Deep Proteomics of Breast Cancer Cells Reveals that Metformin Rewires Signaling Networks Away from a Pro-growth State

Harnessing Pharmacomultiomics for Precision Medicine in Diabetes: A Comprehensive Review

Type 2 diabetes (T2D) is the fastest-growing non-communicable disease worldwide, accounting for around 90% of all diabetes cases and imposing a significant health burden globally. Due to its phenotypic heterogeneity and composite genetic underpinnings, T2D requires a precision medicine approach personalized to individual molecular profiles, thereby shifting away from the traditional "one-size-fits-all" medical methods. This review advocates for a thorough pharmacomultiomics approach to enhance precision medicine for T2D. It emphasizes personalized treatment strategies that enhance treatment efficacy while minimizing adverse effects by integrating data from genomics, proteomics, metabolomics, transcriptomics, microbiomics, and epigenomics. We summarize key findings on candidate genes impacting diabetic medication responses and explore the potential of pharmacometabolomics in predicting drug efficacy. The role of pharmacoproteomics in prognosis and discovering new therapeutic targets is discussed, along with transcriptomics' contribution to understanding T2D pathophysiology. Additionally, pharmacomicrobiomics is explored to understand gut microbiota interactions with antidiabetic drugs. Emerging evidence on utilizing epigenomic profiles in improving drug efficacy and personalized treatment is also reviewed, illustrating their implications in personalized medicine. In this paper, we discuss the integration of these layers of omics data, examining recently developed paradigms that leverage complex data to deepen our understanding of diabetes. Such integrative approaches advance precision medicine strategies to tackle the disease by better understanding its complex biology.

An anti-neoplastic tale of metformin through its transport

Metformin is an attractive candidate drug among all the repurposed drugs for cancer. Extensive preclinical and clinical research has evaluated its efficacy in cancer therapy, revealing a mixed outcome in clinical settings. To fully exploit metformin's therapeutic potential, understanding cellular factors relevant to its transport and accumulation in cancer cells needs to be understood. This review highlights the relevance of metformin transporter status towards its anti-cancer potential. Metformin transporters are regulated at pre-transcriptional, transcriptional, and post-translational levels. Moreover, the tumour microenvironment can also influence metformin accumulation in cancer cells. Also, Metformin treatment can regulate its transporters by altering global DNA methylation, protein acetylation, and transcription factors. Importantly, metformin transporters not only influence chemotherapeutic drug toxicity but are also associated with the prognosis and survival of individuals having cancer. Strategic decisions based on the expression and regulation of metformin transporters holds promise for its therapeutic implications and relevance.

Metformin and its potential influence on cell fate decision between apoptosis and senescence in cancer, with a special emphasis on glioblastoma

Despite reaching enormous achievements in therapeutic approaches worldwide, GBM still remains the most incurable malignancy among various cancers. It emphasizes the necessity of adjuvant therapies from the perspectives of both patients and healthcare providers. Therefore, most emerging studies have focused on various complementary and adjuvant therapies. Among them, metabolic therapy has received special attention, and metformin has been considered as a treatment in various types of cancer, including GBM. It is clearly evident that reaching efficient approaches without a comprehensive evaluation of the key mechanisms is not possible. Among the studied mechanisms, one of the more challenging ones is the effect of metformin on apoptosis and senescence. Moreover, metformin is well known as an insulin sensitizer. However, if insulin signaling is facilitated in the tumor microenvironment, it may result in tumor growth. Therefore, to partially resolve some paradoxical issues, we conducted a narrative review of related studies to address the following questions as comprehensively as possible: 1) Does the improvement of cellular insulin function resulting from metformin have detrimental or beneficial effects on GBM cells? 2) If these effects are detrimental to GBM cells, which is more important: apoptosis or senescence? 3) What determines the cellular decision between apoptosis and senescence?

SignalingProfiler 2.0 a network-based approach to bridge multi-omics data to phenotypic hallmarks

Unraveling how cellular signaling is remodeled upon perturbation is crucial for understanding disease mechanisms and identifying potential drug targets. In this pursuit, computational tools generating mechanistic hypotheses from multi-omics data have invaluable potential. Here, we present a newly implemented version (2.0) of SignalingProfiler, a multi-step pipeline to draw mechanistic hypotheses on the signaling events impacting cellular phenotypes. SignalingProfiler 2.0 derives context-specific signaling networks by integrating proteogenomic data with the prior knowledge-causal network. This is a freely accessible and flexible tool that incorporates statistical, footprint-based, and graph algorithms to accelerate the integration and interpretation of multi-omics data. Through a benchmarking process on three proof-of-concept studies, we demonstrate the tool's ability to generate hierarchical mechanistic networks recapitulating novel and known perturbed signaling and phenotypic outcomes, in both human and mice contexts. In summary, SignalingProfiler 2.0 addresses the emergent need to derive biologically relevant information from complex multi-omics data by extracting interpretable networks.

The One Hour Human Proteome

We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS1 scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.

Drug repurposing for cancer therapy

Cancer, a complex and multifactorial disease, presents a significant challenge to global health. Despite significant advances in surgical, radiotherapeutic and immunological approaches, which have improved cancer treatment outcomes, drug therapy continues to serve as a key therapeutic strategy. However, the clinical efficacy of drug therapy is often constrained by drug resistance and severe toxic side effects, and thus there remains a critical need to develop novel cancer therapeutics. One promising strategy that has received widespread attention in recent years is drug repurposing: the identification of new applications for existing, clinically approved drugs. Drug repurposing possesses several inherent advantages in the context of cancer treatment since repurposed drugs are typically cost-effective, proven to be safe, and can significantly expedite the drug development process due to their already established safety profiles. In light of this, the present review offers a comprehensive overview of the various methods employed in drug repurposing, specifically focusing on the repurposing of drugs to treat cancer. We describe the antitumor properties of candidate drugs, and discuss in detail how they target both the hallmarks of cancer in tumor cells and the surrounding tumor microenvironment. In addition, we examine the innovative strategy of integrating drug repurposing with nanotechnology to enhance topical drug delivery. We also emphasize the critical role that repurposed drugs can play when used as part of a combination therapy regimen. To conclude, we outline the challenges associated with repurposing drugs and consider the future prospects of these repurposed drugs transitioning into clinical application.

Systematic Investigation of Dose-Dependent Protein Thermal Stability Changes to Uncover the Mechanisms of the Pleiotropic Effects of Metformin

Metformin is a widely used drug to treat type II diabetes. Beyond lowering blood sugar, it has been reported to have pleiotropic effects such as suppressing cancer growth and attenuating cell oxidative stress and inflammation. However, the underlying mechanisms of these effects remain to be explored. Here, we systematically study the thermal stability changes of proteins in liver cells (HepG2) induced by a wide dosage range of metformin by using the proteome integral solubility alteration (PISA) assay. The current results demonstrate that, besides the most accepted target of metformin (complex I), low concentrations of metformin (such as 0.2 μM) stabilize the complex IV subunits, suggesting its important role in the sugar-lowering effect. Low-dose metformin also results in stability alterations of ribosomal proteins, correlating with its inhibitive effect on cell proliferation. We further find that low-concentration metformin impacts mitochondrial cargo and vesicle transport, while high-concentration metformin affects cell redox responses and cell membrane protein sorting. This study provides mechanistic insights into the molecular mechanisms of lowering blood sugar and the pleiotropic effects of metformin.

