Proteomics of microparticles with SILAC Quantification (PROMIS-Quan): a novel proteomic method for plasma biomarker quantification

Neat plasma proteomics: getting the best out of the worst

Plasma proteomics holds immense potential for clinical research and biomarker discovery, serving as a non-invasive "liquid biopsy" for tissue sampling. Mass spectrometry (MS)-based proteomics, thanks to improvement in speed and robustness, emerges as an ideal technology for exploring the plasma proteome for its unbiased and highly specific protein identification and quantification. Despite its potential, plasma proteomics is still a challenge due to the vast dynamic range of protein abundance, hindering the detection of less abundant proteins. Different approaches can help overcome this challenge. Conventional depletion methods face limitations in cost, throughput, accuracy, and off-target depletion. Nanoparticle-based enrichment shows promise in compressing dynamic range, but cost remains a constraint. Enrichment strategies for extracellular vesicles (EVs) can enhance plasma proteome coverage dramatically, but current methods are still too laborious for large series. Neat plasma remains popular for its cost-effectiveness, time efficiency, and low volume requirement. We used a test set of 33 plasma samples for all evaluations. Samples were digested using S-Trap and analyzed on Evosep One and nanoElute coupled to a timsTOF Pro using different elution gradients and ion mobility ranges. Data were mainly analyzed using library-free searches using DIA-NN. This study explores ways to improve proteome coverage in neat plasma both in MS data acquisition and MS data analysis. We demonstrate the value of sampling smaller hydrophilic peptides, increasing chromatographic separation, and using library-free searches. Additionally, we introduce the EV boost approach, that leverages on the extracellular vesicle fraction to enhance protein identification in neat plasma samples. Globally, our optimized analysis workflow allows the quantification of over 1000 proteins in neat plasma with a 24SPD throughput. We believe that these considerations can be of help independently of the LC-MS platform used.

Tumor-derived microvesicles for cancer therapy

Extracellular vesicles (EVs) are vesicles with lipid bilayer structures shed from the plasma membrane of cells. Microvesicles (MVs) are a subset of EVs containing proteins, lipids, nucleic acids, and other metabolites. MVs can be produced under specific cell stimulation conditions and isolated by modern separation technology. Due to their tumor homing and large volume, tumor cell-derived microvesicles (TMVs) have attracted interest recently and become excellent delivery carriers for therapeutic vaccines, imaging agents or antitumor drugs. However, preparing sufficient and high-purity TMVs and conducting clinical transformation has become a challenge in this field. In this review, the recent research achievements in the generation, isolation, characterization, modification, and application of TMVs in cancer therapy are reviewed, and the challenges facing therapeutic applications are also highlighted.

Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10-12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.

Monitoring drug metabolic pathways through extracellular vesicles in mouse plasma

The ability to monitor the response of metabolic enzymes to drug exposure in individuals is highly appealing and critical to personalized medicine. Although pharmacogenomics assesses genotypic differences, it does not report changes in metabolic enzyme activities due to environmental factors such as drug interactions. Here, we report a quantitative proteomics strategy to monitor drug metabolic pathways by profiling metabolic enzymes in circulating extracellular vesicles (EVs) upon drug exposure. Mass spectrometry (MS)-based measurement revealed that changes in metabolic enzyme abundance in EVs paralleled those in hepatic cells isolated from liver tissue. Coupling with multiplexed isotopic labeling, we temporally quantified 34 proteins involved in drug absorption, distribution, metabolism, and excretion (ADME) pathways. Out of 44 known ADME proteins in plasma EVs, previously annotated mouse cytochrome P450 3A11 (Cyp3a11), homolog to human CYP3A4, and uridine 5'-diphospho (UDP) glucuronosyltransferase 2A3 (Ugt2a3), increased upon daily rifampicin dosage. Dasatinib, a tyrosine kinase inhibitor to treat leukemia, also elevated Cyp3a11 levels in plasma EVs, but to a lesser extent. Altogether, this study demonstrates that measuring drug enzymes in circulating EVs as an effective surrogate is highly feasible and may transform today's drug discovery and development for personalized medicine.

Deep proteomic analysis of obstetric antiphospholipid syndrome by DIA-MS of extracellular vesicle enriched fractions

Proteins in the plasma/serum mirror an individual's physiology. Circulating extracellular vesicles (EVs) proteins constitute a large portion of the plasma/serum proteome. Thus, deep and unbiased proteomic analysis of circulating plasma/serum extracellular vesicles holds promise for discovering disease biomarkers as well as revealing disease mechanisms. We established a workflow for simple, deep, and reproducible proteome analysis of both serum large and small EVs enriched fractions by ultracentrifugation plus 4D-data-independent acquisition mass spectrometry (4D-DIA-MS). In our cohort study of obstetric antiphospholipid syndrome (OAPS), 4270 and 3328 proteins were identified from large and small EVs enriched fractions respectively. Both of them revealed known or new pathways related to OAPS. Increased levels of von Willebrand factor (VWF) and insulin receptor (INSR) were identified as candidate biomarkers, which shed light on hypercoagulability and abnormal insulin signaling in disease progression. Our workflow will significantly promote our understanding of plasma/serum-based disease mechanisms and generate new biomarkers.

