A perception-based nanosensor platform to detect cancer biomarkers Journal Article


Authors: Yaari, Z.; Yang, Y.; Apfelbaum, E.; Cupo, C.; Settle, A. H.; Cullen, Q.; Cai, W.; Long Roche, K.; Levine, D. A.; Fleisher, M.; Ramanathan, L.; Zheng, M.; Jagota, A.; Heller, D. A.
Article Title: A perception-based nanosensor platform to detect cancer biomarkers
Abstract: 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. © 2021 The Authors.
Keywords: survival rate; biomarkers; molecular recognition; body fluids; antibodies; gynecologic cancer; diseases; cancer biomarkers; machine learning; implants (surgical); learning algorithms; molecular recognition element; machine learning algorithms; optical nanosensors; implantable devices; biofluids; biomolecular assays; perception-based
Journal Title: Science Advances
Volume: 7
Issue: 47
ISSN: 2375-2548
Publisher: Amer Assoc Advancement Science  
Date Published: 2021-11-19
Start Page: abj00852
Language: English
DOI: 10.1126/sciadv.abj0852
PROVIDER: scopus
PMCID: PMC8604403
PUBMED: 34797711
DOI/URL:
Notes: Article -- Export Date: 3 January 2022 -- Source: Scopus
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MSK Authors
  1. Martin Fleisher
    312 Fleisher
  2. Daniel Alan Heller
    112 Heller
  3. Alexander Howard Settle
    7 Settle
  4. Zvi Aharon Yaari
    11 Yaari
  5. Christian Cupo
    3 Cupo