scholarly journals Demonstration of a Flexible Graphene-Based Biosensor for Sensitive and Rapid Detection of Ovarian Cancer Cells

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ling Han ◽  
Qi Wan ◽  
Ai Zheng ◽  
Yunchuan Guo ◽  
Yali Chen

AbstractIt is significant to develop an efficient early detection and prediction method for ovarian cancer via a facile and low-cost approach. To address such issues, herein, we develop a novel circulating tumor cell (CTC) detection method to sensitively detect ovarian cancer by using a flexible graphene-based biosensor on polyethylene terephthalate (PET) substrate. The results show that the graphene-based flexible biosensor demonstrates sensitive and rapid detection for ovarian cancer cells: it delivers obvious different responses for cell culture medium and cancer solution, different cancer cells and cancer cell solution with different concentrations; it demonstrates high sensitivity for detecting several tens of ovarian cancer cells per ml; moreover, the flexible graphene biosensor is very suitable for rapid and sensitive detection of ovarian cancer cells within 5 s. This work provides a low-cost and facile graphene biosensor fabrication strategy to sensitively and rapidly detect / identify CTC ovarian cancer cells. Graphical Abstract

Molecules ◽  
2021 ◽  
Vol 26 (23) ◽  
pp. 7265
Author(s):  
Qi Wan ◽  
Ling Han ◽  
Yunchuan Guo ◽  
Huijun Yu ◽  
Li Tan ◽  
...  

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.


2020 ◽  
Vol 10 (10) ◽  
pp. 1615-1619
Author(s):  
Shuai Zhang ◽  
Junhui Liang ◽  
Changzhong Li ◽  
Fei Wang

To investigate the pharmacodynamic effect of urushin nanoparticles upon the proliferation inhibition in human ovarian cancer SKOV3 cells, and in order to explore their biomechanism, the cell cycle and the percentage of apoptotic cells in human ovarian cancer SKOV3 cells were analyzed utilizing flow cytometry. The concentration of astragalin nanoparticles in SKOV3 cells was identified utilizing HPIC. Consequently, the morphological characteristics of SKOV3 cells in a culture medium of 5 mg/L were investigated and measured. In our findings, the 50 mg cancer cells containing 50 mg IC did not display this noted effect. The results exhibit the discovery that urushin nanoparticles inhibit cell proliferation, which is related to the inhibition of DNA replication and the regulation of the cell proliferation cycle. HPLC results demonstrated that the pharmacological effect of urushin nanoparticles was directly related to the drug concentration present within the studied cells. Hence, urushin nanoparticles can effectively enter cells and then effectively inhibit cell proliferation.


2017 ◽  
Vol 1060 ◽  
pp. 30-35
Author(s):  
Agnieszka Klupczynska ◽  
Anna Maria Sulej-Suchomska ◽  
Hanna Piotrowska-Kempisty ◽  
Marcin Wierzchowski ◽  
Jadwiga Jodynis-Liebert ◽  
...  

2009 ◽  
Vol 282 (2) ◽  
pp. 214-228 ◽  
Author(s):  
Alessia Petronelli ◽  
Ernestina Saulle ◽  
Luca Pasquini ◽  
Eleonora Petrucci ◽  
Gualtiero Mariani ◽  
...  

2018 ◽  
Author(s):  
F Guo ◽  
Z Yang ◽  
J Xu ◽  
J Sehouli ◽  
AE Albers ◽  
...  

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