Journal Article

Diagnosis of head and neck cancer by AI-based tumor-educated platelet RNA profiling of liquid biopsies

Terhaard, Chris H.J., Lamers, Femke, Langendijk, Johannes A., Würdinger, Thomas, van Wieringen, Wessel N., Best, Myron G., Klausch, Thomas, Leemans, C. René, de Jong, Robert J. Baatenburg, Takes, Robert P., Veld, Sjors G.J.G. In ‘t, Post, Edward, Mes, Steven W., Brakenhoff, Ruud H., Leeuw, Irma M. Verdonck-de, Poell, Jos B., Wondergem, Niles E., Bloemena, Elisabeth

2026

Overview

Over 95% of head and neck cancers are squamous cell carcinoma (HNSCC). HNSCC is mostly diagnosed late, causing a poor prognosis despite the application of invasive treatment protocols. Tumor-educated platelets (TEPs) have been shown to hold promise as a molecular tool for early cancer diagnosis. We sequenced platelet mRNA isolated from blood of 101 patients with HNSCC and 101 propensity-score matched noncancer controls. Two independent machine learning classification strategies were employed using a training and validation approach to identify a cancer predictor: a particle swarm optimized support vector machine (PSO-SVM) and a least absolute shrinkage and selection operator (LASSO) logistic regression model. The best performing PSO-SVM predictor consisted of 245 platelet transcripts and reached a maximum area under the curve (AUC) of 0.87. For the LASSO-based prediction model, 1,198 mRNAs were selected, resulting in a median AUC of 0.84, independent of HPV status. Our data show that TEP RNA classification by different AI tools is promising in the diagnosis of HNSCC.

• Publisher: American Society for Clinical Investigation
• Subject: Accuracy / Adult / Aged / Alcohol / Algorithms / Artificial intelligence / Biomarkers / Biomarkers, Tumor - blood / Biomarkers, Tumor - genetics / Biopsy / Blood platelets / Blood Platelets - metabolism / Cancer / Classification / Diagnosis / Female / Head & neck cancer / Head and neck carcinoma / Head and Neck Neoplasms - blood / Head and Neck Neoplasms - diagnosis / Head and Neck Neoplasms - genetics / Human papillomavirus / Humans / Liquid Biopsy - methods / Machine Learning / Male / Medical diagnosis / Medical prognosis / Middle Aged / Platelets / Prediction models / Quality control / Quality of life / RNA, Messenger - genetics / Smoking / Squamous cell carcinoma / Squamous Cell Carcinoma of Head and Neck - blood / Squamous Cell Carcinoma of Head and Neck - diagnosis / Squamous Cell Carcinoma of Head and Neck - genetics / Support Vector Machine / Support vector machines / Tumors