Summary of project PR001322
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001322. The data can be accessed directly via it's Project DOI: 10.21228/M8TT44 This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Project ID: | PR001322 |
| Project DOI: | doi: 10.21228/M8TT44 |
| Project Title: | Predicting dying: a study of the metabolic changes and the dying process in patients with lung cancer |
| Project Summary: | Background: Accurately recognising that a person may be dying is central for improving their experience of care. Yet recognising dying is difficult and predicting dying frequently inaccurate. Methods: Serial urine samples from patients (n=112) with lung cancer were analysed using high resolution untargeted mass spectrometry. ANOVA and volcano plot analysis demonstrated metabolites that changed in the last weeks of life. Further analysis identified potential biological pathways affected. Cox lasso logistic regression was engaged to develop a multivariable model predicting the probability of survival within the last 30 days of life. Results: In total 124 metabolites changed. ANOVA analysis identified 93 metabolites and volcano plot analysis 85 metabolites. 53 metabolites changed using both approaches. Pathways altered in the last weeks included those associated with decreased oral intake, muscle loss, decreased RNA and protein synthesis, mitochondrial dysfunction, disrupted β-oxidation and one carbon metabolism. Epinephrine and cortisol increased in the last 2 weeks and week respectively. A model predicting time to death using 7 metabolites had excellent accuracy (AUC= 0.86 at day 30, 0.88 at day 20 and 0.85 at day 10) and enabled classification of patients at low, medium and high risk of dying on a Kaplan-Meier survival curve. Conclusions: Metabolomic analysis identified metabolites and their associated pathways that change in the last weeks and days of life in patients with lung cancer. Prognostic tests based on the metabolites identified have the potential to change clinical practice and improve the care of dying patients. |
| Institute: | University of Liverpool Institute of Life Course Medical Sciences |
| Last Name: | Norman |
| First Name: | Brendan |
| Address: | William Henry Duncan Building, 6 West Derby Street, Liverpool, Merseyside, L7 8TX, United Kingdom |
| Email: | bnorman@liv.ac.uk |
| Phone: | (+44)151 794 9064 |
| Funding Source: | This research received a Wellcome Trust Seed award for Science (202022/Z/16/Z) and a North West Cancer Research award (SI2018.11) |
| Contributors: | Séamus Coyle, Elinor Chapman, David Hughes, James Baker, Andrew S Davison, Brendan P Norman, Amara Callistus Nwosu, Mark Boyd, Catriona R Mayland, Stephen Mason, John Ellershaw, Chris Probert |
Summary of all studies in project PR001322
| Study ID | Study Title | Species | Institute | Analysis(* : Contains Untargted data) | Release Date | Version | Samples | Download(* : Contains raw data) |
|---|---|---|---|---|---|---|---|---|
| ST002082 | Predicting dying: a study of the metabolic changes and the dying process in patients with lung cancer | Homo sapiens | University of Liverpool Institute of Life Course & Medical Sciences | MS | 2022-02-24 | 1 | 112 | Uploaded data (367.6G)* |
