The human DEPhOsphorylation Database DEPOD: 2019 update

Multi-scale signaling and tumor evolution in high-grade gliomas

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

The substrate quality of CK2 target sites has a determinant role on their function and evolution

Most biological processes are regulated by signaling modules that bind to short linear motifs. For protein kinases, substrates may have full or only partial matches to the kinase recognition motif, a property known as "substrate quality." However, it is not clear whether differences in substrate quality represent neutral variation or if they have functional consequences. We examine this question for the kinase CK2, which has many fundamental functions. We show that optimal CK2 sites are phosphorylated at maximal stoichiometries and found in many conditions, whereas minimal substrates are more weakly phosphorylated and have regulatory functions. Optimal CK2 sites tend to be more conserved, and substrate quality is often tuned by selection. For intermediate sites, increases or decreases in substrate quality may be deleterious, as we demonstrate for a CK2 substrate at the kinetochore. The results together suggest a strong role for substrate quality in phosphosite function and evolution. A record of this paper's transparent peer review process is included in the supplemental information.

SHP2-EGFR States in Dephosphorylation Can Inform Selective SHP2 Inhibitors, Dampening RasGAP Action

SHP2 is a positive regulator of the EGFR-dependent Ras/MAPK pathway. It dephosphorylates a regulatory phosphorylation site in EGFR that serves as the binding site to RasGAP (RASA1 or p120RasGAP). RASA1 is activated by binding to the EGFR phosphate group. Active RASA1 deactivates Ras by hydrolyzing Ras-bound GTP to GDP. Thus, SHP2 dephosphorylation of EGFR effectively prevents RASA1-mediated deactivation of Ras, thereby stimulating proliferation. Despite knowledge of this vital regulation in cell life, mechanistic in-depth structural understanding of the involvement of SHP2, EGFR, and RASA1 in the Ras/MAPK pathway has largely remained elusive. Here we elucidate the interactions, the factors influencing EGFR's recruitment of RASA1, and SHP2's recognition of the substrate site in EGFR. We reveal that RASA1 specifically interacts with the DEpY992LIP motif in EGFR featuring a proline residue at the +3 position C-terminal to pY primarily through its nSH2 domain. This interaction is strengthened by the robust attraction of two acidic residues, E991 and D990, of EGFR to two basic residues in the BC-loop near the pY-binding pocket of RASA1's nSH2. In the stable precatalytic state of SHP2 with EGFR (DADEpY992LIPQ), the E-loop of SHP2's active site favors the interaction with the (-2)-position D990 and (-4)-position D988 N-terminal to pY992 in EGFR, while the pY-loop constrains the (+4)-position Q996 C-terminal to pY992. These specific interactions not only provide a structural basis for identifying negative regulatory sites in other RTKs but can inform selective, high-affinity active-site SHP2 inhibitors tailored for SHP2 mutants.

Mapping the substrate landscape of protein phosphatase 2A catalytic subunit PPP2CA

Protein phosphatase 2A (PP2A) is an essential Ser/Thr phosphatase. The PP2A holoenzyme complex comprises a scaffolding (A), regulatory (B), and catalytic (C) subunit, with PPP2CA being the principal catalytic subunit. The full scope of PP2A substrates in cells remains to be defined. To address this, we employed dTAG proteolysis-targeting chimeras to efficiently and selectively degrade dTAG-PPP2CA in homozygous knock-in HEK293 cells. Unbiased global phospho-proteomics identified 2,204 proteins with significantly increased phosphorylation upon dTAG-PPP2CA degradation, implicating them as potential PPP2CA substrates. A vast majority of these are novel. Bioinformatic analyses revealed involvement of the potential PPP2CA substrates in spliceosome function, cell cycle, RNA transport, and ubiquitin-mediated proteolysis. We identify a pSP/pTP motif as a predominant target for PPP2CA and confirm some of our phospho-proteomic data with immunoblotting. We provide an in-depth atlas of potential PPP2CA substrates and establish targeted degradation as a robust tool to unveil phosphatase substrates in cells.

A strategy to disentangle direct and indirect effects on (de)phosphorylation by chemical modulators of the phosphatase PP1 in complex cellular contexts

Chemical activators and inhibitors are useful probes to identify substrates and downstream effects of enzymes; however, due to the complex signaling environment within cells, it is challenging to distinguish between direct and indirect effects. This is particularly the case for phosphorylation, where a single (de)phosphorylation event can trigger rapid changes in many other phosphorylation sites. An additional complication arises when a single catalytic entity, which acts in the form of many different holoenzymes with different substrates, is activated or inhibited, as it is unclear which holoenzymes are affected, and in turn which of their substrates are (de)phosphorylated. Direct target engaging MS-based technologies to study targets of drugs do not address these challenges. Here, we tackle this by studying the modulation of protein phosphatase-1 (PP1) activity by PP1-disrupting peptides (PDPs), as well as their selectivity toward PP1, by using a combination of mass spectrometry-based experiments. By combining cellular treatment with the PDP with in vitro dephosphorylation by the enzyme, we identify high confidence substrate candidates and begin to separate direct and indirect effects. Together with experiments analyzing which holoenzymes are particularly susceptible to this treatment, we obtain insights into the effect of the modulator on the complex network of protein (de)phosphorylation. This strategy holds promise for enhancing our understanding of PP1 in particular and, due to the broad applicability of the workflow and the MS-based read-out, of chemical modulators with complex mode of action in general.