Integrated proteomics and phosphoproteomics profiling reveals the cardioprotective mechanism of bioactive compounds derived from Salvia miltiorrhiza Burge

BACKGROUND

Natural products are an important source for discovering novel drugs due to their various pharmacological activities. Salvia miltiorrhiza Burge (Danshen) has been shown to have promising therapeutic potential in the management of heart diseases, making it a candidate for cardiovascular drug discovery. Currently, there is limited quantitative analysis of the phosphorylation levels of Danshen-derived natural products on a proteome-wide, which may bias the study of their mechanisms of action.

PURPOSE

This study aimed to evaluate the global signaling perturbation induced by Danshen-derived bioactive compounds and their potential relationship with myocardial ischemia/reperfusion (IR) injury therapy.

STUDY DESIGN

We employed quantitative proteome and phosphoproteome analysis to identify dysregulated signaling in IR injury hearts from mice. We compared changes induced by Danshen-derived compounds based on IR-associated phospho-events, using an integrative approach that maps relative abundance of proteins and phosphorylation sites.

METHODS

Isobaric chemical tandem mass tags (TMT) labeled multiplexing strategy was used to generate unbiased quantitative proteomics and phosphoproteomics data. Highly accurate and precise TMT quantitation was performed using the Orbitrap Fusion Tribrid Mass Spectrometer with synchronous precursor selection MS3 detection mode. Mass spectrometric raw files were analyzed with MaxQuant (2.0.1.0) and statistical and bioinformatics analysis was conducted with Perseus (1.6.15).

RESULTS

We quantified 3661 proteins and over 11,000 phosphosites in impaired heart tissue of the IR mice model, expanding our knowledge of signaling pathways and other biological processes disrupted in IR injury. Next, 1548 and 5545 differently expressed proteins and phosphosites were identified by quantifying the proteome and phosphoproteome of H9c2 cells treated by five Danshen bioactive compounds respectively. Results revealed the vast differences in abilities of five Danshen-derived bioactive compounds to regulate phosphorylation modifications in cardiomyocytes, with dihydrotanshinone I (DHT) showing potential for protecting against IR injury by modulating the AMPK/mTOR signaling pathway.

CONCLUSIONS

This study provides a new strategy for analyzing drug/natural product-regulated phosphorylation modification levels on a proteome-wide scale, leading to a better understanding of cell signaling pathways and downstream phenotypic responses.

Proteomic Analysis Reveals Changes in Tight Junctions in the Small Intestinal Epithelium of Mice Fed a High-Fat Diet

The impact of a high-fat diet (HFD) on intestinal permeability has been well established. When bacteria and their metabolites from the intestinal tract flow into the portal vein, inflammation in the liver is triggered. However, the exact mechanism behind the development of a leaky gut caused by an HFD is unclear. In this study, we investigated the mechanism underlying the leaky gut related to an HFD. C57BL/6J mice were fed an HFD or control diet for 24 weeks, and their small intestine epithelial cells (IECs) were analyzed using deep quantitative proteomics. A significant increase in fat accumulation in the liver and a trend toward increased intestinal permeability were observed in the HFD group compared to the control group. Proteomics analysis of the upper small intestine epithelial cells identified 3684 proteins, of which 1032 were differentially expressed proteins (DEPs). Functional analysis of DEPs showed significant enrichment of proteins related to endocytosis, protein transport, and tight junctions (TJ). Expression of Cldn7 was inversely correlated with intestinal barrier function and strongly correlated with that of Epcam. This study will make important foundational contributions by providing a comprehensive depiction of protein expression in IECs affected by HFD, including an indication that the Epcam/Cldn7 complex plays a role in leaky gut.

Low HER2 expression in normal breast epithelium enables dedifferentiation and malignant transformation via chromatin opening

Overexpression of the HER2 protein in breast cancer patients is a predictor of poor prognosis and resistance to therapies. We used an inducible breast cancer transformation system that allows investigation of early molecular changes. HER2 overexpression to similar levels as those observed in a subtype of HER2-positive breast cancer patients induced transformation of MCF10A cells and resulted in gross morphological changes, increased anchorage-independent growth of cells, and altered the transcriptional programme of genes associated with oncogenic transformation. Global phosphoproteomic analysis during HER2 induction predominantly detected an increase in protein phosphorylation. Intriguingly, this correlated with chromatin opening, as measured by ATAC-seq on acini isolated from 3D cell culture. HER2 overexpression resulted in opening of many distal regulatory regions and promoted reprogramming-associated heterogeneity. We found that a subset of cells acquired a dedifferentiated breast stem-like phenotype, making them likely candidates for malignant transformation. Our data show that this population of cells, which counterintuitively enriches for relatively low HER2 protein abundance and increased chromatin accessibility, possesses transformational drive, resulting in increased anchorage-independent growth in vitro compared to cells not displaying a stem-like phenotype.

Phosphoproteomic analysis of metformin signaling in colorectal cancer cells elucidates mechanism of action and potential therapeutic opportunities

BACKGROUND

The biguanide drug metformin is a safe and widely prescribed drug for type 2 diabetes. Interestingly, hundreds of clinical trials have been set to evaluate the potential role of metformin in the prevention and treatment of cancer including colorectal cancer (CRC). However, the "metformin signaling" remains controversial.

AIMS AND METHODS

To interrogate cell signaling induced by metformin in CRC and explore the druggability of the metformin-rewired phosphorylation network, we performed integrative analysis of phosphoproteomics, bioinformatics, and cell proliferation assays on a panel of 12 molecularly heterogeneous CRC cell lines. Using the high-resolute data-independent analysis mass spectrometry (DIA-MS), we monitored a total of 10,142 proteins and 56,080 phosphosites (P-sites) in CRC cells upon a short- and a long-term metformin treatment.

RESULTS AND CONCLUSIONS

We found that metformin tended to primarily remodel cell signaling in the long-term and only minimally regulated the total proteome expression levels. Strikingly, the phosphorylation signaling response to metformin was highly heterogeneous in the CRC panel, based on a network analysis inferring kinase/phosphatase activities and cell signaling reconstruction. A "MetScore" was determined to assign the metformin relevance of each P-site, revealing new and robust phosphorylation nodes and pathways in metformin signaling. Finally, we leveraged the metformin P-site signature to identify pharmacodynamic interactions and confirmed a number of candidate metformin-interacting drugs, including navitoclax, a BCL-2/BCL-xL inhibitor. Together, we provide a comprehensive phosphoproteomic resource to explore the metformin-induced cell signaling for potential cancer therapeutics. This resource can be accessed at https://yslproteomics.shinyapps.io/Metformin/.

