Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis

ABSTRACT Exosomes are nano-sized extracellular vesicles released by many cells that contain molecules characteristic of their cell-of-origin, including microRNA. Exosomes released by glioblastoma cross the blood-brain-barrier into the peripheral circulation, and carry molecular cargo distinct to that of ‘free-circulating’ miRNA. In this pilot study, serum exosomal-microRNAs were isolated from glioblastoma ( n =12) patients and analyzed using unbiased deep sequencing. Results were compared to sera from age- and gender-matched healthy controls, and to grades II-III ( n =10) glioma patients. Significant differentially expressed microRNAs were identified, and the predictive power of individual and subsets of microRNAs were tested using univariate and multivariate analyses. Additional sera from glioblastoma patients ( n =4) and independent sets of healthy ( n =9) and non-glioma ( n =10) controls were used to further test the specificity and predictive power of this unique exosomal-microRNA signature. Twenty-six microRNAs were differentially expressed in serum exosomes from glioblastoma patients’ relative to healthy controls. Random forest modeling and data partitioning selected seven miRNAs (miR-182-5p, miR-328-3p, miR-339-5p, miR-340-5p, miR-485-3p, miR-486-5p and miR-543) as the most stable for classifying glioblastoma. Strikingly, within this model, six iterations of these miRNA classifiers could distinguish glioblastoma patients from controls with perfect accuracy. The seven-miRNA panel was able to correctly classify all specimens in validation cohorts ( n =23). Also identified were 23 dysregulated miRNAs in IDH MUT gliomas, a partially overlapping yet distinct signature of lower grade glioma. Serum exosomal-miRNA signatures can accurately diagnose glioblastoma preoperatively. miRNA signatures identified are distinct from previously reported ‘free-circulating’ miRNA studies in GBM patients, and appear to be superior.