IDPpub: Illuminating the Dark Phosphoproteome Through PubMed Mining

Global phosphoproteomics experiments quantify tens of thousands of phosphorylation sites. However, data interpretation is hampered by our limited knowledge on functions, biological contexts, or precipitating enzymes of the phosphosites. This study establishes a repository of phosphosites with associated evidence in biomedical abstracts, using deep learning-based natural language processing techniques. Our model for illuminating the dark phosphoproteome through PubMed mining (IDPpub) was generated by fine-tuning BioBERT, a deep learning tool for biomedical text mining. Trained using sentences containing protein substrates and phosphorylation site positions from 3000 abstracts, the IDPpub model was then used to extract phosphorylation sites from all MEDLINE abstracts. The extracted proteins were normalized to gene symbols using the National Center for Biotechnology Information gene query, and sites were mapped to human UniProt sequences using ProtMapper and mouse UniProt sequences by direct match. Precision and recall were calculated using 150 curated abstracts, and utility was assessed by analyzing the CPTAC (Clinical Proteomics Tumor Analysis Consortium) pan-cancer phosphoproteomics datasets and the PhosphoSitePlus database. Using 10-fold cross validation, pairs of correct substrates and phosphosite positions were extracted with an average precision of 0.93 and recall of 0.94. After entity normalization and site mapping to human reference sequences, an independent validation achieved a precision of 0.91 and recall of 0.77. The IDPpub repository contains 18,458 unique human phosphorylation sites with evidence sentences from 58,227 abstracts and 5918 mouse sites in 14,610 abstracts. This included evidence sentences for 1803 sites identified in CPTAC studies that are not covered by manually curated functional information in PhosphoSitePlus. Evaluation results demonstrate the potential of IDPpub as an effective biomedical text mining tool for collecting phosphosites. Moreover, the repository (http://idppub.ptmax.org), which can be automatically updated, can serve as a powerful complement to existing resources.

Enzyme Databases in the Era of Omics and Artificial Intelligence

Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over the years, various databases that cover different aspects of enzyme biology (e.g., kinetic parameters, enzyme occurrence, and reaction mechanisms) have been developed. Most of the databases are curated manually, which improves reliability of the information; however, such curation cannot keep pace with the exponential growth in published data. Lack of data standardization is another obstacle for data extraction and analysis. Improving machine readability of databases is especially important in the light of recent advances in deep learning algorithms that require big training datasets. This review provides information regarding the current state of enzyme databases, especially in relation to the ever-increasing amount of generated research data and recent advancements in artificial intelligence algorithms. Furthermore, it describes several enzyme databases, providing the reader with necessary information for their use.

A proteogenomics data-driven knowledge base of human cancer

By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.

The Fanconi anemia core complex promotes CtIP-dependent end-resection to drive homologous recombination at DNA double-strand breaks

Homologous Recombination (HR) is a high-fidelity repair mechanism of DNA Double-Strand Breaks (DSBs), which are induced by irradiation, genotoxic chemicals or physiological DNA damaging processes. DSBs are also generated as intermediates during the repair of interstrand crosslinks (ICLs). In this context, the Fanconi anemia (FA) core complex, which is effectively recruited to ICLs, promotes HR-mediated DSB-repair. However, whether the FA core complex also promotes HR at ICL-independent DSBs remains controversial. Here, we identified the FA core complex members FANCL and Ube2T as HR-promoting factors in a CRISPR/Cas9-based screen with cells carrying the DSB-repair reporter DSB-Spectrum. Using isogenic cell-line models, we validated the HR-function of FANCL and Ube2T, and demonstrated a similar function for their ubiquitination-substrate FANCD2. We further show that FANCL and Ube2T are directly recruited to DSBs and are required for the accumulation of FANCD2 at these break sites. Mechanistically, we demonstrate that FANCL ubiquitin ligase activity is required for the accumulation of the nuclease CtIP at DSBs, and consequently for optimal end-resection and Rad51 loading. CtIP overexpression rescues HR in FANCL-deficient cells, validating that FANCL primarily regulates HR by promoting CtIP recruitment. Together, these data demonstrate that the FA core complex and FANCD2 have a dual genome maintenance function by promoting repair of DSBs as well as the repair of ICLs.

