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. 2023 Apr 15;28(8):3488.
doi: 10.3390/molecules28083488.

Volatile Markers for Cancer in Exhaled Breath-Could They Be the Signature of the Gut Microbiota?

Manohar Prasad Bhandari  1 , Inese Polaka  1 , Reinis Vangravs  1 , Linda Mezmale  1   2   3 , Viktors Veliks  1 , Arnis Kirshners  1 , Pawel Mochalski  4   5 , Emmanuel Dias-Neto  6 , Marcis Leja  1   7   8
Affiliations

Volatile Markers for Cancer in Exhaled Breath-Could They Be the Signature of the Gut Microbiota?

Manohar Prasad Bhandari et al. Molecules. .

Abstract

It has been shown that the gut microbiota plays a central role in human health and disease. A wide range of volatile metabolites present in exhaled breath have been linked with gut microbiota and proposed as a non-invasive marker for monitoring pathological conditions. The aim of this study was to examine the possible correlation between volatile organic compounds (VOCs) in exhaled breath and the fecal microbiome by multivariate statistical analysis in gastric cancer patients (n = 16) and healthy controls (n = 33). Shotgun metagenomic sequencing was used to characterize the fecal microbiota. Breath-VOC profiles in the same participants were identified by an un_targeted gas chromatography-mass spectrometry (GC-MS) technique. A multivariate statistical approach involving a canonical correlation analysis (CCA) and sparse principal component analysis identified the significant relationship between the breath VOCs and fecal microbiota. This relation was found to differ between gastric cancer patients and healthy controls. In 16 cancer cases, 14 distinct metabolites identified from the breath belonging to hydrocarbons, alcohols, aromatics, ketones, ethers, and organosulfur compounds were highly correlated with 33 fecal bacterial taxa (correlation of 0.891, p-value 0.045), whereas in 33 healthy controls, 7 volatile metabolites belonging to alcohols, aldehydes, esters, phenols, and benzamide derivatives correlated with 17 bacterial taxa (correlation of 0.871, p-value 0.0007). This study suggested that the correlation between fecal microbiota and breath VOCs was effective in identifying exhaled volatile metabolites and the functional effects of microbiome, thus helping to understand cancer-related changes and improving the survival and life expectancy in gastric cancer patients.

Keywords: VOCs; breath analysis; breath biomarker; canonical correlation analysis; fecal microbiota; gastric cancer; volatile organic compounds.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Stacked bar plot of relative abundances of different dominant phyla in both cancer and control groups, where the x-axis represents the samples, and the y-axis, the relative abundance of the phyla.
Figure 2
Figure 2
Two-dimensional NMDS plot of fecal microbial communities, based on beta-diversity (OTU level), derived from fecal samples of cancer patients (red) and healthy controls (blue).
Figure 3
Figure 3
A box-plot showing the presence of significantly different bacterial taxa between cancer (red) and control (blue) groups (p-value < 0.05).
Figure 4
Figure 4
Cluster heatmap of breath VOC levels for each study participant (21 VOCs and 49 participants). The x-axis depicts the respective breath VOCs and the y-axis, the patient IDs. Red color on the left vertical axis indicates gastric cancer cases, whereas blue color indicates healthy controls. The darker-colored cells indicate higher concentrations of metabolites, and lighter-colored cells represent lower concentration levels for each subject. The intensity of color corresponds to the concentration levels of VOCs.
Figure 5
Figure 5
Box-plots showing the VOC concentrations according to study groups: (A) gastric cancer patients, (B) healthy controls. Data are expressed as medians and interquartile range (IQR), minimum–maximum, and extreme values or outliers (p-value < 0.05 is considered as statistically significant).
Figure 6
Figure 6
Canonical correlation score plot between the selected breath VOCs (the x-axis) and fecal microbiome composition (the y-axis) using the first canonical components for (A) cancer patients; (B) healthy controls. CCAs were performed on the sets of 14 and 7 breath VOCs, and 33 and 17 bacterial species, of the cancer patients and healthy controls, respectively.
Figure 7
Figure 7
Correlation heatmap of the 14 VOCs and 33 fecal bacterial species in cancer patients. Red color indicates negative correlations, and white or light yellow color indicates positive correlations. The quantitative color scheme is shown at the top.
Figure 8
Figure 8
Correlation heatmap of the 7 VOCs and 17 fecal bacterial species in healthy controls. Red color indicates negative correlations, and white or light yellow color indicates positive correlations. The quantitative color scheme is shown at the top.
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