RNA-sequencing of tumor-educated platelets, a novel biomarker for blood-based sarcoma diagnostics

Kimberley M. Heinhuis, Sjors G.J.G. In’t Veld, Govert Dwarshuis, Daan Van Den Broek, Nik Sol, Myron G. Best, Frits Van Coevorden, Rick L. Haas, Jos H. Beijnen, Winan J. van Houdt, Tom Würdinger, Neeltje Steeghs*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Sarcoma is a heterogeneous group of rare malignancies arising from mesenchymal tissues. Recurrence rates are high and methods for early detection by blood-based biomarkers do not exist. Hence, development of blood-based liquid biopsies as disease recurrence monitoring biomarkers would be an important step forward. Recently, it has been shown that tumor-educated platelets (TEPs) harbor specific spliced ribonucleic acid(RNA)-profiles. These RNA-repertoires are potentially applicable for cancer diagnostics. We aim to evaluate the potential of TEPs for bloodbased diagnostics of sarcoma patients. Fifty-seven sarcoma patients (active disease), 38 former sarcoma patients (cancer free for ≥3 years) and 65 healthy donors were included. RNA was isolated from platelets and sequenced. Quantified read counts were processed with self-learning particleswarm optimization-enhanced thromboSeq analysis and subjected to analysis of variance (ANOVA) statistics. Highly correlating spliced platelet messenger RNAs (mRNAs) of sarcoma patients were compared to controls (former sarcoma + healthy donors) to identify a quantitative sarcoma-specific signature measure, the TEP-score. ANOVA analysis identified distinctive platelet RNA expression patterns of 2647 genes (false discovery rate <0.05) in sarcoma patients as compared to controls. The self-learning algorithm reached a diagnostic accuracy of 87% (validation set only; n = 53 samples, area under the curve (AUC): 0.93, 95% confidence interval (CI): 0.86-1). Our data indicates that TEP RNA-based liquid biopsies may enable for sarcoma diagnostics.

Original languageEnglish
Article number1372
JournalCancers
Volume12
Issue number6
DOIs
Publication statusPublished - Jun 2020

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