A groundbreaking study published in Cell Reports Medicine reveals the identification of novel small RNA molecules, termed oncRNAs, which serve as cancer-specific barcodes detectable in blood samples. Researchers cataloged over 260,000 oncRNAs across 32 tumor types, finding distinctive patterns linked to specific tissues. Using machine learning, they demonstrated that these oncRNA signatures could differentiate cancer types and subtypes. This method holds promise for improving liquid biopsies, particularly in monitoring breast cancer post-therapy by potentially offering a non-invasive marker for tracking minimal residual disease and predicting patient outcomes.
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