Highly sensitive detection of malignant glioma cells using metamaterial-inspired THz biosensor based on electromagnetically induced transparency

Biosens Bioelectron. 2021 Aug 1:185:113241. doi: 10.1016/j.bios.2021.113241. Epub 2021 Apr 22.

Abstract

Metamaterial-inspired biosensors have been extensively studied recently years for fast and low-cost THz detection. However, only the variation of the resonance frequency has been closely concerned in such sensors so far, whiles the magnitude variation, which also provide important information of the analyte, has not been sufficiently analyzed. In this paper, by the observation of two degree of variations, we propose a label-free biosensing approach for molecular classification of glioma cells. The metamaterial biosensor consisting of cut wires and split ring resonators are proposed to realize polarization-independent electromagnetic induced transparency (EIT) at THz frequencies. Simulated results show that the EIT-like resonance experiences both resonance frequency and magnitude variations when the properties of analyte change, which is further explained with coupled oscillators model theory. The theoretical sensitivity of the biosensor is evaluated up to 496.01 GHz/RIU. In experiments, two types of glioma cells (mutant and wild-type) are cultured on the biosensor surface. The dependences of frequency shifts and the peak magnitude variations on the cells concentrations for different types give new perspective for molecular classification of glioma cells. The measured results indicate that the mutant and wild-type glioma cells can be distinguished directly by observing both the variations of EIT resonance frequency and magnitude at any cells concentrations without antibody introduction. Our metamaterial-based biosensor shows a great potential in the recognition of molecule types of glioma cells, opening alternative way to sensitive biosensing technology.

Keywords: Biosensing; Cancer detection; Metamaterials; THz.

MeSH terms

  • Biosensing Techniques*
  • Glioma* / diagnosis
  • Humans