Data-independent acquisition phosphoproteomics of urinary extracellular vesicles enables renal cell carcinoma grade differentiation

Proteomic and phosphoproteomic profiling of urinary small extracellular vesicles in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer and a major cause of cancer-related mortality worldwide. Small extracellular vesicles (sEVs) are heterogeneous populations of membrane-structured vesicles that can be found in many biological fluids and are currently considered as a potential source of disease-associated biomarkers for diagnosis. The purpose of this study was to define the proteomic and phosphoproteomic landscape of urinary sEVs in patients with HCC. Mass spectrometry-based methods were used to detect the global proteome and phosphoproteome profiles of sEVs isolated by differential ultracentrifugation. Label-free quantitation analysis showed that 348 differentially expressed proteins (DEPs) and 548 differentially expressed phosphoproteins (DEPPs) were identified in the HCC group. Among them, multiple phosphoproteins related to HCC, including HSP90AA1, IQGAP1, MTOR, and PRKCA, were shown to be upregulated in the HCC group. Pathway enrichment analysis indicated that the upregulated DEPPs participate in the regulation of autophagy, proteoglycans in cancer, and the MAPK/mTOR/Rap1 signaling pathway. Furthermore, kinase-substrate enrichment analysis revealed activation of MTOR, AKT1, MAP2Ks, and MAPKs family kinases in HCC-derived sEVs, indicating that dysregulation of the MAPK and mTOR signaling pathways may be the primary sEV-mediated molecular mechanisms involved in the development and progression of HCC. This study demonstrated that urinary sEVs are enriched in proteomic and phosphoproteomic signatures that could be further explored for their potential use in early HCC diagnostic and therapeutic applications.

Kidney Cancer and Potential Use of Urinary Extracellular Vesicles

Kidney cancer is the 14th most common cancer globally. The 5-year relative survival rate of kidney cancer at a localized stage is 92.9% and it declines to 17.4% in metastatic stage. Currently, the most accurate method of its diagnosis is tissue biopsy. However, the invasive and costly nature of biopsies makes it undesirable in many patients. Therefore, novel biomarkers for diagnosis and prognosis should be explored. Urinary extracellular vesicles (uEVs) are small vesicles (50-200 nm) in urine carrying nucleic acids, proteins and lipids as their cargos. These uEVs' cargos can provide non-invasive alternative to monitor kidney health. In this review, we have summarized recent studies investigating potential use of uEVs' cargos as biomarkers in kidney cancer for diagnosis, prognosis and therapeutic intervention.

Therapeutic potential and pharmacological significance of extracellular vesicles derived from traditional medicinal plants

Medicinal plants are the primary sources for the discovery of novel medicines and the basis of ethnopharmacological research. While existing studies mainly focus on the chemical compounds, there is little research about the functions of other contents in medicinal plants. Extracellular vesicles (EVs) are functionally active, nanoscale, membrane-bound vesicles secreted by almost all eukaryotic cells. Intriguingly, plant-derived extracellular vesicles (PDEVs) also have been implicated to play an important role in therapeutic application. PDEVs were reported to have physical and chemical properties similar to mammalian EVs, which are rich in lipids, proteins, nucleic acids, and pharmacologically active compounds. Besides these properties, PDEVs also exhibit unique advantages, especially intrinsic bioactivity, high stability, and easy absorption. PDEVs were found to be transferred into recipient cells and significantly affect their biological process involved in many diseases, such as inflammation and tumors. PDEVs also could offer unique morphological and compositional characteristics as natural nanocarriers by innately shuttling bioactive lipids, RNA, proteins, and other pharmacologically active substances. In addition, PDEVs could effectively encapsulate hydrophobic and hydrophilic chemicals, remain stable, and cross stringent biological barriers. Thus, this study focuses on the pharmacological action and mechanisms of PDEVs in therapeutic applications. We also systemically deal with facets of PDEVs, ranging from their isolation to composition, biological functions, and biotherapeutic roles. Efforts are also made to elucidate recent advances in re-engineering PDEVs applied as stable, effective, and non-immunogenic therapeutic applications to meet the ever-stringent demands. Considering its unique advantages, these studies not only provide relevant scientific evidence on therapeutic applications but could also replenish and inherit precious cultural heritage.

