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Screening of salivary volatiles for putative breast cancer discrimination: an exploratory study involving geographically distant populations


Saliva is possibly the easiest biofluid to analyse and, despite its simple composition, contains relevant metabolic information. In this work, we explored the potential of the volatile composition of saliva samples as biosignatures for breast cancer (BC) non-invasive diagnosis. To achieve this, 106 saliva samples of BC patients and controls in two distinct geographic regions in Portugal and India were extracted and analysed using optimised headspace solid-phase microextraction gas chromatography mass spectrometry (HS-SPME/GC-MS, 2 mL acidified saliva containing 10% NaCl, stirred (800 rpm) for 45 min at 38 °C and using the CAR/PDMS SPME fibre) followed by multivariate statistical analysis (MVSA). Over 120 volatiles from distinct chemical classes, with significant variations among the groups, were identified. MVSA retrieved a limited number of volatiles, viz. 3-methyl-pentanoic acid, 4-methyl-pentanoic acid, phenol and p-tert-butyl-phenol (Portuguese samples) and acetic, propanoic, benzoic acids, 1,2-decanediol, 2-decanone, and decanal (Indian samples), statistically relevant for the discrimination of BC patients in the populations analysed. This work defines an experimental layout, HS-SPME/GC-MS followed by MVSA, suitable to characterise volatile fingerprints for saliva as putative biosignatures for BC non-invasive diagnosis. Here, it was applied to BC samples from geographically distant populations and good disease separation was obtained. Further studies using larger cohorts are therefore very pertinent to challenge and strengthen this proof-of-concept study.

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Breast cancer


Carboxen®/polydimethylsiloxane SPME fiber


Control healthy subjects


Hierarchical cluster analysis


Hydrogen chloride


Headspace solid-phase microextraction gas chromatography mass spectrometry


Indian samples (Pune)


Monte Carlo cross-validation


Multivariate statistical analysis


Orthogonal projections to latent structures discriminant analysis


Principal component analysis


Partial least squares discriminant analysis


Portuguese samples (Madeira Island)


Receiver operator characteristic


Random forest


Solid-phase microextraction


Volatile organic metabolites


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This research was supported by Fundação para a Ciência e a Tecnologia (projects PEst-OE/QUI/UI0674/2013, CQM, New-INDIGO/0003/2012 and INNOINDIGO/0001/2015, Portuguese Government funds), and through Madeira 14-20 Program, project PROEQUIPRAM - Reforço do Investimento em Equipamentos e Infraestruturas Científicas na RAM (M1420-01-0145-FEDER-000008) and by ARDITI - Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação, through the project M1420-01-0145-FEDER-000005 - Centro de Química da Madeira - CQM+ (Madeira 14-20), and project M1420 - 09-5369-FSE-000001 for the Post-Doctoral fellowship granted to JAMP. SR, KT, and HN gratefully acknowledge the support of Department of Biotechnology (DBT), Government of India (New Indigo project grant no. BT/IN/New Indigo/03/RS/2013) and Department of Science & Technology (DST), Government of India (Inno-Indigo NCD-CAPomics project grant no. DST/IMRCD/EU/Inno-Indigo/NCDs-CAPomics/2015). RT acknowledges Council of Scientific and Industrial Research (CSIR), New Delhi, India, for research associateship. SR, KT and RT would like to acknowledge Col. Dharmesh Soneji (AFMC, Pune) for sample collection.

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Correspondence to Jorge A. M. Pereira.

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This work involved human participants and previous clearance from the ethical committees of the institutions involved, as well as signed informed consent of the subjects recruited, was obtained.

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Cavaco, C., Pereira, J.A.M., Taunk, K. et al. Screening of salivary volatiles for putative breast cancer discrimination: an exploratory study involving geographically distant populations. Anal Bioanal Chem 410, 4459–4468 (2018).

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