Detecting low-frequency mutations within a high-abundant wild-type (WT) background is critical for precision cancer diagnostics. Standard methods, such as qPCR and NGS, face challenges including high costs, workflow complexity, and long turnaround times. Electrochemical biosensors that rely on mutation-specific capture probes present a promising alternative through their simplicity and cost-effectiveness but currently lack the sensitivity required for low-abundant mutation detection. We developed a high-throughput platform to study the affinity between biorecognition elements (i.
Detecting low-frequency mutations within a high-abundance wild-type (WT) background is essential for precision cancer diagnostics. Standard methods like qPCR and NGS, while effective, are hindered by high costs, complexity, and lengthy workflows. Electrochemical biosensors using mutation-specific capture probes offer a simpler, cost-effective alternative but lack the selectivity needed for detecting low-abundance mutations. To address this, we developed a high-throughput platform for systematically evaluating the hybridization affinity between biorecognition elements (capture probes) and target DNA under varied conditions.