Extracellular vesicle biomarkers for prostate cancer diagnosis: A systematic review and meta-analysis

Extracellular vesicle (EV) biomarkers have promising diagnostic and screening capabilities for several cancers, and growing evidence indicates that EV biomarkers can be used as diagnostic markers for prostate cancer (CaP). However, data on the diagnostic accuracy of EV biomarkers for CaP diagnosis are conflicting. We performed a systematic review and meta-analysis, aimed to summarize the diagnostic performance of EV biomarkers for CaP. We systematically searched PubMed, Medline, and Web of Science from inception to 12 September 2022 for studies that assessed the diagnostic accuracy of EV biomarkers for CaP. We summarized the pooled sensitivity and specificity calculated using a random-effects model. We identified 19 studies involving 976 CaP patients and 676 noncancerous controls; one study conducted independent validation tests. Ten studies emphasized EV RNAs, 6 on EV proteins, and 9 on biomarker panels. MiR-141, miR-221, and PSMA were the most frequently reported RNAs and proteins for CaP diagnosis. For individual RNAs and proteins, the pooled sensitivity and specificity were 70% (95% CI: 68%-71%), 79% (95% CI: 77%-80%), 85% (95% CI: 81%-87%), and 83% (95% CI: 80%-86%), respectively. The pooled sensitivity and specificity of the EV panels were 84% (95% CI: 82%-86%) and 86% (95% CI: 84%-88%), respectively. The studies may have been somewhat limited by the EV isolation and detection techniques. EV biomarkers showed promising diagnostic capability for CaP. Addressing deficiencies in EV isolation and detection techniques has important implications for the application of these novel noninvasive biomarkers in clinical practice.

Proteomics of Plasma and Plasma-Treated Podocytes: Application to Focal and Segmental Glomerulosclerosis

Focal and segmental glomerulosclerosis (FSGS) is a severe form of idiopathic nephrotic syndrome (INS), a glomerulopathy of presumably immune origin that is attributed to extrarenal pathogenic circulating factors. The recurrence of FSGS (rFSGS) after transplant occurs in 30% to 50% of cases. The direct analysis of patient plasma proteome has scarcely been addressed to date, mainly due to the methodological difficulties associated with plasma complexity and dynamic range. In this study, first, we compared different methods of plasma preparation, second, we compared the plasma proteomes of rFSGS and controls using two preparation methods, and third, we analyzed the early proximal signaling events in podocytes subjected to patient plasma, through a combination of phosphoproteomics and lipid-raft proteomics (raftomics). By combining immunodepletion and high pH fractionation, we performed a differential proteomic analysis of soluble plasma proteins and of extracellular vesicles (EV) obtained from healthy controls, non-INS patient controls, and rFSGS patients (n = 4). In both the soluble- and the EV-protein sets from the rFSGS patients, we found a statistically significant increase in a cluster of proteins involved in neutrophil degranulation. A group of lipid-binding proteins, generally associated with lipoproteins, was found to be decreased in the soluble set from the rFSGS patients. In addition, three amino acid transporters involved in mTORC1 activation were found to be significantly increased in the EV from the rFSGS. Next, we incubated human podocytes for 30 min with 10% plasma from both groups of patients. The phosphoproteomics and raftomics of the podocytes revealed profound differences in the proteins involved in the mTOR pathway, in autophagy, and in cytoskeleton organization. We analyzed the correlation between the abundance of plasma and plasma-regulated podocyte proteins. The observed changes highlight some of the mechanisms involved in FSGS recurrence and could be used as specific early markers of circulating-factor activity in podocytes.

Oral squamous cell carcinoma-derived EVs promote tumor progression by regulating inflammatory cytokines and the IL-17A-induced signaling pathway

BACKGROUND

Inflammatory cytokines in the tumor microenvironment (TME) contribute to tumor growth, proliferation, and invasion, and tumor-derived extracellular vesicles (EVs) act as critical "messengers" of communication in the tumor microenvironment. The effects of EVs derived from oral squamous cell carcinoma (OSCC) cells on tumor progression and the inflammatory microenvironment are still unclear. Our study aims to investigate the role of OSCC-derived EVs in tumor progression, the imbalanced TME, and immunosuppression and their effect on the IL-17A-induced signaling pathway.

METHODS

EVs were isolated from the supernatant of a mouse OSCC cell line, SCC7. The effects of SCC7-EVs and the EV release-specific inhibitor GW4869 on the proliferation and migration of SCC7 cells were investigated in vitro by using CCK-8 and scratch wound healing assays. RT-qPCR and ELISA were performed to examine the alterations in cytokine levels. Then, a mouse xenograft model of OSCC was established by submucosal injection of SCC7 cells with or without SCC7-EV and GW4869 treatment. The effects of GW4869 and SCC7-EVs on xenograft tumor proliferation and invasion were investigated by tumor volume determination and histopathological examination. ELISA was used to investigate the changes in serum cytokine levels. Immunohistochemistry was adopted to analyze the alterations in the levels of inflammatory cytokines, immune factors, and crucial molecules in the IL-17A signaling pathway.

RESULTS

SCC7-derived EVs increased the supernatant and serum levels of IL-17A, IL-10, IL-1β, and PD-L1, while GW4869 decreased those of TNF-α and IFN-γ. SCC7-EV treatment significantly increased xenograft tumor growth and invasion in mice but resulted in little liquefactive necrosis in tumors. However, GW4869 treatment significantly inhibited xenograft tumor growth but resulted in more liquefactive necrosis. SCC7-derived EVs decreased the expression level of PTPN2, suppressing the immune responses of CD8 + T cells in vivo. Moreover, SCC7-EV treatment significantly enhanced the tumor expression levels of crucial molecules in the IL-17A pathway, including IL-17A, TRAF6 and c-FOS, whereas GW4869 treatment significantly reduced those levels in tumor tissues.

