Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks

Bioinspired Nucleic Acid-Based Bandpass Filters and Their Concentration-Adaptive Functions

Natural signaling networks can act as bandpass filters to interpret external stimuli within defined concentration ranges for differential cellular activities. Replicating such a bandpass filtering mechanism by synthetic networks poses a significant challenge. Herein, we introduce a modular design of nucleic acid-based multilayer threshold-gated incoherent feedforward networks as multiband bandpass filters to produce mutually exclusive responses within defined input concentration ranges. In these networks, nucleic acids demonstrate triple functionality by acting as threshold-gated entities to discern input concentration levels, serving as network nodes to assemble incoherent feedforward loops for nonlinear signal processing, and functioning as signal transduction units for coupling downstream functional modules. These modular networks enable the fine-tuning of filtering performance in terms of band position, bandwidth, cascades, and responses. A mathematical simulation model allows us to predict the filtering behaviors under various conditions. Also, the networks are integrated with upstream signal conversion modules to process concentration information on molecules beyond nucleic acids, such as adenosine and its derivatives. Furthermore, connections to downstream functional modules allow the system to regulate various processes in a concentration bandpass manner, realizing concentration-adaptive DNAzyme biocatalysis, tristate logic operations, RNA transcription, and DNA condensate formation. These findings underscore the potential of enzyme-free DNA reaction networks in complex signal processing and lay a solid foundation for developing chemical and material systems with highly adaptive and autonomous behaviors.

Bistable dynamics of TAN-NK cells in tumor growth and control of radiotherapy-induced neutropenia in lung cancer treatment

Neutrophils play a crucial role in the innate immune response as a first line of defense in many diseases, including cancer. Tumor-associated neutrophils (TANs) can either promote or inhibit tumor growth in various steps of cancer progression via mutual interactions with cancer cells in a complex tumor microenvironment (TME). In this study, we developed and analyzed mathematical models to investigate the role of natural killer cells (NK cells) and the dynamic transition between N1 and N2 TAN phenotypes in killing cancer cells through key signaling networks and how adjuvant therapy with radiation can be used in combination to increase anti-tumor efficacy. We examined the complex immune-tumor dynamics among N1/N2 TANs, NK cells, and tumor cells, communicating through key extracellular mediators (Transforming growth factor (TGF-$ \beta $), Interferon gamma (IFN-$ \gamma $)) and intracellular regulation in the apoptosis signaling network. We developed several tumor prevention strategies to eradicate tumors, including combination (IFN-$ \gamma $, exogenous NK, TGF-$ \beta $ inhibitor) therapy and optimally-controlled ionizing radiation in a complex TME. Using this model, we investigated the fundamental mechanism of radiation-induced changes in the TME and the impact of internal and external immune composition on the tumor cell fate and their response to different treatment schedules.

Dynamic proteome and phosphoproteome profiling reveals regulatory mechanisms in LPS-stimulated macrophage inflammatory responses

Macrophage-mediated acute inflammation is crucial for pathogen clearance and tissue repair, yet the underlying molecular mechanisms remain inadequately understood. The present study focused on the dynamic profiles of the proteome and phosphoproteome of macrophages exposed to lipopolysaccharide within 1 h. Gene Set Enrichment Analysis (GSEA) identified significantly enriched pathways in fatty acid metabolism and translation during the early inflammatory phase. Further trend analysis of the differentially expressed proteins revealed patterns associated with translation regulation such as translation initiation. Importantly, the nascent chain experiment demonstrated no significant changes in overall gene translation levels during this phase. These data indicate that macrophages maintain intracellular protein homeostasis through translational regulation, with post-translational modifications (PTMs) playing a crucial role in the rapid cellular response to pathogen invasion. Phosphorylation is a key PTM that regulates protein functions in almost all cellular processes. Time-resolved phosphoproteome analysis identified 367 differentially expressed phosphopeptides involved in immune-related pathways that resist infection. Additionally, weighted gene co-expression network analysis (WGCNA) discovered core modules that regulate translation-related processes such as RNA export from nucleus. Moreover, conjoint analysis of the proteome and phosphoproteome identified the hub protein EF1B that exhibited the largest fold change and is also involved in translation. Our data not only provide a more comprehensive understanding of the dynamic molecular networks of acute macrophage inflammation but also provide a systematic proteomic resource for further studies.

The proteomic landscape of diffuse midline glioma highlights the therapeutic potential of non-histone protein methyltransferases

BACKGROUND

Diffuse Midline Glioma (DMG) is a highly aggressive pediatric brain tumor with limited treatment options despite extensive genomic characterization. The aim of this study was to investigate the proteomic landscape of DMG to identify potential therapeutic targets.

METHODS

We conducted a comprehensive proteomic analysis using LC-MS3, along with DNA methylation and DNA/RNA sequencing in 55 DMG patients' samples. PTM profiling (phosphoproteome and methylproteome) was conducted in 30 patient samples. We then investigated the effects of modulating key protein targets on protein methylation, protein synthesis, and DMG cell growth in vitro and in vivo.

RESULTS

DMGs exhibited high global protein methylation, with significant enrichment of translation machinery proteins and factors involved in apoptosis regulation. Surprisingly, while targets of key kinases were highly phosphorylated, overall protein phosphorylation was lower in DMG compared to normal brain tissues. Non-histone methyltransferases METTL13 and METTL21B, along with protein kinases PAK2, PRKACA, and AKT1, were identified as key players in DMG methylproteome and phosphoproteome, respectively. METTL13 knockdown led to reduced EEF1A1 protein methylation, a shift in oncoprotein synthesis, and inhibited DMG cell growth in vitro and in vivo.

CONCLUSIONS

Our findings highlight the dependency of DMG on methyl-signaling pathways, particularly involving METTL13, which regulates EEF1A1 protein methylation and oncoprotein synthesis. Targeting the non-histone methyltransferases offers a promising therapeutic strategy for DMG. This study underscores the potential of post-translational modifications, specifically methyl-signaling pathways, as novel therapeutic targets for DMG and possibly other currently incurable cancers.

Quantitative Analysis of Nonhistone Lysine Methylation Sites and Lysine Demethylases in Breast Cancer Cell Lines

Growing evidence shows that lysine methylation is a widespread protein post-translational modification (PTM) that regulates protein function on histone and nonhistone proteins. Numerous studies have demonstrated that the dysregulation of lysine methylation mediators contributes to cancer growth and chemotherapeutic resistance. While changes in histone methylation are well-documented with extensive analytical techniques available, there is a lack of high-throughput methods to reproducibly quantify changes in the abundances of the mediators of lysine methylation and nonhistone lysine methylation (Kme) simultaneously across multiple samples. Recent studies by our group and others have demonstrated that antibody enrichment is not required to detect lysine methylation, prompting us to investigate the use of tandem mass tag (TMT) labeling for global Kme quantification without antibody enrichment in four different breast cancer cell lines (MCF-7, MDA-MB-231, HCC1806, and MCF10A). To improve the quantification of KDMs, we incorporated a lysine demethylase (KDM) isobaric trigger channel, which enabled 96% of all KDMs to be quantified while simultaneously quantifying 326 Kme sites. Overall, 142 differentially abundant Kme sites and eight differentially abundant KDMs were identified among the four cell lines, revealing cell line-specific patterning.

