Tumor-educated platelets in cancer diagnostics and prognostics: A critical appraisal and roadmap for clinical translation

Abstract

Tumor-educated platelets (TEPs) are emerging as a compelling frontier in liquid biopsy, functioning as dynamic, systemic sensors that sequester and process tumor-derived biomolecules. This interaction imprints an integrated molecular signature of malignancy—spanning the transcriptome, proteome, lipidome, and crucially, the captured genome—within the circulating platelet population. Recent mechanistic evidence suggests that platelets can sequester extracellular DNA, including circulating tumor DNA (ctDNA), and may thereby act as a relatively protected, time-integrated reservoir that extends the biological persistence of tumor-derived fragments beyond the short plasma half-life (tens of minutes to a few hours). This emerging platelet-sequestered DNA (pDNA) signal complements more established platelet transcriptomic data; to date, most TEP-based molecular profiling has relied on RNA and has shown promising performance in identifying diverse solid malignancies, including premalignant lesions, and in some settings facilitating localization of the tissue of origin. However, the translation of these findings into clinical-grade assays is obstructed by substantial hurdles. Pre-analytical inconsistencies (e.g., leukocyte/erythrocyte contamination, isolation protocol choice) introduce technical noise and pervasive batch effects that compromise reproducibility. These vulnerabilities have been underscored by failed external validations and poor generalizability of discovery-phase classifiers in independent cohorts and prospective settings. This review critically dissects the factors influencing TEP diagnostic performance and outlines a concrete roadmap for clinical translation. We argue that rigorous standardization—universal standard operating procedures, harmonized pre-analytics, and quantitative quality-control metrics—is the sine qua non for implementation, to be followed by large-scale, prospective validation trials designed to demonstrate clinical utility and by multi-omics integration to maximize diagnostic yield.