Phosphoproteomics reveals that cinobufotalin promotes intrahepatic cholangiocarcinoma cell apoptosis by activating the ATM/CHK2/p53 signaling pathway

Intrahepatic cholangiocarcinoma (ICC) is a malignant tumor that originates from bile duct’s epithelial cells and is usually characterized by insidious symptoms and poor prognosis. Cinobufotalin (CB), an active ingredient obtained from the Traditional Chinese Medicine ChanSu, is purported to exhibit a wide range of antitumorigenic activities. However, the mechanism by which it achieves such pharmacological effects remains elusive. Here, we disclosed the mechanism of action by which CB inhibits ICC cells. Initial experiments revealed that the proliferation of RBE and HCCC-9810 cells was significantly inhibited by CB with IC50 values of 0.342 μM and 0.421 μM respectively. CB induced the expression of caspase-3 subsequently leading to the apoptosis of ICC cells. Phosphoproteomics revealed that the phosphorylation of many proteins associated with DNA damage response increased. Kinase-substrate enrichment analysis revealed that ATM was activated after CB treatment, while CDK1 was inactivated. Activated ATM increased p-CHK2-T68 and p-p53-S15, which promoted the expression of FAS, DR4 and DR5 and triggered cell apoptosis. In summary, this work reveals the role of CB in inducing DNA damage and cell apoptosis involved in the activation of the ATM/CHK2/p53 signaling pathway, and indicates that CB may serve as a chemotherapeutic drug candidate for ICC treatment.

SIGNORApp: a Cytoscape 3 application to access SIGNOR data

SUMMARY

SIGNORApp is a Cytoscape 3 (3.8 and later) application that provides access to causal interactions annotated in the SIGNOR resource. The application builds networks that can be represented as weighted, signed, directed graphs, where nodes are interacting biological entities and edges represent causal interactions captured by expert curators from experiments reported in peer reviewed journals. Users can query the SIGNOR dataset with (i) single or multiple entity name(s) or identifier(s) and optionally they may require to include in the output network their interacting partners, (ii) browse pathways that are annotated in the SIGNOR resource and (iii) extract the entire causal interactome. The app offers two visualizations modes: one only displaying entity interactions and a second emphasizing the post-translational modifications occurring as a consequence of the interaction. In addition, users can click on nodes and edges to access entity and interaction annotations. Causal information is available for three model organisms: Homo sapiens, Mus musculus and Rattus norvegicus.

AVAILABILITY AND IMPLEMENTATION

SIGNORApp has been developed for Cytoscape 3 (3.8 and later) in the Java programming language. The latest source code and the plugin can be found at: https://github.com/SIGNORcysAPP/signor-app and https://apps.cytoscape.org/apps/signorapp, respectively.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mitochondrial complex I inhibitors suppress tumor growth through concomitant acidification of the intra- and extracellular environment

The disruption of the tumor microenvironment (TME) is a promising anti-cancer strategy, but its effective targeting for solid tumors remains unknown. Here, we investigated the anti-cancer activity of the mitochondrial complex I inhibitor intervenolin (ITV), which modulates the TME independent of energy depletion. By modulating lactate metabolism, ITV induced the concomitant acidification of the intra- and extracellular environment, which synergistically suppressed S6K1 activity in cancer cells through protein phosphatase-2A-mediated dephosphorylation via G-protein-coupled receptor(s). Other complex I inhibitors including metformin and rotenone were also found to exert the same effect through an energy depletion-independent manner as ITV. In mouse and patient-derived xenograft models, ITV was found to suppress tumor growth and its mode of action was further confirmed. The TME is usually acidic owing to glycolytic cancer cell metabolism, and this condition is more susceptible to complex I inhibitors. Thus, we have demonstrated a potential treatment strategy for solid tumors.

Capturing the third dimension in drug discovery: Spatially-resolved tools for interrogation of complex 3D cell models

Advanced three-dimensional (3D) cell models have proven to be capable of depicting architectural and microenvironmental features of several tissues. By providing data of higher physiological and pathophysiological relevance, 3D cell models have been contributing to a better understanding of human development, pathology onset and progression mechanisms, as well as for 3D cell-based assays for drug discovery. Nonetheless, the characterization and interrogation of these tissue-like structures pose major challenges on the conventional analytical methods, pushing the development of spatially-resolved technologies. Herein, we review recent advances and pioneering technologies suitable for the interrogation of multicellular 3D models, while capable of retaining biological spatial information. We focused on imaging technologies and omics tools, namely transcriptomics, proteomics and metabolomics. The advantages and shortcomings of these novel methodologies are discussed, alongside the opportunities to intertwine data from the different tools.

Pretreatment with metformin prevents microcystin-LR-induced tau hyperphosphorylation via mTOR-dependent PP2A and GSK-3β activation

Microcystin-leucine-arginine (MC-LR) is a toxin secreted by freshwater cyanobacteria that is considered a potential environmental risk factor for Alzheimer's disease (AD). A previous study indicated that tau protein hyperphosphorylation via protein phosphatase 2A (PP2A) and GSK-3β inhibition was the mechanism by which MC-LR induces neurotoxicity; however, how MC-LR-induced neurotoxicity can be effectively prevented remains unclear. In this study, the reversal effect of metformin on MC-LR-induced neurotoxicity was investigated. The results showed that metformin effectively prevented tau hyperphosphorylation at Ser202 caused by MC-LR through PP2A and GSK-3b activity. The effect of metformin on PP2A activity was dependent on the inhibition of mTOR in MC-LR-treated SH-SY5Y cells. Metformin prevented spatial memory deficits in rats caused by intrahippocampal MC-LR administration. In sum, the results suggested that metformin can ameliorate the MC-LR-induced AD-like phenotype by preventing tau phosphorylation at Ser202, which was mainly mediated by mTOR-dependent PP2A and GSK-3β activation.

Metformin and arsenic trioxide synergize to trigger Parkin/pink1-dependent mitophagic cell death in human cervical cancer HeLa cells

Mitochondria are involved in various biological processes including intracellular homeostasis, proliferation, senescence, and death, and mitochondrial mitophagy is closely related to the development and regression of malignant tumors. Recent studies confirmed that the hypoglycemic drug metformin (Met) exerted various antitumor effects, protected neural cells, and improved immunity, while arsenic trioxide (ATO) is an effective chemotherapeutic agent for the clinical treatment of leukemia and various solid tumors. However, the possible combined antitumor effects of Met and ATO and their cellular molecular mechanisms are unclear. We investigated the role of Parkin-mediated mitochondrial mitophagy in the anti-tumor mechanism of Met and ATO by studying the effects of Met and/or ATO on the proliferation and apoptosis of cervical cancer HeLa cells. Both Met and ATO effectively inhibited the proliferative activity of HeLa cells and induced apoptosis by activating Bax and inhibiting Bcl-2. Met and ATO treatment alone or in combination stimulated mitophagosome accumulation in HeLa cells, increased the conversion of microtubule-associated protein light chain 3 (LC3)-I to LC3-II, and decreased levels of the mitophagic lysosomal substrate protein P62. The mitochondrial membrane potential of HeLa cells also decreased, accompanied by activation of the mitochondrial translocase TOM system and the Pink1/Parkin signaling pathway. These results suggested that Met and/or ATO could induce mitophagy in HeLa cells via the Pink1/Parkin signaling pathway, leading to mitophagic apoptosis and inhibition of tumor cell proliferation. The combination of Met and ATO thus has enhanced antitumor effects, suggesting that this combination has potential clinical applications for the treatment of cervical cancer and other tumors.

