Person:

Hochberg, Fred H

Background: RNA from exosomes and other microvesicles contain transcripts of tumour origin. In this study we sought to identify biomarkers of glioblastoma multiforme in microvesicle RNA from serum of affected patients. Methods: Microvesicle RNA from serum from patients with de-novo primary glioblastoma multiforme (N = 9) and normal controls (N = 7) were analyzed by microarray analysis. Samples were collected according to protocols approved by the Institutional Review Board. Differential expressions were validated by qRT-PCR in a separate set of samples (N = 10 in both groups). Results: Expression profiles of microvesicle RNA correctly separated individuals in two groups by unsupervised clustering. The most significant differences pertained to down-regulated genes (121 genes > 2-fold down) in the glioblastoma multiforme patient microvesicle RNA, validated by qRT-PCR on several genes. Overall, yields of microvesicle RNA from patients was higher than from normal controls, but the additional RNA was primarily of size < 500 nt. Gene ontology of the down-regulated genes indicated these are coding for ribosomal proteins and genes related to ribosome production. Conclusions: Serum microvesicle RNA from patients with glioblastoma multiforme has significantly down-regulated levels of RNAs coding for ribosome production, compared to normal healthy controls, but a large overabundance of RNA of unknown origin with size < 500 nt.

Microvesicles are nano-sized lipid vesicles released by all cells in vivo and in vitro. They are released physiologically under normal conditions but their rate of release is higher under pathological conditions such as tumors. Once released they end up in the systemic circulation and have been found and characterized in all biofluids such as plasma, serum, cerebrospinal fluid, breast milk, ascites, and urine. Microvesicles represent the status of the donor cell they are released from and they are currently under intense investigation as a potential source for disease biomarkers. Currently, the “gold standard” for isolating microvesicles is ultracentrifugation, although alternative techniques such as affinity purification have been explored. Viscosity is the resistance of a fluid to a deforming force by either shear or tensile stress. The different chemical and molecular compositions of biofluids have an effect on its viscosity and this could affect movements of the particles inside the fluid. In this manuscript we addressed the issue of whether viscosity has an effect on sedimentation efficiency of microvesicles using ultracentrifugation. We used different biofluids and spiked them with polystyrene beads and assessed their recovery using the Nanoparticle Tracking Analysis. We demonstrate that MVs recovery inversely correlates with viscosity and as a result, sample dilutions should be considered prior to ultracentrifugation when processing any biofluids.

Development of biofluid-based molecular diagnostic tests for cancer is an important step towards tumor characterization and real-time monitoring in a minimally invasive fashion. Extracellular vesicles (EVs) are released from tumor cells into body fluids and can provide a powerful platform for tumor biomarkers because they carry tumor proteins and nucleic acids. Detecting rare point mutations in the background of wild-type sequences in biofluids such as blood and cerebrospinal fluid (CSF) remains a major challenge. Techniques such as BEAMing (beads, emulsion, amplification, magnetics) PCR and droplet digital PCR (ddPCR) are substantially more sensitive than many other assays for mutant sequence detection. Here, we describe a novel approach that combines biofluid EV RNA and BEAMing RT-PCR (EV-BEAMing), as well droplet digital PCR to interrogate mutations from glioma tumors. EVs from CSF of patients with glioma were shown to contain mutant IDH1 transcripts, and we were able to reliably detect and quantify mutant and wild-type IDH1 RNA transcripts in CSF of patients with gliomas. EV-BEAMing and EV-ddPCR represent a valuable new strategy for cancer diagnostics, which can be applied to a variety of biofluids and neoplasms.