Large-scale phosphomimetic screening identifies phospho-modulated motif-based protein interactions

Phosphorylation is a ubiquitous post-translation modification that regulates protein function by promoting, inhibiting or modulating protein-protein interactions. Hundreds of thousands of phosphosites have been identified but the vast majority have not been functionally characterised and it remains a challenge to decipher phosphorylation events modulating interactions. We generated a phosphomimetic proteomic peptide-phage display library to screen for phosphosites that modulate short linear motif-based interactions. The peptidome covers ~13,500 phospho-serine/threonine sites found in the intrinsically disordered regions of the human proteome. Each phosphosite is represented as wild-type and phosphomimetic variant. We screened 71 protein domains to identify 248 phosphosites that modulate motif-mediated interactions. Affinity measurements confirmed the phospho-modulation of 14 out of 18 tested interactions. We performed a detailed follow-up on a phospho-dependent interaction between clathrin and the mitotic spindle protein hepatoma-upregulated protein (HURP), demonstrating the essentiality of the phospho-dependency to the mitotic function of HURP. Structural characterisation of the clathrin-HURP complex elucidated the molecular basis for the phospho-dependency. Our work showcases the power of phosphomimetic ProP-PD to discover novel phospho-modulated interactions required for cellular function.

Proteogenomic characterization of ferroptosis regulators reveals therapeutic potential in glioblastoma

BACKGROUND

Ferroptosis is iron-dependent non-apoptotic cell death, that is characterized by the excessive accumulation of lipid peroxides. Ferroptosis-inducing therapy also shows promise in the treatment of cancers. However, ferroptosis-inducing therapy for glioblastoma multiforme (GBM) is still in the exploratory stage.

METHODS

We identified the differentially expressed ferroptosis regulators using Mann-Whitney U test in the proteome data from Clinical Proteomic Tumor Analysis Consortium (CPTAC). We next analyzed the effect of mutation on protein abundance. A multivariate Cox model was constructed to identify the prognostic signature.

RESULTS

In this study, we systemically portrayed the proteogenomic landscape of ferroptosis regulators in GBM. We observed that some mutation-specific ferroptosis regulators, such as down-regulated ACSL4 in EGFR-mutated patients and up-regulated FADS2 in IDH1-mutated patients, were linked to the inhibited ferroptosis activity in GBM. To interrogate the valuable treatment targets, we performed the survival analysis and identified five ferroptosis regulators (ACSL3, HSPB1, ELAVL1, IL33, and GPX4) as the prognostic biomarkers. We also validated their efficiency in external validation cohorts. Notably, we found overexpressed protein and phosphorylation abundances of HSPB1 were poor prognosis markers for overall survival of GBM to inhibit ferroptosis activity. Alternatively, HSPB1 showed a significant association with macrophage infiltration levels. Macrophage-secreted SPP1 could be a potential activator for HSPB1 in glioma cells. Finally, we recognized that ipatasertib, a novel pan-Akt inhibitor, could be a potential drug for suppressing HSPB1 phosphorylation, inducing ferroptosis of glioma cells.

CONCLUSION

In summary, our study characterized the proteogenomic landscape of ferroptosis regulators and identified that HSPB1 could be a candidate target for ferroptosis-inducing therapy strategy for GBM.

Deep Learning in Phosphoproteomics: Methods and Application in Cancer Drug Discovery

Protein phosphorylation is a key post-translational modification (PTM) that is a central regulatory mechanism of many cellular signaling pathways. Several protein kinases and phosphatases precisely control this biochemical process. Defects in the functions of these proteins have been implicated in many diseases, including cancer. Mass spectrometry (MS)-based analysis of biological samples provides in-depth coverage of phosphoproteome. A large amount of MS data available in public repositories has unveiled big data in the field of phosphoproteomics. To address the challenges associated with handling large data and expanding confidence in phosphorylation site prediction, the development of many computational algorithms and machine learning-based approaches have gained momentum in recent years. Together, the emergence of experimental methods with high resolution and sensitivity and data mining algorithms has provided robust analytical platforms for quantitative proteomics. In this review, we compile a comprehensive collection of bioinformatic resources used for the prediction of phosphorylation sites, and their potential therapeutic applications in the context of cancer.

Inducible protein degradation as a strategy to identify Phosphoprotein Phosphatase 6 substrates in RAS-mutant colorectal cancer cells

Protein phosphorylation is an essential regulatory mechanism that controls most cellular processes, including cell cycle progression, cell division, and response to extracellular stimuli, among many others, and is deregulated in many diseases. Protein phosphorylation is coordinated by the opposing activities of protein kinases and protein phosphatases. In eukaryotic cells, most serine/threonine phosphorylation sites are dephosphorylated by members of the Phosphoprotein Phosphatase (PPP) family. However, we only know for a few phosphorylation sites which specific PPP dephosphorylates them. Although natural compounds such as calyculin A and okadaic acid inhibit PPPs at low nanomolar concentrations, no selective chemical PPP inhibitors exist. Here, we demonstrate the utility of endogenous tagging of genomic loci with an auxin-inducible degron (AID) as a strategy to investigate specific PPP signaling. Using Protein Phosphatase 6 (PP6) as an example, we demonstrate how rapidly inducible protein degradation can be employed to identify dephosphorylation SITES and elucidate PP6 biology. Using genome editing, we introduce AID-tags into each allele of the PP6 catalytic subunit (PP6c) in DLD-1 cells expressing the auxin receptor Tir1. Upon rapid auxin-induced degradation of PP6c, we perform quantitative mass spectrometry-based proteomics and phosphoproteomics to identify PP6 substrates in mitosis. PP6 is an essential enzyme with conserved roles in mitosis and growth signaling. Consistently, we identify candidate PP6c-dependent phosphorylation sites on proteins implicated in coordinating the mitotic cell cycle, cytoskeleton, gene expression, and mitogen-activated protein kinase (MAPK) and Hippo signaling. Finally, we demonstrate that PP6c opposes the activation of large tumor suppressor 1 (LATS1) by dephosphorylating Threonine 35 (T35) on Mps One Binder (MOB1), thereby blocking the interaction of MOB1 and LATS1. Our analyses highlight the utility of combining genome engineering, inducible degradation, and multiplexed phosphoproteomics to investigate signaling by individual PPPs on a global level, which is currently limited by the lack of tools for specific interrogation.

