Oral Presentation Australasian Extracellular Vesicles Conference 2018

Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis (#19)

Saeideh Ebrahimkhani 1 2 , Fatemeh Vafaee 3 , Susannah Hallal 1 4 , Heng Wei 2 , Maggie Y.T. Lee 2 , Paul E Young 5 , Laveniya Satgunaseelan 6 , Brindha Shivalingam 7 , Catherine M Suter 8 , Michael E Buckland 2 , Kimberley L Kaufman 9
  1. Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
  2. Department of Neuropathology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
  3. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, NSW, Australia
  4. Discipline of Pathology, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia
  5. Division of Molecular Structural and Computational Biology, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia
  6. Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, NSW, Australia
  7. Department of Surgery, Chris O'Brien Lifehouse, Camperdown, NSW, Australia
  8. Faculty of Medicine, University of New South Wales, Kensington, NSW, Australia
  9. School of Life and Environmental Science, Brain and Mind Centre, The University of Sydney, Camperdown, NSW, Australia

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. Serum exosomal-microRNAs were isolated from IDHWT glioblastoma (n=12) patients and analysed using unbiased deep sequencing. Results were compared to sera from age- and gender-matched healthy controls, and to grades II-III (n=10) IDHMUT 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. 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 the miRNA classifiers could distinguish glioblastoma patients from controls with perfect accuracy. 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. 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.