RNA biosensors in oncology: Mechanisms, Cancer-specific applications, and a Hallmark-aligned clinical roadmap.
TL;DR
Key RNA biosensor classes developed for oncology are examined, spanning fluorescence based platforms such as aptamers, FRET probes, and molecular beacons, enzymatic and electrochemical architectures including CRISPR Cas systems and field effect transistors, metabolite responsive designs encompassing riboswitches, RNA thermometers, and reactive oxygen species sensors and sequence specific toehold switches alongside exosomal detectors.
Abstract
Cancer diagnosis continues to rely on invasive tissue sampling and static molecular assessments that cannot reflect the real time RNA alterations driving tumour progression. RNA biosensors are genetically encoded or synthetic devices that translate specific RNA markers and tumour microenvironment signals into measurable outputs offer a compelling alternative, particularly for liquid biopsy applications where non-invasive, dynamic monitoring is essential. This review systematically examines key RNA biosensor classes developed for oncology, spanning fluorescence based platforms such as aptamers, FRET probes, and molecular beacons, enzymatic and electrochemical architectures including CRISPR Cas systems and field effect transistors, metabolite responsive designs encompassing riboswitches, RNA thermometers, and reactive oxygen species sensors and sequence specific toehold switches alongside exosomal detectors. For each class, we discuss operating principles, cancer relevant applications, reported detection thresholds reaching into the zeptomolar range, and current limitations. These biosensor capabilities are mapped onto Hanahan's hallmarks of cancer, and practical clinical roadmaps are outlined for three priority applications early population screening, longitudinal therapy response and resistance monitoring, and tumour microenvironment prognostication. Convergence with microfluidic integration, AI assisted interpretation, and multiplexed nanotechnology represents the critical next step in translating these platforms from laboratory tools into routine diagnostic practice.