Tumor-Educated Platelet RNA Profiling for Cancer Detection and Treatment Monitoring: A Comprehensive Narrative Review

Abstract

Liquid biopsy has emerged as a transformative approach in oncology, offering minimally invasive means for cancer detection, molecular characterization, and longitudinal disease monitoring. Among the diverse biosources available for liquid biopsy, tumor-educated platelets (TEPs) have garnered substantial interest as a rich and dynamic source of RNA-based biomarkers. Unlike circulating tumor DNA, which may present with low mutant allele fractions in early-stage disease, platelets offer abundant and relatively stable RNA that can be isolated from routine blood draws. Platelets, though anucleate, harbor megakaryocyte-derived messenger RNA and possess the capacity for RNA processing, enabling them to generate diverse transcriptomic repertoires. Importantly, platelets can sequester tumor-derived RNA from the circulation and through contact with tumor cells, producing disease-specific RNA signatures that can be captured through RNA sequencing and analysed using machine learning algorithms. Pan-cancer studies have demonstrated that TEP profiles can distinguish cancer patients from healthy controls with high accuracy, identify the primary site of tumor origin, and detect actionable molecular alterations. Disease-specific investigations have further validated TEP-based diagnostics across multiple solid tumor types, including non-small cell lung cancer, glioblastoma, colorectal cancer, ovarian cancer, pancreatic cancer, and sarcoma. Beyond diagnosis, TEP RNA signatures exhibit dynamic changes during treatment, supporting their application in monitoring therapeutic response and detecting disease progression. Nevertheless, critical challenges remain, including protocol sensitivity, pre-analytical confounding, and the need for rigorous prospective validation. This narrative review comprehensively examines the biological foundations of platelet tumor-RNA sequestration, synthesizes evidence on diagnostic and monitoring performance across cancer types, discusses technical platforms and computational methodologies, addresses limitations and negative findings, compares TEPs with other liquid biopsy modalities, and delineates future research priorities necessary to translate this promising approach into clinical practice.