A time-course Raman spectroscopic analysis of spontaneous in vitro microcalcifications in a breast cancer cell line

Date published

2021-06-11

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Nature Publishing Group

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Article

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0023-6837

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Bouzy P, O’Grady S, Madupalli H, et al., (2021) A time-course Raman spectroscopic analysis of spontaneous in vitro microcalcifications in a breast cancer cell line. Laboratory Investigation, Volume 101, Issue 9, September 2021, pp. 1267–1280

Abstract

Microcalcifications are early markers of breast cancer and can provide valuable prognostic information to support clinical decision-making. Current detection of calcifications in breast tissue is based on X-ray mammography, which involves the use of ionizing radiation with potentially detrimental effects, or MRI scans, which have limited spatial resolution. Additionally, these techniques are not capable of discriminating between microcalcifications from benign and malignant lesions. Several studies show that vibrational spectroscopic techniques are capable of discriminating and classifying breast lesions, with a pathology grade based on the chemical composition of the microcalcifications. However, the occurrence of microcalcifications in the breast and the underlying mineralization process are still not fully understood. Using a previously established model of in vitro mineralization, the MDA-MB-231 human breast cancer cell line was induced using two osteogenic agents, inorganic phosphate (Pi) and β-glycerophosphate (βG), and direct monitoring of the mineralization process was conducted using Raman micro-spectroscopy. MDA-MB-231 cells cultured in a medium supplemented with Pi presented more rapid mineralization (by day 3) than cells exposed to βG (by day 11). A redshift of the phosphate stretching peak for cells supplemented with βG revealed the presence of different precursor phases (octacalcium phosphate) during apatite crystal formation. These results demonstrate that Raman micro-spectroscopy is a powerful tool for nondestructive analysis of mineral species and can provide valuable information for evaluating mineralization dynamics and any associated breast cancer progression, if utilized in pathological samples.

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Github

Keywords

Breast cancer, Cancer models

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Attribution 4.0 International

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