Assessment of a Noninvasive Exhaled Breath Test for the Diagnosis of Oesophagogastric Cancer

Markar, Sheraz R.; Wiggins, Tom; Antonowicz, Stefan; Chin, Sung‐Tong; Romano, Andrea; Nikolić, Konstantin; Evans, Benjamin Patrick; Cunningham, David; Mughal, Muntzer; Lagergren, Jesper

doi:10.1001/jamaoncol.2018.0991

Cited by 94 publications

(105 citation statements)

References 35 publications

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“…Only a handful of these compounds appeared as top discriminating features in either study. Aldehydes are known to be found endogenously, mostly due to lipid peroxidation, and have been proposed as potential biomarkers in exhaled breath in several different types of cancer including lung 59–62 , breast 63 , ovarian 64 , colorectal 65 , and, most notably, OGC 66–68 . The alkanes and methyl branched alkanes have not been previously associated with oesophageal or gastric cancer, but have been associated with lung and breast cancer in exhaled breath 60,61,63,69,70 .…”

Section: Resultsmentioning

confidence: 99%

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS

Aksenov¹,

Laponogov²,

Zhang³

et al. 2020

Preprint

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Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a “balance score” that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

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Section: Resultsmentioning

confidence: 99%

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS

Aksenov¹,

Laponogov²,

Zhang³

et al. 2020

Preprint

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“…All studies were Phase I biomarker discovery studies. Of the 30 included studies, 18 were from Asia and the Far East [8,9,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26], seven from Europe [27][28][29][30][31][32][33], three from North America [34][35][36], and two from the Middle East [37,38]. ASCC tumour sites identified were the head and neck (n = 17), oesophageal (n = 8), and lung (n = 5).…”

Section: Resultsmentioning

confidence: 99%

“…Metabolites may be more appealing as they are amenable to noninvasive sampling and translatable to point-of-care analytical tools [7]. For example, in upper gastrointestinal adenocarcinoma (the other major ASCC subtype), exhaled metabolites have demonstrated promise for detecting treatable disease stages [8][9][10]. However, progress in this field has been hampered by inadequate standardisation, inconsistent quality assurance, and evolving analytical technology [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

Goh

Antonowicz

Boshier

et al. 2020

Oxidative Medicine and Cellular Longevity

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Introduction. Aerodigestive squamous cell carcinomas (ASCC) constitute a major source of global cancer deaths. Patients typically present with advanced, incurable disease, so new means of detecting early disease are a research priority. Metabolite quantitation is amenable to point-of-care analysis and can be performed in ASCC surrogates such as breath and saliva. The purpose of this systematic review is to summarise progress of ASCC metabolomic studies, with an emphasis on the critical appraisal of methodological quality and reporting. Method. A systematic online literature search was performed to identify studies reporting metabolic biomarkers of ASCC. This review was conducted in accordance with the recommendations of the Cochrane Library and MOOSE guidelines. Results. Thirty studies comprising 2117 patients were included in the review. All publications represented phase-I biomarker discovery studies, and none validated their findings in an independent cohort. There was heterogeneity in study design and methodological and reporting quality. Sensitivities and specificities were higher in oesophageal and head and neck squamous cell carcinomas compared to those in lung squamous cell carcinoma. The metabolic phenotypes of these cancers were similar, as was the kinetics of metabolite groups when comparing blood, tissue, and breath/saliva concentrations. Deregulation of amino acid metabolism was the most frequently reported theme. Conclusion. Metabolite analysis has shown promising diagnostic performance, especially for oesophageal and head and neck ASCC subtypes, which are phenotypically similar. However, shortcomings in study design have led to inconsistencies between studies. To support future studies and ultimately clinical adoption, these limitations are discussed.

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“…Elevated levels of some of the selected aldehydes, phenols and sulphur compounds after using toothpaste and mouthwash would in fact suggest that these interventions may contaminate exhaled breath. Previous work by our group has suggested aldehydes, in particular decanal, as a potential biomarker for early detection of oesophagogastric cancer . The overlap between decanal and menthone is an important finding as use of these interventions containing flavoured ingredients may compromise results.…”

Section: Discussionmentioning

confidence: 98%

“…Details of exhaled VOCs that were analysed in this study, including their chemical formula, SIFT‐MS reagent and product ions, are presented in Table . The VOCs were chosen from five chemical classes, which have been linked to human disease, including cancer, in earlier studies . The abundant endogenous compounds, acetone and isoprene, were also analysed together with the common flavourant, menthone.…”

Section: Methodsmentioning

confidence: 99%

Impact of oral cleansing strategies on exhaled volatile organic compound levels

Vadhwana

Belluomo

Boshier

et al. 2020

Rapid Comm Mass Spectrometry

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Rationale:The analysis of volatile organic compounds (VOCs) within exhaled breath potentially offers a non-invasive method for the detection and surveillance of human disease. Oral contamination of exhaled breath may influence the detection of systemic VOCs relevant to human disease. This study aims to assess the impact of oral cleansing strategies on exhaled VOC levels in order to standardise practice for breath sampling.Methods: Ten healthy volunteers consumed a nutrient challenge followed by four oral cleansing methods: (a) water, (b) saltwater, (c) toothbrushing, and (d) alcoholfree mouthwash. Direct breath sampling was performed using selected ion flow tube mass spectrometry after each intervention.Results: Proposed reactions suggest that volatile fatty acid and alcohol levels (butanoic, pentanoic acid, ethanol) declined with oral cleansing interventions, predominantly after an initial oral rinse with water. Concentrations of aldehydes and phenols (acetaldehyde, menthone, p-cresol) declined with oral water rinse; however, they increased after toothbrushing and mouthwash use, secondary to flavoured ingredients within these products. No significant reductions were observed with sulphur compounds. Conclusions:Findings suggest that oral rinsing with water prior to breath sampling may reduce oral contamination of VOC levels, and further interventions for oral decontamination with flavoured products may compromise results. This intervention may serve as a simple and inexpensive method of standardisation within breath research.

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Assessment of a Noninvasive Exhaled Breath Test for the Diagnosis of Oesophagogastric Cancer

Cited by 94 publications

References 35 publications

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS

Metabolic Biomarkers of Squamous Cell Carcinoma of the Aerodigestive Tract: A Systematic Review and Quality Assessment

Impact of oral cleansing strategies on exhaled volatile organic compound levels

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