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Graphene Oxide-Functionalized Optical Sensor for Label-Free Detection of Breast Cancer Cells.

Jiaxing Sun¹, Hanlin Jiang¹, Kartikey J Chavan¹

¹Department of Physics, School of Science and Technology, Nottingham Trent University, Nottingham NG11 8NS, United Kingdom.

ACS Applied Nano Materials

|September 4, 2025

Summary

This study introduces a novel graphene oxide-functionalized fiber optic sensor for detecting breast cancer cells. The sensor offers highly sensitive, label-free detection of cancer cell density using secreted byproducts.

Keywords:

Breast cancer Cancer cell detection Graphene oxide Label-free sensor Long-period fiber grating

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Area of Science:

Bionanophotonics
Fiber Optic Sensing
Cancer Diagnostics

Background:

Accurate cancer cell detection is crucial for early diagnosis and monitoring.
Current methods like hemocytometry lack sensitivity and scalability.
Noninvasive, label-free detection methods are needed for improved cancer diagnostics.

Purpose of the Study:

To demonstrate the feasibility of a graphene oxide-functionalized long-period fiber grating (GO-LPG) sensor.
To enable label-free detection of human breast cancer cell density (MCF-7).
To investigate the sensor's performance based on secreted cellular byproducts.

Main Methods:

Fabrication of GO-LPG sensors using in situ layer-by-layer (i-LbL) assembly.
Characterization of GO nanocoatings using SEM, AFM, and Raman spectroscopy.
Detection of cancer cell density via refractive index modulation caused by secreted metabolites.

Main Results:

GO nanocoatings enhanced light-matter interaction and mode coupling.
Sensor performance showed distinct thickness-dependent behavior of GO nanocoatings.
Achieved ultrahigh sensitivity with a limit of detection (LOD) of 270 cells/mL for MCF-7 cells.

Conclusions:

The GO-LPG sensor enables real-time, label-free, and noninvasive detection of cancer cell density.
This bionanophotonic platform shows significant potential for cancer diagnostics and metabolic sensing.
The sensor's sensitivity and noninvasive nature offer advantages over traditional methods.