Shinchi, H. | bioRxiv Science

bioRxiv2025

Development of a liquid biopsy for bladder cancer using a mutant protein panel in urinary extracellular vesicles

Non-muscle invasive bladder cancer often relapses after cystoscopic surgery, necessitating rigorous monitoring for recurrence through invasive and painful cystoscopy. To develop a novel non-invasive and cancer-specific diagnostic method, somatic mutant proteins in urinary extracellular vesicles (EVs) were for the first time investigated using a proteogenomics pipeline consisting of whole exome sequencing and LC/MS. The analysis of bladder cancer tissues, cultured tissue-derived EVs, and urinary EVs from five patients identified 11,207, 9,809, and 5,828 unique proteins, respectively. Notably, 39, 32, and 4 mutant proteins were found in each of the sample sets. Furthermore, mass spectrometric absolute quantification measurements were conducted using prospectively collected urine samples, revealing that the levels of all monitored mutant proteins (LCP1_D321H, TKT_K102N, and PLCD1_R639H) exhibited a clear correlation with the cystoscopic tumor burden. Therefore, the presence of mutant proteins in Evs presents an ideal approach for liquid biopsy, serving as a non-invasive urine test for bladder cancer. TeaserMutant proteins in urine were identified using a proteogenomic pipeline, which may serve as a novel method for monitoring bladder cancer.

cancer biology↗

bioRxiv2023

Differentiation of Large Extracellular Vesicles in Oral Fluid: Combined Protocol of Small Force Centrifugation and Pattern Analysis

Extracellular vesicles (EVs) in biofluids are highly heterogeneous entities in terms of their origins and physicochemical properties. Considering the application of EVs in diagnostic and therapeutic fields, it is of extreme importance to establish differentiating methods by which focused EV subclasses are operationally defined. Several differentiation protocols have been proposed; however, they have mainly focused on smaller types of EVs, and the heterogeneous nature of large EVs has not yet been fully explored. In this report, to classify large EVs into subgroups based on their physicochemical properties, we have developed a protocol, named EV differentiation by sedimentation patterns (ESP), in which entities in the crude large EV fraction are first moved through a density gradient of iodixanol with small centrifugation forces, and then the migration patterns of molecules through the gradients are analyzed using a non-hierarchical data clustering algorithm. Based on this method, proteins in the large EV fractions of oral fluids clustered into three groups: proteins shared with small EV cargos and enriched in immuno-related proteins (Group 1), proteins involved in energy metabolism and protein synthesis (Group 2), and proteins required for vesicle trafficking (Group 3). These observations indicate that the physiochemical properties of EVs, which are defined through low-speed gradient centrifugation, are well associated with their functions within cells. This protocol enables the detailed subclassification of EV populations that are difficult to differentiate using conventional separation methods.

molecular biology↗