Metformin exerts anti-AR-negative prostate cancer activity via AMPK/autophagy signaling pathway

BACKGROUND

Encouraged by the goal of developing an effective treatment strategy for prostate cancer, this study explored the mechanism involved in metformin-mediated inhibition of AR-negative prostate cancer.

METHODS

Cell behaviors of DU145 and PC3 cells were determined by CCK8 test, colony formation experiment and scratch test. Flow cytometry was used to detect cell cycle distribution. Cell autophagy was induced with metformin, and an autophagy inhibitor, 3-MA, was used to assess the level of autophagy. Detection of LC3B by immunofluorescence was conducted to determine autophagy level. Cell proliferation, autophagy and cell cycle were examined by performing Western blot. DU145 and PC3 cell lines were transfected with AMPK siRNA targeting AMPK-α1 and AMPK-α2. Tumor formation experiment was carried out to evaluate the anti-prostate cancer effect of metformin in vivo.

RESULTS

The inhibitory effect of metformin on the proliferation of prostate cancer cell lines was confirmed in this study, and the mechanism of such an effect was related to autophagy and the block of cell cycle at G0/G1 phase. Metformin also induced the activation of AMPK, markedly promoted expression of LC3II, and down-regulated the expression of p62/SQSTM1. Animal experiments showed that the tumor volume of metformin group was smaller, meanwhile, the levels of p-AMPK (Thr172) and LC3B were up-regulated and the Ki-67 level was down-regulated, without abnormalities in biochemical indicators.

CONCLUSION

This study found that autophagy induction might be the mechanism through which metformin suppressed the growth of AR-negative prostate cancer. Moreover, the activation of AMPK/autophagy pathway might be a therapeutically effective for treating AR-negative prostate cancer in the future.

Biguanides drugs: Past success stories and promising future for drug discovery

Biguanides have attracted much attention a century ago and showed resurgent interest in recent years after a long period of dormancy. They constitute an important class of therapeutic agents suitable for the treatment of a wide spectrum of diseases. Therapeutic indications of biguanides include antidiabetic, antimalarial, antiviral, antiplaque, and bactericidal applications. This review presents an extensive overview of the biological activity of biguanides and different mechanisms of action of currently marketed biguanide-containing drugs, as well as their pharmacological properties when applicable. We highlight the recent developments in research on biguanide compounds, with a primary focus on studies on metformin in the field of oncology. We aim to provide a critical overview of all main bioactive biguanide compounds and discuss future perspectives for the design of new drugs based on the biguanide fragment.

Proteomic Analysis Reveals That Metformin Suppresses PSMD2, STIP1, and CAP1 for Preventing Gastric Cancer AGS Cell Proliferation and Migration

Metformin is one of the most widely used anti-diabetic drugs in type-II diabetes treatment. The mechanism of decreasing blood glucose is believed to suppress hepatic gluconeogenesis by increasing muscular glucose uptake and insulin sensitivity. Recent studies suggest that metformin may reduce cancer risk; however, its anticancer mechanism in gastric cancers remains unclear. Here, we aim to evaluate the anticancer effects of metformin on human gastric adenocarcinoma (AGS) cells. Our results showed that metformin inhibited AGS cell proliferation in a dose-dependent manner. Using small-scale quantitative proteomics, we identified 177 differentially expressed proteins upon metformin treatment; among these, nine proteins such as 26S proteasome non-ATPase regulatory subunit 2 (PSMD2), stress-induced phosphoprotein 1 (STIP1), and adenylyl cyclase-associated protein 1 (CAP1) were significantly altered. We found that metformin induced cell cycle arrest at the G0/G1 phase, suppressed cell migration, and affected cytoskeleton distribution. Additionally, patients with highly expressed PSMD2, STIP1, and CAP1 have a poor clinical outcome. Our study provides a novel view of developing therapies for gastric cancer.

Unsupervised logic-based mechanism inference for network-driven biological processes

Modern analytical techniques enable researchers to collect data about cellular states, before and after perturbations. These states can be characterized using analytical techniques, but the inference of regulatory interactions that explain and predict changes in these states remains a challenge. Here we present a generalizable, unsupervised approach to generate parameter-free, logic-based models of cellular processes, described by multiple discrete states. Our algorithm employs a Hamming-distance based approach to formulate, test, and identify optimized logic rules that link two states. Our approach comprises two steps. First, a model with no prior knowledge except for the mapping between initial and attractor states is built. We then employ biological constraints to improve model fidelity. Our algorithm automatically recovers the relevant dynamics for the explored models and recapitulates key aspects of the biochemical species concentration dynamics in the original model. We present the advantages and limitations of our work and discuss how our approach could be used to infer logic-based mechanisms of signaling, gene-regulatory, or other input-output processes describable by the Boolean formalism.

Measuring pathway database coverage of the phosphoproteome

Protein phosphorylation is one of the best known post-translational mechanisms playing a key role in the regulation of cellular processes. Over 100,000 distinct phosphorylation sites have been discovered through constant improvement of mass spectrometry based phosphoproteomics in the last decade. However, data saturation is occurring and the bottleneck of assigning biologically relevant functionality to phosphosites needs to be addressed. There has been finite success in using data-driven approaches to reveal phosphosite functionality due to a range of limitations. The alternate, more suitable approach is making use of prior knowledge from literature-derived databases. Here, we analysed seven widely used databases to shed light on their suitability to provide functional insights into phosphoproteomics data. We first determined the global coverage of each database at both the protein and phosphosite level. We also determined how consistent each database was in its phosphorylation annotations compared to a global standard. Finally, we looked in detail at the coverage of each database over six experimental datasets. Our analysis highlights the relative strengths and weaknesses of each database, providing a guide in how each can be best used to identify biological mechanisms in phosphoproteomic data.

Disease-specific interactome alterations via epichaperomics: the case for Alzheimer's disease

The increasingly appreciated prevalence of complicated stressor-to-phenotype associations in human disease requires a greater understanding of how specific stressors affect systems or interactome properties. Many currently untreatable diseases arise due to variations in, and through a combination of, multiple stressors of genetic, epigenetic, and environmental nature. Unfortunately, how such stressors lead to a specific disease phenotype or inflict a vulnerability to some cells and tissues but not others remains largely unknown and unsatisfactorily addressed. Analysis of cell- and tissue-specific interactome networks may shed light on organization of biological systems and subsequently to disease vulnerabilities. However, deriving human interactomes across different cell and disease contexts remains a challenge. To this end, this opinion article links stressor-induced protein interactome network perturbations to the formation of pathologic scaffolds termed epichaperomes, revealing a viable and reproducible experimental solution to obtaining rigorous context-dependent interactomes. This article presents our views on how a specialized 'omics platform called epichaperomics may complement and enhance the currently available conventional approaches and aid the scientific community in defining, understanding, and ultimately controlling interactome networks of complex diseases such as Alzheimer's disease. Ultimately, this approach may aid the transition from a limited single-alteration perspective in disease to a comprehensive network-based mindset, which we posit will result in precision medicine paradigms for disease diagnosis and treatment.

