A Robust Cell-Free RNA Approach for the Early Detection of Colorectal Cancer

Colorectal cancer (CRC) screening remains limited by patient adherence and sub-optimal sensitivity for early-stage disease. While liquid biopsy has revolutionized cancer diagnostics, cfDNA-based methods often struggle with early-stage detection due to low analyte levels. Here, we present a robust cell-free RNA (cfRNA) platform for the early detection of CRC. Using a retrospective cohort of 255 healthy controls and 250 CRC patients, we implemented an optimized workflow featuring a RUVg-based normalization strategy to remove platelet-driven transcriptomic noise. We identified differentially expressed genes enriched in key CRC-associated biological pathways, including inflammation, EMT, and metabolic dysregulation. An XGBoost classifier trained on these features achieved a mean AUC of 0.92 in cross-validation and 0.89 in a validation cohort, demonstrating 67% sensitivity at 90% specificity. Notably, our platform showed particular efficacy in identifying early stage cancer (stage I and II), achieving 73.7% sensitivity at 90% specificity. These findings suggest that cfRNA profiling offers a powerful, non-invasive orthogonal approach to CRC screening, capable of overcoming the sensitivity limitations of DNA-based assays in early-stage disease.