Home > Research > Publications & Outputs > GC-MS Techniques Investigating Potential Biomar...

Research

Links

Text available via DOI:

Keywords

View graph of relations

GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer. / Chapman , Elinor ; Baker, James; Aggarwal, Prashant et al.
In: International Journal of Molecular Sciences, Vol. 24, No. 2, 1591, 13.01.2023.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Chapman , E, Baker, J, Aggarwal, P, Hughes, D, Nwosu, A, Boyd, M, Mayland, C, Mason, S, Ellershaw, JE, Probert, C & Coyle, S 2023, 'GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer', International Journal of Molecular Sciences, vol. 24, no. 2, 1591. https://doi.org/10.3390/ijms24021591

APA

Chapman , E., Baker, J., Aggarwal, P., Hughes, D., Nwosu, A., Boyd, M., Mayland, C., Mason, S., Ellershaw, J. E., Probert, C., & Coyle, S. (2023). GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer. International Journal of Molecular Sciences, 24(2), Article 1591. https://doi.org/10.3390/ijms24021591

Vancouver

Chapman E, Baker J, Aggarwal P, Hughes D, Nwosu A, Boyd M et al. GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer. International Journal of Molecular Sciences. 2023 Jan 13;24(2):1591. doi: 10.3390/ijms24021591

Author

Chapman , Elinor ; Baker, James ; Aggarwal, Prashant et al. / GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer. In: International Journal of Molecular Sciences. 2023 ; Vol. 24, No. 2.

Bibtex

@article{227ac30f03d14d0194a0319f4fec4986,
title = "GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer",
abstract = "Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making.",
keywords = "GC-MS, lung cancer, dying, urine, VOCs, volatile, biomarkers, palliative, SPME",
author = "Elinor Chapman and James Baker and Prashant Aggarwal and David Hughes and Amara Nwosu and Mark Boyd and Catriona Mayland and Stephen Mason and Ellershaw, {John E} and Chris Probert and Seamus Coyle",
year = "2023",
month = jan,
day = "13",
doi = "10.3390/ijms24021591",
language = "English",
volume = "24",
journal = "International Journal of Molecular Sciences",
issn = "1422-0067",
publisher = "MDPI AG",
number = "2",

}

RIS

TY - JOUR

T1 - GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer

AU - Chapman , Elinor

AU - Baker, James

AU - Aggarwal, Prashant

AU - Hughes, David

AU - Nwosu, Amara

AU - Boyd, Mark

AU - Mayland, Catriona

AU - Mason, Stephen

AU - Ellershaw, John E

AU - Probert, Chris

AU - Coyle, Seamus

PY - 2023/1/13

Y1 - 2023/1/13

N2 - Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making.

AB - Predicting when a patient with advanced cancer is dying is a challenge and currently no prognostic test is available. We hypothesised that a dying process from cancer is associated with metabolic changes and specifically with changes in volatile organic compounds (VOCs). We analysed urine from patients with lung cancer in the last weeks of life by headspace gas chromatography mass spectrometry. Urine was acidified or alkalinised before analysis. VOC changes in the last weeks of life were identified using univariate, multivariate and linear regression analysis; 12 VOCs increased (11 from the acid dataset, 2 from the alkali dataset) and 25 VOCs decreased (23 from the acid dataset and 3 from the alkali dataset). A Cox Lasso prediction model using 8 VOCs predicted dying with an AUC of 0.77, 0.78 and 0.85 at 30, 20 and 10 days and stratified patients into a low (median 10 days), medium (median 50 days) or high risk of survival. Our data supports the hypothesis there are specific metabolic changes associated with the dying. The VOCs identified are potential biomarkers of dying in lung cancer and could be used as a tool to provide additional prognostic information to inform expert clinician judgement and subsequent decision making.

KW - GC-MS

KW - lung cancer

KW - dying

KW - urine

KW - VOCs

KW - volatile

KW - biomarkers

KW - palliative

KW - SPME

U2 - 10.3390/ijms24021591

DO - 10.3390/ijms24021591

M3 - Journal article

VL - 24

JO - International Journal of Molecular Sciences

JF - International Journal of Molecular Sciences

SN - 1422-0067

IS - 2

M1 - 1591

ER -