Posttranslational Modifications of -Synuclein, Their Therapeutic Potential, and Crosstalk in Health and Neurodegenerative Diseases

α-Synuclein (α-Syn) aggregation in Lewy bodies and Lewy neurites has emerged as a key pathogenetic feature in Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. Various factors, including posttranslational modifications (PTMs), can influence the propensity of α-Syn to misfold and aggregate. PTMs are biochemical modifications of a protein that occur during or after translation and are typically mediated by enzymes. PTMs modulate several characteristics of proteins including their structure, activity, localization, and stability. α-Syn undergoes various posttranslational modifications, including phosphorylation, ubiquitination, SUMOylation, acetylation, glycation, O-GlcNAcylation, nitration, oxidation, polyamination, arginylation, and truncation. Different PTMs of a protein can physically interact with one another or work together to influence a particular physiological or pathological feature in a process known as PTMs crosstalk. The development of detection techniques for the cooccurrence of PTMs in recent years has uncovered previously unappreciated mechanisms of their crosstalk. This has led to the emergence of evidence supporting an association between α-Syn PTMs crosstalk and synucleinopathies. In this review, we provide a comprehensive evaluation of α-Syn PTMs, their impact on misfolding and pathogenicity, the pharmacological means of targeting them, and their potential as biomarkers of disease. We also highlight the importance of the crosstalk between these PTMs in α-Syn function and aggregation. Insight into these PTMS and the complexities of their crosstalk can improve our understanding of the pathogenesis of synucleinopathies and identify novel targets of therapeutic potential. SIGNIFICANCE STATEMENT: α-Synuclein is a key pathogenic protein in Parkinson's disease and other synucleinopathies, making it a leading therapeutic target for disease modification. Multiple posttranslational modifications occur at various sites in α-Synuclein and alter its biophysical and pathological properties, some interacting with one another to add to the complexity of the pathogenicity of this protein. This review details these modifications, their implications in disease, and potential therapeutic opportunities.

Quantitative analysis of non-histone lysine methylation sites and lysine demethylases in breast cancer cell lines

Growing evidence shows that lysine methylation is a widespread protein post-translational modification that regulates protein function on histone and non-histone proteins. Numerous studies have demonstrated that dysregulation of lysine methylation mediators contributes to cancer growth and chemotherapeutic resistance. While changes in histone methylation are well documented with extensive analytical techniques available, there is a lack of high-throughput methods to reproducibly quantify changes in the abundances of the mediators of lysine methylation and non-histone lysine methylation (Kme) simultaneously across multiple samples. Recent studies by our group and others have demonstrated that antibody enrichment is not required to detect lysine methylation, prompting us to investigate the use of Tandem Mass Tag (TMT) labeling for global Kme quantification sans antibody enrichment in four different breast cancer cell lines (MCF-7, MDA-MB-231, HCC1806, and MCF10A). To improve the quantification of KDMs, we incorporated a lysine demethylase (KDM) isobaric trigger channel, which enabled 96% of all KDMs to be quantified while simultaneously quantifying 326 Kme sites. Overall, 142 differentially abundant Kme sites and eight differentially abundant KDMs were identified between the four cell lines, revealing cell line-specific patterning.

Protein biomarkers for subtyping breast cancer and implications for future research: a 2024 update

INTRODUCTION

Breast cancer subtyping is used clinically for diagnosis, prognosis, and treatment decisions. Subtypes are categorized by cell of origin, histomorphology, gene expression signatures, hormone receptor status, and/or protein levels. Categorizing breast cancer based on gene expression signatures aids in assessing a patient's recurrence risk. Protein biomarkers, on the other hand, provide functional data for selecting therapies for primary and recurrent tumors. We provide an update on protein biomarkers in breast cancer subtypes and their application in prognosis and therapy selection.

AREAS COVERED

Protein pathways in breast cancer subtypes are reviewed in the context of current protein-targeted treatment options. PubMed, Science Direct, Scopus, and Cochrane Library were searched for relevant studies between 2017 and 17 August 2024.

EXPERT OPINION

Post-translationally modified proteins and their unmodified counterparts have become clinically useful biomarkers for defining breast cancer subtypes from a therapy perspective. Tissue heterogeneity influences treatment outcomes and disease recurrence. Spatial profiling has revealed complex cellular subpopulations within the breast tumor microenvironment. Deciphering the functional relationships between and within tumor clonal cell populations will further aid in defining breast cancer subtypes and create new treatment paradigms for recurrent, drug resistant, and metastatic disease.

Craniofacial chondrogenesis in organoids from human stem cell-derived neural crest cells

Knowledge of cell signaling pathways that drive human neural crest differentiation into craniofacial chondrocytes is incomplete, yet essential for using stem cells to regenerate craniomaxillofacial structures. To accelerate translational progress, we developed a differentiation protocol that generated self-organizing craniofacial cartilage organoids from human embryonic stem cell-derived neural crest stem cells. Histological staining of cartilage organoids revealed tissue architecture and staining typical of elastic cartilage. Protein and post-translational modification (PTM) mass spectrometry and snRNA-seq data showed that chondrocyte organoids expressed robust levels of cartilage extracellular matrix (ECM) components: many collagens, aggrecan, perlecan, proteoglycans, and elastic fibers. We identified two populations of chondroprogenitor cells, mesenchyme cells and nascent chondrocytes, and the growth factors involved in paracrine signaling between them. We show that ECM components secreted by chondrocytes not only create a structurally resilient matrix that defines cartilage, but also play a pivotal autocrine cell signaling role in determining chondrocyte fate.

Extracellular Vesicle Protein Expression in Doped Bioactive Glasses: Further Insights Applying Anomaly Detection

Proteomic analysis of extracellular vesicles presents several challenges due to the unique nature of these small membrane-bound structures. Alternative analyses could reveal outcomes hidden from standard statistics to explore and develop potential new biological hypotheses that may have been overlooked during the initial evaluation of the data. An analysis sequence focusing on deviating protein expressions from donors' primary cells was performed, leveraging machine-learning techniques to analyze small datasets, and it has been applied to evaluate extracellular vesicles' protein content gathered from mesenchymal stem cells cultured on bioactive glass discs doped or not with metal ions. The goal was to provide additional opportunities for detecting details between experimental conditions that are not entirely revealed with classic statistical inference, offering further insights regarding the experimental design and assisting the researchers in interpreting the outcomes. The methodology extracted a set of EV-related proteins whose differences between conditions could be partially explainable with statistics, suggesting the presence of other factors involved in the bioactive glasses' interactions with tissues. Outlier identification of extracellular vesicles' protein expression levels related to biomaterial preparation was instrumental in improving the interpretation of the experimental outcomes.

