Cell Reports Medicine
Combined multi-omics and multi-spectral profiling of plasma extracellular vesicles reveals liquid biopsy biomarkers for glioma diagnosis
Stephen David Robinson, Biniam Tsegay Haile, Matthew Reily-Bell, Olivia Iwanowytsch, Siobhan Palmer, Dorte Schou Nørøxe, Panagiota S. Filippou, Joanna Renaut, Alan Lazarus, Georgios Antoniou, Mark Samuels, Viviana Vella, Chrysa Filippopoulou, William Jones, Josephine Jung, Xiaoou Li, Nan Ji, Yang Zhang, Aleena Azam, Jane Skjoeth-Rasmussen, Ulrik Lassen, Adriana Saraiva, Ahmad Taha, Tania Slatter, Greg Jones, Rajesh Katare, Holly J. Butler, Matthew J. Baker, Marilena Hadjidemetriou, Duncan Gilbert, Benjamin Towler, Keyoumars Ashkan, Giles Critchley, Frances M.G. Pearl, and Georgios Giamas.
Plasma small extracellular vesicles (sEVs) are a promising liquid biopsy tool. This study aims to delineate and validate a multimodal plasma sEV biomarker signature for glioma. We use size exclusion chromatography to separate sEVs from plasma (1 mL) and a combination of multi-spectral (Fourier transform infrared/Raman) and orthogonal multi-omics (proteomic/microRNA) approaches on 206 plasma samples (159 individuals) across three independent cohorts. We identify distinct glioma sEV biomolecular profiles, including differences in sEV protein/nucleic acid composition, and consistent alterations in 45 proteins and 20 microRNAs. Machine learning models derived from training cohort data achieve high diagnostic performance (areas under the curve [AUCs] 0.931–0.971), while external validation across independent cohorts confirms the signature’s diagnostic potential, with 100% accuracy for the proteomic and multimodal signatures in the longitudinal cohort. Our findings, generated through a rigorous multi-cohort and multi-algorithmic framework, establish the potential of plasma sEV signatures as a clinically relevant diagnostic liquid biopsy approach for glioma.