Extracellular RNAs (exRNAs), protected from degradation in biofluids by a diverse set of carriers, are currently considered as promising biomarkers. Indeed, it was shown that during disease progression, impacted cells/tissues modify their registries of secreted exRNAs, carried by one or several protein or vesicular carriers, which then participate in a modification of the global exRNAs profile in related biofluids. However, the clinically- relevant exRNA modifications often represent a small fraction of the circulating exRNA within a given biofluid, and could then remain undetectable when examining total biofluids exRNAs profiles. As such, establishing efficient and specific exRNAs-carrier isolation methods, and downstream associated exRNAs reference profiles in normal and disease situations, represents a prerequisite towards implementation of biofluid exRNAs profiling as a routine diagnostic tool. The objective of the P.R.I.S.M project (Purification of exRNA by Immuno-capture and Sorting using Microfluidics), is to combine viscoleastic extracellular nanovesicle sorting with protein-affinity capture methods, using different microfluidic chip device, in order to isolate distinct exRNA carriers (vesicles, lipoproteins, or RNA-binding proteins) from a single sample of human biofluids (plasma, CSF, urine, milk), prior to RNA profiling. This project will not only establish essential carrier-specific exRNA reference profiles for different human biofluids, but should also dramatically improve the reproducibility, speed, sensitivity and specificity of exRNA-based diagnostic assays compared to the current state-of-the-art in the field.
Circulating extracellular RNA (exRNAs) in biofluids, protected by distinct proteins and vesicular carriers, are currently considered as promising biomarkers in diseases, such a cancer. However, only a small percentage of the total exRNAs, clustered in some specific exRNA carriers, contain the clinically relevant information. Our project aims at developing microfluidic methods for fractionating biofluid into its most relevant exRNAs carrier components, from a single low volume of biofluid sample before characterizing their exRNA content. Upon conclusion, we expect to reach a dramatic improvement in the specificity and sensitivity of exRNA diagnostic strategies.