Phosphoproteomics Profiling of Nonsmall Cell Lung Cancer Cells Treated with a Novel Phosphatase Activator

Regulation and role of the PP2A-B56 holoenzyme family in cancer

Protein phosphatase 2A (PP2A) inactivation is common in cancer, leading to sustained activation of pro-survival and growth-promoting pathways. PP2A consists of a scaffolding A-subunit, a catalytic C-subunit, and a regulatory B-subunit. The functional complexity of PP2A holoenzymes arises mainly through the vast repertoire of regulatory B-subunits, which determine both their substrate specificity and their subcellular localization. Therefore, a major challenge for developing more effective therapeutic strategies for cancer is to identify the specific PP2A complexes to be targeted. Of note, the development of small molecules specifically directed at PP2A-B56α has opened new therapeutic avenues in both solid and hematological tumors. Here, we focus on the B56/PR61 family of PP2A regulatory subunits, which have a central role in directing PP2A tumor suppressor activity. We provide an overview of the mechanisms controlling the formation and regulation of these complexes, the pathways they control, and the mechanisms underlying their deregulation in cancer.

Loss of LCMT1 and biased protein phosphatase 2A heterotrimerization drive prostate cancer progression and therapy resistance

Loss of the tumor suppressive activity of the protein phosphatase 2A (PP2A) is associated with cancer, but the underlying molecular mechanisms are unclear. PP2A holoenzyme comprises a heterodimeric core, a scaffolding A subunit and a catalytic C subunit, and one of over 20 distinct substrate-directing regulatory B subunits. Methylation of the C subunit regulates PP2A heterotrimerization, affecting B subunit binding and substrate specificity. Here, we report that the leucine carboxy methyltransferase (LCMT1), which methylates the L309 residue of the C subunit, acts as a suppressor of androgen receptor (AR) addicted prostate cancer (PCa). Decreased methyl-PP2A-C levels in prostate tumors is associated with biochemical recurrence and metastasis. Silencing LCMT1 increases AR activity and promotes castration-resistant prostate cancer growth. LCMT1-dependent methyl-sensitive AB56αCme heterotrimers target AR and its critical coactivator MED1 for dephosphorylation, resulting in the eviction of the AR-MED1 complex from chromatin and loss of target gene expression. Mechanistically, LCMT1 is regulated by S6K1-mediated phosphorylation-induced degradation requiring the β-TRCP, leading to acquired resistance to anti-androgens. Finally, feedforward stabilization of LCMT1 by small molecule activator of phosphatase (SMAP) results in attenuation of AR-signaling and tumor growth inhibition in anti-androgen refractory PCa. These findings highlight methyl-PP2A-C as a prognostic marker and that the loss of LCMT1 is a major determinant in AR-addicted PCa, suggesting therapeutic potential for AR degraders or PP2A modulators in prostate cancer treatment.

PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping

Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances' mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols.

Computational systems approach towards phosphoproteomics and their downstream regulation

Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low-throughput biochemical assays. The advancement of mass spectrometry (MS)-based phosphoproteomics transformed the field by enabling measurement of proteome-wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large-scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS-based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast-growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.

Alteration in tyrosine phosphorylation of cardiac proteome and EGFR pathway contribute to hypertrophic cardiomyopathy

Alterations of serine/threonine phosphorylation of the cardiac proteome are a hallmark of heart failure. However, the contribution of tyrosine phosphorylation (pTyr) to the pathogenesis of cardiac hypertrophy remains unclear. We use global mapping to discover and quantify site-specific pTyr in two cardiac hypertrophic mouse models, i.e., cardiac overexpression of ErbB2 (TgErbB2) and α myosin heavy chain R403Q (R403Q-αMyHC Tg), compared to control hearts. From this, there are significant phosphoproteomic alterations in TgErbB2 mice in right ventricular cardiomyopathy, hypertrophic cardiomyopathy (HCM), and dilated cardiomyopathy (DCM) pathways. On the other hand, R403Q-αMyHC Tg mice indicated that the EGFR1 pathway is central for cardiac hypertrophy, along with angiopoietin, ErbB, growth hormone, and chemokine signaling pathways activation. Surprisingly, most myofilament proteins have downregulation of pTyr rather than upregulation. Kinase-substrate enrichment analysis (KSEA) shows a marked downregulation of MAPK pathway activity downstream of k-Ras in TgErbB2 mice and activation of EGFR, focal adhesion, PDGFR, and actin cytoskeleton pathways. In vivo ErbB2 inhibition by AG-825 decreases cardiomyocyte disarray. Serine/threonine and tyrosine phosphoproteome confirm the above-described pathways and the effectiveness of AG-825 Treatment. Thus, altered pTyr may play a regulatory role in cardiac hypertrophic models.

