Automated Proteomics Sample Preparation of Phosphatidylserine-Positive Extracellular Vesicles from Human Body Fluids

Overcoming Analytical Challenges in Proximity Labeling Proteomics

Proximity labeling (PL) proteomics has emerged as a powerful tool to capture both stable and transient protein interactions and subcellular networks. Despite the wide biological applications, PL still faces technical challenges in robustness, reproducibility, specificity, and sensitivity. Here, we discuss major analytical challenges in PL proteomics and highlight how the field is advancing to address these challenges by refining study design, tackling interferences, overcoming variation, developing novel tools, and establishing more robust platforms. We also provide our perspectives on best practices and the need for more robust, scalable, and quantitative PL technologies.

Proteomic Characterization of Transfusable Blood Components: Fresh Frozen Plasma, Cryoprecipitate, and Derived Extracellular Vesicles via Data-Independent Mass Spectrometry

Extracellular vesicles (EVs) are a heterogeneous collection of particles that play a crucial role in cell-to-cell communication, primarily due to their ability to transport molecules, such as proteins. Thus, profiling EV-associated proteins offers insight into their biological effects. EVs can be isolated from various biological fluids, including donor blood components such as cryoprecipitate and fresh frozen plasma (FFP). In this study, we conducted a proteomic analysis of five single donor units of cryoprecipitate, FFP, and EVs derived from these blood components using a quantitative mass spectrometry approach. EVs were successfully isolated from both cryoprecipitate and FFP based on community guidelines. We identified and quantified approximately 360 proteins across all sample groups. Principal component analysis and heatmaps revealed that both cryoprecipitate and FFP are similar. Similarly, EVs derived from cryoprecipitate and FFP are comparable. However, they differ between the originating fluids and their derived EVs. Using the R-package MS-DAP, differentially expressed proteins (DEPs) were identified. The DEPs for all comparisons, when submitted for gene enrichment analysis, are involved in the complement and coagulation pathways. The protein profile generated from this study will have important clinical implications in increasing our knowledge of the proteins that are associated with EVs derived from blood components.

Harnessing the power of proteomics in precision diabetes medicine

Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.

Unlocking Exosome-Based Theragnostic Signatures: Deciphering Secrets of Ovarian Cancer Metastasis

Ovarian cancer (OC) is a common gynecological cancer worldwide. Unfortunately, the lack of early detection methods translates into a substantial cohort of women grappling with the pressing health crisis. The discovery of extracellular vesicles (EVs) (their major subpopulation exosomes, microvesicles, and apoptotic bodies) has provided new insights into the understanding of cancer. Exosomes, a subpopulation of EVs, play a crucial role in cellular communication and reflect the cellular status under both healthy and pathological conditions. Tumor-derived exosomes (TEXs) dynamically influence ovarian cancer progression by regulating uncontrolled cell growth, immune suppression, angiogenesis, metastasis, and the development of drug and therapeutic resistance. In the field of OC diagnostics, TEXs offer potential biomarkers in various body fluids. On the other hand, exosomes have also shown promising abilities to cure ovarian cancer. In this review, we address the interlink between exosomes and ovarian cancer and explore their theragnostic signature. Finally, we highlight future directions of exosome-based ovarian cancer research.

The Role of Extracellular Vesicles in the Pathogenesis of Hematological Malignancies: Interaction with Tumor Microenvironment; a Potential Biomarker and Targeted Therapy

The tumor microenvironment (TME) plays an important role in the development and progression of hematological malignancies. In recent years, studies have focused on understanding how tumor cells communicate within the TME. In addition to several factors, such as growth factors, cytokines, extracellular matrix (ECM) molecules, etc., a growing body of evidence has indicated that extracellular vesicles (EVs) play a crucial role in the communication of tumor cells within the TME, thereby contributing to the pathogenesis of hematological malignancies. The present review focuses on how EVs derived from tumor cells interact with the cells in the TME, such as immune cells, stromal cells, endothelial cells, and ECM components, and vice versa, in the context of various hematological malignancies. EVs recovered from the body fluids of cancer patients often carry the bioactive molecules of the originating cells and hence can be considered new predictive biomarkers for specific types of cancer, thereby also acting as potential therapeutic targets. Here, we discuss how EVs influence hematological tumor progression via tumor-host crosstalk and their use as biomarkers for hematological malignancies, thereby benefiting the development of potential therapeutic targets.

Challenges and Opportunities for Extracellular Vesicles in Clinical Oncology Therapy

Extracellular vesicles (EVs) are membrane-bound vesicles that can be released by all cell types. They may have different biogenesis, physical features, and cargo. EVs are important biomarkers for the diagnosis and prediction of many diseases due to their essential role in intercellular communication, their highly variable cargoes, and their accumulation in various body fluids. These natural particles have been investigated as potential therapeutic materials for many diseases. In our previous studies, the clinical usage of tumor-cell-derived microparticles (T-MPs) as a novel medication delivery system was examined. This review summarizes the clinical translation of EVs and related clinical trials, aiming to provide suggestions for safer and more effective oncology therapeutic systems, particularly in biotherapeutic and immunotherapeutic systems.