IL-17 induces NSCLC cell migration and invasion by elevating MMP19 gene transcription and expression through the interaction of p300-dependent STAT3-K631 acetylation and its Y705-phosphorylation

The cancer cell metastasis is a major death reason for patients with non-small cell lung cancer (NSCLC). Although researchers have disclosed that interleukin 17 (IL-17) can increase matrix metalloproteinases (MMPs) induction causing NSCLC cell metastasis, the underlying mechanism remains unclear. In the study, we found that IL-17 receptor A (IL-17RA), p300, p-STAT3, Ack-STAT3, and MMP19 were up-regulated both in NSCLC tissues and NSCLC cells stimulated with IL-17. p300, STAT3 and MMP19 overexpression or knockdown could raise or reduce IL-17-induced p-STAT3, Ack-STAT3 and MMP19 level as well as the cell migration and invasion. Mechanism investigation revealed that STAT3 and p300 bound to the same region (-544 to -389 nt) of MMP19 promoter, and p300 could acetylate STAT3-K631 elevating STAT3 transcriptional activity, p-STAT3 or MMP19 expression and the cell mobility exposed to IL-17. Meanwhile, p300-mediated STAT3-K631 acetylation and its Y705-phosphorylation could interact, synergistically facilitating MMP19 gene transcription and enhancing cell migration and invasion. Besides, the animal experiments exhibited that the nude mice inoculated with NSCLC cells by silencing p300, STAT3 or MMP19 gene plus IL-17 treatment, the nodule number, and MMP19, Ack-STAT3, or p-STAT3 production in the lung metastatic nodules were all alleviated. Collectively, these outcomes uncover that IL-17-triggered NSCLC metastasis involves up-regulating MMP19 expression via the interaction of STAT3-K631 acetylation by p300 and its Y705-phosphorylation, which provides a new mechanistic insight and potential strategy for NSCLC metastasis and therapy.

Proteomics Applications in Toxoplasma gondii: Unveiling the Host-Parasite Interactions and Therapeutic Target Discovery

Toxoplasma gondii, a protozoan parasite with the ability to infect various warm-blooded vertebrates, including humans, is the causative agent of toxoplasmosis. This infection poses significant risks, leading to severe complications in immunocompromised individuals and potentially affecting the fetus through congenital transmission. A comprehensive understanding of the intricate molecular interactions between T. gondii and its host is pivotal for the development of effective therapeutic strategies. This review emphasizes the crucial role of proteomics in T. gondii research, with a specific focus on host-parasite interactions, post-translational modifications (PTMs), PTM crosstalk, and ongoing efforts in drug discovery. Additionally, we provide an overview of recent advancements in proteomics techniques, encompassing interactome sample preparation methods such as BioID (BirA*-mediated proximity-dependent biotin identification), APEX (ascorbate peroxidase-mediated proximity labeling), and Y2H (yeast two hybrid), as well as various proteomics approaches, including single-cell analysis, DIA (data-independent acquisition), targeted, top-down, and plasma proteomics. Furthermore, we discuss bioinformatics and the integration of proteomics with other omics technologies, highlighting its potential in unraveling the intricate mechanisms of T. gondii pathogenesis and identifying novel therapeutic targets.

Unraveling the battle for lysine: A review of the competition among post-translational modifications

Proteins play a critical role as key regulators in various biological systems, influencing crucial processes such as gene expression, cell cycle progression, and cellular proliferation. However, the functions of proteins can be further modified through post-translational modifications (PTMs), which expand their roles and contribute to disease progression when dysregulated. In this review, we delve into the methodologies employed for the characterization of PTMs, shedding light on the techniques and tools utilized to help unravel their complexity. Furthermore, we explore the prevalence of crosstalk and competition that occurs between different types of PTMs, specifically focusing on both histone and non-histone proteins. The intricate interplay between different modifications adds an additional layer of regulation to protein function and cellular processes. To gain insights into the competition for lysine residues among various modifications, computational systems such as MethylSight have been developed, allowing for a comprehensive analysis of the modification landscape. Additionally, we provide an overview of the exciting developments in the field of inhibitors or drugs targeting PTMs, highlighting their potential in combatting prevalent diseases. The discovery and development of drugs that modulate PTMs present promising avenues for therapeutic interventions, offering new strategies to address complex diseases. As research progresses in this rapidly evolving field, we anticipate remarkable advancements in our understanding of PTMs and their roles in health and disease, ultimately paving the way for innovative treatment approaches.

Network models of protein phosphorylation, acetylation, and ubiquitination connect metabolic and cell signaling pathways in lung cancer

We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy.

Lactoferrin suppresses the progression of colon cancer under hyperglycemia by targeting WTAP/m6A/NT5DC3/HKDC1 axis

BACKGROUND

Although the relationship between type 2 diabetes (T2D) and the increased risk of colorectal carcinogenesis is widely defined in clinical studies, the therapeutic methods and molecular mechanism of T2D-induced colon cancer and how does hyperglycemia affect the progression is still unknown. Here, we studied the function of lactoferrin (LF) in suppressing the progression of colon cancer in T2D mice, and uncovered the related molecular mechanisms in DNA 5mC and RNA m6A levels.

METHODS

We examined the effects of LF (50% iron saturation) on the migration and invasion of colon tumor cells under high concentration of glucose. Then, transcriptomics and DNA methylation profilings of colon tumor cells was co-analyzed to screen out the special gene (NT5DC3), and the expression level of NT5DC3 in 75 clinical blood samples was detected by q-PCR and western blot, to investigate whether NT5DC3 was a biomarker to distinguish T2D patients and T2D-induced colon cancer patients from healthy volunteers. Futhermore, in T2D mouse with xenografted colon tumor models, the inhibitory effects of LF and NT5DC3 protein on colon tumors were investigated. In addition, epigenetic alterations were measured to examine the 5mC/m6A modification sites of NT5DC3 regulated by LF. Utilizing siRNA fragments of eight m6A-related genes, the special gene (WTAP) regulating m6A of NT5DC was proved, and the effect of LF on WTAP/NT5DC3/HKDC1 axis was finally evaluated.