Excessive Inorganic Phosphate Burden Perturbed Intracellular Signaling: Quantitative Proteomics and Phosphoproteomics Analyses

Inorganic phosphate (Pi) is an essential nutrient for the human body which exerts adverse health effects in excess and deficit. High Pi-mediated cytotoxicity has been shown to induce systemic organ damage, though the underlying molecular mechanisms are poorly understood. In this study, we employed proteomics and phosphoproteomics to analyze Pi-mediated changes in protein abundance and phosphorylation. Bioinformatic analyses and literature review revealed that the altered proteins and phosphorylation were enriched in signaling pathways and diverse biological processes. Western blot analysis confirms the extensive change in protein level and phosphorylation in key effectors that modulate pre-mRNA alternative splicing. Global proteome and phospho-profiling provide a bird-eye view of excessive Pi-rewired cell signaling networks, which deepens our understanding of the molecular mechanisms of phosphate toxicity.

Robust inference of kinase activity using functional networks

Mass spectrometry enables high-throughput screening of phosphoproteins across a broad range of biological contexts. When complemented by computational algorithms, phospho-proteomic data allows the inference of kinase activity, facilitating the identification of dysregulated kinases in various diseases including cancer, Alzheimer’s disease and Parkinson’s disease. To enhance the reliability of kinase activity inference, we present a network-based framework, RoKAI, that integrates various sources of functional information to capture coordinated changes in signaling. Through computational experiments, we show that phosphorylation of sites in the functional neighborhood of a kinase are significantly predictive of its activity. The incorporation of this knowledge in RoKAI consistently enhances the accuracy of kinase activity inference methods while making them more robust to missing annotations and quantifications. This enables the identification of understudied kinases and will likely lead to the development of novel kinase inhibitors for targeted therapy of many diseases. RoKAI is available as web-based tool at http://rokai.io.

Kinases drive fundamental changes in cell state, but predicting kinase activity based on substrate-level changes can be challenging. Here the authors introduce a computational framework that utilizes similarities between substrates to robustly infer kinase activity.

Phosphoproteomic strategies in cancer research: a minireview

Understanding the cellular processes is central to comprehend disease conditions and is also true for cancer research. Proteomic studies provide significant insight into cancer mechanisms and aid in the diagnosis and prognosis of the disease. Phosphoproteome is one of the most studied complements of the whole proteome given its importance in the understanding of cellular processes such as signaling and regulations. Over the last decade, several new methods have been developed for phosphoproteome analysis. A significant amount of these efforts pertains to cancer research. The current use of powerful analytical instruments in phosphoproteomic approaches has paved the way for deeper and sensitive investigations. However, these methods and techniques need further improvements to deal with challenges posed by the complexity of samples and scarcity of phosphoproteins in the whole proteome, throughput and reproducibility. This review aims to provide a comprehensive summary of the variety of steps used in phosphoproteomic methods applied in cancer research including the enrichment and fractionation strategies. This will allow researchers to evaluate and choose a better combination of steps for their phosphoproteome studies.

MSpectraAI: a powerful platform for deciphering proteome profiling of multi-tumor mass spectrometry data by using deep neural networks

BACKGROUND

Mass spectrometry (MS) has become a promising analytical technique to acquire proteomics information for the characterization of biological samples. Nevertheless, most studies focus on the final proteins identified through a suite of algorithms by using partial MS spectra to compare with the sequence database, while the pattern recognition and classification of raw mass-spectrometric data remain unresolved.

RESULTS

We developed an open-source and comprehensive platform, named MSpectraAI, for analyzing large-scale MS data through deep neural networks (DNNs); this system involves spectral-feature swath extraction, classification, and visualization. Moreover, this platform allows users to create their own DNN model by using Keras. To evaluate this tool, we collected the publicly available proteomics datasets of six tumor types (a total of 7,997,805 mass spectra) from the ProteomeXchange consortium and classified the samples based on the spectra profiling. The results suggest that MSpectraAI can distinguish different types of samples based on the fingerprint spectrum and achieve better prediction accuracy in MS1 level (average 0.967).

