interestingly, a decade ago, it was observed that metformin-treated diabetic patients have a significantly lower cancer risk. Although a variety of in vivo and in vitro observations emphasising the role of metformin as anticancer drug have been reported, the underlying mechanisms are still poorly understood. Here, we discuss our current understanding of the molecular mechanisms that are perturbed by metformin treatment and that might be relevant to understand its antitumour activities. We focus on the cell-autonomous mechanisms modulating growth and death of cancer cells.

MINT, the molecular interaction database: 2012 update.

The Molecular INTeraction Database (MINT, http://mint.bio.uniroma2.it/mint/) is a public repository for protein-protein interactions (PPI) reported in peer-reviewed journals. The database grows steadily over the years and at September 2011 contains approximately 235,000 binary interactions captured from over 4750 publications. The web interface allows the users to search, visualize and download interactions data. MINT is one of the members of the International Molecular Exchange consortium (IMEx) and adopts the Molecular Interaction Ontology of the Proteomics Standard Initiative (PSI-MI) standards for curation and data exchange. MINT data are freely accessible and downloadable at http://mint.bio.uniroma2.it/mint/download.do. We report here the growth of the database, the major changes in curation policy and a new algorithm to assign a confidence to each interaction.

Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction.

Currently, the identification of patient-specific therapies in cancer is mainly informed by personalized genomic analysis. In the setting of acute myeloid leukemia (AML), patient-drug treatment matching fails in a subset of patients harboring atypical internal tandem duplications (ITDs) in the tyrosine kinase domain of the FLT3 gene. To address this unmet medical need, here we develop a systems-based strategy that integrates multiparametric analysis of crucial signaling pathways, and patient-specific genomic and transcriptomic data with a prior knowledge signaling network using a Boolean-based formalism. By this approach, we derive personalized predictive models describing the signaling landscape of AML FLT3-ITD positive cell lines and patients. These models enable us to derive mechanistic insight into drug resistance mechanisms and suggest novel opportunities for combinatorial treatments. Interestingly, our analysis reveals that the JNK kinase pathway plays a crucial role in the tyrosine kinase inhibitor response of FLT3-ITD cells through cell cycle regulation. Finally, our work shows that patient-specific logic models have the potential to inform precision medicine approaches.

Mapping the human phosphatome on growth pathways.

Large-scale siRNA screenings allow linking the function of poorly characterized genes to phenotypic readouts. According to this strategy, genes are associated with a function of interest if the alteration of their expression perturbs the phenotypic readouts. However, given the intricacy of the cell regulatory network, the mapping procedure is low resolution and the resulting models provide little mechanistic insights. We have developed a new strategy that combines multiparametric analysis of cell perturbation with logic modeling to achieve a more detailed functional mapping of human genes onto complex pathways. A literature-derived optimized model is used to infer the cell activation state following upregulation or downregulation of the model entities. By matching this signature with the experimental profile obtained in the high-throughput siRNA screening it is possible to infer the target of each protein, thus defining its 'entry point' in the network. By this novel approach, 41 phosphatases that affect key growth pathways were identified and mapped onto a human epithelial cell-specific growth model, thus providing insights into the mechanisms underlying their function.

A key role of the WEE1-CDK1 axis in mediating TKI-therapy resistance in FLT3-ITD positive acute myeloid leukemia patients.

The insertion site of the internal tandem duplications (ITDs) in the FLT3 gene affects the sensitivity to tyrosine kinase inhibitors (TKIs) therapy in acute myeloid leukemia (AML). Patients with the ITD in the tyrosine kinase domain lack effective therapeutic options. Here, to identify genotype-driven strategies increasing the TKI therapy efficacy, we developed SignalingProfiler, a strategy supporting the integration of high-sensitive mass spectrometry-based (phospho)proteomics, RNA sequencing datasets with literature-derived signaling networks. The approach generated FLT3-ITD genotype-specific predictive models and revealed a conserved role of the WEE1-CDK1 axis in TKIs resistance. Remarkably, pharmacological inhibition of the WEE1 kinase synergizes and strengthens the pro-apoptotic effect of TKIs therapy in cell lines and patient-derived primary blasts. Finally, we propose a new molecular mechanism of TKIs resistance in AML and suggest the combination of WEE1 inhibitor and TKI as a therapeutic option to improve patients clinical outcome.

Caspase-8 as a novel mediator linking Src kinase signaling to enhanced glioblastoma malignancy.

