An integrated comparative phosphoproteomic and bioinformatic approach reveals a novel class of MPM-2 motifs upregulated in EGFRvIII-expressing glioblastoma cells

Phosphoproteomics identifies microglial Siglec-F inflammatory response during neurodegeneration

Alzheimer's disease (AD) is characterized by the appearance of amyloid-β plaques, neurofibrillary tangles, and inflammation in brain regions involved in memory. Using mass spectrometry, we have quantified the phosphoproteome of the CK-p25, 5XFAD, and Tau P301S mouse models of neurodegeneration. We identified a shared response involving Siglec-F which was upregulated on a subset of reactive microglia. The human paralog Siglec-8 was also upregulated on microglia in AD. Siglec-F and Siglec-8 were upregulated following microglial activation with interferon gamma (IFNγ) in BV-2 cell line and human stem cell-derived microglia models. Siglec-F overexpression activates an endocytic and pyroptotic inflammatory response in BV-2 cells, dependent on its sialic acid substrates and immunoreceptor tyrosine-based inhibition motif (ITIM) phosphorylation sites. Related human Siglecs induced a similar response in BV-2 cells. Collectively, our results point to an important role for mouse Siglec-F and human Siglec-8 in regulating microglial activation during neurodegeneration.

Substrate-based kinase activity inference identifies MK2 as driver of colitis

Inflammatory bowel disease (IBD) is a chronic and debilitating disorder that has few treatment options due to a lack of comprehensive understanding of its molecular pathogenesis. We used multiplexed mass spectrometry to collect high-content information on protein phosphorylation in two different mouse models of IBD. Because the biological function of the vast majority of phosphorylation sites remains unknown, we developed Substrate-based Kinase Activity Inference (SKAI), a methodology to infer kinase activity from phosphoproteomic data. This approach draws upon prior knowledge of kinase-substrate interactions to construct custom lists of kinases and their respective substrate sites, termed kinase-substrate sets that employ prior knowledge across organisms. This expansion as much as triples the amount of prior knowledge available. We then used these sets within the Gene Set Enrichment Analysis framework to infer kinase activity based on increased or decreased phosphorylation of its substrates in a dataset. When applied to the phosphoproteomic datasets from the two mouse models, SKAI predicted largely non-overlapping kinase activation profiles. These results suggest that chronic inflammation may arise through activation of largely divergent signaling networks. However, the one kinase inferred to be activated in both mouse models was mitogen-activated protein kinase-activated protein kinase 2 (MAPKAPK2 or MK2), a serine/threonine kinase that functions downstream of p38 stress-activated mitogen-activated protein kinase. Treatment of mice with active colitis with ATI450, an orally bioavailable small molecule inhibitor of the MK2 pathway, reduced inflammatory signaling in the colon and alleviated the clinical and histological features of inflammation. These studies establish MK2 as a therapeutic target in IBD and identify ATI450 as a potential therapy for the disease.

Ca2+ Signaling and Homeostasis in Mammalian Oocytes and Eggs

Changes in the intracellular concentration of calcium ([Ca2+]i) represent a vital signaling mechanism enabling communication between and among cells as well as with the environment. Cells have developed a sophisticated set of molecules, "the Ca2+ toolkit," to adapt [Ca2+]i changes to specific cellular functions. Mammalian oocytes and eggs, the subject of this review, are not an exception, and in fact the initiation of embryo devolvement in all species is entirely dependent on distinct [Ca2+]i responses. Here, we review the components of the Ca2+ toolkit present in mammalian oocytes and eggs, the regulatory mechanisms that allow these cells to accumulate Ca2+ in the endoplasmic reticulum, release it, and maintain basal and stable cytoplasmic concentrations. We also discuss electrophysiological and genetic studies that have uncovered Ca2+ influx channels in oocytes and eggs, and we analyze evidence supporting the role of a sperm-specific phospholipase C isoform as the trigger of Ca2+ oscillations during mammalian fertilization including its implication in fertility.

Advances in mass spectrometry based strategies to study receptor tyrosine kinases

Receptor tyrosine kinases (RTKs) are key transmembrane environmental sensors that are capable of transmitting extracellular information into phenotypic responses, including cell proliferation, survival and metabolism. Advances in mass spectrometry (MS)-based phosphoproteomics have been instrumental in providing the foundations of much of our current understanding of RTK signalling networks and activation dynamics. Furthermore, new insights relating to the deregulation of RTKs in disease, for instance receptor co-activation and kinome reprogramming, have largely been identified using phosphoproteomic-based strategies. This review outlines the current approaches employed in phosphoproteomic workflows, including phosphopeptide enrichment and MS data-acquisition methods. Here, recent advances in the application of MS-based phosphoproteomics to bridge critical gaps in our knowledge of RTK signalling are focused on. The current limitations of the technology are discussed and emerging areas such as computational modelling, high-throughput phospho-proteomic workflows and next-generation single-cell approaches to further our understanding in new areas of RTK biology are highlighted.

