Person:

Breakefield, Xandra

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.

Glioblastoma cells secrete extra-cellular vesicles (EVs) containing microRNAs (miRNAs). Analysis of these EV miRNAs in the bio-fluids of afflicted patients represents a potential platform for biomarker development. However, the analytic algorithm for quantitative assessment of EV miRNA remains under-developed. Here, we demonstrate that the reference transcripts commonly used for quantitative PCR (including GAPDH, 18S rRNA, and hsa-miR-103) were unreliable for assessing EV miRNA. In this context, we quantitated EV miRNA in absolute terms and normalized this value to the input EV number. Using this method, we examined the abundance of miR-21, a highly over-expressed miRNA in glioblastomas, in EVs. In a panel of glioblastoma cell lines, the cellular levels of miR-21 correlated with EV miR-21 levels (p<0.05), suggesting that glioblastoma cells actively secrete EVs containing miR-21. Consistent with this hypothesis, the CSF EV miR-21 levels of glioblastoma patients (n=13) were, on average, ten-fold higher than levels in EVs isolated from the CSF of non-oncologic patients (n=13, p<0.001). Notably, none of the glioblastoma CSF harbored EV miR-21 level below 0.25 copies per EV in this cohort. Using this cut-off value, we were able to prospectively distinguish CSF derived from glioblastoma and non-oncologic patients in an independent cohort of twenty-nine patients (Sensitivity=87%; Specificity=93%; AUC=0.91, p<0.01). Our results suggest that CSF EV miRNA analysis of miR-21 may serve as a platform for glioblastoma biomarker development.

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.

Extracellular vesicles (EVs) are lipid membrane vesicles released by cells. They carry active biomolecules including DNA, RNA, and protein which can be transferred to recipient cells. Isolation and purification of EVs from culture cell media and biofluids is still a major challenge. The most widely used isolation method is ultracentrifugation (UC) which requires expensive equipment and only partially purifies EVs. Previously we have shown that heparin blocks EV uptake in cells, supporting a direct EV-heparin interaction. Here we show that EVs can be purified from cell culture media and human plasma using ultrafiltration (UF) followed by heparin-affinity beads. UF/heparin-purified EVs from cell culture displayed the EV marker Alix, contained a diverse RNA profile, had lower levels of protein contamination, and were functional at binding to and uptake into cells. RNA yield was similar for EVs isolated by UC. We were able to detect mRNAs in plasma samples with comparable levels to UC samples. In conclusion, we have discovered a simple, scalable, and effective method to purify EVs taking advantage of their heparin affinity.

Extracellular RNAs (exRNAs) have been identified in all tested biofluids and have been associated with a variety of extracellular vesicles, ribonucleoprotein complexes and lipoprotein complexes. Much of the interest in exRNAs lies in the fact that they may serve as signalling molecules between cells, their potential to serve as biomarkers for prediction and diagnosis of disease and the possibility that exRNAs or the extracellular particles that carry them might be used for therapeutic purposes. Among the most significant bottlenecks to progress in this field is the lack of robust and standardized methods for collection and processing of biofluids, separation of different types of exRNA-containing particles and isolation and analysis of exRNAs. The Sample and Assay Standards Working Group of the Extracellular RNA Communication Consortium is a group of laboratories funded by the U.S. National Institutes of Health to develop such methods. In our first joint endeavour, we held a series of conference calls and in-person meetings to survey the methods used among our members, placed them in the context of the current literature and used our findings to identify areas in which the identification of robust methodologies would promote rapid advancements in the exRNA field.