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Tumor-Educated Platelet RNA for the Detection and (Pseudo)progression Monitoring of Glioblastoma

Authors :
Sol, Nik
in ‘t Veld, Sjors G.J.G.
Vancura, Adrienne
Tjerkstra, Maud
Leurs, Cyra
Rustenburg, François
Schellen, Pepijn
Verschueren, Heleen
Post, Edward
Zwaan, Kenn
Ramaker, Jip
Wedekind, Laurine E.
Tannous, Jihane
Ylstra, Bauke
Killestein, Joep
Mateen, Farrah
Idema, Sander
de Witt Hamer, Philip C.
Navis, Anna C.
Leenders, William P.J.
Hoeben, Ann
Moraal, Bastiaan
Noske, David P.
Vandertop, W. Peter
Nilsson, R. Jonas A.
Tannous, Bakhos A.
Wesseling, Pieter
Reijneveld, Jaap C.
Best, Myron G.
Wurdinger, Thomas
Source :
Cell Reports Medicine; October 2020, Vol. 1 Issue: 7
Publication Year :
2020

Abstract

Tumor-educated platelets (TEPs) are potential biomarkers for cancer diagnostics. We employ TEP-derived RNA panels, determined by swarm intelligence, to detect and monitor glioblastoma. We assessed specificity by comparing the spliced RNA profile of TEPs from glioblastoma patients with multiple sclerosis and brain metastasis patients (validation series, n = 157; accuracy, 80%; AUC, 0.81 [95% CI, 0.74–0.89; p < 0.001]). Second, analysis of patients with glioblastoma versus asymptomatic healthy controls in an independent validation series (n = 347) provided a detection accuracy of 95% and AUC of 0.97 (95% CI, 0.95–0.99; p < 0.001). Finally, we developed the digitalSWARM algorithm to improve monitoring of glioblastoma progression and demonstrate that the TEP tumor scores of individual glioblastoma patients represent tumor behavior and could be used to distinguish false positive progression from true progression (validation series, n = 20; accuracy, 85%; AUC, 0.86 [95% CI, 0.70–1.00; p < 0.012]). In conclusion, TEPs have potential as a minimally invasive biosource for blood-based diagnostics and monitoring of glioblastoma patients.

Details

Language :
English
ISSN :
26663791
Volume :
1
Issue :
7
Database :
Supplemental Index
Journal :
Cell Reports Medicine
Publication Type :
Periodical
Accession number :
ejs54459035
Full Text :
https://doi.org/10.1016/j.xcrm.2020.100101