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.

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

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

Epstein-Barr Virus LMP1 Modulates the CD63 Interactome

Tetraspanin CD63 is a cluster of cell surface proteins with four transmembrane domains; it is associated with tetraspanin-enriched microdomains and typically localizes to late endosomes and lysosomes. CD63 plays an important role in the cellular trafficking of different proteins, EV cargo sorting, and vesicle formation. We have previously shown that CD63 is important in LMP1 trafficking to EVs, and this also affects LMP1-mediated intracellular signaling including MAPK/ERK, NF-κB, and mTOR activation. Using the BioID method combined with mass spectrometry, we sought to define the broad CD63 interactome and how LMP1 modulates this network of interacting proteins. We identified a total of 1600 total proteins as a network of proximal interacting proteins to CD63. Biological process enrichment analysis revealed significant involvement in signal transduction, cell communication, protein metabolism, and transportation. The CD63-only interactome was enriched in Rab GTPases, SNARE proteins, and sorting nexins, while adding LMP1 into the interactome increased the presence of signaling and ribosomal proteins. Our results showed that LMP1 alters the CD63 interactome, shifting the network of protein enrichment from protein localization and vesicle-mediated transportation to metabolic processes and translation. We also show that LMP1 interacts with mTOR, Nedd4 L, and PP2A, indicating the formation of a multiprotein complex with CD63, thereby potentially regulating LMP1-dependent mTOR signaling. Collectively, the comprehensive analysis of CD63 proximal interacting proteins provides insights into the network of partners required for endocytic trafficking and extracellular vesicle cargo sorting, formation, and secretion.

Metformin Increases Protein Phosphatase 2A Activity in Primary Human Skeletal Muscle Cells Derived from Lean Healthy Participants

OBJECTIVE

To investigate if PP2A plays a role in metformin-induced insulin sensitivity improvement in human skeletal muscle cells. Participants. Eight lean insulin-sensitive nondiabetic participants (4 females and 4 males; age: 21.0 ± 1.0 years; BMI: 22.0 ± 0.7 kg/m²; 2-hour OGTT: 97.0 ± 6.0 mg/dl; HbA1c: 5.3 ± 0.1%; fasting plasma glucose: 87.0 ± 2.0 mg/dl; M value; 11.0 ± 1.0 mg/kgBW/min).

DESIGN

A hyperinsulinemic-euglycemic clamp was performed to assess insulin sensitivity in human subjects, and skeletal muscle biopsy samples were obtained. Primary human skeletal muscle cells (shown to retain metabolic characteristics of donors) were cultured from these muscle biopsies that included 8 lean insulin-sensitive participants. Cultured cells were expanded, differentiated into myotubes, and treated with 50 μM metformin for 24 hours before harvesting. PP2Ac activity was measured by a phosphatase activity assay kit (Millipore) according to the manufacturer's protocol.

RESULTS

The results indicated that metformin significantly increased the activity of PP2A in the myotubes for all 8 lean insulin-sensitive nondiabetic participants, and the average fold increase is 1.54 ± 0.11 (P < 0.001).

CONCLUSIONS

These results provided the first evidence that metformin can activate PP2A in human skeletal muscle cells derived from lean healthy insulin-sensitive participants and may help to understand metformin's action in skeletal muscle in humans.

Proteome-wide Analysis Reveals Substrates of E3 Ligase RNF146 Targeted for Degradation

Specific E3 ligases target tumor suppressors for degradation. Inhibition of such E3 ligases may be an important approach to cancer treatment. RNF146 is a RING domain and PARylation-dependent E3 ligase that functions as an activator of the β-catenin/Wnt and YAP/Hippo pathways by targeting the degradation of several tumor suppressors. Tankyrases 1 and 2 (TNKS1/2) are the only known poly-ADP-ribosyltransferases that require RNF146 to degrade their substrates. However, systematic identification of RNF146 substrates have not yet been performed. To uncover substrates of RNF146 that are targeted for degradation, we generated RNF146 knockout cells and TNKS1/2-double knockout cells and performed proteome profiling with label-free quantification as well as transcriptome analysis. We identified 160 potential substrates of RNF146, which included many known substrates of RNF146 and TNKS1/2 and 122 potential TNKS-independent substrates of RNF146. In addition, we validated OTU domain-containing protein 5 and Protein mono-ADP-ribosyltransferase PARP10 as TNKS1/2-independent substrates of RNF146 and SARDH as a novel substrate of TNKS1/2 and RNF146. Our study is the first proteome-wide analysis of potential RNF146 substrates. Together, these findings not only demonstrate that proteome profiling can be a useful general approach for the systemic identification of substrates of E3 ligases but also reveal new substrates of RNF146, which provides a resource for further functional studies.

Proteomics Profiling of KAIMRC1 in Comparison to MDA-MB231 and MCF-7

Proteomics characterization of KAIMRC1 cell line, a naturally immortalized breast cancer cells, is described in comparison to MCF-7 and MDA-MB-231 breast cancer cells. Quantitative proteomics analysis using the tandem mass tag (TMT)-labeled technique in conjunction with the phosphopeptide enrichment method was used to perform comparative profiling of proteins and phosphoproteins in the three cell lines. In total, 673 proteins and 33 Phosphoproteins were differentially expressed among these cell lines. These proteins are involved in several key cellular pathways that include DNA replication and repair, splicing machinery, amino acid metabolism, cellular energy, and estrogen signaling pathway. Many of the differentially expressed proteins are associated with different types of tumors including breast cancer. For validation, 4 highly significant expressed proteins including S-methyl-5'-thioadenosine phosphorylase (MTAP), BTB/POZ domain-containing protein (KCTD12), Poly (ADP-ribose) polymerase 1 (PARP 1), and Prelamin-A/C were subjected to western blotting, and the results were consistent with proteomics analysis. Unlike MCF-7 and MDA-MB-231, KAIMRC1 showed different phospho- and non-phosphoproteomic phenotypes which make it a potential model to study breast cancer.

Metabolic reprogramming of fibro/adipogenic progenitors facilitates muscle regeneration

High-fat diet ameliorates muscle dystrophic phenotype by promoting the FAP-dependent myogenesis of satellite cells.

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

Pediatric Clinical Endpoint and Pharmacodynamic Biomarkers: Limitations and Opportunities

Medical research in children typically lags behind that of adult research in both quantity and quality. The conduct of rigorous clinical trials in children can raise ethical concerns because of children's status as a 'vulnerable' population. Moreover, carrying out studies in pediatrics also requires logistical considerations that rarely occur with adult clinical trials. Due to the relatively smaller number of pediatric studies to support evidence-based medicine, the practice of medicine in children is far more reliant upon expert opinion than in adult medicine. Children are at risk of not receiving the same level of benefits from precision medicine research, which has flourished with new technologies capable of generating large amounts of data quickly at an individual level. Although progress has been made in pediatric pharmacokinetics, which has led to safer and more effective dosing, gaps in knowledge still exists when it comes to characterization of pediatric disease and differences in pharmacodynamic response between children and adults. This review highlights three specific therapeutic areas where biomarker development can enhance precision medicine in children: asthma, type 2 diabetes mellitus, and pain. These 'case studies' are meant to update the reader on biomarkers used currently in the diagnosis and treatment of these conditions, and their shortcomings within a pediatric context. Current research on surrogate endpoints and pharmacodynamic biomarkers in the above therapeutic areas will also be described. These cases highlight the current lack in pediatric specific surrogate endpoints and pharmacodynamic biomarkers, as well as the research presently being conducted to address these deficiencies. We finally briefly highlight other therapeutic areas where further research in pediatric surrogate endpoints and pharmacodynamic biomarkers can be impactful to the care of children.