RESULTS

A special gene NT5DC3 was screened out through co-analysis of transcriptomics and DNA methylation profiling, and HKDC1 might be a downstream sensor of NT5DC3. Mechanistically, LF-dependent cellular DNA 5mC and RNA m6A profiling remodeling transcriptionally regulate NT5DC3 expression. WTAP plays a key role in regulating NT5DC3 m6A modification and subsequently controls NT5DC3 downstream target HKDC1 expression. Moreover, co-treatment of lactoferrin and NT5DC3 protein restrains the growth of colon tumors by altering the aberrant epigenetic markers. Strikingly, clinical blood samples analysis demonstrates NT5DC3 protein expression is required to direct the distinction of T2D or T2D-induced colon cancer with healthy humans.

CONCLUSIONS

Together, this study reveals that lactoferrin acts as a major factor to repress the progression of colon cancer under hyperglycemia, thus, significantly expanding the landscape of natural dietary mediated tumor suppression.

Control of protein stability by post-translational modifications

Post-translational modifications (PTMs) can occur on specific amino acids localized within regulatory domains of target proteins, which control a protein's stability. These regions, called degrons, are often controlled by PTMs, which act as signals to expedite protein degradation (PTM-activated degrons) or to forestall degradation and stabilize a protein (PTM-inactivated degrons). We summarize current knowledge of the regulation of protein stability by various PTMs. We aim to display the variety and breadth of known mechanisms of regulation as well as highlight common themes in PTM-regulated degrons to enhance potential for identifying novel drug targets where druggable targets are currently lacking.

qPTM: an updated database for PTM dynamics in human, mouse, rat and yeast

Post-translational modifications (PTMs) are critical molecular mechanisms that regulate protein functions temporally and spatially in various organisms. Since most PTMs are dynamically regulated, quantifying PTM events under different states is crucial for understanding biological processes and diseases. With the rapid development of high-throughput proteomics technologies, massive quantitative PTM proteome datasets have been generated. Thus, a comprehensive one-stop data resource for surfing big data will benefit the community. Here, we updated our previous phosphorylation dynamics database qPhos to the qPTM (http://qptm.omicsbio.info). In qPTM, 11 482 553 quantification events among six types of PTMs, including phosphorylation, acetylation, glycosylation, methylation, SUMOylation and ubiquitylation in four different organisms were collected and integrated, and the matched proteome datasets were included if available. The raw mass spectrometry based false discovery rate control and the recurrences of identifications among datasets were integrated into a scoring system to assess the reliability of the PTM sites. Browse and search functions were improved to facilitate users in swiftly and accurately acquiring specific information. The results page was revised with more abundant annotations, and time-course dynamics data were visualized in trend lines. We expected the qPTM database to be a much more powerful and comprehensive data repository for the PTM research community.

Fourier-transform ion cyclotron resonance mass spectrometry for characterizing proteoforms

Proteoforms contribute functional diversity to the proteome and aberrant proteoforms levels have been implicated in biological dysfunction and disease. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), with its ultrahigh mass-resolving power, mass accuracy, and versatile tandem MS capabilities, has empowered top-down, middle-down, and native MS-based approaches for characterizing proteoforms and their complexes in biological systems. Herein, we review the features which make FT-ICR MS uniquely suited for measuring proteoform mass with ultrahigh resolution and mass accuracy; obtaining in-depth proteoform sequence coverage with expansive tandem MS capabilities; and unambiguously identifying and localizing post-translational and noncovalent modifications. We highlight examples from our body of work in which we have quantified and comprehensively characterized proteoforms from cardiac and skeletal muscle to better understand conditions such as chronic heart failure, acute myocardial infarction, and sarcopenia. Structural characterization of monoclonal antibodies and their proteoforms by FT-ICR MS and emerging applications, such as native top-down FT-ICR MS and high-throughput top-down FT-ICR MS-based proteomics at 21 T, are also covered. Historically, the information gleaned from FT-ICR MS analyses have helped provide biological insights. We predict FT-ICR MS will continue to enable the study of proteoforms of increasing size from increasingly complex endogenous mixtures and facilitate the benchmarking of sensitive and specific assays for clinical diagnostics. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Optimal regulation of tumour-associated neutrophils in cancer progression

In a tumour microenvironment, tumour-associated neutrophils could display two opposing differential phenotypes: anti-tumour (N1) and pro-tumour (N2) effector cells. Converting N2 to N1 neutrophils provides innovative therapies for cancer treatment. In this study, a mathematical model for N1-N2 dynamics describing the cancer survival and immune inhibition in response to TGF-β and IFN-β is considered. The effects of exogenous intervention of TGF-β inhibitor and IFN-β are examined in order to enhance N1 recruitment to combat tumour progression. Our approach employs optimal control theory to determine drug infusion protocols that could minimize tumour volume with least administration cost possible. Four optimal control scenarios corresponding to different therapeutic strategies are explored, namely, TGF-β inhibitor control only, IFN-β control only, concomitant TGF-β inhibitor and IFN-β controls, and alternating TGF-β inhibitor and IFN-β controls. For each scheme, different initial conditions are varied to depict different pathophysiological condition of a cancer patient, leading to adaptive treatment schedule. TGF-β inhibitor and IFN-β drug dosages, total drug amount, infusion times and relative cost of drug administrations are obtained under various circumstances. The control strategies achieved could guide in designing individualized therapeutic protocols.

Hsp90 interaction networks in fungi-tools and techniques

Heat-shock protein 90 (Hsp90) is a central regulator of cellular proteostasis. It stabilizes numerous proteins that are involved in fundamental processes of life, including cell growth, cell-cycle progression and the environmental response. In addition to stabilizing proteins, Hsp90 governs gene expression and controls the release of cryptic genetic variation. Given its central role in evolution and development, it is important to identify proteins and genes that interact with Hsp90. This requires sophisticated genetic and biochemical tools, including extensive mutant collections, suitable epitope tags, proteomics approaches and Hsp90-specific pharmacological inhibitors for chemogenomic screens. These usually only exist in model organisms, such as the yeast Saccharomyces cerevisiae. Yet, the importance of other fungal species, such as Candida albicans and Cryptococcus neoformans, as serious human pathogens accelerated the development of genetic tools to study their virulence and stress response pathways. These tools can also be exploited to map Hsp90 interaction networks. Here, we review tools and techniques for Hsp90 network mapping available in different fungi and provide a summary of existing mapping efforts. Mapping Hsp90 networks in fungal species spanning >500 million years of evolution provides a unique vantage point, allowing tracking of the evolutionary history of eukaryotic Hsp90 networks.