CONCLUSION

This study deciphers proteome profiling of raw mass spectrometry data and broadens the promising application of the classification and prediction of proteomics data from multi-tumor samples using deep learning methods. MSpectraAI also shows a better performance compared to the other classical machine learning approaches.

Phosphoproteomic analysis identifies CLK1 as a novel therapeutic target in gastric cancer

BACKGROUND

Phosphorylation is an important regulatory mechanism of protein activity in cells. Studies in various cancers have reported perturbations in kinases resulting in aberrant phosphorylation of oncoproteins and tumor suppressor proteins.

METHODS

In this study, we carried out quantitative phosphoproteomic analysis of gastric cancer tissues and corresponding xenograft samples. Using these data, we employed bioinformatics analysis to identify aberrant signaling pathways. We further performed molecular inhibition and silencing of the upstream regulatory kinase in gastric cancer cell lines and validated its effect on cellular phenotype. Through an ex vivo technology utilizing patient tumor and blood sample, we sought to understand the therapeutic potential of the kinase by recreating the tumor microenvironment.

RESULTS

Using mass spectrometry-based high-throughput analysis, we identified 1,344 phosphosites and 848 phosphoproteins, including differential phosphorylation of 177 proteins (fold change cut-off ≥ 1.5). Our data showed that a subset of differentially phosphorylated proteins belonged to splicing machinery. Pathway analysis highlighted Cdc2-like kinase (CLK1) as upstream kinase. Inhibition of CLK1 using TG003 and CLK1 siRNA resulted in a decreased cell viability, proliferation, invasion and migration as well as modulation in the phosphorylation of SRSF2. Ex vivo experiments which utilizes patient's own tumor and blood to recreate the tumor microenvironment validated the use of CLK1 as a potential target for gastric cancer treatment.

CONCLUSIONS

Our data indicates that CLK1 plays a crucial role in the regulation of splicing process in gastric cancer and that CLK1 can act as a novel therapeutic target in gastric cancer.

Phosphoproteomics of short-term hedgehog signaling in human medulloblastoma cells

BACKGROUND

Aberrant hedgehog (HH) signaling is implicated in the development of various cancer entities such as medulloblastoma. Activation of GLI transcription factors was revealed as the driving force upon pathway activation. Increased phosphorylation of essential effectors such as Smoothened (SMO) and GLI proteins by kinases including Protein Kinase A, Casein Kinase 1, and Glycogen Synthase Kinase 3 β controls effector activity, stability and processing. However, a deeper and more comprehensive understanding of phosphorylation in the signal transduction remains unclear, particularly during early response processes involved in SMO activation and preceding GLI target gene regulation.

METHODS

We applied temporal quantitative phosphoproteomics to reveal phosphorylation dynamics underlying the short-term chemical activation and inhibition of early hedgehog signaling in HH responsive human medulloblastoma cells. Medulloblastoma cells were treated for 5.0 and 15 min with Smoothened Agonist (SAG) to induce and with vismodegib to inhibit the HH pathway.

RESULTS

Our phosphoproteomic profiling resulted in the quantification of 7700 and 10,000 phosphosites after 5.0 and 15 min treatment, respectively. The data suggest a central role of phosphorylation in the regulation of ciliary assembly, trafficking, and signal transduction already after 5.0 min treatment. ERK/MAPK signaling, besides Protein Kinase A signaling and mTOR signaling, were differentially regulated after short-term treatment. Activation of Polo-like Kinase 1 and inhibition of Casein Kinase 2A1 were characteristic for vismodegib treatment, while SAG treatment induced Aurora Kinase A activity. Distinctive phosphorylation of central players of HH signaling such as SMO, SUFU, GLI2 and GLI3 was observed only after 15 min treatment.

CONCLUSIONS

This study provides evidence that phosphorylation triggered in response to SMO modulation dictates the localization of hedgehog pathway components within the primary cilium and affects the regulation of the SMO-SUFU-GLI axis. The data are relevant for the development of targeted therapies of HH-associated cancers including sonic HH-type medulloblastoma. A deeper understanding of the mechanisms of action of SMO inhibitors such as vismodegib may lead to the development of compounds causing fewer adverse effects and lower frequencies of drug resistance. Video Abstract.

Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets

Recent technological advances for the acquisition of multi-omics data have allowed an unprecedented understanding of the complex intricacies of biological systems. In parallel, a myriad of computational analysis techniques and bioinformatics tools have been developed, with many efforts directed towards the creation and interpretation of networks from this data. In this review, we begin by examining key network concepts and terminology. Then, computational tools that allow for their construction and analysis from high-throughput omics datasets are presented. We focus on the study of functional relationships such as co-expression, protein-protein interactions, and regulatory interactions that are particularly amenable to modeling using the framework of networks. We envisage that many potential users of these analytical strategies may not be completely literate in programming languages and code adaptation, and for this reason, emphasis is given to tools' user-friendliness, including plugins for the widely adopted Cytoscape software, an open-source, cross-platform tool for network analysis, visualization, and data integration.

PP2A inhibition is a druggable MEK inhibitor resistance mechanism in KRAS-mutant lung cancer cells

Kinase inhibitor resistance constitutes a major unresolved clinical challenge in cancer. Furthermore, the role of serine/threonine phosphatase deregulation as a potential cause for resistance to kinase inhibitors has not been thoroughly addressed. We characterize protein phosphatase 2A (PP2A) activity as a global determinant of KRAS-mutant lung cancer cell resistance across a library of >200 kinase inhibitors. The results show that PP2A activity modulation alters cancer cell sensitivities to a large number of kinase inhibitors. Specifically, PP2A inhibition ablated mitogen-activated protein kinase kinase (MEK) inhibitor response through the collateral activation of AKT/mammalian target of rapamycin (mTOR) signaling. Combination of mTOR and MEK inhibitors induced cytotoxicity in PP2A-inhibited cells, but even this drug combination could not abrogate MYC up-regulation in PP2A-inhibited cells. Treatment with an orally bioavailable small-molecule activator of PP2A DT-061, in combination with the MEK inhibitor AZD6244, resulted in suppression of both p-AKT and MYC, as well as tumor regression in two KRAS-driven lung cancer mouse models. DT-061 therapy also abrogated MYC-driven tumorigenesis. These data demonstrate that PP2A deregulation drives MEK inhibitor resistance in KRAS-mutant cells. These results emphasize the need for better understanding of phosphatases as key modulators of cancer therapy responses.

Protein phosphatase 2A controls ongoing DNA replication by binding to and regulating cell division cycle 45 (CDC45)

Genomic replication is a highly regulated process and represents both a potential benefit and liability to rapidly dividing cells; however, the precise post-translational mechanisms regulating genomic replication are incompletely understood. Protein phosphatase 2A (PP2A) is a serine/threonine phosphatase that regulates a diverse array of cellular processes. Here, utilizing both a gain-of-function chemical biology approach and loss-of-function genetic approaches to modulate PP2A activity, we found that PP2A regulates DNA replication. We demonstrate that increased PP2A activity can interrupt ongoing DNA replication, resulting in a prolonged S phase. The impaired replication resulted in a collapse of replication forks, inducing dsDNA breaks, homologous recombination, and a PP2A-dependent replication stress response. Additionally, we show that during replication, PP2A exists in complex with cell division cycle 45 (CDC45) and that increased PP2A activity caused dissociation of CDC45 and polymerase α from the replisome. Furthermore, we found that individuals harboring mutations in the PP2A Aα gene have a higher fraction of genomic alterations, suggesting that PP2A regulates ongoing replication as a mechanism for maintaining genomic integrity. These results reveal a new function for PP2A in regulating ongoing DNA replication and a potential role for PP2A in the intra-S-phase checkpoint.

Protein phosphatase 2A as a therapeutic target in inflammation and neurodegeneration

Protein phosphatase 2A (PP2A) is a highly complex heterotrimeric enzyme that catalyzes the selective removal of phosphate groups from protein serine and threonine residues. Emerging evidence suggests that it functions as a tumor suppressor by constraining phosphorylation-dependent signalling pathways that regulate cellular transformation and metastasis. Therefore, PP2A-activating drugs (PADs) are being actively sought and investigated as potential novel anti-cancer treatments. Here we explore the concept that PP2A also constrains inflammatory responses through its inhibitory effects on various signalling pathways, suggesting that PADs may be effective in the treatment of inflammation-mediated pathologies.