PSL Chemical Biology Symposia Third Edition: A Branch of Science in its Explosive Phase

This symposium is the third PSL (Paris Sciences & Lettres) Chemical Biology meeting (2016, 2019, 2023) held at Institut Curie. This initiative originally started at Institut de Chimie des Substances Naturelles (ICSN) in Gif-sur-Yvette (2013, 2014), under the directorship of Professor Max Malacria, with a strong focus on chemistry. It was then continued at the Institut Curie (2015) covering a larger scope, before becoming the official PSL Chemical Biology meeting. This latest edition was postponed twice for the reasons that we know. This has given us the opportunity to invite additional speakers of great standing. This year, Institut Curie hosted around 300 participants, including 220 on site and over 80 online. The pandemic has had, at least, the virtue of promoting online meetings, which we came to realize is not perfect but has its own merits. In particular, it enables those with restricted time and resources to take part in events and meetings, which can now accommodate unlimited participants. We apologize to all those who could not attend in person this time due to space limitation at Institut Curie.

A compilation of bioinformatic approaches to identify novel downstream targets for the detection and prophylaxis of cancer

The paradigm of cancer genomics has been radically changed by the development in next-generation sequencing (NGS) technologies making it possible to envisage individualized treatment based on tumor and stromal cells genome in a clinical setting within a short timeframe. The abundance of data has led to new avenues for studying coordinated alterations that impair biological processes, which in turn has increased the demand for bioinformatic tools for pathway analysis. While most of this work has been concentrated on optimizing certain algorithms to obtain quicker and more accurate results. Large volumes of these existing algorithm-based data are difficult for the biologists and clinicians to access, download and reanalyze them. In the present study, we have listed the bioinformatics algorithms and user-friendly graphical user interface (GUI) tools that enable code-independent analysis of big data without compromising the quality and time. We have also described the advantages and drawbacks of each of these platforms. Additionally, we emphasize the importance of creating new, more user-friendly solutions to provide better access to open data and talk about relevant problems like data sharing and patient privacy.

Synergistic Targeting of DNA-PK and KIT Signaling Pathways in KIT Mutant Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is the most common and aggressive form of acute leukemia, with a 5-year survival rate of just 24%. Over a third of all AML patients harbor activating mutations in kinases, such as the receptor tyrosine kinases FLT3 (receptor-type tyrosine-protein kinase FLT3) and KIT (mast/stem cell growth factor receptor kit). FLT3 and KIT mutations are associated with poor clinical outcomes and lower remission rates in response to standard-of-care chemotherapy. We have recently identified that the core kinase of the non-homologous end joining DNA repair pathway, DNA-PK (DNA-dependent protein kinase), is activated downstream of FLT3; and targeting DNA-PK sensitized FLT3-mutant AML cells to standard-of-care therapies. Herein, we investigated DNA-PK as a possible therapeutic vulnerability in KIT mutant AML, using isogenic FDC-P1 mouse myeloid progenitor cell lines transduced with oncogenic mutant KIT (V560G and D816V) or vector control. Targeted quantitative phosphoproteomic profiling identified phosphorylation of DNA-PK in the T2599/T2605/S2608/S2610 cluster in KIT mutant cells, indicative of DNA-PK activation. Accordingly, proliferation assays revealed that KIT mutant FDC-P1 cells were more sensitive to the DNA-PK inhibitors M3814 or NU7441, compared with empty vector controls. DNA-PK inhibition combined with inhibition of KIT signaling using the kinase inhibitors dasatinib or ibrutinib, or the protein phosphatase 2A activators FTY720 or AAL(S), led to synergistic cell death. Global phosphoproteomic analysis of KIT-D816V cells revealed that dasatinib and M3814 single-agent treatments inhibited extracellular signal-regulated kinase and AKT (RAC-alpha serine/threonine-protein kinase)/MTOR (serine/threonine-protein kinase mTOR) activity, with greater inhibition of both pathways when used in combination. Combined dasatinib and M3814 treatment also synergistically inhibited phosphorylation of the transcriptional regulators MYC and MYB. This study provides insight into the oncogenic pathways regulated by DNA-PK beyond its canonical role in DNA repair and demonstrates that DNA-PK is a promising therapeutic target for KIT mutant cancers.

