PO-498 Spliced RNA panels from tumor-educated platelets (TEP) enable detection of early breast cancer

Abstract

IntroductionDetection of early-stage breast cancer from blood is a highly desirable screening application of liquid biopsies. Tumor-educated platelets (TEP) contain distinct spliced RNA repertoires and can function as a blood-based biosource for the detection of cancer (Best et al. Cancer Cell 2015). Here, we investigated the potential of TEP RNA profiles as an early breast cancer diagnostics algorithm.Material and methodsWe sequenced platelets of women with stage I-III breast cancer (n=134) and asymptomatic non-cancer females (n=121). Samples were divided over a training, evaluation and validation set. We developed a TEP RNA-based classification algorithm, which was tailored towards two clinically relevant diagnostic applications. The first application is to rule out breast cancer in women with an abnormal mammography. The second application is to rule in breast cancer in asymptomatic women carrying an elevated baseline breast cancer risk. We examined if classifications depended on patient age, tumour stage, subtype, BRCA mutation status, and breast density. In addition, we tested if the algorithm was breast cancer specific by testing our algorithm in a pan-cancer cohort (n=192).Results and discussionsIn the evaluation cohort (n=48 of which n=24 early breast cancer cases) the TEP RNA-based breast cancer classification had an accuracy of 90% with an AUC of 0.96 (95% confidence interval (CI) 0.92–1.00; p<0.001). In the validation cohort, the TEP RNA-based classification algorithm reached an overall accuracy of 86% and an AUC of 0.93 (95% CI 0.89–0.98, p<0.001). Most important, the accuracy was 91% in stage I/II disease. In a confirmatory rule-out application (positive mammography) sensitivity would be 94% with a specificity of 67%; whereas in a screening setting sensitivity would be 80% with a specificity of 93%. The classifier performance is consistent across subgroups based on patient age, tumour stage, subtype, tissue density, or BRCA1/2-status. The breast cancer TEP profiles were distinct from those of women with other tumour types (n=192, accuracy: 87%, AUC: 0.91, 95% CI 0.87–0.96, p<0.001). Although results look promising, sensitivity and specificity should be improved for clinical implementation. Follow-up studies should, among others, require sample collection in actual screening and confirmatory settings.ConclusionWe show that platelet RNA signatures may enable blood-based screening for early breast cancer, and warrant validation in a confirmatory and screening setting.