Affinity capture in bottom-up protein analysis - Overview of current status of proteolytic peptide capture using antibodies and molecularly imprinted polymers

Antibody-based affinity capture has become the gold standard in sample preparation for determination of low-abundance protein biomarkers in biological matrices prior to liquid chromatography-mass spectrometry (LC-MS) determination. This comprises both capture of intact proteins prior to the digestion step and capture of proteolytic peptides after digestion of the sample. The latter can be performed both using antibodies specifically developed to capture target proteolytic peptides, as well as by the less explored use of anti-protein antibodies to capture the proteolytic epitope peptide. Molecularly imprinted polymers (MIPs), also called plastic antibodies are another affinity-based approach emerging as sample preparation technique in LC-MS based protein biomarker analysis. The current review gives a critical and comprehensive overview of proteolytic peptide capture using antibodies and MIPs in LC-MS based protein biomarker determination during the last five years. The main emphasis is on capture of non-modified peptides, while a brief overview of affinity capture of peptides containing post-translational modifications (PTMs) is provided.

Altered Protein Abundance and Localization Inferred from Sites of Alternative Modification by Ubiquitin and SUMO

Protein modification by ubiquitin or SUMO can alter the function, stability or activity of target proteins. Previous studies have identified thousands of substrates that were modified by ubiquitin or SUMO on the same lysine residue. However, it remains unclear whether such overlap could result from a mere higher solvent accessibility, whether proteins containing those sites are associated with specific functional traits, and whether selectively perturbing their modification by ubiquitin or SUMO could result in different phenotypic outcomes. Here, we mapped reported lysine modification sites across the human proteome and found an enrichment of sites reported to be modified by both ubiquitin and SUMO. Our analysis uncovered thousands of proteins containing such sites, which we term Sites of Alternative Modification (SAMs). Among more than 36,000 sites reported to be modified by SUMO, 51.8% have also been reported to be modified by ubiquitin. SAM-containing proteins are associated with diverse biological functions including cell cycle, DNA damage, and transcriptional regulation. As such, our analysis highlights numerous proteins and pathways as putative targets for further elucidating the crosstalk between ubiquitin and SUMO. Comparing the biological and biochemical properties of SAMs versus other non-overlapping modification sites revealed that these sites were associated with altered cellular localization or abundance of their host proteins. Lastly, using S. cerevisiae as model, we show that mutating the SAM motif in a protein can influence its ubiquitination as well as its localization and abundance.

The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

Co-occurrence of Protein Crotonylation and 2-Hydroxyisobutyrylation in the Proteome of End-Stage Renal Disease

End-stage renal disease (ESRD) is gradually becoming a major public healthcare burden worldwide. Post-translational modifications carrying epigenetic information play a crucial role in the pathogenesis of many chronic diseases. We performed lysine crotonylation (KCr) and lysine 2-hydroxyisobutyrylation (Khib) analyses with liquid chromatography-tandem mass spectrometry to obtain a comprehensive profile and reveal the specific pathogenesis of peripheral blood mononuclear cells in ESRD patients. 218 overlap proteins among differentially modified proteins (DMPs) of both 2-hydroxyisobutyrylation and crotonylation were identified. KEGG analysis enriched pathways of protein processing in endoplasmic reticulum (ER) and glycolysis/gluconeogenesis which is closely related with cell apoptosis. In Bip, a master regulator in the ER, eight sites were identified as having both KCr and Khib modifications. Five differentially KCr modification sites and three differentially Khib-modified sites were detected between ESRD patients and normal controls. Besides Bip, other proteins (GRP94, CNX, CRT, PDIs, GlcII, ERP57, Bap31, Hsp70, and Hsp90) happened both KCr and Khib modifications. Nine DMPs having both KCr and Khib modifications were related to the glycolysis/gluconeogenesis pathway containing two key regulatory enzymes of hexokinase-1 and pyruvate kinase. The two most abundant dual modification proteins were ENO1 and PGK1 with 15 sites and 8 sites, respectively. Lysine residue K228 with both KCr and Khib modifications in ENO1 was on its surface and made it accessible for p300 mediating dynamic modifications. Overall, we hypothesize that KCr and Khib comodifications may influence the number of immunocytes and further induce immune senescence in ESRD patients through the glycolysis/gluconeogenesis pathway and protein processing in the ER process, which may be a potential therapeutic direction in the future.

Counterion Optimization Dramatically Improves Selectivity for Phosphopeptides and Glycopeptides in Electrostatic Repulsion-Hydrophilic Interaction Chromatography

A well-hydrated counterion can selectively and dramatically increase retention of a charged analyte in hydrophilic interaction chromatography. The effect is enhanced if the column is charged, as in electrostatic repulsion-hydrophilic interaction chromatography (ERLIC). This combination was exploited in proteomics for the isolation of peptides with certain post-translational modifications (PTMs). The best salt additive examined was magnesium trifluoroacetate. The well-hydrated Mg⁺² ion promoted retention of peptides with functional groups that retained negative charge at low pH, while the poorly hydrated trifluoroacetate counterion tuned down the retention due to the basic residues. The result was an enhancement in selectivity ranging from 6- to 66-fold. These conditions were applied to a tryptic digest of mouse cortex. Gradient elution produced fractions enriched in peptides with phosphate, mannose-6-phosphate, and N- and O-linked glycans. The numbers of such peptides identified either equaled or exceeded the numbers afforded by the best alternative methods. This method is a productive and convenient way to isolate peptides simultaneously that contain a number of different PTMs, facilitating study of proteins with "crosstalk" modifications. The fractions from the ERLIC column were desalted prior to C-18-reversed phase liquid chromatography-tandem mass spectrometry analysis. Between 47-100% of the peptides with more than one phosphate or sialyl residue or with a mannose-6 phosphate group were not retained by a C-18 cartridge but were retained by a cartridge of porous graphitic carbon. This finding implies that the abundance of such peptides may have been significantly underestimated in some past studies.

The emerging role of cellular post-translational modifications in modulating growth and productivity of recombinant Chinese hamster ovary cells

Chinese hamster ovary (CHO) cells are one of the most commonly used host cell lines used for the production human therapeutic proteins. Much research over the past two decades has focussed on improving the growth, titre and cell specific productivity of CHO cells and in turn lowering the costs associated with production of recombinant proteins. CHO cell engineering has become of particular interest in recent years following the publication of the CHO cell genome and the availability of data relating to the proteome, transcriptome and metabolome of CHO cells. However, data relating to the cellular post-translational modification (PTMs) which can affect the functionality of CHO cellular proteins has only begun to be presented in recent years. PTMs are important to many cellular processes and can further alter proteins by increasing the complexity of proteins and their interactions. In this review, we describe the research presented from CHO cells to date related on three of the most important PTMs; glycosylation, phosphorylation and ubiquitination.

