Indication of high lipid content in epithelial-mesenchymal transitions of breast tissues

• Published in: Scientific reports Vol. 11; no. 1; p. 3250
• Main Authors: Sabtu, Siti Norbaini, Sani, S. F. Abdul, Looi, L. M., Chiew, S. F., Pathmanathan, Dharini, Bradley, D. A., Osman, Z.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05.02.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 631/57; 631/57/2272; 639/766/400; 639/766/747; Breast - chemistry; Breast - pathology; Breast cancer; Breast Neoplasms - chemistry; Breast Neoplasms - pathology; Epithelial-Mesenchymal Transition; Female; Humanities and Social Sciences; Humans; Lipids; Lipids - analysis; Mesenchyme; Metabolism; Metastases; multidisciplinary; Multivariate analysis; Nucleic acids; Paraffin; Principal components analysis; Proteins - analysis; Raman spectroscopy; Science; Science (multidisciplinary); Spectroscopy; Spectrum analysis; Spectrum Analysis, Raman - methods; Tissues; Variance analysis
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-81426-x

The epithelial-mesenchymal transition (EMT) is a crucial process in cancer progression and metastasis. Study of metabolic changes during the EMT process is important in seeking to understand the biochemical changes associated with cancer progression, not least in scoping for therapeutic strategies aimed at targeting EMT. Due to the potential for high sensitivity and specificity, Raman spectroscopy was used here to study the metabolic changes associated with EMT in human breast cancer tissue. For Raman spectroscopy measurements, tissue from 23 patients were collected, comprising non-lesional, EMT and non-EMT formalin-fixed and paraffin embedded breast cancer samples. Analysis was made in the fingerprint Raman spectra region (600–1800 cm −1 ) best associated with cancer progression biochemical changes in lipid, protein and nucleic acids. The ANOVA test followed by the Tukey’s multiple comparisons test were conducted to see if there existed differences between non-lesional, EMT and non-EMT breast tissue for Raman spectroscopy measurements. Results revealed that significant differences were evident in terms of intensity between the non-lesional and EMT samples, as well as the EMT and non-EMT samples. Multivariate analysis involving independent component analysis, Principal component analysis and non-negative least square were used to analyse the Raman spectra data. The results show significant differences between EMT and non-EMT cancers in lipid, protein, and nucleic acids. This study demonstrated the capability of Raman spectroscopy supported by multivariate analysis in analysing metabolic changes in EMT breast cancer tissue.