# Plasma extracellular vesicle sampling from glioblastoma demonstrates a small RNA signature indicative of disease and identifies lncRNA RPPH1 as a biomarker

## TL;DR

This study shows that small RNA in blood extracellular vesicles can indicate glioblastoma and identifies RPPH1 as a potential biomarker for tracking the disease.

## Contribution

The study identifies RPPH1 as a novel biomarker in plasma extracellular vesicles for glioblastoma diagnosis and progression.

## Key findings

- Over 750 differentially expressed small RNAs were found in glioblastoma patient plasma EVs.
- RPPH1 levels decreased after surgery and increased with disease progression.
- MiRNA pathway analysis confirmed the relevance of EV cargo to glioblastoma biology.

## Abstract

Glioblastoma (GBM) and cells of the tumour microenvironment (TME) secrete extracellular vesicles (EVs) into the plasma that contain genetic and protein cargo, which function in paracrine signaling. Isolation of these EVs and their cargo from plasma could lead to a simplistic tool that can inform on diagnosis and disease course of GBM.

In the present study, plasma EVs were captured utilizing a peptide affinity method (Vn96 peptide) from GBM patients and normal controls followed by next generation sequencing to define a small RNA (sRNA) signature unique to GBM.

Over 750 differentially expressed sRNA (miRNA, snoRNA, lncRNA, tRNA, mRNA fragments and non-annotated regions) were identified between GBM and controls. MiEAA 2.0 pathway analysis of the miRNA in the sRNA signature revealed miRNA highly enriched in both EV and GBM pathways demonstrating the validity of results in capturing a signal from the TME. Also revealed were several novel GBM plasma EV sRNA biomarkers including lncRNA RPPH1 (Ribonuclease P Component H1), RNY4 (Ro60-Associated Y4) and RNY5 (Ro60-Associated Y5). Furthermore, in paired longitudinal patient plasma sampling, RPPH1 informed on surgical resection (decreased on resection) and importantly, RPPH1 increased again on clinically defined progression.

The present provides preliminary data that support the continued investigation of plasma EV sRNA sampling (and particularly RPPH1) as part of a multi-pronged approach to GBM diagnosis and disease course surveillance.