Proteomics-based interrogation of the kinome and its implications for precision oncology

The identification of specific protein kinases as oncogenic drivers in a variety of cancer types, coupled with the clinical success of particular kinase-directed targeted therapies, has cemented the human kinome as an attractive source of "actionable" targets for cancer therapy. However, "mining" of the human kinome for precision oncology applications has yet to yield its full potential. This reflects a variety of issues, including oncogenic kinase dysregulation at levels not detectable by genomic sequencing and the uncharacterized nature of a considerable fraction of the kinome. In addition, selective therapeutic targeting of specific kinases requires efficient mapping of total kinome space impacted by candidate small molecule drugs. Fortunately, recent developments in proteomics techniques, particularly in mass spectrometry-based phosphoproteomics and kinomics, provide the necessary technology platforms to address these impediments. Moreover, initiatives such as the Clinical Proteomic Tumour Analysis Consortium have enabled the generation, deposition and integration of genomic, transcriptomic and (phospho)proteomic data for many cancer types, providing unprecedented insights into oncogenic kinases and cancer cell signalling generally. These multi-omic data are identifying novel therapeutic targets, highlighting opportunities for drug re-purposing, and helping assign optimal therapies to specific tumour subtypes, heralding a new era of "enhanced" precision oncology.

Histone Deacetylase Inhibitors as Multitarget-Directed Epi-Drugs in Blocking PI3K Oncogenic Signaling: A Polypharmacology Approach

Genetic mutations and aberrant epigenetic alterations are the triggers for carcinogenesis. The emergence of the drugs targeting epigenetic aberrations has provided a better outlook for cancer treatment. Histone deacetylases (HDACs) are epigenetic modifiers playing critical roles in numerous key biological functions. Inappropriate expression of HDACs and dysregulation of PI3K signaling pathway are common aberrations observed in human diseases, particularly in cancers. Histone deacetylase inhibitors (HDACIs) are a class of epigenetic small-molecular therapeutics exhibiting promising applications in the treatment of hematological and solid malignancies, and in non-neoplastic diseases. Although HDACIs as single agents exhibit synergy by inhibiting HDAC and the PI3K pathway, resistance to HDACIs is frequently encountered due to activation of compensatory survival pathway. Targeted simultaneous inhibition of both HDACs and PI3Ks with their respective inhibitors in combination displayed synergistic therapeutic efficacy and encouraged the development of a single HDAC-PI3K hybrid molecule via polypharmacology strategy. This review provides an overview of HDACs and the evolution of HDACs-based epigenetic therapeutic approaches targeting the PI3K pathway.

PAG1 directs SRC-family kinase intracellular localization to mediate receptor tyrosine kinase-induced differentiation

All receptor tyrosine kinases (RTKs) activate similar downstream signaling pathways through a common set of effectors, yet it is not fully understood how different receptors elicit distinct cellular responses to cause cell proliferation, differentiation, or other cell fates. We tested the hypothesis that regulation of SRC family kinase (SFK) signaling by the scaffold protein, PAG1, influences cell fate decisions following RTK activation. We generated a neuroblastoma cell line expressing a PAG1 fragment that lacks the membrane-spanning domain (PAG1TM-) and localized to the cytoplasm. PAG1TM- cells exhibited higher amounts of active SFKs and increased growth rate. PAG1TM- cells were unresponsive to TRKA and RET signaling, two RTKs that induce neuronal differentiation, but retained responses to EGFR and KIT. Under differentiation conditions, PAG1TM- cells continued to proliferate and did not extend neurites or increase β-III tubulin expression. FYN and LYN were sequestered in multivesicular bodies (MVBs), and dramatically more FYN and LYN were in the lumen of MVBs in PAG1TM- cells. In particular, activated FYN was sequestered in PAG1TM- cells, suggesting that disruption of FYN localization led to the observed defects in differentiation. The results demonstrate that PAG1 directs SFK intracellular localization to control activity and to mediate signaling by RTKs that induce neuronal differentiation.

ERK Dephosphorylation through MKP1 Deacetylation by SIRT1 Attenuates RAS-Driven Tumorigenesis

The role of Situin 1 (SIRT1) in tumorigenesis is still controversial due to its wide range of substrates, including both oncoproteins and tumor suppressors. A recent study has demonstrated that SIRT1 interferes in the Kirsten rat sarcoma viral oncogene homolog (KRAS)-driven activation of the Raf-mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) kinase (MEK)-ERK pathway, thereby inhibiting tumorigenesis. However, the molecular mechanism of SIRT1 as a tumor suppressor in RAS-driven tumorigenesis has been less clearly determined. This study presents evidence that the ectopic expression of SIRT1 attenuates RAS- or MEK-driven ERK activation and reduces cellular proliferation and transformation in vitro. The attenuation of ERK activation by SIRT1 results from prompt dephosphorylation of ERK, while MEK activity remains unchanged. We identified that MKP1, a dual specific phosphatase for MAPK, was deacetylated by SIRT1. Deacetylation of MKP1 by direct interaction with SIRT1 increased the binding affinity to ERK which in turn facilitated inactivation of ERK. Taken together, these results suggest that SIRT1 would act as a tumor suppressor by modulating RAS-driven ERK activity through MKP1 deacetylation.

A computational framework for a Lyapunov-enabled analysis of biochemical reaction networks

Complex molecular biological processes such as transcription and translation, signal transduction, post-translational modification cascades, and metabolic pathways can be described in principle by biochemical reactions that explicitly take into account the sophisticated network of chemical interactions regulating cell life. The ability to deduce the possible qualitative behaviors of such networks from a set of reactions is a central objective and an ongoing challenge in the field of systems biology. Unfortunately, the construction of complete mathematical models is often hindered by a pervasive problem: despite the wealth of qualitative graphical knowledge about network interactions, the form of the governing nonlinearities and/or the values of kinetic constants are hard to uncover experimentally. The kinetics can also change with environmental variations. This work addresses the following question: given a set of reactions and without assuming a particular form for the kinetics, what can we say about the asymptotic behavior of the network? Specifically, it introduces a class of networks that are "structurally (mono) attractive" meaning that they are incapable of exhibiting multiple steady states, oscillation, or chaos by virtue of their reaction graphs. These networks are characterized by the existence of a universal energy-like function called a Robust Lyapunov function (RLF). To find such functions, a finite set of rank-one linear systems is introduced, which form the extremals of a linear convex cone. The problem is then reduced to that of finding a common Lyapunov function for this set of extremals. Based on this characterization, a computational package, Lyapunov-Enabled Analysis of Reaction Networks (LEARN), is provided that constructs such functions or rules out their existence. An extensive study of biochemical networks demonstrates that LEARN offers a new unified framework. Basic motifs, three-body binding, and genetic networks are studied first. The work then focuses on cellular signalling networks including various post-translational modification cascades, phosphotransfer and phosphorelay networks, T-cell kinetic proofreading, and ERK signalling. The Ribosome Flow Model is also studied.