CK2 in Cancer: Cellular and Biochemical Mechanisms and Potential Therapeutic Target

CK2 genes are overexpressed in many human cancers, and most often overexpression is associated with worse prognosis. Site-specific expression in mice leads to cancer development (e.g., breast, lymphoma) indicating the oncogenic nature of CK2. CK2 is involved in many key aspects of cancer including inhibition of apoptosis, modulation of signaling pathways, DNA damage response, and cell cycle regulation. A number of CK2 inhibitors are now available and have been shown to have activity against various cancers in vitro and in pre-clinical models. Some of these inhibitors are now undergoing exploration in clinical trials as well. In this review, we will examine some of the major cancers in which CK2 inhibition has promise based on in vitro and pre-clinical studies, the proposed cellular and signaling mechanisms of anti-cancer activity by CK2 inhibitors, and the current or recent clinical trials using CK2 inhibitors.

ProteomeScout: a repository and analysis resource for post-translational modifications and proteins

ProteomeScout (https://proteomescout.wustl.edu) is a resource for the study of proteins and their post-translational modifications (PTMs) consisting of a database of PTMs, a repository for experimental data, an analysis suite for PTM experiments, and a tool for visualizing the relationships between complex protein annotations. The PTM database is a compendium of public PTM data, coupled with user-uploaded experimental data. ProteomeScout provides analysis tools for experimental datasets, including summary views and subset selection, which can identify relationships within subsets of data by testing for statistically significant enrichment of protein annotations. Protein annotations are incorporated in the ProteomeScout database from external resources and include terms such as Gene Ontology annotations, domains, secondary structure and non-synonymous polymorphisms. These annotations are available in the database download, in the analysis tools and in the protein viewer. The protein viewer allows for the simultaneous visualization of annotations in an interactive web graphic, which can be exported in Scalable Vector Graphics (SVG) format. Finally, quantitative data measurements associated with public experiments are also easily viewable within protein records, allowing researchers to see how PTMs change across different contexts. ProteomeScout should prove useful for protein researchers and should benefit the proteomics community by providing a stable repository for PTM experiments.

A microphysiological system model of therapy for liver micrometastases

Metastasis accounts for almost 90% of cancer-associated mortality. The effectiveness of cancer therapeutics is limited by the protective microenvironment of the metastatic niche and consequently these disseminated tumors remain incurable. Metastatic disease progression continues to be poorly understood due to the lack of appropriate model systems. To address this gap in understanding, we propose an all-human microphysiological system that facilitates the investigation of cancer behavior in the liver metastatic niche. This existing LiverChip is a 3D-system modeling the hepatic niche; it incorporates a full complement of human parenchymal and non-parenchymal cells and effectively recapitulates micrometastases. Moreover, this system allows real-time monitoring of micrometastasis and assessment of human-specific signaling. It is being utilized to further our understanding of the efficacy of chemotherapeutics by examining the activity of established and novel agents on micrometastases under conditions replicating diurnal variations in hormones, nutrients and mild inflammatory states using programmable microdispensers. These inputs affect the cues that govern tumor cell responses. Three critical signaling groups are targeted: the glucose/insulin responses, the stress hormone cortisol and the gut microbiome in relation to inflammatory cues. Currently, the system sustains functioning hepatocytes for a minimum of 15 days; confirmed by monitoring hepatic function (urea, α-1-antitrypsin, fibrinogen, and cytochrome P450) and injury (AST and ALT). Breast cancer cell lines effectively integrate into the hepatic niche without detectable disruption to tissue, and preliminary evidence suggests growth attenuation amongst a subpopulation of breast cancer cells. xMAP technology combined with systems biology modeling are also employed to evaluate cellular crosstalk and illustrate communication networks in the early microenvironment of micrometastases. This model is anticipated to identify new therapeutic strategies for metastasis by elucidating the paracrine effects between the hepatic and metastatic cells, while concurrently evaluating agent efficacy for metastasis, metabolism and tolerability.

