A perception-based nanosensor platform to detect cancer biomarkers

Zvi Yaari, Yoona Yang, Elana Apfelbaum, Christian Cupo, Alex H. Settle, Quinlan Cullen, Winson Cai, Kara Long Roche, Douglas A. Levine, Martin Fleisher, Lakshmi Ramanathan, Ming Zheng, Anand Jagota, Daniel A. Heller*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Conventional molecular recognition elements, such as antibodies, present issues for developing biomolecular assays for use in certain technologies, such as implantable devices. Additionally, antibody development and use, especially for highly multiplexed applications, can be slow and costly. We developed a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids. We demonstrated this platform in gynecologic cancers, often diagnosed at advanced stages, leading to low survival rates. We investigated the detection of protein biomarkers in uterine lavage samples, which are enriched with certain cancer markers compared to blood. We found that the method enables the simultaneous detection of multiple biomarkers in patient samples, with F1-scores of ∼0.95 in uterine lavage samples from patients with cancer. This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements.

Original languageAmerican English
Article numberabj0852
JournalScience advances
Issue number47
StatePublished - 19 Nov 2021
Externally publishedYes

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