Comprehensive Proteomic Characterization Reveals Subclass-Specific Molecular Aberrations within Triple-negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer lacking targeted therapies. This is attributed to its high heterogeneity that complicates elucidation of its molecular aberrations. Here, we report identification of specific proteome expression profiles pertaining to two TNBC subclasses, basal A and basal B, through in-depth proteomics analysis of breast cancer cells. We observed that kinases and proteases displayed unique expression patterns within the subclasses. Systematic analyses of protein-protein interaction and co-regulation networks of these kinases and proteases unraveled dysregulated pathways and plausible targets for each TNBC subclass. Among these, we identified kinases AXL, PEAK1, and TGFBR2 and proteases FAP, UCHL1, and MMP2/14 as specific targets for basal B subclass, which represents the more aggressive TNBC cell lines. Our study highlights intricate mechanisms and distinct targets within TNBC and emphasizes that these have to be exploited in a subclass-specific manner rather than a one-for-all TNBC therapy.

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Proteome profiling reveals functionally distinct subclasses within TNBC

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Kinases and proteases underlie unique functional signatures among the subclasses

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Kinase-protease-centric networks highlight subclass-specific molecular rewiring

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Protein association dysregulations reveal TNBC subclass-specific protein targets

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.

Metformin strongly affects transcriptome of peripheral blood cells in healthy individuals

Metformin is a commonly used antihyperglycaemic agent for the treatment of type 2 diabetes mellitus. Nevertheless, the exact mechanisms of action, underlying the various therapeutic effects of metformin, remain elusive. The goal of this study was to evaluate the alterations in longitudinal whole-blood transcriptome profiles of healthy individuals after a one-week metformin intervention in order to identify the novel molecular targets and further prompt the discovery of predictive biomarkers of metformin response. Next generation sequencing-based transcriptome analysis revealed metformin-induced differential expression of genes involved in intestinal immune network for IgA production and cytokine-cytokine receptor interaction pathways. Significantly elevated faecal sIgA levels during administration of metformin, and its correlation with the expression of genes associated with immune response (CXCR4, HLA-DQA1, MAP3K14, TNFRSF21, CCL4, ACVR1B, PF4, EPOR, CXCL8) supports a novel hypothesis of strong association between metformin and intestinal immune system, and for the first time provide evidence for altered RNA expression as a contributing mechanism of metformin's action. In addition to universal effects, 4 clusters of functionally related genes with a subject-specific differential expression were distinguished, including genes relevant to insulin production (HNF1B, HNF1A, HNF4A, GCK, INS, NEUROD1, PAX4, PDX1, ABCC8, KCNJ11) and cholesterol homeostasis (APOB, LDLR, PCSK9). This inter-individual variation of the metformin effect on the transcriptional regulation goes in line with well-known variability of the therapeutic response to the drug.

Systems biology based drug repositioning for development of cancer therapy

Drug repositioning is a powerful method that can assists the conventional drug discovery process by using existing drugs for treatment of a disease rather than its original indication. The first examples of repurposed drugs were discovered serendipitously, however data accumulated by high-throughput screenings and advancements in computational biology methods have paved the way for rational drug repositioning methods. As chemotherapeutic agents have notorious side effects that significantly reduce quality of life, drug repositioning promises repurposed noncancer drugs with little or tolerable adverse effects for cancer patients. Here, we review current drug-related data types and databases including some examples of web-based drug repositioning tools. Next, we describe systems biology approaches to be used in drug repositioning for effective cancer therapy. Finally, we highlight examples of mostly repurposed drugs for cancer treatment and provide an overview of future expectations in the field for development of effective treatment strategies.

Phosphoproteomics Reveals the GSK3-PDX1 Axis as a Key Pathogenic Signaling Node in Diabetic Islets

Progressive decline of pancreatic beta cell function is central to the pathogenesis of type 2 diabetes. Protein phosphorylation regulates glucose-stimulated insulin secretion from beta cells, but how signaling networks are remodeled in diabetic islets in vivo remains unknown. Using high-sensitivity mass spectrometry-based proteomics, we quantified 6,500 proteins and 13,000 phosphopeptides in islets of obese diabetic mice and matched controls, revealing drastic remodeling of key kinase hubs and signaling pathways. Integration with a literature-derived signaling network implicated GSK3 kinase in the control of the beta cell-specific transcription factor PDX1. Deep phosphoproteomic analysis of human islets chronically treated with high glucose demonstrated a conserved glucotoxicity-dependent role of GSK3 kinase in regulating insulin secretion. Remarkably, the ability of beta cells to secrete insulin in response to glucose was rescued almost completely by pharmacological inhibition of GSK3. Thus, our resource enables investigation of mechanisms and drug targets in type 2 diabetes.

Fibro-adipogenic progenitors of dystrophic mice are insensitive to NOTCH regulation of adipogenesis

Fibro-adipogenic progenitors (FAPs) promote satellite cell differentiation in adult skeletal muscle regeneration. However, in pathological conditions, FAPs are responsible for fibrosis and fatty infiltrations. Here we show that the NOTCH pathway negatively modulates FAP differentiation both in vitro and in vivo. However, FAPs isolated from young dystrophin-deficient mdx mice are insensitive to this control mechanism. An unbiased mass spectrometry-based proteomic analysis of FAPs from muscles of wild-type and mdx mice suggested that the synergistic cooperation between NOTCH and inflammatory signals controls FAP differentiation. Remarkably, we demonstrated that factors released by hematopoietic cells restore the sensitivity to NOTCH adipogenic inhibition in mdx FAPs. These results offer a basis for rationalizing pathological ectopic fat infiltrations in skeletal muscle and may suggest new therapeutic strategies to mitigate the detrimental effects of fat depositions in muscles of dystrophic patients.