Hands-Free Proteomic Profiling of Urinary Extracellular Vesicles with a High-Throughput Automated Workflow

Extracellular vesicles (EVs) have emerged as a promising source of disease biomarkers for noninvasive early stage diagnoses, but a bottleneck in EV sample processing restricts their immense potential in clinical applications. Existing methods are limited by a low EV yield and integrity, slow processing speeds, low sample capacity, and poor recovery efficiency. We aimed to address these issues with a high-throughput automated workflow for EV isolation, EV lysis, protein extraction, and protein denaturation. The automation can process clinical urine samples in parallel, resulting in protein-covered beads ready for various analytical methods, including immunoassays, protein quantitation assays, and mass spectrometry. Compared to the standard manual lysis method for contamination levels, efficiency, and consistency of EV isolation, the automated protocol shows reproducible and robust proteomic quantitation with less than a 10% median coefficient of variation. When we applied the method to clinical samples, we identified a total 3,793 unique proteins and 40,380 unique peptides, with 992 significantly upregulated proteins in kidney cancer patients versus healthy controls. These upregulated proteins were found to be involved in several important kidney cancer metabolic pathways also identified with a manual control. This hands-free workflow represents a practical EV extraction and profiling approach that can benefit both clinical and research applications, streamlining biomarker discovery, tumor monitoring, and early cancer diagnoses.

One-Pot Analytical Pipeline for Efficient and Sensitive Proteomic Analysis of Extracellular Vesicles

Extracellular vesicle (EV) proteomics emerges as an effective tool for discovering potential biomarkers for disease diagnosis, monitoring, and therapeutics. However, the current workflow of mass spectrometry-based EV proteome analysis is not fully compatible in a clinical setting due to inefficient EV isolation methods and a tedious sample preparation process. To streamline and improve the efficiency of EV proteome analysis, here we introduce a one-pot analytical pipeline integrating a robust EV isolation approach, EV total recovery and purification (EVtrap), with in situ protein sample preparation, to detect urinary EV proteome. By incorporating solvent-driven protein capture and fast on-bead digestion, the one-pot pipeline enabled the whole EV proteome analysis to be completed within one day. In comparison with the existing workflow, the one-pot pipeline was able to obtain better peptide yield and identify the equivalent number of unique EV proteins from 1 mL of urine. Finally, we applied the one-pot pipeline to profile proteomes in urinary EVs of bladder cancer patients. A total of 2774 unique proteins were identified in 53 urine samples using a 15 min gradient library-free data-independent acquisition method. Taken altogether, our novel one-pot analytical pipeline demonstrated its potential for routine and robust EV proteomics in biomedical applications.

Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson's disease

BACKGROUND

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson's disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease.

METHODS

Utilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs).

RESULTS

After efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation.

CONCLUSIONS

These findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.

Isolation and Identification of Plasma Extracellular Vesicles Protein Biomarkers

Extracellular vesicles (EVs) have emerged as a valuable source for disease biomarkers and an alternative drug delivery system due to their ability to carry cargo and target specific cells. Proper isolation, identification, and analytical strategy are required for evaluating their potential in diagnostics and therapeutics. Here, a method is detailed to isolate plasma EVs and analyze their proteomic profiling, combining EVtrap-based high-recovery EV isolation, phase-transfer surfactant method for protein extraction, and mass spectrometry qualitative and quantitative strategies for EV proteome characterization. The pipeline provides a highly effective EV-based proteome analysis technique that can be applied for EV characterization and evaluation of EV-based diagnosis and therapy.