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Detection of Human Leukocyte Antigen Biomarkers in Breast Cancer Utilizing Label-free Biosensor Technology

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High Sensitivity Sensor Based on Bound State in the Continuum in Detection for Cancer Cells.

Yuqi Cao, Liran Shen, Heng Liu

IEEE Transactions on Bio-Medical Engineering

|October 31, 2025

Summary

This study introduces a terahertz (THz) biosensor using quasi-bound states in the continuum (Q-BIC) for high-sensitivity cancer cell detection. The novel biosensor enables label-free, long-term cellular monitoring and discrimination using machine learning.

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Area of Science:

Biomedical Engineering
Terahertz (THz) Photonics
Biosensing Technology

Background:

Terahertz (THz) metasurfaces utilizing bound states in the continuum (BIC) show promise for biomedical applications.
High-sensitivity detection of cancer cells using THz technology faces implementation challenges.

Purpose of the Study:

To develop and validate a THz biosensor for sensitive cancer cell detection and discrimination.
To establish a label-free, long-term cellular monitoring platform using THz technology.

Main Methods:

Utilized dual split-ring resonator (DSRR) arrays exhibiting quasi-bound states in the continuum (Q-BIC).
Performed numerical simulations to determine resonance characteristics and detection sensitivity.
Experimentally validated the biosensor performance with normal and cancer cell lines.
Integrated machine learning algorithms for cell type discrimination based on spectral data.

Main Results:

Achieved a high-Q resonance dip at 2.35 THz with a high detection sensitivity of 522 GHz/RIU.
Successfully detected and differentiated between normal murine splenocytes and three cancer cell lines (LLC, LoVo, MC38).
Demonstrated effective cell type discrimination by projecting high-dimensional spectral data into a low-dimensional space using machine learning.

Conclusions:

The developed THz biosensor offers a sensitive and label-free method for cancer cell detection.
The integration of Q-BIC metasurfaces and machine learning advances THz technology for practical biomedical applications.
This approach facilitates long-term cellular monitoring and holds potential for innovative diagnostic tools.