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A perception-based nanosensor platform to detect cancer biomarkers
Zvi Yaari1, Yoona Yang2, Elana Apfelbaum1
1Memorial Sloan Kettering Cancer Center, NY, New York 10065, USA.
Science Advances
|November 19, 2021
Summary
This study introduces a novel perception-based platform using optical nanosensors and machine learning for detecting multiple cancer biomarkers in biofluids. This approach offers a faster, cost-effective alternative to traditional antibody-based methods for disease diagnostics.
Area of Science:
- Biomedical Engineering
- Nanotechnology
- Machine Learning
Background:
- Conventional molecular recognition elements like antibodies pose challenges for developing assays in technologies such as implantable devices.
- Antibody development and application, particularly for highly multiplexed assays, can be time-consuming and expensive.
Purpose of the Study:
- To develop a perception-based platform utilizing an optical nanosensor array and machine learning for the simultaneous detection of multiple protein biomarkers in biofluids.
- To demonstrate the platform's efficacy in gynecologic cancer diagnostics using uterine lavage samples.
Main Methods:
- Development of a perception-based platform integrating an optical nanosensor array with machine learning algorithms.
- Application of the platform to detect multiple protein biomarkers in uterine lavage samples from gynecologic cancer patients.
Main Results:
- The platform successfully enabled simultaneous detection of multiple biomarkers in patient samples.
- Achieved high performance with F1-scores of approximately 0.95 in uterine lavage samples from cancer patients.
Conclusions:
- The perception-based system shows significant potential for developing multiplexed disease biomarker sensors.
- This approach bypasses the need for specific molecular recognition elements, offering a more versatile diagnostic tool.
