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Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies

Radiation therapy (RT) is used to treat approximately 50% of all cancer patients. However, RT causes a wide range of adverse late effects that can affect a patient’s quality of life. There are currently no predictive assays in clinical use to identify patients at risk of normal tissue radiation toxi...

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Autores principales: Medipally, Dinesh K.R., Nguyen, Thi Nguyet Que, Bryant, Jane, Untereiner, Valérie, Sockalingum, Ganesh D., Cullen, Daniel, Noone, Emma, Bradshaw, Shirley, Finn, Marie, Dunne, Mary, Shannon, Aoife M., Armstrong, John, Lyng, Fiona M., Meade, Aidan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679106/
https://www.ncbi.nlm.nih.gov/pubmed/31269684
http://dx.doi.org/10.3390/cancers11070925
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author Medipally, Dinesh K.R.
Nguyen, Thi Nguyet Que
Bryant, Jane
Untereiner, Valérie
Sockalingum, Ganesh D.
Cullen, Daniel
Noone, Emma
Bradshaw, Shirley
Finn, Marie
Dunne, Mary
Shannon, Aoife M.
Armstrong, John
Lyng, Fiona M.
Meade, Aidan D.
author_facet Medipally, Dinesh K.R.
Nguyen, Thi Nguyet Que
Bryant, Jane
Untereiner, Valérie
Sockalingum, Ganesh D.
Cullen, Daniel
Noone, Emma
Bradshaw, Shirley
Finn, Marie
Dunne, Mary
Shannon, Aoife M.
Armstrong, John
Lyng, Fiona M.
Meade, Aidan D.
author_sort Medipally, Dinesh K.R.
collection PubMed
description Radiation therapy (RT) is used to treat approximately 50% of all cancer patients. However, RT causes a wide range of adverse late effects that can affect a patient’s quality of life. There are currently no predictive assays in clinical use to identify patients at risk of normal tissue radiation toxicity. This study aimed to investigate the potential of Fourier transform infrared (FTIR) spectroscopy for monitoring radiotherapeutic response. Blood plasma was acquired from 53 prostate cancer patients at five different time points: prior to treatment, after hormone treatment, at the end of radiotherapy, two months post radiotherapy and eight months post radiotherapy. FTIR spectra were recorded from plasma samples at all time points and the data was analysed using MATLAB software. Discrimination was observed between spectra recorded at baseline versus follow up time points, as well as between spectra from patients showing minimal and severe acute and late toxicity using principal component analysis. A partial least squares discriminant analysis model achieved sensitivity and specificity rates ranging from 80% to 99%. This technology may have potential to monitor radiotherapeutic response in prostate cancer patients using non-invasive blood plasma samples and could lead to individualised patient radiotherapy.
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spelling pubmed-66791062019-08-19 Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies Medipally, Dinesh K.R. Nguyen, Thi Nguyet Que Bryant, Jane Untereiner, Valérie Sockalingum, Ganesh D. Cullen, Daniel Noone, Emma Bradshaw, Shirley Finn, Marie Dunne, Mary Shannon, Aoife M. Armstrong, John Lyng, Fiona M. Meade, Aidan D. Cancers (Basel) Article Radiation therapy (RT) is used to treat approximately 50% of all cancer patients. However, RT causes a wide range of adverse late effects that can affect a patient’s quality of life. There are currently no predictive assays in clinical use to identify patients at risk of normal tissue radiation toxicity. This study aimed to investigate the potential of Fourier transform infrared (FTIR) spectroscopy for monitoring radiotherapeutic response. Blood plasma was acquired from 53 prostate cancer patients at five different time points: prior to treatment, after hormone treatment, at the end of radiotherapy, two months post radiotherapy and eight months post radiotherapy. FTIR spectra were recorded from plasma samples at all time points and the data was analysed using MATLAB software. Discrimination was observed between spectra recorded at baseline versus follow up time points, as well as between spectra from patients showing minimal and severe acute and late toxicity using principal component analysis. A partial least squares discriminant analysis model achieved sensitivity and specificity rates ranging from 80% to 99%. This technology may have potential to monitor radiotherapeutic response in prostate cancer patients using non-invasive blood plasma samples and could lead to individualised patient radiotherapy. MDPI 2019-07-02 /pmc/articles/PMC6679106/ /pubmed/31269684 http://dx.doi.org/10.3390/cancers11070925 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Medipally, Dinesh K.R.
Nguyen, Thi Nguyet Que
Bryant, Jane
Untereiner, Valérie
Sockalingum, Ganesh D.
Cullen, Daniel
Noone, Emma
Bradshaw, Shirley
Finn, Marie
Dunne, Mary
Shannon, Aoife M.
Armstrong, John
Lyng, Fiona M.
Meade, Aidan D.
Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies
title Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies
title_full Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies
title_fullStr Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies
title_full_unstemmed Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies
title_short Monitoring Radiotherapeutic Response in Prostate Cancer Patients Using High Throughput FTIR Spectroscopy of Liquid Biopsies
title_sort monitoring radiotherapeutic response in prostate cancer patients using high throughput ftir spectroscopy of liquid biopsies
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679106/
https://www.ncbi.nlm.nih.gov/pubmed/31269684
http://dx.doi.org/10.3390/cancers11070925
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