Extracellular Vesicles from Neurosurgical Aspirates Identifies Chaperonin Containing TCP1 Subunit 6A as a Potential Glioblastoma Biomarker with Prognostic Significance.

Glioblastoma, WHO-grade IV glioma, carries a dismal prognosis owing to its infiltrative growth and limited treatment options. Glioblastoma-derived extracellular vesicles (EVs; 30-1000 nm membranous particles) influence the microenvironment to mediate tumor aggressiveness and carry oncogenic cargo across the blood-brain barrier into the circulation. As such, EVs are biomarker reservoirs with enormous potential for assessing glioblastoma tumors in situ. Neurosurgical aspirates are rich sources of EVs, isolated directly from glioma microenvironments. EV proteomes enriched from glioblastoma (n = 15) and glioma grade II-III (n = 7) aspirates are compared and 298 differentially-abundant proteins (p-value < 0.00496) are identified using quantitative LC-MS/MS. Along with previously reported glioblastoma-associated biomarkers, levels of all eight subunits of the key molecular chaperone, T-complex protein 1 Ring complex (TRiC), are higher in glioblastoma-EVs, including CCT2, CCT3, CCT5, CCT6A, CCT7, and TCP1 (p < 0.00496). Analogous increases in TRiC transcript levels and DNA copy numbers are detected in silico; CCT6A has the greatest induction of expression and amplification in glioblastoma and shows a negative association with survival (p = 0.006). CCT6A is co-localized with EGFR at 7p11.2, with a strong tendency for co-amplification (p < 0.001). Immunohistochemistry corroborates the CCT6A proteomics measurements and indicated a potential link between EGFR and CCT6A tissue expression. Putative EV-biomarkers described here should be further assessed in peripheral blood.

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

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 grade 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 IDHMUT 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.