Casein Kinase 2: a novel player in glioblastoma therapy and cancer stem cells

Casein kinase 2 (CK2) is an oncogenic protein kinase which contributes to tumor development, proliferation, and suppression of apoptosis in multiple cancer types. The mechanism by which CK2 expression and activity leads to tumorigenesis in glioblastoma (GBM), a stage IV primary brain tumor, is being studied. Recent studies demonstrate that CK2 plays an important role in GBM formation and growth through the inhibition of tumor suppressors and activation of oncogenes. In addition, intriguing new reports indicate that CK2 may regulate GBM formation in a novel manner; CK2 may play a critical role in cancer stem cell (CSC) maintenance. Since glial CSCs have the ability to self-renew and initiate tumor growth, new treatments which target these CSCs are needed to treat this fatal disease. Inhibition of CK2 is potentially a novel method to inhibit GBM growth and reoccurrence by targeting the glial CSCs. A new, orally available, selective CK2 inhibitor, CX-4945 has had promising results when tested in cancer cell lines, in vivo xenograft models, and human clinical trials. The development of CK2 targeted inhibitors, starting with CX-4945, may lead to a new class of more effective cancer therapies.

Experimental models to study drug distributions in tissue using MALDI mass spectrometry imaging

Requirements for patient safety and improved efficacy are steadily increasing in modern healthcare and are key drivers in modern drug development. New drug characterization assays are central in providing evidence of the specificity and selectivity of drugs. Meeting this need, matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) is used to study drug localization within microenvironmental tissue compartments. Thin sections of human lung tumor and rat xenograft tissues were exposed to pharmaceutical drugs by either spotting or submerging. These drugs, the epidermal growth factor receptor antagonists, erlotinib (Tarceva) and gefitinib (Iressa), and the acetylcholine receptor antagonist, tiotropium, were characterized by microenvironment localization. Intact tissue blocks were also immersed in drug solution, followed by sectioning. MALDI-MSI was then performed using a Thermo MALDI LTQ Orbitrap XL instrument to localize drug-distribution patterns. We propose three MALDI-MSI models measuring drug disposition that have been used to map the selected compounds within tissue compartments of tumors isolated from lung cancer patients.

Targeting protein kinase CK2 suppresses prosurvival signaling pathways and growth of glioblastoma

PURPOSE

Gliomas are the most frequently occurring primary malignancies in the brain, and glioblastoma is the most aggressive of these tumors. Protein kinase CK2 is composed of two catalytic subunits (α and/or α') and two β regulatory subunits. CK2 suppresses apoptosis, promotes neoangiogenesis, and enhances activation of the JAK/STAT, NF-κB, PI3K/AKT, Hsp90, Wnt, and Hedgehog pathways. Aberrant activation of the NF-κB, PI3K/AKT, and JAK/STAT-3 pathways is implicated in glioblastoma progression. As CK2 is involved in their activation, the expression and function of CK2 in glioblastoma was evaluated.

EXPERIMENTAL DESIGN AND RESULTS

Analysis of 537 glioblastomas from The Cancer Genome Atlas Project demonstrates the CSNK2A1 gene, encoding CK2α, has gene dosage gains in glioblastoma (33.7%), and is significantly associated with the classical glioblastoma subtype. Inhibition of CK2 activity by CX-4945, a selective CK2 inhibitor, or CK2 knockdown by siRNA suppresses activation of the JAK/STAT, NF-κB, and AKT pathways and downstream gene expression in human glioblastoma xenografts. On a functional level, CX-4945 treatment decreases the adhesion and migration of glioblastoma cells, in part through inhibition of integrin β1 and α4 expression. In vivo, CX-4945 inhibits activation of STAT-3, NF-κB p65, and AKT, and promotes survival of mice with intracranial human glioblastoma xenografts.

CONCLUSIONS

CK2 inhibitors may be considered for treatment of patients with glioblastoma.

Cell signalling analyses in the functional genomics era

The advancements in proteomics over the past decade have brought tremendous increases in sensitivity of mass spectrometry (MS) analyses and new technologies such as methods for quantitative MS and phosphoproteomics. The development of antibodies targeting a large fraction of the human proteome as well as specific antibodies that detect phosphorylations and other post-translational modifications now allows detection of a great variety of signalling marks. Combined with medium and high throughput methods for detecting many parallel signalling events such as phospho-flow cytometry analyses and MS-based analyses to identify signalling complexes, the available tools now allows analysis of whole signalling networks facilitating systems level understanding of cellular signalling. The even more recent advances in chemical biology and chemical proteomics are further enhancing the development in this area by providing a cache of small molecule compounds allowing perturbations of signal pathways further advancing our global understanding of the signal transduction dynamics at the single cell level as well as in cellular system, tissue and whole organs. This review highlights the recent advances of quantitative MS, phosphoflow cytometry and chemical biology with focus on the dynamic spatiotemporal phosphorylation events, and examples of their application.

