A new integrated method for tissue extracellular vesicle enrichment and proteome profiling

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.

Recent research on material-based methods for isolation of extracellular vesicles

Extracellular vesicles (EVs) are nanoparticles secreted by cells with a closed phospholipid bilayer structure, which can participate in various physiological and pathological processes and have significant clinical value in disease diagnosis, targeted therapy and prognosis assessment. EV isolation methods currently include differential ultracentrifugation, ultrafiltration, size exclusion chromatography, immunoaffinity, polymer co-precipitation and microfluidics. In addition, material-based biochemical or biophysical approaches relying on intrinsic properties of the material or its surface-modified functionalized monomers, demonstrated unique advantages in the efficient isolation of EVs. In order to provide new ideas for the subsequent development of material-based EV isolation methods, this review will focus on the principle, research status and application prospects of material-based EV isolation methods based on different material carriers and functional monomers.

Extracellular vesicles as nanotheranostic platforms for targeted neurological disorder interventions

Central Nervous System (CNS) disorders represent a profound public health challenge that affects millions of people around the world. Diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and traumatic brain injury (TBI) exemplify the complexities and diversities that complicate their early detection and the development of effective treatments. Amid these challenges, the emergence of nanotechnology and extracellular vesicles (EVs) signals a new dawn for treating and diagnosing CNS ailments. EVs are cellularly derived lipid bilayer nanosized particles that are pivotal in intercellular communication within the CNS and have the potential to revolutionize targeted therapeutic delivery and the identification of novel biomarkers. Integrating EVs with nanotechnology amplifies their diagnostic and therapeutic capabilities, opening new avenues for managing CNS diseases. This review focuses on examining the fascinating interplay between EVs and nanotechnology in CNS theranostics. Through highlighting the remarkable advancements and unique methodologies, we aim to offer valuable perspectives on how these approaches can bring about a revolutionary change in disease management. The objective is to harness the distinctive attributes of EVs and nanotechnology to forge personalized, efficient interventions for CNS disorders, thereby providing a beacon of hope for affected individuals. In short, the confluence of EVs and nanotechnology heralds a promising frontier for targeted and impactful treatments against CNS diseases, which continue to pose significant public health challenges. By focusing on personalized and powerful diagnostic and therapeutic methods, we might improve the quality of patients.

Identification of hepatocellular carcinoma-related subtypes and development of a prognostic model: a study based on ferritinophagy-related genes

BACKGROUND

Hepatocellular carcinoma still has a high incidence and mortality rate worldwide, and further research is needed to investigate its occurrence and development mechanisms in depth in order to identify new therapeutic targets. Ferritinophagy is a type of autophagy and a key factor in ferroptosis that could influence tumor onset and progression. Although, the potential role of ferritinophagy-related genes (FRGs) in liver hepatocellular carcinoma (LIHC) is unknown.

METHODS

Single-cell RNA sequencing (scRNA-seq) data of LIHC were obtained from the Gene Expression Omnibus (GEO) dataset. In addition, transcriptome and clinical follow-up outcome data of individuals with LIHC were extracted from the The Cancer Genome Atlas (TCGA) dataset. FRGs were collected through the GeneCards database. Differential cell subpopulations were distinguished, and differentially expressed FRGs (DEFRGs) were obtained. Differential expression of FRGs and prognosis were observed according to the TCGA database. An FRG-related risk model was constructed to predict patient prognosis by absolute shrinkage and selection operator (LASSO) and COX regression analyses, and its prognosis predictive power was validated. Ultimately, the association between risk score and tumor microenvironment (TME), immune cell infiltration, immune checkpoints, drug sensitivity, and tumor mutation burden (TMB) was analyzed. We also used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to validate the expression of key genes in normal liver cells and liver cancer cells.

RESULTS

We ultimately identified 8 cell types, and 7 differentially expressed FRGs genes (ZFP36, NCOA4, FTH1, FTL, TNF, PCBP1, CYB561A3) were found among immune cells, and we found that Monocytes and Macrophages were closely related to FRGs genes. Subsequently, COX regression analysis showed that patients with high expression of FTH1, FTL, and PCBP1 had significantly worse prognosis than those with low expression, and our survival prediction model, constructed based on age, stage, and risk score, showed better prognostic prediction ability. Our risk model based on 3 FRGs genes ultimately revealed significant differences between high-risk and low-risk groups in terms of immune infiltration and immune checkpoint correlation, drug sensitivity, and somatic mutation risk. Finally, we validated the key prognostic genes FTH1, FTL, using qRT-PCR, and found that the expression of FTH1 and FTL was significantly higher in various liver cancer cells than in normal liver cells. At the same time, immunohistochemistry showed that the expression of FTH1, FTL in tumor tissues was significantly higher than that in para-tumor tissues.

CONCLUSION

This study identifies a considerable impact of FRGs on immunity and prognosis in individuals with LIHC. The collective findings of this research provide new ideas for personalized treatment of LIHC and a more targeted therapy approach for individuals with LIHC to improve their prognosis.

Proteomic Research of Extracellular Vesicles in Clinical Biofluid

Extracellular vesicles (EVs), the lipid bilayer membranous structures of particles, are produced and released from almost all cells, including eukaryotes and prokaryotes. The versatility of EVs has been investigated in various pathologies, including development, coagulation, inflammation, immune response modulation, and cell-cell communication. Proteomics technologies have revolutionized EV studies by enabling high-throughput analysis of their biomolecules to deliver comprehensive identification and quantification with rich structural information (PTMs, proteoforms). Extensive research has highlighted variations in EV cargo depending on vesicle size, origin, disease, and other features. This fact has sparked activities to use EVs for diagnosis and treatment to ultimately achieve clinical translation with recent endeavors summarized and critically reviewed in this publication. Notably, successful application and translation require a constant improvement of methods for sample preparation and analysis and their standardization, both of which are areas of active research. This review summarizes the characteristics, isolation, and identification approaches for EVs and the recent advances in EVs for clinical biofluid analysis to gain novel knowledge by employing proteomics. In addition, the current and predicted future challenges and technical barriers are also reviewed and discussed.