Pathway Commons 2019 Update: integration, analysis and exploration of pathway data

Pathway Commons (https://www.pathwaycommons.org) is an integrated resource of publicly available information about biological pathways including biochemical reactions, assembly of biomolecular complexes, transport and catalysis events and physical interactions involving proteins, DNA, RNA, and small molecules (e.g. metabolites and drug compounds). Data is collected from multiple providers in standard formats, including the Biological Pathway Exchange (BioPAX) language and the Proteomics Standards Initiative Molecular Interactions format, and then integrated. Pathway Commons provides biologists with (i) tools to search this comprehensive resource, (ii) a download site offering integrated bulk sets of pathway data (e.g. tables of interactions and gene sets), (iii) reusable software libraries for working with pathway information in several programming languages (Java, R, Python and Javascript) and (iv) a web service for programmatically querying the entire dataset. Visualization of pathways is supported using the Systems Biological Graphical Notation (SBGN). Pathway Commons currently contains data from 22 databases with 4794 detailed human biochemical processes (i.e. pathways) and ∼2.3 million interactions. To enhance the usability of this large resource for end-users, we develop and maintain interactive web applications and training materials that enable pathway exploration and advanced analysis.

Microarray-assisted size-effect study of amorphous silica nanoparticles on human bronchial epithelial cells

Amorphous silica nanoparticles (SiNPs) are not only abundant in nature, but also the second largest engineering nanomaterials in terms of annual output. Respiratory exposure is the main route for SiNPs to enter the human body. A large number of studies have focused on the respiratory toxicity of SiNPs and demonstrated that SiNPs could induce pulmonary tissue damage, inflammation, fibrosis, and even the malignant transformation of bronchial epithelial cells, while the size-dependent toxicity of SiNPs and their underlying biological mechanisms remain unclear. In this regard, a transcriptomics study would be conductive to gaining a better understanding of the toxic mechanism. In the present study, microarray analysis was performed to investigate the genome-wide transcriptional alteration induced by different sizes of SiNPs in human primary bronchial epithelial cells (BEAS-2B). To determine the effect of the particle size on the toxicity, nanoparticles of two sizes (41 nm and 61 nm) and submicron particles of one size (206 nm) were introduced. The bioinformatics analysis results indicated that: (1) the number of differentially expressed genes in the three SiNP-treated groups increased with the particle size decreasing; (2) the genes involved in the immune and inflammatory response, gene expression, signal transduction, endoplasmic reticulum stress, oxidative stress, cell metabolism, and cell proliferation were gradually upregulated with the particle size decreasing, while the genes related to the morphological development of the respiratory system were gradually downregulated with the particle size decreasing; (3) the modes of action of the two nanoparticles overlapped with each other to some degree, and there existed many different modes compared to those from the submicron particles; (4) both the silica nanoparticles affected the pathways associated with the cell entry of silica nanoparticles, autophagy and lysosomal dysfunction, endoplasmic reticulum stress, inflammatory response, DNA damage, and gene expression, as well as apoptotic resistance and cancer. To the best of our knowledge, this is the first study that has reported the alteration trend of gene expression profiles with the change in silica particle size. Our study provides a great deal of information on the toxic mechanisms underlying the respiratory toxicity induced by SiNPs, and can also serve as an experimental basis for the toxicity and safety evaluation of silica nanoparticles.

Activation of Src mediates acquired cisplatin resistance in human lung carcinoma cells

Cisplatin (CDDP) is the most effective chemotherapeutic drug against lung carcinoma. However, the emergence of resistant clones has severely limited its clinical application. We found that the cisplatin-resistant lung carcinoma cell line A549/CDDP had increased levels of the phosphorylated gap junction protein Cx43 and SRC tyrosine kinase, and low levels of total Cx43 protein and reduced gap junction formation. The SRC kinase inhibitor PP2 increased the expression of total Cx43 protein and enhanced cisplatin sensitivity, indicating that activated SRC kinase induces chemoresistance by decrease total Cx43 level. Furthermore, Cx43 gene silencing in the drug-resistant cell lines abrogated the sensitizing effect of PP2. Taken together, targeting SRC kinase by PP2 reverses cisplatin resistance by upregulating Cx43 protein levels, indicating a novel pathway of cisplatin resistance that may be amenable to therapeutic intervention.

Comprehensive Characterization of the Recombinant Catalytic Subunit of cAMP-Dependent Protein Kinase by Top-Down Mass Spectrometry

Reversible phosphorylation plays critical roles in cell growth, division, and signal transduction. Kinases which catalyze the transfer of γ-phosphate groups of nucleotide triphosphates to their substrates are central to the regulation of protein phosphorylation and are therefore important therapeutic targets. Top-down mass spectrometry (MS) presents unique opportunities to study protein kinases owing to its capabilities in comprehensive characterization of proteoforms that arise from alternative splicing, sequence variations, and post-translational modifications. Here, for the first time, we developed a top-down MS method to characterize the catalytic subunit (C-subunit) of an important kinase, cAMP-dependent protein kinase (PKA). The recombinant PKA C-subunit was expressed in Escherichia coli and successfully purified via his-tag affinity purification. By intact mass analysis with high resolution and high accuracy, four different proteoforms of the affinity-purified PKA C-subunit were detected, and the most abundant proteoform was found containing seven phosphorylations with the removal of N-terminal methionine. Subsequently, the seven phosphorylation sites of the most abundant PKA C-subunit proteoform were characterized simultaneously using tandem MS methods. Four sites were unambiguously identified as Ser10, Ser11, Ser18, and Ser30, and the remaining phosphorylation sites were localized to Ser2/Ser3, Ser358/Thr368, and Thr[215-224]Tyr in the PKA C-subunit sequence with a 20mer 6xHis-tag added at the N-terminus. Interestingly, four of these seven phosphorylation sites were located at the 6xHis-tag. Furthermore, we have performed dephosphorylation reaction by Lambda protein phosphatase and showed that all phosphorylations of the recombinant PKA C-subunit phosphoproteoforms were removed by this phosphatase.