Quantitative phospho-proteomics to investigate the polo-like kinase 1-dependent phospho-proteome

Polo-like kinase 1 (PLK1) is a key regulator of mitotic progression and cell division, and small molecule inhibitors of PLK1 are undergoing clinical trials to evaluate their utility in cancer therapy. Despite this importance, current knowledge about the identity of PLK1 substrates is limited. Here we present the results of a proteome-wide analysis of PLK1-regulated phosphorylation sites in mitotic human cells. We compared phosphorylation sites in HeLa cells that were or were not treated with the PLK1-inhibitor BI 4834, by labeling peptides via methyl esterification, fractionation of peptides by strong cation exchange chromatography, and phosphopeptide enrichment via immobilized metal affinity chromatography. Analysis by quantitative mass spectrometry identified 4070 unique mitotic phosphorylation sites on 2069 proteins. Of these, 401 proteins contained one or multiple phosphorylation sites whose abundance was decreased by PLK1 inhibition. These include proteins implicated in PLK1-regulated processes such as DNA damage, mitotic spindle formation, spindle assembly checkpoint signaling, and chromosome segregation, but also numerous proteins that were not suspected to be regulated by PLK1. Analysis of amino acid sequence motifs among phosphorylation sites down-regulated under PLK1 inhibition in this data set identified two potential novel variants of the PLK1 consensus motif.

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology (‘MCAM’) employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems.

Proteomic measurements, especially modification measurements, are greatly expanding the current knowledge of the state of proteins under various conditions. Harnessing these measurements to understand how these modifications are enzymatically regulated and their subsequent function in cellular signaling and physiology is a challenging new problem. Clustering has been very useful in reducing the dimensionality of many types of high-throughput biological data, as well inferring function of poorly understood molecular species. However, its implementation requires a great deal of technical expertise since there are a large number of parameters one must decide on in clustering, including data transforms, distance metrics, and algorithms. Previous knowledge of useful parameters does not exist for measurements of a new type. In this work we address two issues. First, we develop a framework that incorporates any number of possible parameters of clustering to produce a suite of clustering solutions. These solutions are then judged on their ability to infer biological information through statistical enrichment of existing biological annotations. Second, we apply this framework to dynamic phosphorylation measurements of the ERBB network, constructing the first extensive analysis of clustering of phosphoproteomic data and generating insight into novel components and novel functions of known components of the ERBB network.

Ca2+ signaling during mammalian fertilization: requirements, players, and adaptations

Changes in the intracellular concentration of calcium ([Ca(2+)](i)) represent a vital signaling mechanism enabling communication among cells and between cells and the environment. The initiation of embryo development depends on a [Ca(2+)](i) increase(s) in the egg, which is generally induced during fertilization. The [Ca(2+)](i) increase signals egg activation, which is the first stage in embryo development, and that consist of biochemical and structural changes that transform eggs into zygotes. The spatiotemporal patterns of [Ca(2+)](i) at fertilization show variability, most likely reflecting adaptations to fertilizing conditions and to the duration of embryonic cell cycles. In mammals, the focus of this review, the fertilization [Ca(2+)](i) signal displays unique properties in that it is initiated after gamete fusion by release of a sperm-derived factor and by periodic and extended [Ca(2+)](i) responses. Here, we will discuss the events of egg activation regulated by increases in [Ca(2+)](i), the possible downstream targets that effect these egg activation events, and the property and identity of molecules both in sperm and eggs that underpin the initiation and persistence of the [Ca(2+)](i) responses in these species.

Phosphoproteomics-based modeling defines the regulatory mechanism underlying aberrant EGFR signaling

Background

Mutation of the epidermal growth factor receptor (EGFR) results in a discordant cell signaling, leading to the development of various diseases. However, the mechanism underlying the alteration of downstream signaling due to such mutation has not yet been completely understood at the system level. Here, we report a phosphoproteomics-based methodology for characterizing the regulatory mechanism underlying aberrant EGFR signaling using computational network modeling.

Methodology/Principal Findings

Our phosphoproteomic analysis of the mutation at tyrosine 992 (Y992), one of the multifunctional docking sites of EGFR, revealed network-wide effects of the mutation on EGF signaling in a time-resolved manner. Computational modeling based on the temporal activation profiles enabled us to not only rediscover already-known protein interactions with Y992 and internalization property of mutated EGFR but also further gain model-driven insights into the effect of cellular content and the regulation of EGFR degradation. Our kinetic model also suggested critical reactions facilitating the reconstruction of the diverse effects of the mutation on phosphoproteome dynamics.

