Characterization and discrimination of human colorectal cancer cells using terahertz spectroscopy

• Published in: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Molecular and biomolecular spectroscopy, 2021-07, Vol.256, p.119713, Article 119713
• Main Authors: Cao, Yuqi, Chen, Jiani, Zhang, Guangxin, Fan, Shuyu, Ge, Weiting, Hu, Wangxiong, Huang, Pingjie, Hou, Dibo, Zheng, Shu
• Format: Article
• Language: English
• Subjects: Cancer cells discrimination; DLD-1 cell line; HT-29 cell line; Principal component analysis; Terahertz time-domain attenuated total reflection spectroscopy
• ISSN: 1386-1425
• DOI: 10.1016/j.saa.2021.119713

[Display omitted] •Terahertz time-domain spectroscopy was employed to characterize and discriminate human cancer cell lines (DLD-1 and HT-29).•PCA was adopted for feature extraction and cell characterization.•Correlations between characteristic parameters and cell lines were analyzed.•Cancer cells were discriminated by using random forests with three characteristic parameters separately, and absorption coefficient showed the best performance for cancer cell recognition.•The main purpose of this work is to explore the possibility of detection of cancer cell solutions. Terahertz technology has been widely used in biomedical research. Herein, terahertz time-domain attenuated total reflection (THz TD-ATR) spectroscopy was employed to characterize and discriminate human cancer cell lines (DLD-1 and HT-29). Terahertz responses of the cell lines were measured and Savitzky-Golay algorithm was applied to smooth the spectra of refractive index, absorption coefficient and dielectric loss tangent in terahertz regime. Principal component analysis (PCA) was then adopted for feature extraction and cell characterization. Based on the processed data, cancer cell lines were discriminated by applying random forests (RF) method to analyze three characteristic parameters separately and the results from them were compared. Results indicate that absorption coefficient was the most sensitive parameter for cancer cell discrimination. Our study suggests great potential for human cancer cell recognition and provides experimental basis for liquid biopsy.