CONCLUSION

Our results indicated that OSCC-derived EVs can promote tumor progression by altering the TME, causing an inflammatory cytokine imbalance, inducing immunosuppression, and contributing to overactivation of the IL-17A-induced signaling pathway. Our study might provide novel insights into the role of OSCC-derived EVs in tumor biological behavior and immune dysregulation.

Biology of the Extracellular Proteasome

Proteasomes are traditionally considered intracellular complexes that play a critical role in maintaining proteostasis by degrading short-lived regulatory proteins and removing damaged proteins. Remarkably, in addition to these well-studied intracellular roles, accumulating data indicate that proteasomes are also present in extracellular body fluids. Not much is known about the origin, biological role, mode(s) of regulation or mechanisms of extracellular transport of these complexes. Nevertheless, emerging evidence indicates that the presence of proteasomes in the extracellular milieu is not a random phenomenon, but rather a regulated, coordinated physiological process. In this review, we provide an overview of the current understanding of extracellular proteasomes. To this end, we examine 143 proteomic datasets, leading us to the realization that 20S proteasome subunits are present in at least 25 different body fluids. Our analysis also indicates that while 19S subunits exist in some of those fluids, the dominant proteasome activator in these compartments is the PA28α/β complex. We also elaborate on the positive correlations that have been identified in plasma and extracellular vesicles, between 20S proteasome and activity levels to disease severity and treatment efficacy, suggesting the involvement of this understudied complex in pathophysiology. In addition, we address the considerations and practical experimental methods that should be taken when investigating extracellular proteasomes. Overall, we hope this review will stimulate new opportunities for investigation and thoughtful discussions on this exciting topic that will contribute to the maturation of the field.

Microparticles: biogenesis, characteristics and intervention therapy for cancers in preclinical and clinical research

Extracellular vesicles (EVs), spherical biological vesicles, mainly contain nucleic acids, proteins, lipids and metabolites for biological information transfer between cells. Microparticles (MPs), a subtype of EVs, directly emerge from plasma membranes, and have gained interest in recent years. Specific cell stimulation conditions, such as ultraviolet and X-rays irradiation, can induce the release of MPs, which are endowed with unique antitumor functionalities, either for therapeutic vaccines or as direct antitumor agents. Moreover, the size of MPs (100–1000 nm) and their spherical structures surrounded by a lipid bilayer membrane allow MPs to function as delivery vectors for bioactive antitumor compounds, with favorable phamacokinetic behavior, immunostimulatory activity and biological function, without inherent carrier-specific toxic side effects. In this review, the mechanisms underlying MP biogenesis, factors that influence MP production, properties of MP membranes, size, composition and isolation methods of MPs are discussed. Additionally, the applications and mechanisms of action of MPs, as well as the main hurdles for their applications in cancer management, are introduced.

Purification and Phosphoproteomic Analysis of Plasma-Derived Extracellular Vesicles

A successful phosphoproteomics analysis of extracellular vesicles (EVs) requires a unique approach, fine-tuned to address the challenges that have plagued plasma-based biomarker discovery. Here, I detail a procedure, which combines EVtrap-based high-recovery EV isolation, phase-transfer surfactant method for protein extraction, and PolyMAC-based enrichment of phosphopeptides. The combination of these methods provides a highly effective strategy for EV-based phosphoproteome analysis and leads to the discovery of novel phospho-markers previously undetectable.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Human body-fluid proteome: quantitative profiling and computational prediction

Empowered by the advancement of high-throughput bio technologies, recent research on body-fluid proteomes has led to the discoveries of numerous novel disease biomarkers and therapeutic drugs. In the meantime, a tremendous progress in disclosing the body-fluid proteomes was made, resulting in a collection of over 15 000 different proteins detected in major human body fluids. However, common challenges remain with current proteomics technologies about how to effectively handle the large variety of protein modifications in those fluids. To this end, computational effort utilizing statistical and machine-learning approaches has shown early successes in identifying biomarker proteins in specific human diseases. In this article, we first summarized the experimental progresses using a combination of conventional and high-throughput technologies, along with the major discoveries, and focused on current research status of 16 types of body-fluid proteins. Next, the emerging computational work on protein prediction based on support vector machine, ranking algorithm, and protein-protein interaction network were also surveyed, followed by algorithm and application discussion. At last, we discuss additional critical concerns about these topics and close the review by providing future perspectives especially toward the realization of clinical disease biomarker discovery.

Multi-Omics Data Integration in Extracellular Vesicle Biology-Utopia or Future Reality?

