Please enter verification code
Confirm
A Review of Exhaled Volatile Organic Compounds as Biomarkers for Thoracic Malignancies
American Journal of Biomedical and Life Sciences
Volume 8, Issue 6, December 2020, Pages: 231-247
Received: Dec. 2, 2020; Accepted: Dec. 10, 2020; Published: Dec. 31, 2020
Views 33      Downloads 38
Authors
Gerardo Velez, Department of Cardiothoracic Surgery, NYU Langone Health, New York, USA
Harvey Pass, Department of Cardiothoracic Surgery, NYU Langone Health, New York, USA
Article Tools
Follow on us
Abstract
Lung cancer, malignant pleural mesothelioma, and esophageal cancer are the most common thoracic malignancies and are responsible for substantial cancer-related morbidity and mortality worldwide. Early cancer identification prompts earlier intervention and can therefore improve patient survival. Traditional diagnostics are costly and invasive, however, creating an urgent need for alternative methods. Over the past 30 years, breath analysis has emerged as a rapid, minimally invasive, and cost-effective approach. Metabolites in exhaled breath, known as volatile organic compounds (VOCs), reflect internal biomolecular processes and their composition has been shown to vary in association with numerous pathological states. This review provides an overview on the use of VOCs in exhaled breath for the early screening and diagnosis of thoracic malignancies. Study design, methodology, and significant results from over sixty studies published since 1990 are specified and summarized. A total of 439 significant VOCs are reported in the literature, mainly consisting of aromatic compounds, aldehydes, alkanes, lipids, ketones, and sulfur-containing compounds. Diagnostic sensitivities and specificities range from 51-100% and 68.8 – 100%, respectively. Cancer-specific VOC profiles and associations of clinical interest (e.g., comorbidities, histology, and staging) are emphasized and discussed. While there is considerable evidence to support the diagnostic utility of VOCs, the lack of standardization and external validation in large independent cohorts remain key barriers to clinical translation. However, efforts to address these limitations are currently underway.
Keywords
Lung Cancer, Esophageal Cancer, Mesothelioma, Volatile Organic Compounds, VOCs, Breath Analysis, Biomarker
To cite this article
Gerardo Velez, Harvey Pass, A Review of Exhaled Volatile Organic Compounds as Biomarkers for Thoracic Malignancies, American Journal of Biomedical and Life Sciences. Vol. 8, No. 6, 2020, pp. 231-247. doi: 10.11648/j.ajbls.20200806.17
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Creaney, J. and B. W. S. Robinson, Malignant Mesothelioma Biomarkers: From Discovery to Use in Clinical Practice for Diagnosis, Monitoring, Screening, and Treatment. Chest, 2017. 152 (1): p. 143-149.
[2]
Kim, J. A. and P. M. Shah, Screening and prevention strategies and endoscopic management of early esophageal cancer. Chin Clin Oncol, 2017. 6 (5): p. 50.
[3]
Hoffman, R. M. and R. Sanchez, Lung Cancer Screening. Med Clin North Am, 2017. 101 (4): p. 769-785.
[4]
Rivera, M. P., A. C. Mehta, and M. M. Wahidi, Establishing the Diagnosis of Lung Cancer: Diagnosis and Management of Lung Cancer, 3rd ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest, 2013. 143 (5, Supplement): p. e142S-e165S.
[5]
Alsop, B. R. and P. Sharma, Esophageal Cancer. Gastroenterology Clinics of North America, 2016. 45 (3): p. 399-412.
[6]
Shaheen, N. J., et al., ACG Clinical Guideline: Diagnosis and Management of Barrett's Esophagus. Am J Gastroenterol, 2016. 111 (1): p. 30-50; quiz 51.
[7]
Arif, Q. and A. N. Husain, Malignant Mesothelioma Diagnosis. Arch Pathol Lab Med, 2015. 139 (8): p. 978-80.
[8]
Kindler, H. L., et al., Treatment of Malignant Pleural Mesothelioma: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol, 2018. 36 (13): p. 1343-1373.
[9]
Torre, L. A., R. L. Siegel, and A. Jemal, Lung Cancer Statistics. Adv Exp Med Biol, 2016. 893: p. 1-19.
[10]
World Health Organization. Cancer Fact Sheet. 2018 [cited 2020 8/31].