Spa-RQ: an Image Analysis Tool to Visualise and Quantify Spatial Phenotypes Applied to Non-Small Cell Lung Cancer

To facilitate analysis of spatial tissue phenotypes, we created an open-source tool package named ‘Spa-RQ’ for ‘Spatial tissue analysis: image Registration & Quantification’. Spa-RQ contains software for image registration (Spa-R) and quantitative analysis of DAB staining overlap (Spa-Q). It provides an easy-to-implement workflow for serial sectioning and staining as an alternative to multiplexed techniques. To demonstrate Spa-RQ’s applicability, we analysed the spatial aspects of oncogenic KRAS-related signalling activities in non-small cell lung cancer (NSCLC). Using Spa-R in conjunction with ImageJ/Fiji, we first performed annotation-guided tumour-by-tumour phenotyping using multiple signalling markers. This analysis showed histopathology-selective activation of PI3K/AKT and MAPK signalling in Kras mutant murine tumours, as well as high p38MAPK stress signalling in p53 null murine NSCLC. Subsequently, Spa-RQ was applied to measure the co-activation of MAPK, AKT, and their mutual effector mTOR pathway in individual tumours. Both murine and clinical NSCLC samples could be stratified into ‘MAPK/mTOR’, ‘AKT/mTOR’, and ‘Null’ signature subclasses, suggesting mutually exclusive MAPK and AKT signalling activities. Spa-RQ thus provides a robust and easy to use tool that can be employed to identify spatially-distributed tissue phenotypes.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

Protein Post-Translational Modification Crosstalk in Acute Myeloid Leukemia Calls for Action

BACKGROUND

Post-translational modification (PTM) crosstalk is a young research field. However, there is now evidence of the extraordinary characterization of the different proteoforms and their interactions in a biological environment that PTM crosstalk studies can describe. Besides gene expression and phosphorylation profiling of acute myeloid leukemia (AML) samples, the functional combination of several PTMs that might contribute to a better understanding of the complexity of the AML proteome remains to be discovered.

OBJECTIVE

By reviewing current workflows for the simultaneous enrichment of several PTMs and bioinformatics tools to analyze mass spectrometry (MS)-based data, our major objective is to introduce the PTM crosstalk field to the AML research community.

RESULTS

After an introduction to PTMs and PTM crosstalk, this review introduces several protocols for the simultaneous enrichment of PTMs. Two of them allow a simultaneous enrichment of at least three PTMs when using 0.5-2 mg of cell lysate. We have reviewed many of the bioinformatics tools used for PTM crosstalk discovery as its complex data analysis, mainly generated from MS, becomes challenging for most AML researchers. We have presented several non-AML PTM crosstalk studies throughout the review in order to show how important the characterization of PTM crosstalk becomes for the selection of disease biomarkers and therapeutic targets.

CONCLUSION

Herein, we have reviewed the advances and pitfalls of the emerging PTM crosstalk field and its potential contribution to unravel the heterogeneity of AML. The complexity of sample preparation and bioinformatics workflows demands a good interaction between experts of several areas.

Identification, Quantification, and System Analysis of Protein N-ε Lysine Methylation in Anucleate Blood Platelets

Protein posttranslational modifications critically regulate a range of physiological and disease processes. In addition to tyrosine, serine, and threonine phosphorylation, reversible N-ε acylation and alkylation of protein lysine residues also modulate diverse aspects of cellular function. Studies of lysine acyl and alkyl modifications have focused on nuclear proteins in epigenetic regulation; however, lysine modifications are also prevalent on cytosolic proteins to serve increasingly apparent, although less understood roles in cell regulation. Here, the methyl-lysine (meK) proteome of anucleate blood platelets is characterized. With high-resolution, multiplex MS methods, 190 mono-, di-, and tri-meK modifications are identified on 150 different platelet proteins-including 28 meK modifications quantified by tandem mass tag (TMT) labeling. In addition to identifying meK modifications on calmodulin (CaM), GRP78 (HSPA5, BiP), and EF1A1 that have been previously characterized in other cell types, more novel modifications are also uncovered on cofilin, drebin-like protein (DBNL, Hip-55), DOCK8, TRIM25, and numerous other cytoplasmic proteins. Together, the results and analyses support roles for lysine methylation in mediating cytoskeletal, translational, secretory, and other cellular processes. MS data for this study have been deposited into the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD012217.

Role of tumor-associated neutrophils in regulation of tumor growth in lung cancer development: A mathematical model

Neutrophils display rapid and potent innate immune responses in various diseases. Tumor-associated neutrophils (TANs) however either induce or overcome immunosuppressive functions of the tumor microenvironment through complex tumor-stroma crosstalk. We developed a mathematical model to address the question of how phenotypic alterations between tumor suppressive N1 TANS, and tumor promoting N2 TANs affect nonlinear tumor growth in a complex tumor microenvironment. The model provides a visual display of the complex behavior of populations of TANs and tumors in response to various TGF-β and IFN-β stimuli. In addition, the effect of anti-tumor drug administration is incorporated in the model in an effort to achieve optimal anti-tumor efficacy. The simulation results from the mathematical model were in good agreement with experimental data. We found that the N2-to-N1 ratio (N21R) index is positively correlated with aggressive tumor growth, suggesting that this may be a good prognostic factor. We also found that the antitumor efficacy increases when the relative ratio (Dap) of delayed apoptotic cell death of N1 and N2 TANs is either very small or relatively large, providing a basis for therapeutically targeting prometastatic N2 TANs.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

Mass spectrometry and DigiWest technology emphasize protein acetylation profile from Quisinostat-treated HuT78 CTCL cell line

Histone deacetylases (HDACs) are key enzymes involved in epigenetic modulation and were targeted by HDAC inhibitors (HDACis) for cancer treatment. The action of HDACis is not restricted to histones and also prevents deacetylation of other proteins, supporting their wide biological actions. The HuT78 cell line is recognized as a key tool to support and understand cutaneous T-cell lymphoma (CTCL) biology and was used as a predictive model since HDACi such as Vorinostat and Panobinostat have both demonstrated apoptotic activities in HuT78 cells and in primary blood CTCL cells. In this study, Quisinostat (JNJ-26481585) a novel second-generation HDACi with highest potency for HDAC1, was tested on HuT78 cell line. Quantitative mass spectrometry (MS)-based proteomics after acetylated-lysine peptide enrichment and a targeted antibody-based immunoassay (DigiWest) were used as complementary technologies to assess the modifications of the acetylated proteome. As expected, several acetylated lysines of histones were increased by the HDACi. Additional acetylated non-histone proteins were modulated after treatment with Quisinostat including the nucleolin (a major nucleolar protein), the replication protein A 70 kDa DNA-binding subunit, the phosphoglycerate kinase 1, the stress-70 protein, the proto-oncogene Myc and the serine hydroxymethyltransferase. A better knowledge of histone and non-histone acetylated protein profile after Quisinostat treatment can strongly support the understanding of non-clinical and clinical results of this HDACi. These technological tools can also help in designing new HDACis in a pharmaceutical drug discovery program.

SIGNIFICANCE

A better knowledge of histone and non-histone acetylated protein profile after HDAC inhibitors (HDACis) treatment can strongly support the understanding of non-clinical and clinical investigations in a pharmaceutical drug discovery program. Relative quantification using mass spectrometry -based proteomics after acetylated-lysine peptide enrichment and a targeted antibody-based immunoassay (DigiWest) are proposed as complementary technologies to assess the modifications of the acetylated proteome. Quisinostat (JNJ-26481585) a novel second-generation HDACi with highest potency for HDAC1 was better characterized in vitro in HuT78 cells to support and understand cutaneous T-cell lymphoma (CTCL) therapeutic research program.