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      Chemical signature of colorectal cancer: case–control study for profiling the breath print

      Author(s): 1 , 2 , 1 , 1 , 1 , 3 , 3 , 4 , 5 , 3
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      Journal: BJS Open
      Publisher: Wiley

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          Abstract

          Background

          Effective screening for colorectal cancer can reduce mortality by early detection of tumours and colonic polyps. An altered pattern of volatile organic compounds (VOCs) in exhaled breath has been proposed as a potential non-invasive diagnostic tool for detection of cancer. The aim of this study was to evaluate the reliability of breath-testing for colorectal cancer screening and early diagnosis using an advanced breath sampler.

          Methods

          The exhaled breath of patients with colorectal cancer and non-cancer controls with negative findings on colonoscopy was collected using the ReCIVA® Breath Sampler. This portable device is able to capture the alveolar breath fraction without environmental contamination. VOCs were desorbed thermally and analysed by gas chromatography–mass spectrometry. The discriminatory ability of VOCs in detecting colorectal cancer was evaluated by receiver operating characteristic (ROC) curve analysis for each VOC, followed by cross-validation by the leave-one-out method, and by applying stepwise logistic regression analysis.

          Results

          The study included 83 patients with colorectal cancer and 90 non-cancer controls. Fourteen VOCs were found to have significant discriminatory ability in detecting patients with colorectal cancer. The model with the diagnosis of cancer versus no cancer resulted in a statistically significant likelihood of discrimination of 173·45 (P < 0·001), with an area under the ROC curve of 0·979. Cross-validation of the model resulted in a true predictive value for colorectal cancer of 93 per cent overall. Reliability of the breath analysis was maintained irrespective of cancer stage.

          Conclusion

          This study demonstrated that analysis of exhaled VOCs can discriminate patients with colorectal cancer from those without. This finding may eventually lead to the creation of a smart online sensory device, capable of providing a binary answer (cancer/no cancer) and directing to further screening.

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          Detection of lung, breast, colorectal, and prostate cancers from exhaled breath using a single array of nanosensors

          G Peng, R M Hakim, Y Broza … (2010)
          Background: Tumour growth is accompanied by gene and/or protein changes that may lead to peroxidation of the cell membrane species and, hence, to the emission of volatile organic compounds (VOCs). In this study, we investigated the ability of a nanosensor array to discriminate between breath VOCs that characterise healthy states and the most widespread cancer states in the developed world: lung, breast, colorectal, and prostate cancers. Methods: Exhaled alveolar breath was collected from 177 volunteers aged 20–75 years (patients with lung, colon, breast, and prostate cancers and healthy controls). Breath from cancerous subjects was collected before any treatment. The healthy population was healthy according to subjective patient's data. The breath of volunteers was examined by a tailor-made array of cross-reactive nanosensors based on organically functionalised gold nanoparticles and gas chromatography linked to the mass spectrometry technique (GC-MS). Results: The results showed that the nanosensor array could differentiate between ‘healthy' and ‘cancerous' breath, and, furthermore, between the breath of patients having different cancer types. Moreover, the nanosensor array could distinguish between the breath patterns of different cancers in the same statistical analysis, irrespective of age, gender, lifestyle, and other confounding factors. The GC-MS results showed that each cancer could have a unique pattern of VOCs, when compared with healthy states, but not when compared with other cancer types. Conclusions: The reported results could lead to the development of an inexpensive, easy-to-use, portable, non-invasive tool that overcomes many of the deficiencies associated with the currently available diagnostic methods for cancer.
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            Dysbiosis of gut microbiota in promoting the development of colorectal cancer

            Shaomin Zou, Lekun Fang, Mong-Hong Lee (2017)
            Abstract Gastrointestinal microbiome, containing at least 100 trillion bacteria, resides in the mucosal surface of human intestine. Recent studies show that perturbations in the microbiota may influence physiology and link to a number of diseases, including colon tumorigenesis. Colorectal cancer (CRC), the third most common cancer, is the disease resulting from multi-genes and multi-factors, but the mechanistic details between gut microenvironment and CRC remain poorly characterized. Thanks to new technologies such as metagenome sequencing, progress in large-scale analysis of the genetic and metabolic profile of gut microbial has been possible, which has facilitated studies about microbiota composition, taxonomic alterations and host interactions. Different bacterial species and their metabolites play critical roles in the development of CRC. Also, microbiota is important in the inflammatory response and immune processes deregulation during the development and progression of CRC. This review summarizes current studies regarding the association between gastrointestinal microbiota and the development of CRC, which provides insights into the therapeutic strategy of CRC.
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              Metabolomics and metabolic pathway networks from human colorectal cancers, adjacent mucosa, and stool

