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Volume 14
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10.3390/cells14050375
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Article

Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy

by
Obdulia Covarrubias-Zambrano
1,
Deepesh Agarwal
2,
Joan Lewis-Wambi
1,
Raul Neri
1,
Andrea Jewell
3,
Balasubramaniam Natarajan
2 and
Stefan H. Bossmann
1,*
1
Department of Cancer Biology, University of Kansas Medical Center, Kansas City, KS 66160, USA
2
Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA
3
Department of Obstetrics and Gynecology, University of Kansas Medical Center, Kansas City, KS 66160, USA
*
Author to whom correspondence should be addressed.
Cells 2025, 14(5), 375; https://doi.org/10.3390/cells14050375
Submission received: 9 January 2025 / Revised: 26 February 2025 / Accepted: 28 February 2025 / Published: 4 March 2025
(This article belongs to the Special Issue Nanofluidics, Nanopores, and Nanomaterials for Understanding Biology)
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Abstract

Ovarian cancer survival depends strongly on the time of diagnosis. Detection at stage 1 must be the goal of liquid biopsies for ovarian cancer detection. We report the development and validation of graphene-based optical nanobiosensors (G-NBSs) that quantify the activities of a panel of proteases, which were selected to provide a crowd response that is specific for ovarian cancer. These G-NBSs consist of few-layer explosion graphene featuring a hydrophilic coating, which is linked to fluorescently labeled highly selective consensus sequences for the proteases of interest, as well as a fluorescent dye. The panel of G-NBSs showed statistically significant differences in protease activities when comparing localized (early-stage) ovarian cancer with both metastatic (late-stage) and healthy control groups. A hierarchical framework integrated with active learning (AL) as a prediction and analysis tool for early-stage detection of ovarian cancer was implemented, which obtained an overall accuracy score of 94.5%, with both a sensitivity and specificity of 0.94.
Keywords: graphene-based nanobiosensors; biomarkers; liquid biopsy; ovarian cancer detection; protease activity; biophotonics; hierarchical decision structure graphene-based nanobiosensors; biomarkers; liquid biopsy; ovarian cancer detection; protease activity; biophotonics; hierarchical decision structure

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MDPI and ACS Style

Covarrubias-Zambrano, O.; Agarwal, D.; Lewis-Wambi, J.; Neri, R.; Jewell, A.; Natarajan, B.; Bossmann, S.H. Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy. Cells 2025, 14, 375. https://doi.org/10.3390/cells14050375

AMA Style

Covarrubias-Zambrano O, Agarwal D, Lewis-Wambi J, Neri R, Jewell A, Natarajan B, Bossmann SH. Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy. Cells. 2025; 14(5):375. https://doi.org/10.3390/cells14050375

Chicago/Turabian Style

Covarrubias-Zambrano, Obdulia, Deepesh Agarwal, Joan Lewis-Wambi, Raul Neri, Andrea Jewell, Balasubramaniam Natarajan, and Stefan H. Bossmann. 2025. "Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy" Cells 14, no. 5: 375. https://doi.org/10.3390/cells14050375

APA Style

Covarrubias-Zambrano, O., Agarwal, D., Lewis-Wambi, J., Neri, R., Jewell, A., Natarajan, B., & Bossmann, S. H. (2025). Few-Layer Graphene-Based Optical Nanobiosensors for the Early-Stage Detection of Ovarian Cancer Using Liquid Biopsy and an Active Learning Strategy. Cells, 14(5), 375. https://doi.org/10.3390/cells14050375

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