Electrochemical Immunosensor based on NiO for CA 15-3 detection and Agent-Based Modelling for Treatment Optimization

Abstract

Diagnosis of breast cancer at its onset is crucial for the therapeutics so as to make the condition treatable, thereby increasing the patient survival rate. We report herein a simple and efficient electrochemical method using NiO thin film-based immunoelectrode to detect the proteins released by cancerous cells in human plasma (CA 15-3 polyclonal antibody). The raised polyclonal antibody is confirmed by Scanning Electron Microscope (SEM), Western blot and ouchterlony techniques. The developed immunoelectrode (CA 15-3/NiO/ITO/glass) has a low detection limit of 5 U/mL, sensitivity of 0.18 mA/(UmL^-1) and fast response time of 2 s, which is comparable to that obtained with commercial ELISA kit. The testing of real samples of breast cancer was carried out using both the prepared immunoelectrode and CA 15-3 ELISA kit and the outcomes show strong correlation with one another. Interference studies with other diseases such as ovary cancer, lung cancer, asthma and tuberculosis were also analyzed by both techniques. The prepared immunoelectrode (CA 15-3/NiO/ITO/glass) was found to be highly sensitive and selective towards breast cancer detection and pave the way for the development of a simple, cost-effective and fast detection technique for breast cancer detection. We used an agent-based simulation model to evaluate the effects of targeting distinct cancer cell populations in breast cancer. Results showed that targeting cancer stem cells (CSCs) prevents tumor regrowth but harms other living cells, while targeting migratory cancer stem cells reduces metastasis with minimal impact on tumor mass. Targeting transitory cells lowered tumor burden without affecting metastasis. These findings suggest that a combined approach targeting CSCs, migratory stem cells, and transitory cells is crucial for effectively managing tumor growth and metastasis, offering a comprehensive strategy for breast cancer treatment.