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Research Article

An ultra-sensitive metasurface biosensor for instant cancer detection based on terahertz spectra

Peiliang Wang1,2,3,4, Jing Lou2,5, Yun Yu2,8, Lang Sun2, Lan Sun6,7( ), Guangyou Fang1,3,4( ), Chao Chang2( )
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Innovation Laboratory of Terahertz Biophysics, National Innovation Institute of Defense Technology, Beijing 100071, China
The Key Laboratory of Electromagnetic Radiation and Sensing Technology, Chinese Academy of Sciences, Beijing 100190, China
School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
Air and Missile Defense College, Air Force Engineering University, Xi’an 710051, China
Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100007, China
School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing 100871, China
School of Life Science and Technology, Xi’an Jiaotong University, Xi’an 710049, China
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Graphical Abstract

Differences in spectra caused by thousands of cells are easily captured and displayed, while more than 30-fold the number of cells (> 100,000) are required for the current clinical detection technology. The proposed biosensor has achieved the characterization of cells in normal and cancerous states. Compared with the hematoxylin and eosin (HE) staining (more than 100 min), this novel strategy takes at most 5 min to complete the detection of cells, and time consumption is reduced at least 20-fold. Due to the great polarization-insensitivity of the proposed biosensor, it is flexible to set samples and easy to realize automatic operation, which can further reduce labor costs in the future. Furthermore, the results were consistent with pathological results (the gold standard in clinic) by Gaussian curve fitting, which is also more reliable than conventional studies that proved by single physical system.

Abstract

Metasurface biosensors have become the core label-free and rapid-detection technology in bioanalysis. Lung cancer and brain cancer are the first leading causes of cancer death among adults and adolescents, respectively, where poor early diagnosis results from expensive detection costs and time consumption. To tackle the above problems, here, we introduce a terahertz-domain metasurface biosensor for cancer diagnosis, relying on a perfectly symmetrical periodic surface structure, which significantly exhibits polarization-insensitivity at 2.05 THz and the high-sensitivity of 504 GHz/RIU (RIU = refractive index unit). According to the frequency shifts and transmittance variations, four cell types are successfully distinguished from each other. The minimum number of cells is required for thousands of cells to display the differences of spectra, which is 1/30 of clinical methods. Furthermore, the results were consistent with pathological results (the gold standard in clinic) by Gaussian curve fitting. The proposed biosensor has really achieved the characterization of cells in normal and cancerous state. This detection strategy dramatically reduced the cost of detection by reuse and time consumption was reduced to 1/20 of the pathology testing. In addition, it is flexible to set samples and easy to realize automatic operation due to the great polarization-insensitivity of the proposed biosensor, which can further reduce labor costs in the future. It is envisioned that the proposed biosensor will present immense potential in the fields of cancer detection, distinguishing different cancers, and identifying primary lesion cancer or metastatic cancer.

Keywords

terahertzmetasurfacebiosensorcancer detection

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Nano Research
Volume 16 Issue 5,
May 2023
Pages 7304-7311
DOI: 10.1007/s12274-023-5386-7
Cite this article:
Wang P, Lou J, Yu Y, et al. An ultra-sensitive metasurface biosensor for instant cancer detection based on terahertz spectra. Nano Research, 2023, 16(5): 7304-7311. https://doi.org/10.1007/s12274-023-5386-7
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Received: 15 October 2022
Revised: 19 November 2022
Accepted: 04 December 2022
Published: 08 February 2023
© Tsinghua University Press 2023
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