Caspase-8 is a cysteine protease that plays an essential role in apoptosis. Consistently with its canonical proapoptotic function, cancer cells may genetically or epigenetically downregulate its expression. Unexpectedly, Caspase-8 is often retained in cancer, suggesting the presence of alternative mechanisms that may be exploited by cancer cells to their own benefit. In this regard, we reported that Src tyrosine kinase, which is aberrantly activated in many tumors, promotes Caspase-8 phosphorylation on Tyrosine 380 (Y380) preventing its full activation. Here, we investigated the significance of Caspase-8 expression and of its phosphorylation on Y380 in glioblastoma, a brain tumor where both Caspase-8 expression and Src activity are often aberrantly upregulated. Transcriptomic analyses identified inflammatory response as a major target of Caspase-8, and in particular, NFκB signaling as one of the most affected pathways. More importantly, we could show that Src-dependent phosphorylation of Caspase-8 on Y380 drives the assembly of a multiprotein complex that triggers NFκB activation, thereby inducing the expression of inflammatory and pro-angiogenic factors. Remarkably, phosphorylation on Y380 sustains neoangiogenesis and resistance to radiotherapy. In summary, our work identifies a novel interplay between Src kinase and Caspase-8 that allows cancer cells to hijack Caspase-8 to sustain tumor growth.

Phosphoproteomics and Organelle Proteomics in Pancreatic Islets.

Over the recent years, mass spectrometry (MS)-based proteomics has undergone dramatic advances in sample preparation, instrumentation, and computational methods. Here, we describe in detail, how a workflow quantifies global protein phosphorylation in pancreatic islets and characterizes intracellular organelle composition on protein level by MS-based proteomics.

A dysprosium single molecule magnet outperforming current pseudocontact shift agents.

A common criterion for designing performant single molecule magnets and pseudocontact shift tags is a large magnetic anisotropy. In this article we present a dysprosium complex chemically designed to exhibit strong easy-axis type magnetic anisotropy that is preserved in dichloromethane solution at room temperature. Our detailed theoretical and experimental studies on the magnetic properties allowed explaining several features typical of highly performant SMMs. Moreover, the NMR characterization shows remarkably large chemical shifts, outperforming the current state-of-the art PCS tags.

Phosphorylation of FAM134C by CK2 controls starvation-induced ER-phagy.

Selective degradation of the endoplasmic reticulum (ER) via autophagy (ER-phagy) is initiated by ER-phagy receptors, which facilitate the incorporation of ER fragments into autophagosomes. FAM134 reticulon family proteins (FAM134A, FAM134B, and FAM134C) are ER-phagy receptors with structural similarities and nonredundant functions. Whether they respond differentially to the stimulation of ER-phagy is unknown. Here, we describe an activation mechanism unique to FAM134C during starvation. In fed conditions, FAM134C is phosphorylated by casein kinase 2 (CK2) at critical residues flanking the LIR domain. Phosphorylation of these residues negatively affects binding affinity to the autophagy proteins LC3. During starvation, mTORC1 inhibition limits FAM134C phosphorylation by CK2, hence promoting receptor activation and ER-phagy. Using a novel tool to study ER-phagy in vivo and FAM134C knockout mice, we demonstrated the physiological relevance of FAM134C phosphorylation during starvation-induced ER-phagy in liver lipid metabolism. These data provide a mechanistic insight into ER-phagy regulation and an example of autophagy selectivity during starvation.

VirusMINT: a viral protein interaction database.

Understanding the consequences on host physiology induced by viral infection requires complete understanding of the perturbations caused by virus proteins on the cellular protein interaction network. The VirusMINT database (http://mint.bio.uniroma2.it/virusmint/) aims at collecting all protein interactions between viral and human proteins reported in the literature. VirusMINT currently stores over 5000 interactions involving more than 490 unique viral proteins from more than 110 different viral strains. The whole data set can be easily queried through the search pages and the results can be displayed with a graphical viewer. The curation effort has focused on manuscripts reporting interactions between human proteins and proteins encoded by some of the most medically relevant viruses: papilloma viruses, human immunodeficiency virus 1, Epstein-Barr virus, hepatitis B virus, hepatitis C virus, herpes viruses and Simian virus 40.

Assembling Disease Networks From Causal Interaction Resources.

The development of high-throughput high-content technologies and the increased ease in their application in clinical settings has raised the expectation of an important impact of these technologies on diagnosis and personalized therapy. Patient genomic and expression profiles yield lists of genes that are mutated or whose expression is modulated in specific disease conditions. The challenge remains of extracting from these lists functional information that may help to shed light on the mechanisms that are perturbed in the disease, thus setting a rational framework that may help clinical decisions. Network approaches are playing an increasing role in the organization and interpretation of patients' data. Biological networks are generated by connecting genes or gene products according to experimental evidence that demonstrates their interactions. Till recently most approaches have relied on networks based on physical interactions between proteins. Such networks miss an important piece of information as they lack details on the functional consequences of the interactions. Over the past few years, a number of resources have started collecting causal information of the type protein A activates/inactivates protein B, in a structured format. This information may be represented as signed directed graphs where physiological and pathological signaling can be conveniently inspected. In this review we will (i) present and compare these resources and discuss the different scope in comparison with pathway resources; (ii) compare resources that explicitly capture causality in terms of data content and proteome coverage (iii) review how causal-graphs can be used to extract disease-specific Boolean networks.