Terminal modifications independent cell-free RNA sequencing enables sensitive early cancer detection and classification

Jun Wang, Jinyong Huang, Yunlong Hu, Qianwen Guo, Shasha Zhang, Jinglin Tian, Yanqin Niu, Ling Ji, Yuzhong Xu, Peijun Tang, Yaqin He, Yuna Wang, Shuya Zhang, Hao Yang, Kang Kang, Xinchun Chen, Xinying Li, Ming Yang and Deming Gou ()
Additional contact information
Jun Wang: Shenzhen University
Jinyong Huang: Shenzhen University
Yunlong Hu: Peking University Shenzhen Hospital
Qianwen Guo: Shenzhen University
Shasha Zhang: Shenzhen University
Jinglin Tian: Shenzhen University
Yanqin Niu: Shenzhen University
Ling Ji: Peking University Shenzhen Hospital
Yuzhong Xu: People’s Hospital of Bao’an Shenzhen
Peijun Tang: The Fifth People’s Hospital of Suzhou
Yaqin He: General Hospital of Ningxia Medical University
Yuna Wang: Ningxia Medical University
Shuya Zhang: Ningxia Medical University
Hao Yang: The Second People’s Hospital of Shenzhen
Kang Kang: Shenzhen University
Xinchun Chen: Shenzhen University
Xinying Li: Shenzhen Geneups Biotechnology Co.
Ming Yang: Shenzhen University
Deming Gou: Shenzhen University

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: Abstract Cell-free RNAs (cfRNAs) offer an opportunity to detect diseases from a transcriptomic perspective, however, existing techniques have fallen short in generating a comprehensive cell-free transcriptome profile. We develop a sensitive library preparation method that is robust down to 100 µl input plasma to analyze cfRNAs independent of their 5’-end modifications. We show that it outperforms adapter ligation-based method in detecting a greater number of cfRNA species. We perform transcriptome-wide characterizations in 165 lung cancer, 30 breast cancer, 37 colorectal cancer, 55 gastric cancer, 15 liver cancer, and 133 cancer-free participants and demonstrate its ability to identify transcriptomic changes occurring in early-stage tumors. We also leverage machine learning analyses on the differentially expressed cfRNA signatures and reveal their robust performance in cancer detection and classification. Our work sets the stage for in-depth study of the cfRNA repertoire and highlights the value of cfRNAs as cancer biomarkers in clinical applications.

Date: 2024
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DOI: 10.1038/s41467-023-44461-y

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