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.

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.

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.

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.

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.

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.

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.

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.

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.

Combining Mass Spectrometry-Based Phosphoproteomics with a Network-Based Approach to Reveal FLT3-Dependent Mechanisms of Chemoresistance.

FLT3 mutations are the most frequently identified genetic alterations in acute myeloid leukemia (AML) and are associated with poor clinical outcome, relapse and chemotherapeutic resistance. Elucidating the molecular mechanisms underlying FLT3-dependent pathogenesis and drug resistance is a crucial goal of biomedical research. Given the complexity and intricacy of protein signaling networks, deciphering the molecular basis of FLT3-driven drug resistance requires a systems approach. Here we discuss how the recent advances in mass spectrometry (MS)-based (phospho) proteomics and multiparametric analysis accompanied by emerging computational approaches offer a platform to obtain and systematically analyze cell-specific signaling networks and to identify new potential therapeutic targets.

A Resource for the Network Representation of Cell Perturbations Caused by SARS-CoV-2 Infection.

The coronavirus disease 2019 (COVID-19) pandemic has caused more than 2.3 million casualties worldwide and the lack of effective treatments is a major health concern. The development of targeted drugs is held back due to a limited understanding of the molecular mechanisms underlying the perturbation of cell physiology observed after viral infection. Recently, several approaches, aimed at identifying cellular proteins that may contribute to COVID-19 pathology, have been reported. Albeit valuable, this information offers limited mechanistic insight as these efforts have produced long lists of cellular proteins, the majority of which are not annotated to any cellular pathway. We have embarked in a project aimed at bridging this mechanistic gap by developing a new bioinformatic approach to estimate the functional distance between a subset of proteins and a list of pathways. A comprehensive literature search allowed us to annotate, in the SIGNOR 2.0 resource, causal information underlying the main molecular mechanisms through which severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and related coronaviruses affect the host-cell physiology. Next, we developed a new strategy that enabled us to link SARS-CoV-2 interacting proteins to cellular phenotypes via paths of causal relationships. Remarkably, the extensive information about inhibitors of signaling proteins annotated in SIGNOR 2.0 makes it possible to formulate new potential therapeutic strategies. The proposed approach, which is generally applicable, generated a literature-based causal network that can be used as a framework to formulate informed mechanistic hypotheses on COVID-19 etiology and pathology.

Skeletal Muscle Subpopulation Rearrangements upon Rhabdomyosarcoma Development through Single-Cell Mass Cytometry.

The embryonal rhabdomyosarcoma (eRMS) is a soft tissue sarcoma commonly affecting the head and neck, the extremities and the genitourinary tract. To contribute to revealing the cell types that may originate this tumor, we exploited mass cytometry, a single-cell technique that, by using heavy-metal-tagged antibodies, allows the accurate monitoring of the changes occurring in the mononuclear cell composition of skeletal muscle tissue during tumor development. To this end, we compared cell populations of healthy muscles with those from spatiotemporal-induced eRMS tumors in a mouse model (LSL-KrasG12D/+;Tp53Fl/Fl) that can be used to develop rhabdomyosarcoma by means of infection with an adenovirus vector expressing Cre (Ad-Cre) recombinase. By monitoring different time points after tumor induction, we were able to analyze tumor progression and composition, identifying fibro/adipogenic progenitors (FAPs) as the cell type that, in this model system, had a pivotal role in tumor development. In vitro studies highlighted that both FAPs and satellite cells (SCs), upon infection with the Ad-Cre, acquired the potential to develop rhabdomyosarcomas when transplanted into immunocompromised mice. However, only infected FAPs had an antigen profile that was similar to embryonal rhabdomyosarcoma cells. Overall, our analysis supports the involvement of FAPs in eRMS development.

Integrating Patient-Specific Information into Logic Models of Complex Diseases: Application to Acute Myeloid Leukemia.

High throughput technologies such as deep sequencing and proteomics are increasingly becoming mainstream in clinical practice and support diagnosis and patient stratification. Developing computational models that recapitulate cell physiology and its perturbations in disease is a required step to help with the interpretation of results of high content experiments and to devise personalized treatments. As complete cell-models are difficult to achieve, given limited experimental information and insurmountable computational problems, approximate approaches should be considered. We present here a general approach to modeling complex diseases by embedding patient-specific genomics data into actionable logic models that take into account prior knowledge. We apply the strategy to acute myeloid leukemia (AML) and assemble a network of logical relationships linking most of the genes that are found frequently mutated in AML patients. We derive Boolean models from this network and we show that by priming the model with genomic data we can infer relevant patient-specific clinical features. Here we propose that the integration of literature-derived causal networks with patient-specific data should be explored to help bedside decisions.

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.

Adipogenesis of skeletal muscle fibro/adipogenic progenitors is affected by the WNT5a/GSK3/ß-catenin axis.

Fibro/Adipogenic Progenitors (FAPs) are muscle-interstitial progenitors mediating pro-myogenic signals that are critical for muscle homeostasis and regeneration. In myopathies, the autocrine/paracrine constraints controlling FAP adipogenesis are released causing fat infiltrates. Here, by combining pharmacological screening, high-dimensional mass cytometry and in silico network modeling with the integration of single-cell/bulk RNA sequencing data, we highlighted the canonical WNT/GSK/ß-catenin signaling as a crucial pathway modulating FAP adipogenesis triggered by insulin signaling. Consistently, pharmacological blockade of GSK3, by the LY2090314 inhibitor, stabilizes ß-catenin and represses PPARγ expression abrogating FAP adipogenesis ex vivo while limiting fatty degeneration in vivo. Furthermore, GSK3 inhibition improves the FAP pro-myogenic role by efficiently stimulating, via follistatin secretion, muscle satellite cell (MuSC) differentiation into mature myotubes. Combining, publicly available single-cell RNAseq datasets, we characterize FAPs as the main source of WNT ligands inferring their potential in mediating autocrine/paracrine responses in the muscle niche. Lastly, we identify WNT5a, whose expression is impaired in dystrophic FAPs, as a crucial WNT ligand able to restrain the detrimental adipogenic differentiation drift of these cells through the positive modulation of the ß-catenin signaling.

Metabolic reprogramming of fibro/adipogenic progenitors facilitates muscle regeneration.

In Duchenne muscular dystrophy (DMD), the absence of the dystrophin protein causes a variety of poorly understood secondary effects. Notably, muscle fibers of dystrophic individuals are characterized by mitochondrial dysfunctions, as revealed by a reduced ATP production rate and by defective oxidative phosphorylation. Here, we show that in a mouse model of DMD (mdx), fibro/adipogenic progenitors (FAPs) are characterized by a dysfunctional mitochondrial metabolism which correlates with increased adipogenic potential. Using high-sensitivity mass spectrometry-based proteomics, we report that a short-term high-fat diet (HFD) reprograms dystrophic FAP metabolism in vivo. By combining our proteomic dataset with a literature-derived signaling network, we revealed that HFD modulates the ß-catenin-follistatin axis. These changes are accompanied by significant amelioration of the histological phenotype in dystrophic mice. Transplantation of purified FAPs from HFD-fed mice into the muscles of dystrophic recipients demonstrates that modulation of FAP metabolism can be functional to ameliorate the dystrophic phenotype. Our study supports metabolic reprogramming of muscle interstitial progenitor cells as a novel approach to alleviate some of the adverse outcomes of DMD.