              Dustin G. Brown, Sangeeta Rao, Tiffany L. Weir … (2016)
              Background Colorectal cancers (CRC) are associated with perturbations in cellular amino acids, nucleotides, pentose-phosphate pathway carbohydrates, and glycolytic, gluconeogenic, and tricarboxylic acid intermediates. A non-targeted global metabolome approach was utilized for exploring human CRC, adjacent mucosa, and stool. In this pilot study, we identified metabolite profile differences between CRC and adjacent mucosa from patients undergoing colonic resection. Metabolic pathway analyses further revealed relationships between complex networks of metabolites. Methods Seventeen CRC patients participated in this pilot study and provided CRC, adjacent mucosa ~10 cm proximal to the tumor, and stool. Metabolomes were analyzed by gas chromatography-mass spectrometry (GC/MS) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS). All of the library standard identifications were confirmed and further analyzed via MetaboLyncTM for metabolic network interactions. Results There were a total of 728 distinct metabolites identified from colonic tissue and stool matrices. Nineteen metabolites significantly distinguished CRC from adjacent mucosa in our patient-matched cohort. Glucose-6-phosphate and fructose-6-phosphate demonstrated 0.64-fold and 0.75-fold lower expression in CRC compared to mucosa, respectively, whereas isobar: betaine aldehyde, N-methyldiethanolamine, and adenylosuccinate had 2.68-fold and 1.88-fold higher relative abundance in CRC. Eleven of the 19 metabolites had not previously been reported for CRC relevance. Metabolic pathway analysis revealed significant perturbations of short-chain fatty acid metabolism, fructose, mannose, and galactose metabolism, and glycolytic, gluconeogenic, and pyruvate metabolism. In comparison to the 500 stool metabolites identified from human CRC patients, only 215 of those stool metabolites were also detected in tissue. This CRC and stool metabolome investigation identified novel metabolites that may serve as key small molecules in CRC pathogenesis, confirmed the results from previously reported CRC metabolome studies, and showed networks for metabolic pathway aberrations. In addition, we found differences between the CRC and stool metabolomes. Conclusions Stool metabolite profiles were limited for direct associations with CRC and adjacent mucosa, yet metabolic pathways were conserved across both matrices. Larger patient-matched CRC, adjacent non-cancerous colonic mucosa, and stool cohort studies for metabolite profiling are needed to validate these small molecule differences and metabolic pathway aberrations for clinical application to CRC control, treatment, and prevention. Electronic supplementary material The online version of this article (doi:10.1186/s40170-016-0151-y) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Journal
                Title: BJS Open
                Publisher: Wiley
                ISSN (Electronic): 2474-9842
                Publication date Created: December 2020
                Publication date Created: December 02 2020
                Publication date Created: September 29 2020
                Publication date Other: December 2020
                Publication date (Print): December 02 2020
                Publication date (Electronic): September 29 2020
                Volume: 4
                Issue: 6
                Pages: 1189-1199
                Affiliations
                [1 ]Surgical Unit ‘M. Rubino’, Department of Emergency and Organ Transplantation, University Aldo Moro of Bari, Bari, Italy
                [2 ]Apulian Breath Analysis Centre (CeRBA), Istituto Di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Tumori Giovanni Paolo II, Bari, Italy
                [3 ]Department of Chemistry, University Aldo Moro of Bari, Bari, Italy
                [4 ]Surgical Unit, Azienda Ospedaliero-Universitaria Policlinico Bari, Bari, Italy
                [5 ]Statistical Unit, Department of Biomedical Sciences and Human Oncology, University Aldo Moro of Bari, Bari, Italy
                Article
                DOI: 10.1002/bjs5.50354
                SO-VID: 88aeb99b-63af-41dd-bd14-bdd2bc4bbc8a
                Copyright © © 2020
                License:

                http://creativecommons.org/licenses/by/4.0/

                http://creativecommons.org/licenses/by/4.0/

                http://doi.wiley.com/10.1002/tdm_license_1.1

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