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Deep Phosphoproteome Landscape of Interhemispheric Functionality of Neuroanatomical Regions of the Human Brain

Post-translational modifications (PTMs) are one of the compulsive and predominant biological processes that regulate the diverse molecular mechanism, modulate the onset of disease, and are the reason behind the functional diversity of proteins. Despite the widespread research findings in neuroproteomics, one of the key drawbacks has been the lack of proteome-level knowledge of hemispheric lateralization. We have investigated the proteome level expression in different neuroanatomical regions under the Human Brain Proteome Project (HBPP) and developed the global interhemispheric brain proteome map (Brainprot) earlier. Furthermore, this study has extended to decipher the phosphoproteome map of human brain interhemispheric regions through high-resolution mass spectrometry. The phosphoproteomics examination of 12 unique interhemispheric neurological brain regions using Orbitrap fusion liquid chromatography with tandem mass spectrometry provided comprehensive coverage of 996 phosphoproteins, 2010 phosphopeptides, and 3567 phosphosites. Moreover, interhemispheric phosphoproteome profiling has been categorized according to synaptic ontologies and interhemispheric expression to understand the functionality. Finally, we have integrated the phosphosites data under the PhosphoMap section in the Inter-Hemispheric Brain Proteome Map Portal (https://www.brainprot.org/) for the advancement and support of the ongoing neuroproteomics research worldwide. Data is available via ProteomeXchange with the identifier PXD031188.

The Emerging Roles of Protein Interactions with O-GlcNAc Cycling Enzymes in Cancer

The dynamic O-GlcNAc modification of intracellular proteins is an important nutrient sensor for integrating metabolic signals into vast networks of highly coordinated cellular activities. Dysregulation of the sole enzymes responsible for O-GlcNAc cycling, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), and the associated cellular O-GlcNAc profile is a common feature across nearly every cancer type. Many studies have investigated the effects of aberrant OGT/OGA expression on global O-GlcNAcylation activity in cancer cells. However, recent studies have begun to elucidate the roles of protein-protein interactions (PPIs), potentially through regions outside of the immediate catalytic site of OGT/OGA, that regulate greater protein networks to facilitate substrate-specific modification, protein translocalization, and the assembly of larger biomolecular complexes. Perturbation of OGT/OGA PPI networks makes profound changes in the cell and may directly contribute to cancer malignancies. Herein, we highlight recent studies on the structural features of OGT and OGA, as well as the emerging roles and molecular mechanisms of their aberrant PPIs in rewiring cancer networks. By integrating complementary approaches, the research in this area will aid in the identification of key protein contacts and functional modules derived from OGT/OGA that drive oncogenesis and will illuminate new directions for anti-cancer drug development.

An Integrated Proteomic Strategy to Identify SHP2 Substrates

Protein phosphatases play an essential role in normal cell physiology and the development of diseases such as cancer. The innate challenges associated with studying protein phosphatases have limited our understanding of their substrates, molecular mechanisms, and unique functions within highly coordinated networks. Here, we introduce a novel strategy using substrate-trapping mutants coupled with quantitative proteomics methods to identify physiological substrates of Src homology 2 containing protein tyrosine phosphatase 2 (SHP2) in a high-throughput manner. The technique integrates three parallel mass spectrometry-based proteomics experiments, including affinity isolation of substrate-trapping mutant complex using wild-type and SHP2 KO cells, in vivo global quantitative phosphoproteomics, and in vitro phosphatase reaction. We confidently identified 18 direct substrates of SHP2 in the epidermal growth factor receptor signaling pathways, including both known and novel SHP2 substrates. Docking protein 1 was further validated using biochemical assays as a novel SHP2 substrate, providing a mechanism for SHP2-mediated Ras activation. This advanced workflow improves the systemic identification of direct substrates of protein phosphatases, facilitating our understanding of the equally important roles of protein phosphatases in cellular signaling.

Emerging insights into serine/threonine-specific phosphoprotein phosphatase function and selectivity

Protein phosphorylation on serine and threonine residues is a widely distributed post-translational modification on proteins that acts to regulate their function. Phosphoprotein phosphatases (PPPs) contribute significantly to a plethora of cellular functions through the accurate dephosphorylation of phosphorylated residues. Most PPPs accomplish their purpose through the formation of complex holoenzymes composed of a catalytic subunit with various regulatory subunits. PPP holoenzymes then bind and dephosphorylate substrates in a highly specific manner. Despite the high prevalence of PPPs and their important role for cellular function, their mechanisms of action in the cell are still not well understood. Nevertheless, substantial experimental advancements in (phospho-)proteomics, structural and computational biology have contributed significantly to a better understanding of PPP biology in recent years. This Review focuses on recent approaches and provides an overview of substantial new insights into the complex mechanism of PPP holoenzyme regulation and substrate selectivity.

