Biomarker tail genes in blood plasma cell-free RNA enable accurate detection of prostate cancer

The purpose of this study was to assess whether transcripts exhibiting strongly deviating abundance in plasma mRNA profiles can reliably differentiate prostate cancer from non-cancer states. To do so, we focused on biomarker tail genes (BTG), defined as protein-coding genes whose cell-free transcript abundance in an individual sample deviates by at least three standard deviations from a healthy control reference distribution. We applied the BTG identification and classification workflow to blood plasma samples from individuals with newly diagnosed prostate cancer (n = 132; 62 early-stage, 70 late-stage) and healthy donors (n = 48). Classification thresholds were established using a train-test cross validation approach (70%), and performance was evaluated in held-out validation samples (30%) and in a separate non-malignant cohort including healthy donors (n=37) and patients with non-malignant conditions (n=88). Across training and validation analyses, a consensus set of 247 prostate cancer BTG enabled discrimination between prostate cancer samples and healthy controls, with sensitivity and specificity reaching 100% in the validation cohort of male donors. Of note, the number of BTG per plasma sample was not associated with disease stage, and classification remained highly accurate in age-matched subsets, indicating limited influence of age on results. When applied to a cohort of individuals with diverse non-malignant conditions, the established BTG threshold yielded 94.4% specificity, and none of patients with benign prostatic hyperplasia were misclassified (n=5). To explore redundancy within the BTG set, we evaluated both cluster-derived subsets and algorithmically selected minimal panels. Multiple small subsets, including a ten-gene panel identified by a greedy selection strategy, achieved perfect classification within the validation cohort, demonstrating that strong discriminatory power is retained even when BTG sets are substantially reduced. In conclusion, blood plasma BTG constitute a highly accurate signature for prostate cancer detection, and the ability of small BTG subsets to reproduce full-set performance highlights opportunities for targeted assays. Further evaluation in broader populations and across cancer stages will refine the potential of BTG-based approaches for early detection and monitoring. (The last two authors contributed equally to this work)