Optical biosensors for cancer diagnosis and monitoring.

Abstract

Cancer is driven by complex genetic and epigenetic alterations that promote uncontrolled cellular proliferation, invasion, and metastasis. Despite substantial advances in oncology, conventional diagnostic approaches remain constrained by invasiveness, cost, limited sensitivity, and limited capacity to detect malignancies at early stages. Optical biosensors have emerged as promising platforms for sensitive, rapid, and non- or minimally invasive cancer biomarker detection, offering opportunities for real-time, label-free analysis of biofluids. These systems integrate highly selective biorecognition elements with optical transducers that interrogate molecular interactions. Recent advances in nanomaterials and nanophotonic architectures have further improved analytical sensitivity, while artificial intelligence (AI) and machine-learning approaches enable multiplexed biomarker profiling, pattern recognition, and increasingly precise diagnostic interpretation. This review critically presents the fundamental principles, sensor configurations, and applications of optical biosensors for cancer detection and monitoring, with particular emphasis on technological advances that underpin sensitivity, specificity, multiplexing, and clinical translation. The review also discusses key barriers to widespread implementation, including reproducibility, scalability, biofluid complexity, and standardization. Emerging directions, including quantum-enhanced sensing, advanced nanophotonics, and AI-driven analytics, are evaluated in the context of next-generation precision diagnostics. By integrating photonics, molecular biology, nanotechnology, and bioengineering, optical biosensors have strong potential to enable earlier, non-invasive or minimally invasive, patient-centric cancer detection and contribute to more effective precision oncology.