Extracellular vesicles (EVs) are membranous structures derived from the endosomal system or generated by plasma membrane shedding. Due to their composition of DNA, RNA, proteins, and lipids, EVs have garnered a lot of attention as an essential mechanism of cell-to-cell communication, with various implications in physiological and pathological processes. EVs are not only a highly heterogeneous population by means of size and biogenesis, but they are also a source of diverse, functionally rich biomolecules. Recent advances in high-throughput processing of biological samples have facilitated the development of databases comprised of characteristic genomic, transcriptomic, proteomic, metabolomic, and lipidomic profiles for EV cargo. Despite the in-depth approach used to map functional molecules in EV-mediated cellular cross-talk, few integrative methods have been applied to analyze the molecular interplay in these targeted delivery systems. New perspectives arise from the field of systems biology, where accounting for heterogeneity may lead to finding patterns in an apparently random pool of data. In this review, we map the biological and methodological causes of heterogeneity in EV multi-omics data and present current applications or possible statistical methods for integrating such data while keeping track of the current bottlenecks in the field.

Breast Cancer-Derived Microparticles Reduce Cancer Cell Adhesion, an Effect Augmented by Chemotherapy

Tumor cell heterogeneity is primarily dictated by mutational changes, sometimes leading to clones that undergo a metastatic switch. However, little is known about tumor heterogeneity following chemotherapy perturbation. Here we studied the possible involvement of tumor-derived extracellular vesicles, often referred to as tumor-derived microparticles (TMPs), as mediators of the metastatic switch in the tumor microenvironment by hindering cell adhesion properties. Specifically, we show that highly metastatic or chemotherapy-treated breast cancer cells shed an increased number of TMPs compared to their respective controls. We found that these TMPs substantially reduce cell adhesion and disrupt actin filament structure, therefore increasing their biomechanical force pace, further implicating tumor cell dissemination as part of the metastatic cascade. Our results demonstrate that these pro-metastatic effects are mediated in part by CD44 which is highly expressed in TMPs obtained from highly metastatic cells or cells exposed to chemotherapy when compared to cells with low metastatic potential. Consequently, when we inhibited CD44 expression on TMPs by a pharmacological or a genetic approach, increased tumor cell adhesion and re-organized actin filament structure were observed. We also demonstrated that breast cancer patients treated with paclitaxel chemotherapy exhibited increased CD44-expressing TMPs. Overall, our study provides further insights into the role of TMPs in promoting metastasis, an effect which is augmented when tumor cells are exposed to chemotherapy.

Selectively-Packaged Proteins in Breast Cancer Extracellular Vesicles Involved in Metastasis

Cancer-derived extracellular vesicles are known to play a role in the progression of the disease. In this rapidly-growing field, there are many reports of phenotypic changes in cells following exposure to cancer-derived extracellular vesicles. This study examines the protein contents of vesicles derived from three well-known breast cancer cell lines, MCF-7, MDA-MB-231 and T47D, using peptide-centric LC-MS/MS and cytokine multiplex immunoassay analysis to understand the molecular basis of these changes. Through these techniques a large number of proteins within these vesicles were identified. A large proportion of these proteins are known to be important in cancer formation and progression and associated with cancer signaling, angiogenesis, metastasis and invasion and immune regulation. This highlights the importance of extracellular vesicles (EVs) in cancer communications and shows some of the mechanisms the vesicles use to assist in cancer progression.

PSMD11, PTPRM and PTPRB as novel biomarkers of pancreatic cancer progression

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate of all major cancers. Surgery is the only curative intent therapy, but the majority of patients experience disease relapse. Thus, patients who do not benefit from highly morbid surgical resection needs to be identified and offered palliative chemotherapy instead. In this pilot study, we aimed to identify differentially regulated proteins in plasma and plasma derived microparticles from PDAC patients with poor and good prognosis.

METHODS

Plasma and plasma derived microparticle samples were obtained before surgical resection from PDAC patients. Sequential Windowed Acquisition of all Theoretical fragment ion spectra - Mass Spectrometry (SWATH-MS) proteomic analysis was performed to identify and quantify proteins in these samples. Statistical analysis was performed to identify biomarkers for poor prognosis.

RESULTS

A total of 482 and 1024 proteins were identified from plasma and microparticle samples, respectively, by SWATH-MS analysis. Statistical analysis of the data further identified nine and six differentially (log₂ratio > 1, p < .05) expressed proteins in plasma and microparticles, respectively. Protein tyrosine phosphatases, PTPRM and PTPRB, were decreased in plasma of patients with poor PDAC prognosis, while proteasomal subunit PSMD11 was increased in microparticles of patients with poor prognosis.

CONCLUSION AND GENERAL SIGNIFICANCE

A novel blood-based biomarker signature for PDAC prognosis was identified.

Plasma-Derived Extracellular Vesicle Phosphoproteomics through Chemical Affinity Purification

The invasive nature and the pain caused to patients inhibit the routine use of tissue biopsy-based procedures for cancer diagnosis and surveillance. The analysis of extracellular vesicles (EVs) from biofluids has recently gained significant traction in the liquid biopsy field. EVs offer an essential "snapshot" of their precursor cells in real time and contain an information-rich collection of nucleic acids, proteins, lipids, and so on. The analysis of protein phosphorylation, as a direct marker of cellular signaling and disease progression could be an important stepping stone to successful liquid biopsy applications. Here we introduce a rapid EV isolation method based on chemical affinity called EVtrap (extracellular vesicle total recovery and purification) for the EV phosphoproteomics analysis of human plasma. By incorporating EVtrap with high-performance mass spectrometry (MS), we were able to identify over 16 000 unique peptides representing 2238 unique EV proteins from just 5 μL of plasma sample, including most known EV markers, with substantially higher recovery levels compared with ultracentrifugation. Most importantly, more than 5500 unique phosphopeptides representing almost 1600 phosphoproteins in EVs were identified using only 1 mL of plasma. Finally, we carried out a quantitative EV phosphoproteomics analysis of plasma samples from patients diagnosed with chronic kidney disease or kidney cancer, identifying dozens of phosphoproteins capable of distinguishing disease states from healthy controls. The study demonstrates the potential feasibility of our robust analytical pipeline for cancer signaling monitoring by tracking plasma EV phosphorylation.

