Raman spectroscopy and group and basis-restricted non negative matrix factorisation identifies radiation induced metabolic changes in human cancer cells

This work combines single cell Raman spectroscopy (RS) with group and basis restricted non-negative matrix factorisation (GBR-NMF) to identify individual biochemical changes associated with radiation exposure in three human cancer cell lines. The cell lines analysed were derived from lung (H460), br...

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Bibliographic Details
Published in:Scientific reports 2021-02, Vol.11 (1), p.3853-11, Article 3853
Main Authors: Milligan, Kirsty, Deng, Xinchen, Shreeves, Phillip, Ali-Adeeb, Ramie, Matthews, Quinn, Brolo, Alexandre, Lum, Julian J., Andrews, Jeffrey L., Jirasek, Andrew
Format: Article
Language:English
Subjects:
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631/67/1059
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631/67/1612
631/67/2327
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639/705
639/766
639/766/25
692/53
Arginine
Asparagine
Breast
Glycogen
Glycogen - metabolism
Humanities and Social Sciences
Humans
Lecithin
MCF-7 Cells - metabolism
MCF-7 Cells - radiation effects
Models, Biological
multidisciplinary
Phosphatidylcholine
Principal components analysis
Prostate
Raman spectroscopy
Science
Science (multidisciplinary)
Spectroscopy
Spectrum analysis
Spectrum Analysis, Raman
Supervised Machine Learning
Tumor cell lines
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Summary:This work combines single cell Raman spectroscopy (RS) with group and basis restricted non-negative matrix factorisation (GBR-NMF) to identify individual biochemical changes associated with radiation exposure in three human cancer cell lines. The cell lines analysed were derived from lung (H460), breast (MCF7) and prostate (LNCaP) tissue and are known to display varying degrees of radio sensitivity due to the inherent properties of each cell type. The GBR-NMF approach involves the deconstruction of Raman spectra into component biochemical bases using a library of Raman spectra of known biochemicals present in the cells. Subsequently, scores are obtained on each of these bases which can be directly correlated with the contribution of each chemical to the overall Raman spectrum. We validated GBR-NMF through the correlation of GBR-NMF-derived glycogen scores with scores that were previously observed using principal component analysis (PCA). Phosphatidylcholine, glucose, arginine and asparagine showed a distinct differential score pattern between radio-resistant and radio-sensitive cell types. In summary, the GBR-NMF approach allows for the monitoring of individual biochemical radiation-response dynamics previously unattainable with more traditional PCA-based approaches.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-021-83343-5