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Publication
Volatomic pattern of breast cancer and cancer-free tissues as a powerful strategy to identify potential biomarkers
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Advisor(s)
Abstract(s)
Breast cancer (BC), ranked as the fifth amongst all cancers, remains at the top of women’s cancers
worldwide followed by colorectal, lung, cervix, and stomach cancers. The main handicap of most of the
screening/diagnostic methods is based on their low sensitivity and specificity and the invasive behavior
of most sampling procedures. The aim of this study was to establish the volatomic pattern of BC and
cancer-free (CF) tissues (n = 30) from the same patients, as a powerful tool to identify a set of volatile
organic metabolite (VOM) potential BC biomarkers which might be used together or complement with
the traditional BC diagnostics strategies, through the integration of chromatographic data, obtained by
solid-phase microextraction followed by gas chromatography-mass spectrometry (SPME/GC-qMS),
with chemometric tools. A total of four metabolites: limonene, decanoic acid, acetic acid and furfural
presented the highest contribution towards discrimination of BC and CF tissues (VIP > 1, p < 0.05). The
discrimination efficiency and accuracy of BC tissue metabolites was ascertained by ROC curve analysis
that allowed the identification of some metabolites with high sensitivity and specificity. The results
obtained with this approach suggest the possibility of identifying endogenous metabolites as a platform
to find potential BC biomarkers and pave the way to investigate the related metabolomic pathways in
order to improve BC diagnostic tools. Moreover, deeper investigations could unravel novel mechanistic
insights into the disease pathophysiology.
Description
Keywords
Breast cancer Volatomic pattern Biomarkers . Faculdade de Ciências Exatas e da Engenharia Escola Superior de Saúde Centro de Química da Madeira
Citation
Silva, C., Perestrelo, R., Silva, P., Capelinha, F., Tomás, H., & Câmara, J. S. (2019). Volatomic pattern of breast cancer and cancer-free tissues as a powerful strategy to identify potential biomarkers. Analyst, 144(14), 4153-4161. DOI: 10.1039/c9an00263d
Publisher
Royal Society of Chemistry