Sequential phosphoproteomics and N-glycoproteomics of plasma-derived extracellular vesicles

Extracellular vesicles (EVs) are increasingly being recognized as important vehicles for intercellular communication and as promising sources for biomarker discovery. Because the state of protein post-translational modifications (PTMs) such as phosphorylation and glycosylation can be a key determinant of cellular physiology, comprehensive characterization of protein PTMs in EVs can be particularly valuable for early-stage diagnostics and monitoring of disease status. However, the analysis of PTMs in EVs has been complicated by limited amounts of purified EVs, low-abundance PTM proteins, and interference from proteins and metabolites in biofluids. Recently, we developed an approach to isolate phosphoproteins and glycoproteins in EVs from small volumes of human plasma that enabled us to identify nearly 10,000 unique phosphopeptides and 1,500 unique N-glycopeptides. The approach demonstrated the feasibility of using these data to identify potential markers to differentiate disease from healthy states. Here we present an updated workflow to sequentially isolate phosphopeptides and N-glycopeptides, enabling multiple PTM analyses of the same clinical samples. In this updated workflow, we have improved the reproducibility and efficiency of EV isolation, protein extraction, and phosphopeptide/N-glycopeptide enrichment to achieve sensitive analyses of low-abundance PTMs in EVs isolated from 1 mL of plasma. The modularity of the workflow also allows for the characterization of phospho- or glycopeptides only and enables additional analysis of total proteomes and other PTMs of interest. After blood collection, the protocol takes 2 d, including EV isolation, PTM/peptide enrichment, mass spectrometry analysis, and data quantification.

An Update on Isolation Methods for Proteomic Studies of Extracellular Vesicles in Biofluids

Extracellular vesicles (EVs) are lipid bilayer enclosed particles which present in almost all types of biofluids and contain specific proteins, lipids, and RNA. Increasing evidence has demonstrated the tremendous clinical potential of EVs as diagnostic and therapeutic tools, especially in biofluids, since they can be detected without invasive surgery. With the advanced mass spectrometry (MS), it is possible to decipher the protein content of EVs under different physiological and pathological conditions. Therefore, MS-based EV proteomic studies have grown rapidly in the past decade for biomarker discovery. This review focuses on the studies that isolate EVs from different biofluids and contain MS-based proteomic analysis. Literature published in the past decade (2009.1-2019.7) were selected and summarized with emphasis on isolation methods of EVs and MS analysis strategies, with the aim to give an overview of MS-based EV proteomic studies and provide a reference for future research.

Harnessing the tissue and plasma lncRNA-peptidome to discover peptide-based cancer biomarkers

Proteome-centric studies, although have identified numerous lncRNA-encoded polypeptides, lack differential expression analysis of lncRNA-peptidome across primary tissues, cell lines and cancer states. We established a computational-proteogenomic workflow involving re-processing of publicly available LC-MS/MS data, which facilitated the identification of tissue-specific and universally expressed (UExp) lncRNA-polypeptides across 14 primary human tissues and 11 cell lines. The utility of lncRNA-peptidome as cancer-biomarkers was investigated by re-processing LC-MS/MS data from 92 colon-adenocarcinoma (COAD) and 30 normal colon-epithelium tissues. Intriguingly, a significant upregulation of five lncRNA UExp-polypeptides in COAD tissues was observed. Furthermore, clustering of the UExp-polypeptides led to the classification of COAD patients that coincided with the clinical stratification, underlining the prognostic potential of the UExp-polypeptides. Lastly, we identified differential abundance of the UExp-polypeptides in the plasma of prostate-cancer patients highlighting their potential as plasma-biomarker. The analysis of lncRNA-peptidome may pave the way to identify effective tissue/plasma biomarkers for different cancer types.

Microvesicle Proteomic Profiling of Uterine Liquid Biopsy for Ovarian Cancer Early Detection

High-grade ovarian cancer (HGOC) is the leading cause of mortality from gynecological malignancies, because of diagnosis at a metastatic stage. Current screening options fail to improve mortality because of the absence of early-stage-specific biomarkers. We postulated that a liquid biopsy, such as utero-tubal lavage (UtL), may identify localized lesions better than systemic approaches of serum/plasma analysis. Further, while mutation-based assays are challenged by the rarity of tumor DNA within nonmutated DNA, analyzing the proteomic profile, is expected to enable earlier detection, as it reveals perturbations in both the tumor as well as in its microenvironment. To attain deep proteomic coverage and overcome the high dynamic range of this body fluid, we applied our method for microvesicle proteomics to the UtL samples. Liquid biopsies from HGOC patients (n = 49) and controls (n = 127) were divided into a discovery and validation sets. Data-dependent analysis of the samples on the Q-Exactive mass spectrometer provided depth of 8578 UtL proteins in total, and on average ∼3000 proteins per sample. We used support vector machine algorithms for sample classification, and crossed three feature-selection algorithms, to construct and validate a 9-protein classifier with 70% sensitivity and 76.2% specificity. The signature correctly identified all Stage I lesions. These results demonstrate the potential power of microvesicle-based proteomic biomarkers for early cancer diagnosis.