Conclusions/Significance

Our integrative approach provided a mechanistic description of the disorders of mutated EGFR signaling networks, which could facilitate the development of a systematic strategy toward controlling disease-related cell signaling.

Phosphoproteomics in cancer

Reversible protein phosphorylation serves as a basis for regulating a number of cellular processes. Aberrant activation of kinase signaling pathways is commonly associated with several cancers. Recent developments in phosphoprotein/phosphopeptide enrichment strategies and quantitative mass spectrometry have resulted in robust pipelines for high-throughput characterization of phosphorylation in a global fashion. Today, it is possible to profile site-specific phosphorylation events on thousands of proteins in a single experiment. The potential of this approach is already being realized to characterize signaling pathways that govern oncogenesis. In addition, chemical proteomic strategies have been used to unravel targets of kinase inhibitors, which are otherwise difficult to characterize. This review summarizes various approaches used for analysis of the phosphoproteome in general, and protein kinases in particular, highlighting key cancer phosphoproteomic studies.

PTMScout, a Web resource for analysis of high throughput post-translational proteomics studies

The rate of discovery of post-translational modification (PTM) sites is increasing rapidly and is significantly outpacing our biological understanding of the function and regulation of those modifications. To help meet this challenge, we have created PTMScout, a web-based interface for viewing, manipulating, and analyzing high throughput experimental measurements of PTMs in an effort to facilitate biological understanding of protein modifications in signaling networks. PTMScout is constructed around a custom database of PTM experiments and contains information from external protein and post-translational resources, including gene ontology annotations, Pfam domains, and Scansite predictions of kinase and phosphopeptide binding domain interactions. PTMScout functionality comprises data set comparison tools, data set summary views, and tools for protein assignments of peptides identified by mass spectrometry. Analysis tools in PTMScout focus on informed subset selection via common criteria and on automated hypothesis generation through subset labeling derived from identification of statistically significant enrichment of other annotations in the experiment. Subset selection can be applied through the PTMScout flexible query interface available for quantitative data measurements and data annotations as well as an interface for importing data set groupings by external means, such as unsupervised learning. We exemplify the various functions of PTMScout in application to data sets that contain relative quantitative measurements as well as data sets lacking quantitative measurements, producing a set of interesting biological hypotheses. PTMScout is designed to be a widely accessible tool, enabling generation of multiple types of biological hypotheses from high throughput PTM experiments and advancing functional assignment of novel PTM sites. PTMScout is available at http://ptmscout.mit.edu.

Phosphotyrosine signaling analysis of site-specific mutations on EGFRvIII identifies determinants governing glioblastoma cell growth

To evaluate the role of individual EGFR phosphorylation sites in activating components of the cellular signaling network we have performed a mass spectrometry-based analysis of the phosphotyrosine network downstream of site-specific EGFRvIII mutants, enabling quantification of network-level effects of site-specific point mutations. Mutation at Y845, Y1068 or Y1148 resulted in diminished receptor phosphorylation, while mutation at Y1173 led to increased phosphorylation on multiple EGFRvIII residues. Altered phosphorylation at the receptor was recapitulated in downstream signaling network activation levels, with Y1173F mutation leading to increased phosphorylation throughout the network. Computational modeling of GBM cell growth as a function of network phosphorylation levels highlights the Erk pathway as crucial for regulating EGFRvIII-driven U87MG GBM cell behavior, with the unexpected finding that Erk1/2 is negatively correlated to GBM cell growth. Genetic manipulation of this pathway supports the model, demonstrating that EGFRvIII-expressing U87MG GBM cells are sensitive to Erk activation levels. Additionally, we developed a model describing glioblastoma cell growth based on a reduced set of phosphoproteins, which represent potential candidates for future development as therapeutic targets for EGFRvIII-positive glioblastoma patients.

Oncogenic EGFR signaling networks in glioma

The epidermal growth factor receptor (EGFR) is a primary contributor to glioblastoma (GBM) initiation and progression. Here, we examine how EGFR and key downstream signaling networks contribute to the hallmark characteristics of GBM such as rapid cancer cell proliferation and diffused invasion. Additionally, we discuss current therapeutic options for GBM patients and elaborate on the mechanisms through which EGFR promotes chemoresistance. We conclude by offering a perspective on how the potential of integrative systems biology may be harnessed to develop safe and effective treatment strategies for this disease.