Abstract
Recent studies have begun to highlight the advantages of RNA-based liquid biopsy technology for cancer early detection, and we sought to further advance the development of RNA liquid biopsies by incorporating single-molecule, long-read sequencing technology. Cell-free RNAs are dynamically secreted by the cells that comprise our tissues and organs but are thought to be largely degraded in the blood. To determine the true length of cell-free RNAs, we performed long-read nanopore sequencing on cell-free RNAs isolated from pancreatic and esophageal cancer patient plasma and found that thousands of genes are detectable as full-length cell-free RNAs in vivo. By creating a custom annotation of the transcriptome for cell-free RNA quantification, we found that cancer patients exhibit high levels of repetitive cell-free RNAs in plasma, with full-length, SINE-derived cell-free RNAs being among the most abundant repetitive RNAs. Moreover, we found that utilizing repetitive cell-free RNA features substantially improved the performance of our machine learning models for cancer classification. Notably, nanopore sequencing enabled us to discover over 250,000 novel cell-free RNAs that have not been previously annotated in the human genome. Our findings highlight the value and utility of long-read nanopore sequencing of cell-free RNAs for discovering and leveraging novel RNA biomarkers for cancer early detection via RNA liquid biopsy technology.
Citation Format: Daniel H. Kim. Advancing RNA liquid biopsy technology via long-read sequencing [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A023.