Redefining Tissue Crosstalk via Shotgun Proteomic Analyses of Plasma Extracellular Vesicles

Protein signaling between tissues, or tissue cross-talk is becoming recognized as a fundamental biological process that is incompletely understood. Shotgun proteomic analyses of tissues and plasma to explore this concept are regularly challenged by high dynamic range of protein abundance, which limits the identification of lower abundance proteins. In this viewpoint article, it is highlighted how a focus on proteins contained within extracellular vesicles (EVs) not only partially addresses this issue, but can also reveal an underappreciated complexity of the circulating proteome in various physiological and pathological contexts. Furthermore, how quantitative proteomics can inform EV mediated crosstalk is highlighted and the importance of high coverage, sensitive proteomic analyses of EVs to identify both the optimal methods to isolate EV subtypes of interest and proteins that characterize them is stressed.

Highly Efficient Phosphoproteome Capture and Analysis from Urinary Extracellular Vesicles

Analysis of protein phosphorylation in extracellular vesicles (EVs) offers an unprecedented potential for understanding cancer signaling and early stage disease diagnosis. However, prior to the phosphoproteome analysis step, the isolation of EVs from biofluids remains a challenging issue to overcome due to the low yield and impurity from current isolation methods. Here, we carry out an extensive assessment of several EV isolation methods including a novel rapid isolation method EVTRAP for highly efficient capture of extracellular vesicles from human urine sample. We demonstrate that over 95% recovery yield can be consistently achieved by EVTRAP, a significant improvement over current standard techniques. We then applied EVTRAP to identify over 16 000 unique peptides representing 2000 unique EV proteins from 200 μL urine sample, including all known EV markers with substantially increased recovery levels over ultracentrifugation. Most importantly, close to 2000 unique phosphopeptides were identified from more than 860 unique phosphoproteins using 10 mL of urine. The data demonstrated that EVTRAP is a highly effective and potentially widely implementable clinical isolation method for analysis of EV protein phosphorylation.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

Plasma Biomarker Identification and Quantification by Microparticle Proteomics

Plasma biomarker discovery necessitates a method for deep proteomic profiling, as well as for highly accurate quantification of the proteins in the sample. Furthermore, to obtain strong candidates for potential biomarkers, the method should be high throughput to enable a large scale analysis. Here we describe in detail PROMIS-Quan (PROteomics of MIcroparticles using Super-SILAC Quantification), a method for a simple and robust fractionation of the plasma samples by extraction of plasma microparticles, followed by SILAC-based relative and absolute quantification.

Extracellular Vesicles Provide a Means for Tissue Crosstalk during Exercise

Exercise stimulates the release of molecules into the circulation, supporting the concept that inter-tissue signaling proteins are important mediators of adaptations to exercise. Recognizing that many circulating proteins are packaged in extracellular vesicles (EVs), we employed quantitative proteomic techniques to characterize the exercise-induced secretion of EV-contained proteins. Following a 1-hr bout of cycling exercise in healthy humans, we observed an increase in the circulation of over 300 proteins, with a notable enrichment of several classes of proteins that compose exosomes and small vesicles. Pulse-chase and intravital imaging experiments suggested EVs liberated by exercise have a propensity to localize in the liver and can transfer their protein cargo. Moreover, by employing arteriovenous balance studies across the contracting human limb, we identified several novel candidate myokines, released into circulation independently of classical secretion. These data identify a new paradigm by which tissue crosstalk during exercise can exert systemic biological effects.

Discovery of a Potential Plasma Protein Biomarker Panel for Acute-on-Chronic Liver Failure Induced by Hepatitis B Virus

Hepatitis B virus (HBV)-associated acute-on-chronic liver failure (HBV-ACLF), characterized by an acute deterioration of liver function in the patients with chronic hepatitis B (CHB), is lack of predicting biomarkers for prognosis. Plasma is an ideal sample for biomarker discovery due to inexpensive and minimally invasive sampling and good reproducibility. In this study, immuno-depletion of high-abundance plasma proteins followed by iTRAQ-based quantitative proteomic approach was employed to analyze plasma samples from 20 healthy control people, 20 CHB patients and 20 HBV-ACLF patients, respectively. As a result, a total of 427 proteins were identified from these samples, and 42 proteins were differentially expressed in HBV-ACLF patients as compared to both CHB patients and healthy controls. According to bioinformatics analysis results, 6 proteins related to immune response (MMR), inflammatory response (OPN, HPX), blood coagulation (ATIII) and lipid metabolism (APO-CII, GP73) were selected as biomarker candidates. Further ELISA analysis confirmed the significant up-regulation of GP73, MMR, OPN and down-regulation of ATIII, HPX, APO-CII in HBV-ACLF plasma samples (p < 0.01). Moreover, receiver operating characteristic (ROC) curve analysis revealed high diagnostic value of these candidates in assessing HBV-ACLF. In conclusion, present quantitative proteomic study identified 6 novel HBV-ACLF biomarker candidates and might provide fundamental information for development of HBV-ACLF biomarker.

