A High-Sensitivity, Bluetooth-Enabled PCB Biosensor for HER2 and CA15-3 Protein Detection in Saliva: A Rapid, Non-Invasive Approach to Breast Cancer Screening

Abstract

Breast cancer is a leading cause of cancer-related mortality worldwide, requiring efficient diagnostic tools for early detection and monitoring. Human epidermal growth factor receptor 2 (HER2) is a key biomarker for breast cancer classification, typically assessed using immunohistochemistry (IHC). However, IHC requires invasive biopsies and time-intensive laboratory procedures. In this study, we present a biosensor integrated with a reusable printed circuit board (PCB) and functionalized glucose test strips designed for rapid and non-invasive HER2 detection in saliva. The biosensor achieved a limit of detection of 10^-15 g/mL, 4 to 5 orders of magnitude more sensitive than the enzyme-linked immunosorbent assay (ELISA), with a sensitivity of 95/dec and a response time of 1 s. In addition to HER2, the biosensor also detects cancer antigen 15-3 (CA15-3), another clinically relevant breast cancer biomarker. The CA15-3 test demonstrated an equally low limit of detection, 10^-15 g/mL, and a higher sensitivity, 190/dec, further validated using human saliva samples. Clinical validation using 29 saliva samples confirmed our biosensor's ability to distinguish between healthy, in situ breast cancer, and invasive breast cancer patients. The system, which integrates a Bluetooth Low-Energy (BLE) module, enables remote monitoring, reduces hospital visits, and enhances accessibility for point-of-care and mobile screening applications. This ultra-sensitive, rapid, and portable biosensor can serve as a promising alternative for breast cancer detection and monitoring, particularly in rural and underserved communities.

Keywords: CA15-3; HER2; biomarker; biosensor; breast cancer; high sensitivity; non-invasive; printed circuit board; saliva; screening.

Figure 1

Photographic representation of the commercially available test strip used in this study, emphasizing the microfluidic channels and gold-plated electrode, which underwent functionalization for specific detection purposes.

Figure 2

(a) Schematic representation of the printed circuit board (PCB) utilized in this study. (b) Functional block diagram illustrating the design architecture and components of the PCB.

Figure 3

Impact of varying (a) reference voltage, (b) test voltage, and (c) gain settings on the performance of the PCB-based detection system.

Figure 4

Output digital reading from PCB at different HER2 protein concentrations. The limit of detection is 10⁻¹⁵ g/mL, while the sensitivity is 95/dec.

Figure 5

The output digital reading results from the human sample test with strips functionalized by HER2 antibody, classified by (a) breast cancer (BC) status and (b) HER2 score. The black dots are healthy volunteers, blue triangles mean In Situ breast cancer patients, and orange stars are invasive breast cancer patients.

Figure 6

(a) Digital output readings of the biosensor under varying CA15-3 protein concentrations, demonstrating its limit of detection and sensitivity. (b) Biosensor responses from human saliva samples, classified according to health status: healthy, in situ breast cancer, and invasive breast cancer.

Figure 7

Two-dimensional classification of breast cancer risk based on salivary HER2 and CA15-3 levels using a support vector classification (SVC) model. The background color map represents the model’s decision function, where blue indicates regions classified as likely healthy and yellow indicates regions classified as likely requiring further diagnosis. The solid black curve denotes the decision boundary. Green dots represent healthy individuals, red dots represent individuals requiring further diagnosis (in situ or invasive breast cancer), and black-circled points are support vectors that define the classification boundary. This visualization demonstrates the model’s ability to distinguish between classes using salivary biomarkers with high accuracy and interpretability.