Graphene-Based Biosensors with High Sensitivity for Detection of Ovarian Cancer Cells

Ovarian cancer has the highest mortality rate in the world. Therefore, it is urgent but still challenging to develop an efficient circulating tumor cell (CTC) detection method to sensitively detect ovarian cancer. To address such issues, herein, for the first time, we present a novel CTC detection m...

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Bibliographic Details
Published in:Molecules (Basel, Switzerland) Switzerland), 2021-11, Vol.26 (23), p.7265
Main Authors: Wan, Qi, Han, Ling, Guo, Yunchuan, Yu, Huijun, Tan, Li, Zheng, Ai, Chen, Yali
Format: Article
Language:English
Subjects:
Antigens
Biomarkers
Biosensing Techniques
Biosensors
Cell Count
Cell Line, Tumor
Chemical vapor deposition
circulating tumor cell (CTC)
Fabrication
Female
Graphene
graphene-based biosensor
Graphite - chemistry
Humans
Medical prognosis
Metastasis
Methods
Morphology
Mortality
Ovarian cancer
Ovarian carcinoma
Ovarian Neoplasms - diagnosis
Ovarian Neoplasms - pathology
Plasma etching
Quantum dots
Saliva - cytology
Semiconductors
Sensitivity
Time Factors
Tomography
Tumors
Ultrasonic imaging
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Summary:Ovarian cancer has the highest mortality rate in the world. Therefore, it is urgent but still challenging to develop an efficient circulating tumor cell (CTC) detection method to sensitively detect ovarian cancer. To address such issues, herein, for the first time, we present a novel CTC detection method for ovarian cancer cells by designing sensitive and rapid graphene-based biosensors. This graphene-based sensor, consisting of a cell pool and two electrodes, can be prepared by a conventional chip fabrication process. It demonstrates high-sensitivity detection even for several ovarian cancer cells by comparing the electrical signal before and after adding cell solution. Moreover, the graphene-based biosensors can perform rapid detection with good repeatability. This suggests that this novel method is possible to use for the early detection of ovarian cancer with very low CTC cell concentration. This work provides a novel and quick strategy to detect ovarian cancer and further judge or predict the risk of the transfer of ovarian cancer.
ISSN:1420-3049
1420-3049
DOI:10.3390/molecules26237265