Detection of Cancer-Associated Mutations Using Primer Exchange Reaction-Based Signal Amplification and Lateral Flow...

The ability to sensitively and specifically detect cancer-associated nucleic acids carrying single-nucleotide mutations is critical for early cancer detection, patient stratification, and personalized treatment, particularly through non-invasive liquid biopsy approaches. Detecting low-abundance nucleic acid fragments-particularly those with single-nucleotide variations-remains a significant challenge for point-of-care (POC) diagnostics. Here, we report a programmable DNA-based self-assembly strategy that leverages primer exchange reaction (PER) for isothermal signal amplification and enables colorimetric detection of cancer-specific DNA and RNA fragments on gold nanoparticle-based lateral flow assays (LFAs). This method uses PER-generated DNA concatemers functionalized with multiple FITC-labeled imager strands to enhance the visual signal on conventional LFA strips. We demonstrate that this approach enables detection of a synthetic P53 oncogene fragment with a limit of detection as low as 16 pM, representing a 16-fold improvement over single-dye labeled controls. The system also reliably distinguishes single-nucleotide mutations at 10% relative abundance within a wild-type background. Moreover, we show successful detection of mutant fragments in complex biological fluids such as serum and saliva, as well as of RNA extracted from breast cancer cell lines and RNA derived from circulating tumor DNA (ctDNA) from patient plasma samples. Specifically, we detect clinically relevant PIK3CA E545K/A and P53 R280K mutations, consistent with Sanger sequencing results and validating our method for liquid biopsy applications. Overall, this PER-based self-assembly system provides a simple, robust, and sensitive platform for mutation-specific nucleic acid detection using LFAs and offers strong potential for translation into laboratory research applications and POC diagnostics workflows for cancer and other genetic disorders.