OM-sqPCR enables one-Step multiplex quantification of circulating small-RNA subclasses for colorectal cancer classification

Description

Accurate and multiplexed quantification of circulating small RNAs (sRNAs) remains technically challenging due to their structural diversity and low abundance. Here we present OM-sqPCR, an AI-assisted one-step multiplex quantitative PCR platform that enables simultaneous detection of microRNAs, transfer RNA–derived sRNAs (tsRNAs), and ribosomal RNA–derived sRNAs (rsRNAs) in a single closed-tube reaction. The system integrates optimized enzyme–buffer chemistry for short RNA templates with machine-learning–guided primer–probe design, enabling synchronized amplification across multiple optical channels. Applied to a multicentre clinical cohort (n = 651), OM-sqPCR identified a four-sRNA signature that discriminated colorectal cancer from controls with an area under the ROC curve (AUC) = 0.97, 85.9% sensitivity, and 93.1% specificity, outperforming serum carcinoembryonic antigen (CEA) and maintaining high accuracy in early-stage disease (stage I–II, sensitivity: 84.6%). The workflow also validated biomarker panels for renal and thyroid cancers with comparable accuracy (AUC > 0.98). This generalizable, low-cost platform provides a scalable and automation-ready solution for unified small-RNA quantification across diverse clinical contexts.

Institutions

• Nanjing University

  Jiangsu, Nanjing

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