Robust Label-free, Quantitative Profiling of Circulating Plasma Microparticle (MP) Associated Proteins

Cells of the vascular system release spherical vesicles, called microparticles, in the size range of 0.1-1 μm induced by a variety of stress factors resulting in variable concentrations between health and disease. Furthermore, microparticles have intercellular communication/signaling properties and interfere with inflammation and coagulation pathways. Today's most used analytical technology for microparticle characterization, flow cytometry, is lacking sensitivity and specificity, which might have led to the publication of contradicting results in the past.We propose the use of nano-liquid chromatography two-stage mass spectrometry as a nonbiased tool for quantitative MP proteome analysis.For this, we developed an improved microparticle isolation protocol and quantified the microparticle protein composition of twelve healthy volunteers with a label-free, data-dependent and independent proteomics approach on a quadrupole orbitrap instrument.Using aliquots of 250 μl platelet-free plasma from one individual donor, we achieved excellent reproducibility with an interassay coefficient of variation of 2.7 ± 1.7% (mean ± 1 standard deviation) on individual peptide intensities across 27 acquisitions performed over a period of 3.5 months. We show that the microparticle proteome between twelve healthy volunteers were remarkably similar, and that it is clearly distinguishable from whole cell and platelet lysates. We propose the use of the proteome profile shown in this work as a quality criterion for microparticle purity in proteomics studies. Furthermore, one freeze thaw cycle damaged the microparticle integrity, articulated by a loss of cytoplasm proteins, encompassing a specific set of proteins involved in regulating dynamic structures of the cytoskeleton, and thrombin activation leading to MP clotting. On the other hand, plasma membrane protein composition was unaffected. Finally, we show that multiplexed data-independent acquisition can be used for relative quantification of target proteins using Skyline software. Mass spectrometry data are available via ProteomeXchange (identifier PXD003935) and panoramaweb.org (https://panoramaweb.org/labkey/N1OHMk.url).

The ever-expanding myokinome: discovery challenges and therapeutic implications

Exercise reduces the risk of a multitude of disorders, from metabolic disease to cancer, but the molecular mechanisms mediating the protective effects of exercise are not completely understood. The realization that skeletal muscle is an endocrine organ capable of secreting proteins termed 'myokines', which participate in tissue crosstalk, provided a critical link in the exercise-health paradigm. However, the myokine field is still emerging, and several challenges remain in the discovery and validation of myokines. This Review considers these challenges and highlights some recently identified novel myokines with the potential to be therapeutically exploited in the treatment of metabolic disease and cancer.

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed.

SIGNIFICANCE

Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases.

Comparative Proteomic Analysis of Extracellular Vesicles Isolated by Acoustic Trapping or Differential Centrifugation

Extracellular vesicles (ECVs), including microparticles and exosomes, are submicrometer membrane vesicles released by diverse cell types upon activation or stress. Circulating ECVs are potential reservoirs of disease biomarkers, and the complexity of these vesicles is significantly lower compared to their source, blood plasma, which makes ECV-based biomarker studies more promising. Proteomic profiling of ECVs is important not only to discover new diagnostic or prognostic markers but also to understand their roles in biological function. In the current study, we investigated the protein composition of plasma-derived ECVs isolated by acoustic seed trapping. Additionally, the protein composition of ECVs isolated with acoustic trapping was compared to that isolated with a conventional differential centrifugation protocol. Finally, the proteome of ECVs originating from ST-elevation myocardial infarction patients was compared with that of healthy controls using label-free LC-MS quantification. The acoustic trapping platform allows rapid and automated preparation of ECVs from small sample volumes, which are therefore well-suited for biobank repositories. We found that the protein composition of trapped ECVs is very similar to that isolated by the conventional differential centrifugation method.

Interleukin-6 Induced "Acute" Phenotypic Microenvironment Promotes Th1 Anti-Tumor Immunity in Cryo-Thermal Therapy Revealed By Shotgun and Parallel Reaction Monitoring Proteomics

Cryo-thermal therapy has been emerged as a promising novel therapeutic strategy for advanced breast cancer, triggering higher incidence of tumor regression and enhanced remission of metastasis than routine treatments. To better understand its anti-tumor mechanism, we utilized a spontaneous metastatic mouse model and quantitative proteomics to compare N-glycoproteome changes in 94 serum samples with and without treatment. We quantified 231 highly confident N-glycosylated proteins using iTRAQ shotgun proteomics. Among them, 53 showed significantly discriminated regulatory patterns over the time course, in which the acute phase response emerged as the most enhanced pathway. The anti-tumor feature of the acute response was further investigated using parallel reaction monitoring target proteomics and flow cytometry on 23 of the 53 significant proteins. We found that cryo-thermal therapy reset the tumor chronic inflammation to an “acute” phenotype, with up-regulation of acute phase proteins including IL-6 as a key regulator. The IL-6 mediated “acute” phenotype transformed IL-4 and Treg-promoting ICOSL expression to Th1-promoting IFN-γ and IL-12 production, augmented complement system activation and CD86⁺MHCII⁺ dendritic cells maturation and enhanced the proliferation of Th1 memory cells. In addition, we found an increased production of tumor progression and metastatic inhibitory proteins under such “acute” environment, favoring the anti-metastatic effect. Moreover, cryo-thermal on tumors induced the strongest “acute” response compared to cryo/hyperthermia alone or cryo-thermal on healthy tissues, accompanying by the most pronounced anti-tumor immunological effect. In summary, we demonstrated that cryo-thermal therapy induced, IL-6 mediated “acute” microenvironment shifted the tumor chronic microenvironment from Th2 immunosuppressive and pro-tumorigenic to Th1 immunostimulatory and tumoricidal state. Moreover, the magnitude of “acute” and “danger” signals play a key role in determining the efficacy of anti-tumor activity.

