Abstract:
This presentation discusses biosensor detection of ovarian cancer (OC). Personalized medicine offers a promising strategy for tailoring OC treatment to an individual’s genetic makeup and specific cancer subtype. This precision-based approach requires consideration of all parameters influencing OC pathogenesis, including the expression profiles of various biomarkers. To enhance early detection and diagnostic accuracy, particularly in light of OC’s heterogeneity, a multiplex biosensor presents a compelling solution. Unlike single-marker assays, multiplex sensors enable the simultaneous detection of multiple biomarkers associated with different histological subtypes of OC. This reduces the risk of false negatives, such as those that might occur when relying solely on CA-125, which is predominantly elevated HGSC but may remain at normal levels in early-stage disease or in other subtypes. By integrating multiple biomarkers, a multiplex platform improves both sensitivity and specificity, broadening diagnostic coverage across diverse patient populations. Moreover, a better understanding on the various parameters influencing OC supports the advancement of personalized treatment strategies, allowing clinicians to tailor therapeutic interventions based on a patient’s unique combination of biomarker concentrations and disease characteristics. In our work we use a number of electrochemical strategies to produce multiplexed sensing. This includes cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS).
