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The development of accurate, mass-screening tools for the detection of colorectal cancer is paramount, given the social burden imposed and the recognized polyp–cancer sequence in most cases. There are non-invasive techniques designed for detection of cancer by-products, including stool mutated DNA, micro-RNA analysis and tumour-associated antigens/antibodies. Another approach is measurement of the by-products of cellular metabolism, exploiting ‘metabolomic’ differences between cancer- and non-cancer cells using gas chromatography and mass spectrometry. The detection of volatile organic compounds (VOCs) in exhaled breath reflects abnormal peroxygenation of cell membrane-based polyunsaturates from cancer cells, although its discriminatory capacity and statistical methodology are not sufficiently developed to provide a consistent diagnostic performance capable of separating diseased from non-diseased states.

Today, the breath ‘concept’ has expanded to the monitoring of asthma, defining heart transplant rejection, testing for Helicobacter pylori infection, lactose intolerance and bacterial overgrowth, routinely monitoring ventilation during anaesthesia and, of course, catching transgressors driving under the influence of alcohol.

This preliminary study by Altomare and colleagues shows that patients with colorectal cancer have different VOC breath patterns compared with healthy controls, and a sophisticated statistical methodology discriminates between groups with relatively high accuracy. There are, however, a number of issues related to this technique that remain unclear. In lung cancer, exhaled VOC biofingerprints (‘breathprints’) vary between tumour histologies. How do we cater for exogenous cross-contamination within the measurement system or from ambient air? What do we know about the influence of endogenous VOC production by the gut and how to standardize for its effect? Can we correct for exhaled VOCs by subtracting inspiratory levels, calculating alveolar gradients or discarding dead space to result in measurements that are reproducible? In the future, we will need to integrate novel digital and nanosensors with these ‘artificial electronic noses’, allocating them the task of discriminating disease-specific recognition patterns1.

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The author declares no conflict of interest.

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