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Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping
Understanding the response of cancer cells to ionising radiation is a crucial step in modern radiotherapy. Raman microspectroscopy, together with Partial Least Squares Regression (PLSR) analysis has been shown to be a powerful tool for monitoring biochemical changes of irradiated cells on the subcel...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6581960/ https://www.ncbi.nlm.nih.gov/pubmed/31213635 http://dx.doi.org/10.1038/s41598-019-45179-y |
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author | Roman, Maciej Wrobel, Tomasz P. Panek, Agnieszka Efeoglu, Esen Wiltowska-Zuber, Joanna Paluszkiewicz, Czeslawa Byrne, Hugh J. Kwiatek, Wojciech M. |
author_facet | Roman, Maciej Wrobel, Tomasz P. Panek, Agnieszka Efeoglu, Esen Wiltowska-Zuber, Joanna Paluszkiewicz, Czeslawa Byrne, Hugh J. Kwiatek, Wojciech M. |
author_sort | Roman, Maciej |
collection | PubMed |
description | Understanding the response of cancer cells to ionising radiation is a crucial step in modern radiotherapy. Raman microspectroscopy, together with Partial Least Squares Regression (PLSR) analysis has been shown to be a powerful tool for monitoring biochemical changes of irradiated cells on the subcellular level. However, to date, the majority of Raman studies have been performed using a single spectrum per cell, giving a limited view of the total biochemical response of the cell. In the current study, Raman mapping of the whole cell area was undertaken to ensure a more comprehensive understanding of the changes induced by X-ray radiation. On the basis of the collected Raman spectral maps, PLSR models were constructed to elucidate the time-dependent evolution of chemical changes induced in cells by irradiation, and the performance of PLSR models based on whole cell averages as compared to those based on average Raman spectra of cytoplasm and nuclear region. On the other hand, prediction of X-ray doses for individual cellular components showed that cytoplasmic and nuclear regions should be analysed separately. Finally, the advantage of the mapping technique over single point measurements was verified by a comparison of the corresponding PLSR models. |
format | Online Article Text |
id | pubmed-6581960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-65819602019-06-26 Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping Roman, Maciej Wrobel, Tomasz P. Panek, Agnieszka Efeoglu, Esen Wiltowska-Zuber, Joanna Paluszkiewicz, Czeslawa Byrne, Hugh J. Kwiatek, Wojciech M. Sci Rep Article Understanding the response of cancer cells to ionising radiation is a crucial step in modern radiotherapy. Raman microspectroscopy, together with Partial Least Squares Regression (PLSR) analysis has been shown to be a powerful tool for monitoring biochemical changes of irradiated cells on the subcellular level. However, to date, the majority of Raman studies have been performed using a single spectrum per cell, giving a limited view of the total biochemical response of the cell. In the current study, Raman mapping of the whole cell area was undertaken to ensure a more comprehensive understanding of the changes induced by X-ray radiation. On the basis of the collected Raman spectral maps, PLSR models were constructed to elucidate the time-dependent evolution of chemical changes induced in cells by irradiation, and the performance of PLSR models based on whole cell averages as compared to those based on average Raman spectra of cytoplasm and nuclear region. On the other hand, prediction of X-ray doses for individual cellular components showed that cytoplasmic and nuclear regions should be analysed separately. Finally, the advantage of the mapping technique over single point measurements was verified by a comparison of the corresponding PLSR models. Nature Publishing Group UK 2019-06-18 /pmc/articles/PMC6581960/ /pubmed/31213635 http://dx.doi.org/10.1038/s41598-019-45179-y Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Roman, Maciej Wrobel, Tomasz P. Panek, Agnieszka Efeoglu, Esen Wiltowska-Zuber, Joanna Paluszkiewicz, Czeslawa Byrne, Hugh J. Kwiatek, Wojciech M. Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping |
title | Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping |
title_full | Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping |
title_fullStr | Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping |
title_full_unstemmed | Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping |
title_short | Exploring subcellular responses of prostate cancer cells to X-ray exposure by Raman mapping |
title_sort | exploring subcellular responses of prostate cancer cells to x-ray exposure by raman mapping |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6581960/ https://www.ncbi.nlm.nih.gov/pubmed/31213635 http://dx.doi.org/10.1038/s41598-019-45179-y |
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