Browsing by Author "Hadisurya, Marco"

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    Data-Independent Acquisition Phosphoproteomics of Urinary Extracellular Vesicles Enables Renal Cell Carcinoma Grade Differentiation
    (Elsevier, 2023) Hadisurya, Marco; Lee, Zheng-Chi; Luo, Zhuojun; Zhang, Guiyuan; Ding, Yajie; Zhang, Hao; Iliuk, Anton B.; Pili, Roberto; Boris, Ronald S.; Tao, W. Andy; Urology, School of Medicine
    Translating the research capability and knowledge in cancer signaling into clinical settings has been slow and ineffective. Recently, extracellular vesicles (EVs) have emerged as a promising source for developing disease phosphoprotein markers to monitor disease status. This study focuses on the development of a robust data-independent acquisition (DIA) using mass spectrometry to profile urinary EV phosphoproteomics for renal cell cancer (RCC) grades differentiation. We examined gas-phase fractionated library, direct DIA (library-free), forbidden zones, and several different windowing schemes. After the development of a DIA mass spectrometry method for EV phosphoproteomics, we applied the strategy to identify and quantify urinary EV phosphoproteomes from 57 individuals representing low-grade clear cell RCC, high-grade clear cell RCC, chronic kidney disease, and healthy control individuals. Urinary EVs were efficiently isolated by functional magnetic beads, and EV phosphopeptides were subsequently enriched by PolyMAC. We quantified 2584 unique phosphosites and observed that multiple prominent cancer-related pathways, such as ErbB signaling, renal cell carcinoma, and regulation of actin cytoskeleton, were only upregulated in high-grade clear cell RCC. These results show that EV phosphoproteome analysis utilizing our optimized procedure of EV isolation, phosphopeptide enrichment, and DIA method provides a powerful tool for future clinical applications.
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    One-Pot Analytical Pipeline for Efficient and Sensitive Proteomic Analysis of Extracellular Vesicles
    (American Chemical Society, 2023) Liu, Yi-Kai; Wu, Xiaofeng; Hadisurya, Marco; Li, Li; Kaimakliotis, Hristos; Iliuk, Anton; Tao, W. Andy; Urology, School of Medicine
    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.
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    Plasma-Derived Extracellular Vesicle Phosphoproteomics through Chemical Affinity Purification
    (ACS, 2020-05) liuk, Anton; Wu, Xiaofeng; Li, Li; Sun, Jie; Hadisurya, Marco; Boris, Ronald S.; Tao, W. Andy; Urology, School of Medicine
    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.