Loading...
Publication
Urinary Volatomic Expression Pattern: Paving the Way for Identification of Potential Candidate Biosignatures for Lung Cancer
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 1.8 MB | Adobe PDF |
Advisor(s)
Abstract(s)
The urinary volatomic profiling of Indian cohorts composed of 28 lung cancer (LC) pa tients and 27 healthy subjects (control group, CTRL) was established using headspace solid phase
microextraction technique combined with gas chromatography mass spectrometry methodology
as a powerful approach to identify urinary volatile organic metabolites (uVOMs) to discriminate
among LC patients from CTRL. Overall, 147 VOMs of several chemistries were identified in the
intervention groups—including naphthalene derivatives, phenols, and organosulphurs—augmented
in the LC group. In contrast, benzene and terpenic derivatives were found to be more prevalent in
the CTRL group. The volatomic data obtained were processed using advanced statistical analysis,
namely partial least square discriminative analysis (PLS-DA), support vector machine (SVM), random
forest (RF), and multilayer perceptron (MLP) methods. This resulted in the identification of nine
uVOMs with a higher potential to discriminate LC patients from CTRL subjects. These were furan,
o-cymene, furfural, linalool oxide, viridiflorene, 2-bromo-phenol, tricyclazole, 4-methyl-phenol, and
1-(4-hydroxy-3,5-di-tert-butylphenyl)-2-methyl-3-morpholinopropan-1-one. The metabolic pathway
analysis of the data obtained identified several altered biochemical pathways in LC mainly affecting
glycolysis/gluconeogenesis, pyruvate metabolism, and fatty acid biosynthesis. Moreover, acetate
and octanoic, decanoic, and dodecanoic fatty acids were identified as the key metabolites responsible
for such deregulation. Furthermore, studies involving larger cohorts of LC patients would allow us
to consolidate the data obtained and challenge the potential of the uVOMs as candidate biomarkers
for LC.
Description
Keywords
Lung cancer (LC) biomarkers Volatile organic metabolites (VOMs) HS-SPME GC-qMS . Faculdade de Ciências Exatas e da Engenharia Centro de Química da Madeira
Citation
Taunk, K.; Porto-Figueira, P.; Pereira, J.A.M.; Taware, R.; da Costa, N.L.; Barbosa, R.; Rapole, S.; Câmara, J.S. Urinary Volatomic Expression Pattern: Paving the Way for Identification of Potential Candidate Biosignatures for Lung Cancer. Metabolites 2022, 12, 36. https://doi.org/10.3390/ metabo12010036
Publisher
MDPI