From clinic to mechanism: Proteomics-based assessment of angiogenesis in adrenal pheochromocytoma

Adrenal pheochromocytoma (PCC) is a very rare tumor that stems from chromaffin cells, which can develop into malignant tumor. During the operation, abundant blood vessels were often observed in PCC than other adrenal tumors, which increases the difficulty and risk of the surgery. Therefore, it is important to investigate the mechanism of PCC angiogenesis. Twelve surgical specimens of PCC from Ruijin Hospital, Shanghai Jiaotong University were grouped into high and low microvessel density (MVD) group. They were also divided into rich blood supply and nonenriched blood supply group, according to computed tomography (CT) manifestation. Comparative proteomic analysis based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) and bioinformatics analysis revealed that 206 proteins differentially regulated in the high MVD group compared with low MVD group (p < 0.05). Besides, 61 proteins were discovered to be significantly changed when the 12 samples were grouped according to CT manifestation. By intersecting the differentially changed protein from MVD and CT grouping, 25 proteins were filtered out, with pathological function. COX4I2 was verified to be increased gradually with angiogenesis with increasing severity, and PLAT was shown to be decreased with angiogenesis in PCC, by quantitative reverse-transcription polymerase chain reaction and immunohistochemistry. The quantitative proteomics result indicated that the tumor angiogenesis in PCC is associated with hypoxia. COX4I2 and PLAT were highly correlated with blood supply in PCC which contribute to angiogenesis in PCC, which could be used as biomarkers to better indicate tumor angiogenesis, or targets to regress tumor angiogenesis as treatment.

Metformin Delays Satellite Cell Activation and Maintains Quiescence

The regeneration of the muscle tissue relies on the capacity of the satellite stem cell (SC) population to exit quiescence, divide asymmetrically, proliferate, and differentiate. In age-related muscle atrophy (sarcopenia) and several dystrophies, regeneration cannot compensate for the loss of muscle tissue. These disorders are associated with the depletion of the satellite cell pool or with the loss of satellite cell functionality. Recently, the establishment and maintenance of quiescence in satellite cells have been linked to their metabolic state. In this work, we aimed to modulate metabolism in order to preserve the satellite cell pool. We made use of metformin, a calorie restriction mimicking drug, to ask whether metformin has an effect on quiescence, proliferation, and differentiation of satellite cells. We report that satellite cells, when treated with metformin in vitro, ex vivo, or in vivo, delay activation, Pax7 downregulation, and terminal myogenic differentiation. We correlate the metformin-induced delay in satellite cell activation with the inhibition of the ribosome protein RPS6, one of the downstream effectors of the mTOR pathway. Moreover, in vivo administration of metformin induces a belated regeneration of cardiotoxin- (CTX-) damaged skeletal muscle. Interestingly, satellite cells treated with metformin immediately after isolation are smaller in size and exhibit reduced pyronin Y levels, which suggests that metformin-treated satellite cells are transcriptionally less active. Thus, our study suggests that metformin delays satellite cell activation and differentiation by favoring a quiescent, low metabolic state.

Combining Phosphoproteomics Datasets and Literature Information to Reveal the Functional Connections in a Cell Phosphorylation Network

Protein phosphorylation modulates many biological processes. However, the characterization of the complex regulatory circuits underlying cell response to external and internal stimuli is still limited by our inability to describe the phosphorylation network on a global scale. Modern MS-based phosphoproteomics allows monitoring tens of thousands of phosphorylation sites in multiple conditions, making the approach ideal to explore signaling pathways mediated by phosphorylation. Here, we review recent advances in phosphoproteomics and discuss some of the computational approaches developed to facilitate extraction of signaling information from these datasets. Finally, this review focuses on approaches that integrate prior literature information with unbiased phosphoproteomics experiments.

Metformin Inhibit Lung Cancer Cell Growth and Invasion in Vitro as Well as Tumor Formation in Vivo Partially by Activating PP2A

Background

The aim of this study was to investigate whether PP2A activation is involved in the anti-cancer activity of metformin.

Material/Methods

A549 and H1651 human lung cancer cells were constructed with stable α4 overexpression (O/E α4) or knockdown of PP2A catalytic subunit A/B(sh-PP2Ac). Influences of okadaic acid (OA) treatment, O/E α4 or sh-PP2Ac on metformin treated cells were investigated by cell viability, proliferation, apoptosis, and Transwell invasion assay in vitro. Protein expression levels of Bax, Bcl-2, Myc, and Akt as well as serine phosphorylation level of Bax, Myc, and Akt were examined by western blot. For in vivo assays, wild type (WT) or modified A549 cells were subcutaneously injected in nude mice, and metformin treatment on these xenografted tumors were assayed by tumor formation assay and western blot detecting cell proliferation marker PCNA (proliferating cell nuclear antigen) as well as protein expression level and serine phosphorylation level of Akt and Myc.

Results

Metformin treatment significantly reduced A549 or H1651 cell growth and invasive capacity in vitro as well as Ser184 phosphorylation of Bax, Ser62 phosphorylation of Myc, and Ser473 phosphorylation of Akt, all of which could be partially attenuated by OA treatment, O/E α4 or sh-PP2Ac. Metformin treatment also significantly reduced tumor formation in vivo as well as protein expression of PCNA, Akt, Myc, and serine phosphorylation of the latter 2, which can be partially blocked by O/E α4 or sh-PP2Ac.

Conclusions

Metformin reduced lung cancer cell growth and invasion in vitro as well as tumor formation in vivo partially by activating PP2A.

Reconstruction of global regulatory network from signaling to cellular functions using phosphoproteomic data

Cellular signaling regulates various cellular functions via protein phosphorylation. Phosphoproteomic data potentially include information for a global regulatory network from signaling to cellular functions, but a procedure to reconstruct this network using such data has yet to be established. In this paper, we provide a procedure to reconstruct a global regulatory network from signaling to cellular functions from phosphoproteomic data by integrating prior knowledge of cellular functions and inference of the kinase-substrate relationships (KSRs). We used phosphoproteomic data from insulin-stimulated Fao hepatoma cells and identified protein phosphorylation regulated by insulin specifically over-represented in cellular functions in the KEGG database. We inferred kinases for protein phosphorylation by KSRs, and connected the kinases in the insulin signaling layer to the phosphorylated proteins in the cellular functions, revealing that the insulin signal is selectively transmitted via the Pi3k-Akt and Erk signaling pathways to cellular adhesions and RNA maturation, respectively. Thus, we provide a method to reconstruct global regulatory network from signaling to cellular functions based on phosphoproteomic data.

In silico polypharmacology of natural products

Natural products with polypharmacological profiles have demonstrated promise as novel therapeutics for various complex diseases, including cancer. Currently, many gaps exist in our knowledge of which compounds interact with which targets, and experimentally testing all possible interactions is infeasible. Recent advances and developments of systems pharmacology and computational (in silico) approaches provide powerful tools for exploring the polypharmacological profiles of natural products. In this review, we introduce recent progresses and advances of computational tools and systems pharmacology approaches for identifying drug targets of natural products by focusing on the development of targeted cancer therapy. We survey the polypharmacological and systems immunology profiles of five representative natural products that are being considered as cancer therapies. We summarize various chemoinformatics, bioinformatics and systems biology resources for reconstructing drug-target networks of natural products. We then review currently available computational approaches and tools for prediction of drug-target interactions by focusing on five domains: target-based, ligand-based, chemogenomics-based, network-based and omics-based systems biology approaches. In addition, we describe a practical example of the application of systems pharmacology approaches by integrating the polypharmacology of natural products and large-scale cancer genomics data for the development of precision oncology under the systems biology framework. Finally, we highlight the promise of cancer immunotherapies and combination therapies that target tumor ecosystems (e.g. clones or 'selfish' sub-clones) via exploiting the immunological and inflammatory 'side' effects of natural products in the cancer post-genomics era.

