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September 6, 2022

Chinese Academy of Sciences proposes new early cancer detection biosensor

The biosensor identifies target exosomes, which can monitor metastatic cancer cells and detect cancer early.

A group of researchers at the Chinese Academy of Sciences has proposed a new electrochemical biosensor for early cancer diagnosis.

Based on 2D MXene membranes decorated with hierarchical Au nanoarrays, the biosensor detects and identifies target exosomes, potentially detecting cancer at an early stage as well as providing monitoring of metastatic cancer cells.

Exosomes are small extracellular vesicles that are derived from tumour cells.

The new electrochemical biosensor demonstrated satisfactory reproducibility and high sensitivity in sensing exosomes.

It is cost-effective, highly sensitive and selective, with a wide linear range.

The Chinese Academy of Sciences noted that the new biosensor can be considered a suitable analytical platform for measuring exosomes.

The researchers selected MXene nanosheets, a two-dimensional material, as the building blocks for the MXene membrane preparation, which was achieved through facile vacuum filtration.

They later added Au nanoarrays, which were grown on the MXene membranes in situ. 

The work was carried out by Dong Wenfei and his team at the Chinese Academy of Sciences’ Suzhou Institute of Biomedical Engineering and Technology (SIBET).

Chinese Academy of Sciences SIBET doctoral candidate You Qiannan said: “The obtained combination of MXene membrane showed excellent conductivity, a large active site for aptamer immobilisation and accelerated charge transfer.”

Modified by EpCAM recognised aptamer, the composite membrane can specifically capture target exosomes.

These exosomes anchor aptamer for CD63, further improving the sensing sensitivity and accuracy of the biosensor.

The composite membrane used large-scale preparation characteristics and MXene membrane reducibility, which allowed the biosensor to achieve accuracy and stability in identifying the exosomes.

The work was supported by organisations that included the Primary Research and Development Plan of Jiangsu Province, the National Natural Science Foundation of China, and the National Key R&D Program of China.

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