Evolutionary genomic relationships and coupling in MK-STYX and STYX pseudophosphatases

The dual specificity phosphatase (DUSP) family has catalytically inactive members, called pseudophosphatases. They have mutations in their catalytic motifs that render them enzymatically inactive. This study analyzes the significance of two pseudophosphatases, MK-STYX [MAPK (mitogen-activated protein kinase phosphoserine/threonine/tyrosine-binding protein]) and STYX (serine/threonine/tyrosine-interacting protein), throughout their evolution and provides measurements and comparison of their evolutionary conservation. Phylogenetic trees were constructed to show any deviation from various species evolutionary paths. Data was collected on a large set of proteins that have either one of the two domains of MK-STYX, the DUSP domain or the cdc-25 homology (CH2) /rhodanese-like domain. The distance between species pairs for MK-STYX or STYX and Ka/Ks ratio were calculated. In addition, both pseudophosphatases were ranked among a large set of related proteins, including the active homologs of MK-STYX, MKP (MAPK phosphatase)-1 and MKP-3. MK-STYX had one of the highest species-species protein distances and was under weaker purifying selection pressure than most proteins with its domains. In contrast, the protein distances of STYX were lower than 82% of the DUSP-containing proteins and was under one of the strongest purifying selection pressures. However, there was similar selection pressure on the N-terminal sequences of MK-STYX, STYX, MKP-1, and MKP-3. We next perform statistical coupling analysis, a process that reveals interconnected regions within the proteins. We find that while MKP-1,-3, and STYX all have 2 functional units (sectors), MK-STYX only has one, and that MK-STYX is similar to MKP-3 in the evolutionary coupling of the active site and KIM domain. Within those two domains, the mean coupling is also most similar for MK-STYX and MKP-3. This study reveals striking distinctions between the evolutionary patterns of MK-STYX and STYX, suggesting a very specific role for each pseudophosphatase, further highlighting the relevance of these atypical members of DUSP as signaling regulators. Therefore, our study provides computational evidence and evolutionary reasons to further explore the properties of pseudophosphatases, in particular MK-STYX and STYX.

Orchestrating serine/threonine phosphorylation and elucidating downstream effects by short linear motifs

Cellular function is based on protein-protein interactions. A large proportion of these interactions involves the binding of short linear motifs (SLiMs) by folded globular domains. These interactions are regulated by post-translational modifications, such as phosphorylation, that create and break motif binding sites or tune the affinity of the interactions. In addition, motif-based interactions are involved in targeting serine/threonine kinases and phosphatases to their substrate and contribute to the specificity of the enzymatic actions regulating which sites are phosphorylated. Here, we review how SLiM-based interactions assist in determining the specificity of serine/threonine kinases and phosphatases, and how phosphorylation, in turn, affects motif-based interactions. We provide examples of SLiM-based interactions that are turned on/off, or are tuned by serine/threonine phosphorylation and exemplify how this affects SLiM-based protein complex formation.

Quantitative proteomics identifies PTP1B as modulator of B cell antigen receptor signaling

This study analyses the function of the protein tyrosine phosphatase 1B identifying its binding partners and dephosphorylation targets for modulating B cell antigen receptor signaling.

B cell antigen receptor (BCR) signaling is initiated by protein kinases and limited by counteracting phosphatases that currently are less well studied in their regulation of BCR signaling. Here, we used the B cell line Ramos to identify and quantify human B cell signaling components. Specifically, a protein tyrosine phosphatase profiling revealed a high expression of the protein tyrosine phosphatase 1B (PTP1B) in Ramos and human naïve B cells. The loss of PTP1B leads to increased B cell activation. Through substrate trapping in combination with quantitative mass spectrometry, we identified 22 putative substrates or interactors of PTP1B. We validated Igα, CD22, PLCγ1/2, CBL, BCAP, and APLP2 as specific substrates of PTP1B in Ramos B cells. The tyrosine kinase BTK and the two adaptor proteins GRB2 and VAV1 were identified as direct binding partners and potential substrates of PTP1B. We showed that PTP1B dephosphorylates the inhibitory receptor protein CD22 at phosphotyrosine 807. We conclude that PTP1B negatively modulates BCR signaling by dephosphorylating distinct phosphotyrosines in B cell-specific receptor proteins and various downstream signaling components.

Peptidomics and proteogenomics: background, challenges and future needs

INTRODUCTION

With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development.

AREAS COVERED

Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date.

EXPERT OPINION

This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

Proteome Landscape of Epithelial-to-Mesenchymal Transition (EMT) of Retinal Pigment Epithelium Shares Commonalities With Malignancy-Associated EMT

