Toward platelet transcriptomics in cancer diagnosis, prognosis and therapy

Widespread adoption of next-generation techniques such as RNA-sequencing (RNA-seq) has enabled research examining the transcriptome of anucleate blood platelets in health and disease, thus revealing a rich platelet transcriptomic signature that is reprogrammed in response to disease. Platelet signatures not only capture information from parent megakaryocytes and progenitor hematopoietic stem cells but also the bone marrow microenvironment, and underlying disease states. In cancer, the substantive body of research in patients with solid tumours has identified distinct signatures in 'tumour-educated platelets', reflecting influences of the tumour, stroma and vasculature on splicing, sequestration of tumour-derived RNAs, and potentially cytokine and microvesicle influences on megakaryocytes. More recently, platelet RNA expression has emerged as a highly sensitive approach to profiling chronic progressive haematologic malignancies, where the combination of large data cohorts and machine-learning algorithms enables precise feature selection and potential prognostication. Despite these advances, however, our ability to translate platelet transcriptomics toward clinical diagnostic and prognostic efforts remains limited. In this Perspective, we present a few actionable steps for our basic, translational and clinical research communities in advancing the utility of the platelet transcriptome as a highly sensitive biomarker in cancer and collectively enable efforts toward clinical translation and patient benefit.