Abstract
Extracellular vesicles (EVs) are complex ecosystems that can be derived from all body cells and circulated in the body fluids. Characterizing the tissue-cellular source contributing to circulating EVs provides biological information about the cell or tissue of origin and their functional states. However, the relative proportion of tissue-cellular origin of circulating EVs in body fluid has not been thoroughly characterized. Here, we developed an approach for digital EVs quantification, called EV-origin, that enables enumerating of EVs tissue-cellular source contribution from plasma extracellular vesicles long RNA sequencing profiles. EV-origin was constructed by the input matrix of gene expression signatures and robust deconvolution algorithm, collectively used to separate the relative proportions of each tissue or cell type of interest. EV-origin respectively predicted the relative enrichment of seven types of hemopoietic cells and sixteen solid tissue subsets from exLR-seq profile. Using the EV-origin approach, we depicted an integrated landscape of the traceability system of plasma EVs for healthy individuals. We also compared the heterogenous tissue-cellular source components from plasma EVs samples with diverse disease status. Notably, the aberrant liver fraction could reflect the development and progression of hepatic disease. The liver fraction could also serve as a diagnostic indicator and effectively separate HCC patients from normal individuals. The EV-origin provides an approach to decipher the complex heterogeneity of tissue-cellular origin in circulating EVs. Our approach could inform the development of exLR-based applications for liquid biopsy.
Highlights
Extracellular vesicles (EVs), which include exosomes and microvesicles, are nano-scaled and membrane-enclosed particles released from essentially all eukaryotic cells [1]
Several studies have used flow cytometry analysis to trace platelet- and lymphocyte-derived EVs in circulation, these results indicated plasma EVs predominantly originated from platelets, erythrocytes, and other leucocytes [24,25,26,27,28]
Our results showed that Nonnegative Least Squares (NNLS), support vector regression (SVR), and quadratic programming (QP) were efficient in tracing brain fraction from the cerebrospinal fluid (CSF) EVs samples (Fig. 1f)
Summary
Extracellular vesicles (EVs), which include exosomes and microvesicles, are nano-scaled and membrane-enclosed particles released from essentially all eukaryotic cells [1]. Teins, lipids, and nucleic acids that are delivered from the parent cells to the recipient cells [2]. These bioactive molecules function as mediators of intercellular communication [3,4]. EVs are associated with most pathological conditions, including cancers, cardiovascular diseases, neurologic disorders, and infectious diseases. These particles served as diagnostic biomarkers, therapeutic targets, and medicine carriers for disease therapeutics [5].
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