Alisertib Induces Cell Cycle Arrest, Apoptosis, Autophagy and Suppresses EMT in HT29 and Caco-2 Cells

Colorectal cancer (CRC) is one of the most common malignancies worldwide with substantial mortality and morbidity. Alisertib (ALS) is a selective Aurora kinase A (AURKA) inhibitor with unclear effect and molecular interactome on CRC. This study aimed to evaluate the molecular interactome and anticancer effect of ALS and explore the underlying mechanisms in HT29 and Caco-2 cells. ALS markedly arrested cells in G₂/M phase in both cell lines, accompanied by remarkable alterations in the expression level of key cell cycle regulators. ALS induced apoptosis in HT29 and Caco-2 cells through mitochondrial and death receptor pathways. ALS also induced autophagy in HT29 and Caco-2 cells, with the suppression of phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR), but activation of 5′ AMP-activated protein kinase (AMPK) signaling pathways. There was a differential modulating effect of ALS on p38 MAPK signaling pathway in both cell lines. Moreover, induction or inhibition of autophagy modulated basal and ALS-induced apoptosis in both cell lines. ALS potently suppressed epithelial to mesenchymal transition (EMT) in HT29 and Caco-2 cells. Collectively, it suggests that induction of cell cycle arrest, promotion of apoptosis and autophagy, and suppression of EMT involving mitochondrial, death receptor, PI3K/Akt/mTOR, p38 MAPK, and AMPK signaling pathways contribute to the cancer cell killing effect of ALS on CRC cells.

Multijunction Capillary Isoelectric Focusing Device Combined with Online Membrane-Assisted Buffer Exchanger Enables Isoelectric Point Fractionation of Intact Human Plasma Proteins for Biomarker Discovery

Prefractionation of proteins is often employed to improve analysis specificity in proteomics. Prefractionation based on the isoelectric point (pI) is particularly attractive because pI is a well-defined parameter and it is orthogonal to hydrophobicity on which reversed-phase chromatography is based. However, direct capillary electrophoresis of blood proteins is challenging due to its high content of salts and charged small molecules. Here, we couple an online desalinator device to our multijunction capillary isoelectric focusing (MJ-CIEF) instrument and perform direct isoelectric separation of human blood plasma. In a proof-of-principle experiment, pooled samples of patients with progressive mild cognitive impairment and corresponding healthy controls were investigated. Injection of 3 μL of plasma containing over 100 μg of proteins into the desalinator was followed by pI fractionation with MJ-CIEF in less than 1 h. Shotgun proteomics of 12 collected fractions from each of the 5 replicates of pooled samples resulted in the identification and accurate quantification (median CV between the replicates is <4%) of nearly 365 protein groups from 4030 unique peptides (with <1% FDR for both peptides and proteins). The obtained results include several proteins previously reported as AD markers. The isoelectric point of each quantified protein was calculated using a set of 7 synthetic peptides spiked into the samples. Several proteins with a significant pI shift between their isoforms in the patient and control samples were identified. The presented method is straightforward, robust, and scalable; therefore, it can be used in both biological and clinical applications.

Serum apolipoprotein A-1 quantification by LC-MS with a SILAC internal standard reveals reduced levels in smokers

Background:

Absolute quantification of protein biomarkers such as serum apolipoprotein A1 by both immunoassays and LC–MS can provide misleading results.

Results:

Recombinant ApoA-1 internal standard was prepared using stable isotope labeling by amino acids in cell culture with [¹³C₆¹⁵N₂]-lysine and [¹³C₉¹⁵N₁]-tyrosine in human cells. A stable isotope dilution LC–MS method for serum ApoA-1 was validated and levels analyzed for 50 nonsmokers and 50 smokers.

Conclusion:

The concentration of ApoA-1 in nonsmokers was 169.4 mg/dl with an 18.4% reduction to 138.2 mg/dl in smokers. The validated assay will have clinical utility for assessing effects of smoking cessation and therapeutic or dietary interventions in high-risk populations.

Integrated Microfluidics for Protein Modification Discovery

Protein post-translational modifications mediate dynamic cellular processes with broad implications in human disease pathogenesis. There is a large demand for high-throughput technologies supporting post-translational modifications research, and both mass spectrometry and protein arrays have been successfully utilized for this purpose. Protein arrays override the major limitation of target protein abundance inherently associated with MS analysis. This technology, however, is typically restricted to pre-purified proteins spotted in a fixed composition on chips with limited life-time and functionality. In addition, the chips are expensive and designed for a single use, making complex experiments cost-prohibitive. Combining microfluidics with in situ protein expression from a cDNA microarray addressed these limitations. Based on this approach, we introduce a modular integrated microfluidic platform for multiple post-translational modifications analysis of freshly synthesized protein arrays (IMPA). The system's potency, specificity and flexibility are demonstrated for tyrosine phosphorylation and ubiquitination in quasicellular environments. Unlimited by design and protein composition, and relying on minute amounts of biological material and cost-effective technology, this unique approach is applicable for a broad range of basic, biomedical and biomarker research.