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Updated: Jun 11, 2025

Detection and Monitoring of Tumor Associated Circulating DNA in Patient Biofluids
Published on: June 8, 2019
Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal
Samet Kocabey1, Sarah Cattin2, Isabelle Gray1
1Laboratory of Experimental and Translational Oncology, Department of Oncology, Microbiology and Immunology, Faculty of Science and Medicine, University of Fribourg, Chemin Du Musée 18, PER17, 1700, Fribourg, Switzerland; NCCR Bio-inspired Materials, University of Fribourg, 1700, Fribourg, Switzerland.
Abstract:
The detection of cancer-associated nucleic acids and mutations through liquid biopsy has emerged as a highly promising non-invasive approach for early cancer detection and monitoring. In this study, we report the development of primer exchange reaction (PER) based signal amplification strategy that enables the rapid, sensitive and specific detection of nucleic acids bearing cancer specific single nucleotide mutations using flow cytometry. Using micrometer size beads as support for immobilizing oligonucleotides and programmable PER assembly for target oligonucleotide recognition and fluorescence signal amplification, we demonstrated the versatile detection of target nucleic acids including KRAS oligonucleotide, fragmented mRNAs, and miR-21. Moreover, our detection system can discriminate single base mutations frequently occurred in cancer-associated genes including KRAS, PIK3CA and P53 from cell extracts and circulating tumor DNAs (ctDNAs). The detection is highly sensitive, with a limit of detection down to 27 fM without pre-amplification. In view of a clinical application, we demonstrate the detection of single mutations after extraction and pre-amplification of ctDNAs from the plasma of breast cancer patients. Importantly, our detection strategy enabled the detection of single KRAS mutation even in the presence of 1000-fold excess of wild type (WT) DNA using multi-color flow cytometry detection approach. Overall, our strategy holds immense potential for clinical applications, offering significant improvements for early cancer detection and monitoring.