Context-enriched interactome powered by proteomics helps the identification of novel regulators of macrophage activation

The role of pro-inflammatory macrophage activation in cardiovascular disease (CVD) is a complex one amenable to network approaches. While an indispensible tool for elucidating the molecular underpinnings of complex diseases including CVD, the interactome is limited in its utility as it is not specific to any cell type, experimental condition or disease state. We introduced context-specificity to the interactome by combining it with co-abundance networks derived from unbiased proteomics measurements from activated macrophage-like cells. Each macrophage phenotype contributed to certain regions of the interactome. Using a network proximity-based prioritization method on the combined network, we predicted potential regulators of macrophage activation. Prediction performance significantly increased with the addition of co-abundance edges, and the prioritized candidates captured inflammation, immunity and CVD signatures. Integrating the novel network topology with transcriptomics and proteomics revealed top candidate drivers of inflammation. In vitro loss-of-function experiments demonstrated the regulatory role of these proteins in pro-inflammatory signaling.

When human cells or tissues are injured, the body triggers a response known as inflammation to repair the damage and protect itself from further harm. However, if the same issue keeps recurring, the tissues become inflamed for longer periods of time, which may ultimately lead to health problems. This is what could be happening in cardiovascular diseases, where long-term inflammation could damage the heart and blood vessels.

Many different proteins interact with each other to control inflammation; gaining an insight into the nature of these interactions could help to pinpoint the role of each molecular actor. Researchers have used a combination of unbiased, large-scale experimental and computational approaches to develop the interactome, a map of the known interactions between all proteins in humans. However, interactions between proteins can change between cell types, or during disease. Here, Halu et al. aimed to refine the human interactome and identify new proteins involved in inflammation, especially in the context of cardiovascular disease.

Cells called macrophages produce signals that trigger inflammation whey they detect damage in other cells or tissues. The experiments used a technique called proteomics to measure the amounts of all the proteins in human macrophages. Combining these data with the human interactome made it possible to predict new links between proteins known to have a role in inflammation and other proteins in the interactome. Further analysis using other sets of data from macrophages helped identify two new candidate proteins – GBP1 and WARS – that may promote inflammation. Halu et al. then used a genetic approach to deactivate the genes and decrease the levels of these two proteins in macrophages, which caused the signals that encourage inflammation to drop.

These findings suggest that GBP1 and WARS regulate the activity of macrophages to promote inflammation. The two proteins could therefore be used as drug targets to treat cardiovascular diseases and other disorders linked to inflammation, but further studies will be needed to precisely dissect how GBP1 and WARS work in humans.

Topological alternate centrality measure capturing drug targets in the network of MAPK pathways

A new centrality of the nodes in the network is proposed called alternate centrality, which can isolate effective drug targets in the complex signalling network. Alternate centrality metric defined over the network substructure (four nodes - motifs). The nodes involving in alternative activation in the motifs gain in metric values. Targeting high alternative centrality nodes hypothesised to be destructive free to the network due to their alternative activation mechanism. Overlapping and crosstalk among the gene products in the conserved network of MAPK pathways selected for the study. In silico knock-out of high alternate centrality nodes causing rewiring in the network is investigated using MCF-7 breast cancer cell line-based data. Degree of top alternate centrality nodes lies between the degree of bridging and pagerank nodes. Node deletion of high alternate centrality on the centralities such as eccentricity, closeness, betweenness, stress, centroid and radiality causes low perturbation. The authors identified the following alternate centrality nodes ERK1, ERK2, MEKK2, MKK5, MKK4, MLK3, MLK2, MLK1, MEKK4, MEKK1, TAK1, P38alpha, ZAK, DLK, LZK, MLTKa/b and P38beta as efficient drug targets for breast cancer. Alternate centrality identifies effective drug targets and is free from intertwined biological processes and lethality.

Recapitulation of Human Neural Microenvironment Signatures in iPSC-Derived NPC 3D Differentiation

Brain microenvironment plays an important role in neurodevelopment and pathology, where the extracellular matrix (ECM) and soluble factors modulate multiple cellular processes. Neural cell culture typically relies on heterologous matrices poorly resembling brain ECM. Here, we employed neurospheroids to address microenvironment remodeling during neural differentiation of human stem cells, without the confounding effects of exogenous matrices. Proteome and transcriptome dynamics revealed significant changes at cell membrane and ECM during 3D differentiation, diverging significantly from the 2D differentiation. Structural proteoglycans typical of brain ECM were enriched during 3D differentiation, in contrast to basement membrane constituents in 2D. Moreover, higher expression of synaptic and ion transport machinery was observed in 3D cultures, suggesting higher neuronal maturation in neurospheroids. This work demonstrates that 3D neural differentiation as neurospheroids promotes the expression of cellular and extracellular features found in neural tissue, highlighting its value to address molecular defects in cell-ECM interactions associated with neurological disorders.

Surfactant and Chaotropic Agent Assisted Sequential Extraction/On-Pellet Digestion (SCAD) for Enhanced Proteomics

As a popular sample preparation approach, filter-aided sample preparation (FASP) has been widely used in proteomic analysis. However, several limitations have been noted, including sample loss during filtration, repetitive centrifugation steps, and the possibility of breakage of filtration membrane. Extraction bias among different sample preparation strategies presents another challenge. To overcome these limitations and address remaining challenges, we developed a novel surfactant and chaotropic agent assisted sequential extraction/on-pellet digestion (SCAD) protocol. The new strategy resulted in higher protein yield and improved peptide recovery and protein coverage compared to two conventional sample preparation methods (FASP and urea). In combination of three strategies, more than 10,000 distinct protein groups were identified with 1% FDR from MDA-MB-231 cells without any prefractionation. This in-depth proteome analysis was accomplished by optimization of protein extraction, enzymatic digestion, LC gradient, and peptide sequencing method. Ingenuity Pathways Analysis (IPA) of proteins exclusively identified in SCAD revealed several crucial signaling pathways that regulate breast cancer progression. SCAD also enabled an unbiased extraction of different categories of proteins (membrane, intracellular, nuclear) associated with tumorigenesis, which integrates the advantages of FASP and urea extraction. This novel strategy expedites comprehensive protein identification, which is applicable for biomarker discovery in various types of cancers.

Proteomic Profiling of Hsp90 Inhibitors

Mass spectrometry assays demonstrate that Hsp90 inhibitors alter the expression of approximately one-quarter of the assayable proteome in mammalian cells. These changes are extraordinarily robust and reproducible, making "proteomics profiling" the gold standard for validating the effects of new Hsp90 inhibitors on cultured cells. Proteomics assays can also suggest novel hypotheses regarding drug mechanisms. To assist investigators in adopting this approach, this Chapter provides detailed protocols for conducting simple proteomics assays of Hsp90 inhibition. The protocols present a robust label-free approach that utilizes pre-fractionation of protein samples by SDS-PAGE, thereby providing reasonably good penetration into the proteome while addressing common issues with sample quality. The actual programming and operation of liquid chromatography-tandem mass spectrometers is not covered, but expectations for achievable performance are discussed, as are alternative approaches, common challenges, and software for data analysis.