Stress and injury to the retinal pigment epithelium (RPE) often lead to dedifferentiation and epithelial-to-mesenchymal transition (EMT). These processes have been implicated in several retinal diseases, including proliferative vitreoretinopathy, diabetic retinopathy, and age-related macular degeneration. Despite the importance of RPE-EMT and the large body of data characterizing malignancy-related EMT, comprehensive proteomic studies to define the protein changes and pathways underlying RPE-EMT have not been reported. This study sought to investigate the temporal protein expression changes that occur in a human-induced pluripotent stem cell–based RPE-EMT model. We utilized multiplexed isobaric tandem mass tag labeling followed by high-resolution tandem MS for precise and in-depth quantification of the RPE-EMT proteome. We have identified and quantified 7937 protein groups in our tandem mass tag–based MS analysis. We observed a total of 532 proteins that are differentially regulated during RPE-EMT. Furthermore, we integrated our proteomic data with prior transcriptomic (RNA-Seq) data to provide additional insights into RPE-EMT mechanisms. To validate these results, we have performed a label-free single-shot data-independent acquisition MS study. Our integrated analysis indicates both the commonality and uniqueness of RPE-EMT compared with malignancy-associated EMT. Our comparative analysis also revealed that multiple age-related macular degeneration–associated risk factors are differentially regulated during RPE-EMT. Together, our integrated dataset provides a comprehensive RPE-EMT atlas and resource for understanding the molecular signaling events and associated biological pathways that underlie RPE-EMT onset. This resource has already facilitated the identification of chemical modulators that could inhibit RPE-EMT, and it will hopefully aid in ongoing efforts to develop EMT inhibition as an approach for the treatment of retinal disease.

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Proteomics data were integrated with prior transcriptomic (RNA-Seq) data on RPE-EMT.

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Dysregulated RPE-EMT proteome shares commonality with malignancy-associated EMT.

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Altered RPE-EMT proteome signatures correlated with known AMD-associated risk factors.

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Protein kinases and phosphatases crosstalk modulate RPE-EMT.

DTL-DephosSite: Deep Transfer Learning Based Approach to Predict Dephosphorylation Sites

Phosphorylation, which is mediated by protein kinases and opposed by protein phosphatases, is an important post-translational modification that regulates many cellular processes, including cellular metabolism, cell migration, and cell division. Due to its essential role in cellular physiology, a great deal of attention has been devoted to identifying sites of phosphorylation on cellular proteins and understanding how modification of these sites affects their cellular functions. This has led to the development of several computational methods designed to predict sites of phosphorylation based on a protein’s primary amino acid sequence. In contrast, much less attention has been paid to dephosphorylation and its role in regulating the phosphorylation status of proteins inside cells. Indeed, to date, dephosphorylation site prediction tools have been restricted to a few tyrosine phosphatases. To fill this knowledge gap, we have employed a transfer learning strategy to develop a deep learning-based model to predict sites that are likely to be dephosphorylated. Based on independent test results, our model, which we termed DTL-DephosSite, achieved efficiency scores for phosphoserine/phosphothreonine residues of 84%, 84% and 0.68 with respect to sensitivity (SN), specificity (SP) and Matthew’s correlation coefficient (MCC). Similarly, DTL-DephosSite exhibited efficiency scores of 75%, 88% and 0.64 for phosphotyrosine residues with respect to SN, SP, and MCC.

Strategies for Targeting Serine/Threonine Protein Phosphatases with Small Molecules in Cancer

Among numerous posttranslational regulation patterns, phosphorylation is reversibly controlled by the balance of kinases and phosphatases. The major form of cellular signaling involves the reversible phosphorylation of proteins on tyrosine, serine, or threonine residues. However, altered phosphorylation levels are found in diverse diseases, including cancer, making kinases and phosphatases ideal drug targets. In contrast to the success of prosperous kinase inhibitors, design of small molecules targeting phosphatase is struggling due to past bias and difficulty. This is especially true for serine/threonine phosphatases, one of the largest phosphatase families. From this perspective, we aim to provide insights into serine/threonine phosphatases and the small molecules targeting these proteins for drug development, especially in cancer. Through highlighting the modulation strategies, we aim to provide basic principles for the design of small molecules and future perspectives for the application of drugs targeting serine/threonine phosphatases.

Alterations in the Global Proteome and Phosphoproteome in Third Generation EGFR TKI Resistance Reveal Drug Targets to Circumvent Resistance

Lung cancer is the leading cause of cancer mortality worldwide. The treatment of patients with lung cancer harboring mutant EGFR with orally administered EGFR tyrosine kinase inhibitors (TKI) has been a paradigm shift. Osimertinib and rociletinib are third-generation irreversible EGFR TKIs targeting the EGFR T790M mutation. Osimertinib is the current standard of care for patients with EGFR mutations due to increased efficacy, lower side effects, and enhanced brain penetrance. Unfortunately, all patients develop resistance. Genomic approaches have primarily been used to interrogate resistance mechanisms. Here we characterized the proteome and phosphoproteome of a series of isogenic EGFR-mutant lung adenocarcinoma cell lines that are either sensitive or resistant to these drugs, comprising the most comprehensive proteomic dataset resource to date to investigate third generation EGFR TKI resistance in lung adenocarcinoma. Unbiased global quantitative mass spectrometry uncovered alterations in signaling pathways, revealed a proteomic signature of epithelial-mesenchymal transition, and identified kinases and phosphatases with altered expression and phosphorylation in TKI-resistant cells. Decreased tyrosine phosphorylation of key sites in the phosphatase SHP2 suggests its inhibition, resulting in subsequent inhibition of RAS/MAPK and activation of PI3K/AKT pathways. Anticorrelation analyses of this phosphoproteomic dataset with published drug-induced P100 phosphoproteomic datasets from the Library of Integrated Network-Based Cellular Signatures program predicted drugs with the potential to overcome EGFR TKI resistance. The PI3K/MTOR inhibitor dactolisib in combination with osimertinib overcame resistance both in vitro and in vivo. Taken together, this study reveals global proteomic alterations upon third generation EGFR TKI resistance and highlights potential novel approaches to overcome resistance. SIGNIFICANCE: Global quantitative proteomics reveals changes in the proteome and phosphoproteome in lung cancer cells resistant to third generation EGFR TKIs, identifying the PI3K/mTOR inhibitor dactolisib as a potential approach to overcome resistance.

