Paper
3 September 2019 Multiple label-free detection of breast cancer biomarkers using Raman spectroscopy
Author Affiliations +
Abstract
We have investigated a multiple label-free detection method based on Raman spectroscopy and multivariate curve resolution (MCR) analysis to classify breast cancer. Twenty breast tissues collected from five participants during breast surgery were used as biological samples. Ten samples were from malignant tumor mass (cancer core area) and the others were from the safety margin outside of the tumor mass (two sample groups). For each breast tissue sample, twenty Raman spectra were collected using a fiber-optics Raman system consisting of a fiber-optic Raman probe, a low dark current deep-depletion CCD connected to a Czerny-Turner spectrograph and 785-nm laser source. Using MCR analysis iteratively optimized by an alternative least squares (ALS) algorithm, biomarker-dominated spectral data can be obtained from the preprocessed Raman spectra. This allows a more accurate classification between the two sample groups (normal and cancer). We expect that the proposed method based on biomarker analysis using MCR-ALS will more accurately classify breast cancer.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Soogeun Kim, Ayoung Bang, and Samjin Choi "Multiple label-free detection of breast cancer biomarkers using Raman spectroscopy", Proc. SPIE 11089, Nanoengineering: Fabrication, Properties, Optics, Thin Films, and Devices XVI, 110892G (3 September 2019); https://doi.org/10.1117/12.2529749
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KEYWORDS
Raman spectroscopy

Breast cancer

Cancer

Breast

Tissues

Biological research

Fiber optics

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