Chapman, E.A. orcid.org/0000-0002-4398-1705, Baker, J. orcid.org/0000-0002-6562-1081, Aggarwal, P. orcid.org/0000-0002-5146-1400 et al. (8 more authors) (2023) GC-MS Techniques Investigating Potential Biomarkers of Dying in the Last Weeks with Lung Cancer. International Journal of Molecular Sciences, 24 (2). 1591. ISSN 1661-6596
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.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2023 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 (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | GC-MS; lung cancer; dying; urine; VOCs; volatile; biomarkers; palliative; SPME |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > The Medical School (Sheffield) > Division of Genomic Medicine (Sheffield) > Department of Oncology and Metabolism (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 17 Jan 2023 13:25 |
Last Modified: | 17 Jan 2023 13:25 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/ijms24021591 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:195381 |