RABL6A inhibits tumor-suppressive PP2A/AKT signaling to drive pancreatic neuroendocrine tumor growth

Hyperactivated AKT/mTOR signaling is a hallmark of pancreatic neuroendocrine tumors (PNETs). Drugs targeting this pathway are used clinically, but tumor resistance invariably develops. A better understanding of factors regulating AKT/mTOR signaling and PNET pathogenesis is needed to improve current therapies. We discovered that RABL6A, a new oncogenic driver of PNET proliferation, is required for AKT activity. Silencing RABL6A caused PNET cell-cycle arrest that coincided with selective loss of AKT-S473 (not T308) phosphorylation and AKT/mTOR inactivation. Restoration of AKT phosphorylation rescued the G1 phase block triggered by RABL6A silencing. Mechanistically, loss of AKT-S473 phosphorylation in RABL6A-depleted cells was the result of increased protein phosphatase 2A (PP2A) activity. Inhibition of PP2A restored phosphorylation of AKT-S473 in RABL6A-depleted cells, whereas PP2A reactivation using a specific small-molecule activator of PP2A (SMAP) abolished that phosphorylation. Moreover, SMAP treatment effectively killed PNET cells in a RABL6A-dependent manner and suppressed PNET growth in vivo. The present work identifies RABL6A as a new inhibitor of the PP2A tumor suppressor and an essential activator of AKT in PNET cells. Our findings offer what we believe is a novel strategy of PP2A reactivation for treatment of PNETs as well as other human cancers driven by RABL6A overexpression and PP2A inactivation.

Dynamic Phosphoproteomics Uncovers Signaling Pathways Modulated by Anti-oncogenic Sphingolipid Analogs

The anti-neoplastic sphingolipid analog SH-BC-893 starves cancer cells to death by down-regulating cell surface nutrient transporters and blocking lysosomal trafficking events. These effects are mediated by the activation of protein phosphatase 2A (PP2A). To identify putative PP2A substrates, we used quantitative phosphoproteomics to profile the temporal changes in protein phosphorylation in FL5.12 cells following incubation with SH-BC-893 or the specific PP2A inhibitor LB-100. These analyses enabled the profiling of more than 15,000 phosphorylation sites, of which 958 sites on 644 proteins were dynamically regulated. We identified 114 putative PP2A substrates including several nutrient transporter proteins, GTPase regulators (e.g. Agap2, Git1), and proteins associated with actin cytoskeletal remodeling (e.g. Vim, Pxn). To identify SH-BC-893-induced cell signaling events that disrupt lysosomal trafficking, we compared phosphorylation profiles in cells treated with SH-BC-893 or C2-ceramide, a non-vacuolating sphingolipid that does not impair lysosomal fusion. These analyses combined with functional assays uncovered the differential regulation of Akt and Gsk3b by SH-BC-893 (vacuolating) and C2-ceramide (non-vacuolating). Dynamic phosphoproteomics of cells treated with compounds affecting PP2A activity thus enabled the correlation of cell signaling with phenotypes to rationalize their mode of action.

Direct activation of PP2A for the treatment of tyrosine kinase inhibitor-resistant lung adenocarcinoma

Although tyrosine kinase inhibitors (TKIs) have demonstrated significant efficacy in advanced lung adenocarcinoma (LUAD) patients with pathogenic alterations in EGFR, most patients develop acquired resistance to these agents via mechanisms enabling the sustained activation of the PI3K and MAPK oncogenic pathways downstream of EGFR. The tumor suppressor protein phosphatase 2A (PP2A) acts as a negative regulator of these pathways. We hypothesize that activation of PP2A simultaneously inhibits the PI3K and MAPK pathways and represents a promising therapeutic strategy for the treatment of TKI-resistant LUAD. After establishing the efficacy of small molecule activators of PP2A (SMAPs) in a transgenic EGFRL858R model and TKI-sensitive cell lines, we evaluated their therapeutic potential in vitro and in vivo in TKI-resistant models. PP2A activation resulted in apoptosis, significant tumor growth inhibition, and downregulation of PI3K and MAPK pathways. Combination of SMAPs and TKI afatinib resulted in an enhanced effect on the downregulation of the PI3K pathway via degradation of the PP2A endogenous inhibitor CIP2A. An improved effect on tumor growth inhibition was observed in a TKI-resistant xenograft mouse model treated with a combination of both agents. These collective data support the development of PP2A activators for the treatment of TKI-resistant LUAD.