Evaluation of chemotherapeutic retinoic acid effects on malignant cells using fluorescence spectroscopy with selective excitation wavelengths and machine learning

Binlin Wu; Guichen Tang; Yang Pu; Robert Alfano

doi:10.1117/12.2650987

9 March 2023 Evaluation of chemotherapeutic retinoic acid effects on malignant cells using fluorescence spectroscopy with selective excitation wavelengths and machine learning

Binlin Wu, Guichen Tang, Yang Pu, Robert Alfano

Author Affiliations +

Proceedings Volume 12373, Optical Biopsy XXI: Toward Real-Time Spectroscopic Imaging and Diagnosis; 1237306 (2023) https://doi.org/10.1117/12.2650987
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Native fluorescence spectra of retinoic acid (RA)-treated and untreated human breast cancer cells were measured using selective wavelengths of 300 nm and 340 nm for excitation. The spectral data of the two types of cells were analyzed using machine learning algorithms for linear unmixing and classification which yielded high accuracy. The results show that the concentrations of the native fluorophores such as tryptophan, NADH and flavins in the human malignant breast cells change when they are treated with RA. The study shows the dual-wavelength fluorescence spectroscopy aided by machine learning has potential clinical applications in drug development and chemotherapeutic studies.

Conference Presentation

Citation Download Citation

Binlin Wu, Guichen Tang, Yang Pu, and Robert Alfano "Evaluation of chemotherapeutic retinoic acid effects on malignant cells using fluorescence spectroscopy with selective excitation wavelengths and machine learning", Proc. SPIE 12373, Optical Biopsy XXI: Toward Real-Time Spectroscopic Imaging and Diagnosis, 1237306 (9 March 2023); https://doi.org/10.1117/12.2650987

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