Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis
Raman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification o...
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MDPI AG
2021-01-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/22/2/800 |
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| author | Keita Iwasaki Asuka Araki C Murali Krishna Riruke Maruyama Tatsuyuki Yamamoto Hemanth Noothalapati |
| author_facet | Keita Iwasaki Asuka Araki C Murali Krishna Riruke Maruyama Tatsuyuki Yamamoto Hemanth Noothalapati |
| author_sort | Keita Iwasaki |
| collection | DOAJ |
| description | Raman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification of Raman spectral markers for objective diagnosis is necessary for universal adoption of RS. As a model study, we investigated human mammary epithelial cells (HMEpC) and breast cancer cells (MCF-7) by RS and employed various multivariate analyses (MA) including principal components analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) to estimate diagnostic accuracy. Furthermore, to elucidate the underlying molecular changes in cancer cells, we utilized multivariate curve resolution analysis–alternating least squares (MCR-ALS) with non-negative constraints to extract physically meaningful spectra from complex cellular data. Unsupervised PCA and supervised MA, such as LDA and SVM, classified HMEpC and MCF-7 fairly well with high accuracy but without revealing molecular basis. Employing MCR-ALS analysis we identified five pure biomolecular spectra comprising DNA, proteins and three independent unsaturated lipid components. Relative abundance of lipid 1 seems to be strictly regulated between the two groups of cells and could be the basis for excellent discrimination by chemometrics-assisted RS. It was unambiguously assigned to linoleate rich glyceride and therefore serves as a Raman spectral marker for reliable diagnosis. This study successfully identified Raman spectral markers and demonstrated the potential of RS to become an excellent cytodiagnostic tool that can both accurately and objectively discriminates breast cancer from normal cells. |
| first_indexed | 2024-03-09T04:45:16Z |
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| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T04:45:16Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-b6d91d82d84c48a7ba60651bcb6f6e9e2023-12-03T13:16:22ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-01-0122280010.3390/ijms22020800Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution AnalysisKeita Iwasaki0Asuka Araki1C Murali Krishna2Riruke Maruyama3Tatsuyuki Yamamoto4Hemanth Noothalapati5The United Graduate School of Agricultural Sciences, Tottori University, Tottori 680-8550, JapanDepartment of Organ Pathology, Faculty of Medicine, Shimane University, Izumo 693-8501, JapanAdvanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Navi Mumbai 410-210, IndiaDepartment of Organ Pathology, Faculty of Medicine, Shimane University, Izumo 693-8501, JapanFaculty of Life and Environmental Science, Shimane University, Matsue 690-8504, JapanRaman Project Center for Medical and Biological Applications, Shimane University, Matsue 690-8504, JapanRaman spectroscopy (RS), a non-invasive and label-free method, has been suggested to improve accuracy of cytological and even histopathological diagnosis. To our knowledge, this novel technique tends to be employed without concrete knowledge of molecular changes in cells. Therefore, identification of Raman spectral markers for objective diagnosis is necessary for universal adoption of RS. As a model study, we investigated human mammary epithelial cells (HMEpC) and breast cancer cells (MCF-7) by RS and employed various multivariate analyses (MA) including principal components analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) to estimate diagnostic accuracy. Furthermore, to elucidate the underlying molecular changes in cancer cells, we utilized multivariate curve resolution analysis–alternating least squares (MCR-ALS) with non-negative constraints to extract physically meaningful spectra from complex cellular data. Unsupervised PCA and supervised MA, such as LDA and SVM, classified HMEpC and MCF-7 fairly well with high accuracy but without revealing molecular basis. Employing MCR-ALS analysis we identified five pure biomolecular spectra comprising DNA, proteins and three independent unsaturated lipid components. Relative abundance of lipid 1 seems to be strictly regulated between the two groups of cells and could be the basis for excellent discrimination by chemometrics-assisted RS. It was unambiguously assigned to linoleate rich glyceride and therefore serves as a Raman spectral marker for reliable diagnosis. This study successfully identified Raman spectral markers and demonstrated the potential of RS to become an excellent cytodiagnostic tool that can both accurately and objectively discriminates breast cancer from normal cells.https://www.mdpi.com/1422-0067/22/2/800Raman spectroscopybreast cancerlinoleic acidlipid metabolismPUFAcancer diagnosis |
| spellingShingle | Keita Iwasaki Asuka Araki C Murali Krishna Riruke Maruyama Tatsuyuki Yamamoto Hemanth Noothalapati Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis International Journal of Molecular Sciences Raman spectroscopy breast cancer linoleic acid lipid metabolism PUFA cancer diagnosis |
| title | Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis |
| title_full | Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis |
| title_fullStr | Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis |
| title_full_unstemmed | Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis |
| title_short | Identification of Molecular Basis for Objective Discrimination of Breast Cancer Cells (MCF-7) from Normal Human Mammary Epithelial Cells by Raman Microspectroscopy and Multivariate Curve Resolution Analysis |
| title_sort | identification of molecular basis for objective discrimination of breast cancer cells mcf 7 from normal human mammary epithelial cells by raman microspectroscopy and multivariate curve resolution analysis |
| topic | Raman spectroscopy breast cancer linoleic acid lipid metabolism PUFA cancer diagnosis |
| url | https://www.mdpi.com/1422-0067/22/2/800 |
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