A data-independent acquisition-based global phosphoproteomics system enables deep profiling

Phosphoproteomics can provide insights into cellular signaling dynamics. To achieve deep and robust quantitative phosphoproteomics profiling for minute amounts of sample, we here develop a global phosphoproteomics strategy based on data-independent acquisition (DIA) mass spectrometry and hybrid spectral libraries derived from data-dependent acquisition (DDA) and DIA data. Benchmarking the method using 166 synthetic phosphopeptides shows high sensitivity (<0.1 ng), accurate site localization and reproducible quantification (~5% median coefficient of variation). As a proof-of-concept, we use lung cancer cell lines and patient-derived tissue to construct a hybrid phosphoproteome spectral library covering 159,524 phosphopeptides (88,107 phosphosites). Based on this library, our single-shot streamlined DIA workflow quantifies 36,350 phosphosites (19,755 class 1) in cell line samples within two hours. Application to drug-resistant cells and patient-derived lung cancer tissues delineates site-specific phosphorylation events associated with resistance and tumor progression, showing that our workflow enables the characterization of phosphorylation signaling with deep coverage, high sensitivity and low between-run missing values.

Integrated intra- and intercellular signaling knowledge for multicellular omics analysis

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.

canSAR: update to the cancer translational research and drug discovery knowledgebase

canSAR (http://cansar.icr.ac.uk) is the largest, public, freely available, integrative translational research and drug discovery knowledgebase for oncology. canSAR integrates vast multidisciplinary data from across genomic, protein, pharmacological, drug and chemical data with structural biology, protein networks and more. It also provides unique data, curation and annotation and crucially, AI-informed target assessment for drug discovery. canSAR is widely used internationally by academia and industry. Here we describe significant developments and enhancements to the data, web interface and infrastructure of canSAR in the form of the new implementation of the system: canSARblack. We demonstrate new functionality in aiding translation hypothesis generation and experimental design, and show how canSAR can be adapted and utilised outside oncology.

l-Lactate Dehydrogenase Identified as a Protein Tyrosine Phosphatase 1B Substrate by Using K-BIPS

Kinases and phosphatases are major players in a variety of cellular events, including cell signaling. Aberrant activity or mutations in kinases and phosphatases can lead to diseases such as cancer, diabetes, and Alzheimer's. Compared to kinases, phosphatases are understudied; this is partly a result of the limited methods for identifying substrates. As a solution, we developed a proteomics-based method called kinase-catalyzed biotinylation to identify phosphatase substrates (K-BIPS) that previously identified substrates of Ser/Thr phosphatases using small molecule inhibitors. Here, for the first time, K-BIPS was applied to identify substrates of a tyrosine phosphatase, protein tyrosine phosphatase 1B (PTP1B), under siRNA knockdown conditions. Eight possible substrates of PTP1B were discovered in HEK293 cells, including the known substrate pyruvate kinase. In addition, l-lactate dehydrogenase (LDHA) was validated as a novel PTP1B substrate. With the ability to use knockdown conditions with Ser/Thr or Tyr phosphatases, K-BIPS represents a general discovery tool to explore phosphatases biology by identifying unanticipated substrates.

The dead phosphatases society: a review of the emerging roles of pseudophosphatases

Phosphatases are a diverse family of enzymes, comprising at least 10 distinct protein folds. Like most other enzyme families, many have sequence variations that predict an impairment or loss of catalytic activity classifying them as pseudophosphatases. Research on pseudoenzymes is an emerging area of interest, with new biological functions repurposed from catalytically active relatives. Here, we provide an overview of the pseudophosphatases identified to date in all major phosphatase families. We will highlight the degeneration of the various catalytic sequence motifs and discuss the challenges associated with the experimental determination of catalytic inactivity. We will also summarize the role of pseudophosphatases in various diseases and discuss the major challenges and future directions in this field.

Turn and Face the Strange: A New View on Phosphatases

Phosphorylation as a post-translational modification is critical for cellular homeostasis. Kinases and phosphatases regulate phosphorylation levels by adding or removing, respectively, a phosphate group from proteins or other biomolecules. Imbalances in phosphorylation levels are involved in a multitude of diseases. Phosphatases are often thought of as the black sheep, the strangers, of phosphorylation-mediated signal transduction, particularly when it comes to drug discovery and development. This is due to past difficulties to study them and unsuccessful attempts to target them; however, phosphatases have regained strong attention and are actively pursued now in clinical trials. By giving examples for current hot topics in phosphatase biology and for new approaches to target them, it is illustrated here how and why phosphatases made their comeback, and what is envisioned to come in the future.