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

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Abstract

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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Abbreviations

BC:

Breast cancer

CAR/PDMS:

Carboxen®/polydimethylsiloxane SPME fiber

CTRL:

Control healthy subjects

HCA:

Hierarchical cluster analysis

HCl:

Hydrogen chloride

HS-SPME/GC-MS:

Headspace solid-phase microextraction gas chromatography mass spectrometry

IN:

Indian samples (Pune)

MCCV:

Monte Carlo cross-validation

MVSA:

Multivariate statistical analysis

OPLS-DA:

Orthogonal projections to latent structures discriminant analysis

PCA:

Principal component analysis

PLS-DA:

Partial least squares discriminant analysis

PT:

Portuguese samples (Madeira Island)

ROC:

Receiver operator characteristic

RF:

Random forest

SPME:

Solid-phase microextraction

VOMs:

Volatile organic metabolites

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Acknowledgments

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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Authors and Affiliations

  1. CQM-UMa – Centro de Química da Madeira, Universidade da Madeira, Campus Universitário da Penteada, 9020-105, Funchal, Portugal

    Carina Cavaco, Jorge A. M. Pereira & José S. Câmara

  2. Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, 411007, India

    Khushman Taunk, Ravindra Taware & Srikanth Rapole

  3. Laboratory of Computational Biology, Centre for DNA Fingerprinting & Diagnostics (CDFD), Nampally, Hyderabad, 500001, India

    Hampapathalu Nagarajaram

  4. Department of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, 500 046, India

    Hampapathalu Nagarajaram

  5. Faculdade de Ciências Exatas e da Engenharia, Universidade da Madeira, Campus Universitário da Penteada, 9020-105, Funchal, Portugal

    José S. Câmara

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  1. Carina Cavaco
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  2. Jorge A. M. Pereira
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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). https://doi.org/10.1007/s00216-018-1103-x

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