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; et al.; Georgios Giamas

doi:10.1016/j.xcrm.2026.102744

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, …

Cell reports. Medicine, Vol.7(5), 102744

17/04/2026

: https://doi.org/10.1016/j.xcrm.2026.102744

https://hdl.handle.net/10523/50601

machine-learning

glioblastoma

spectroscopy

multi-omics

brain tumor

glioma

biomarker

blood

extracellular vesicle

liquid biopsy

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.

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url

https://doi.org/10.1016/j.xcrm.2026.102744

Published (Version of record)

: 9926854987901891
: 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
et al.
Georgios Giamas
: Physiology
: Cell reports. Medicine, Vol.7(5), 102744
: Elsevier
: 17/04/2026
: Refer to article for funding information
: Copyright © The Author(s) 2026. This work was first published in Cell Reports Medicine (Elsevier). This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://www.creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, provided that the original work is properly attributed to the creator(s) and the source, a link to the Creative Commons license is provided, and any changes made are indicated.
: English
: Journal article