Abstract:
Currently, the primary methods for detecting the ovarian cancer (OC) are transvaginal ultrasound (TVUS) and blood tests for the cancer antigen 125 (CA125) biomarker. However, these methods alone are not suitably sensitive or specific to identify the disease in its early, asymptomatic stages. . HE4, which is also used clinically, improves diagnostic performance, particularly when paired with CA125. Lysophosphatidic acid (LPA) also shows considerable promise and additional testing can help validate its significance to early-stage detection and screening potential. This marker has been the subject of evaluation in our research on OC detection. It has become increasingly clear that implementing a diagnostic panel comprised of several biomarkers is advisable in terms of early stage assay.
Biosensor technology offers great promise in developing multiplex systems for OC detection and monitoring disease progression. Future integration of multiplex biosensors with artificial intelligence (AI) and machine learning approaches may further improve diagnostic capabilities by enabling the analysis of complex biomarker profiles, improving differentiation between disease states, and supporting the development of precision medicine approaches. Electrochemical biosensors offer several advantages, including high sensitivity, relatively low cost, rapid analysis, and compatibility with point-of-care testing applications. This paper aims to discuss current strategies in electrochemical multiplexing and recent advancements in the development of electrochemical multiplexed platforms for ovarian cancer detection. Additionally, we will present two proof-of-concept sensors targeting CA125 and HE4 as initial steps toward the development of a fully multiplexed system.
