Developing Ovarian Cancer Sensors Using Molecular Perceptron

Abstract

Ovarian cancer patient prognosis and quality of life are significantly affected by the failure to accurately diagnose disease at early stage. Currently, less than 15% of ovarian cancer patients are diagnosed at stage 1, when 5-year survival rates are near 93%. Early detection may save more than 80% of women diagnosed with ovarian cancer. Our goal is to develop clinical long-term implantable carbon nanotube-based sensors for ovarian cancer biomarkers to transiently detect and monitor their levels in patients. The proposed sensors will harness the unique optical properties and sensitivity of single-walled carbon nanotubes. To improve sensitivity and specificity of such sensors, previously developed to detect ovarian cancer biomarkers in vivo, we used molecular perceptron—data analytics-based methods to detect specific spectroscopic fingerprints from the binding of protein biomarkers to the nanotube surface.