I’m Yu-Hsin Tseng, a graduate of Asia University. For my B.S. degree, I conducted research on the agu67A gene in Xanthomonas campestris pv. campestris. Currently, I focus on the detection of the BRCA1 gene using Extended Gate Field-Effect Transistors (EGFET) for my M.S. degree.
Detection of Multiple Cancer Biomarkers Using Extended-Gate Field-Effect Transistors
曾宇馨1, 邱冠諭 2,蔡玨欣3, 李硏伃4, 梁美智 1
1College of Engineering Bioscience, National Yang Ming Chiao Tung University
Cancer continues to be a significant contributor to global mortality. According to the 2022 World Health Organization cancer statistics, there are over 19 million new cancer cases worldwide, resulting in nearly 10 million cancer-related deaths. Early detection and treatment are crucial factors in improving patient survival rates. Extended gate field-effect transistor (EGFET) biosensors have shown high sensitivity in detecting nucleic acid and cells, with advantages such as real-time sensing, label-free operation, and low-cost production. The detection of biomarkers for lung cancer and breast cancer has gained increasing attention. MicroRNAs (miRNAs) play a crucial role in gene regulation within cancer cells, and miR-21 has been identified as a potential early diagnostic indicator for lung cancer. As key mediators of intercellular communication, exosomes transport essential molecules such as proteins and nucleic acids, making them valuable for monitoring tumor progression and treatment response. Additionally, BRCA1 gene mutations are closely associated with the development of breast cancer, and detecting these mutations can aid in risk assessment and treatment strategy formulation. This study aims to develop and apply a portable EGFET biosensor on an EGFET biochip to investigate the electrical properties of miR-21, exosomes, and BRCA1 nucleic acid biomarkers. In conclusion, this study presents a novel platform to enhance the detection sensitivity of lung cancer and breast cancer biomarkers. When integrated with microfluidic devices, this EGFET biosensor platform holds great potential for biomedical research and diagnostics applications.