[11]
Brusselmans, L., et al., Breath analysis as a diagnostic and screening tool for malignant pleural mesothelioma: a systematic review. Translational lung cancer research, 2018. 7 (5): p. 520-536.
[12]
Odgerel, C. O., et al., Estimation of the global burden of mesothelioma deaths from incomplete national mortality data. Occup Environ Med, 2017. 74 (12): p. 851-858.
[13]
Pakzad, R., et al., The incidence and mortality of esophageal cancer and their relationship to development in Asia. Ann Transl Med, 2016. 4 (2): p. 29.
[14]
Jemal, A., et al., Global cancer statistics. CA Cancer J Clin, 2011. 61 (2): p. 69-90.
[15]
American Cancer Society. Key Statistics for Esophageal Cancer. [cited 2020 8/31]; Available from: https://www.cancer.org/cancer/esophagus-cancer/about/key-statistics.html.
[16]
Hakim, M., et al., Volatile organic compounds of lung cancer and possible biochemical pathways. Chem Rev, 2012. 112 (11): p. 5949-66.
[17]
Nardi-Agmon, I. and N. Peled, Exhaled breath analysis for the early detection of lung cancer: recent developments and future prospects. Lung Cancer (Auckl), 2017. 8: p. 31-38.
[18]
Gordon, S. M., et al., Volatile organic compounds as breath biomarkers for active and passive smoking. 2002. 110 (7): p. 689-698.
[19]
Pauling, L., et al., Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc Natl Acad Sci U S A, 1971. 68 (10): p. 2374-6.
[20]
Arasaradnam, R. P., et al., Non-invasive exhaled volatile organic biomarker analysis to detect inflammatory bowel disease (IBD). 2016. 48 (2): p. 148-153.
[21]
Dummer, J., et al., Analysis of biogenic volatile organic compounds in human health and disease. 2011. 30 (7): p. 960-967.
[22]
Chambers, S. T., A. Scott-Thomas, and M. J. C. o. i. p.m. Epton, Developments in novel breath tests for bacterial and fungal pulmonary infection. 2012. 18 (3): p. 228-232.
[23]
Phillips, M., et al., Volatile biomarkers of pulmonary tuberculosis in the breath. 2007. 87 (1): p. 44-52.
[24]
Gahleitner, F., et al., Metabolomics pilot study to identify volatile organic compound markers of childhood asthma in exhaled breath. Bioanalysis, 2013. 5 (18): p. 2239-47.
[25]
Montuschi, P., et al., The electronic nose in respiratory medicine. Respiration, 2013. 85 (1): p. 72-84.
[26]
Fens, N., et al., Exhaled breath profiling enables discrimination of chronic obstructive pulmonary disease and asthma. Am J Respir Crit Care Med, 2009. 180 (11): p. 1076-82.
[27]
Tisch, U., et al., Detection of Alzheimer’s and Parkinson’s disease from exhaled breath using nanomaterial-based sensors. 2013. 8 (1): p. 43-56.
[28]
Peng, G., et al., Detection of lung, breast, colorectal, and prostate cancers from exhaled breath using a single array of nanosensors. Br J Cancer, 2010. 103 (4): p. 542-51.
[29]
Phillips, M., et al., Prediction of breast cancer risk with volatile biomarkers in breath. Breast Cancer Res Treat, 2018. 170 (2): p. 343-350.
[30]
Speiser, D., et al., Volatile organic compounds (VOCs) in exhaled breath of patients with breast cancer in a clinical setting. 2012. 83 (10).
[31]
Sun, X., et al., Detection of volatile organic compounds (VOCs) from exhaled breath as noninvasive methods for cancer diagnosis. 2016. 408 (11): p. 2759-2780.
[32]
Bajtarevic A., et al., Noninvasive detection of lung cancer by analysis of exhaled breath. BMC Cancer. 2009 Sep 29; 9: 348.
[33]
Buszewski B., et al., Identification of volatile lung cancer markers by gas chromatography-mass spectrometry: comparison with discrimination by canines. Anal Bioanal Chem. 2012 Jul; 404 (1): 141-6.
[34]
Broza, Y. Y., et al., A nanomaterial-based breath test for short-term follow-up after lung tumor resection. Nanomedicine, 2013. 9 (1): p. 15-21.
[35]
Cai X., et al., A Prediction Model with a Combination of Variables for Diagnosis of Lung Cancer. Med Sci Monit. 2017 Nov 25; 23: 5620-5629.
[36]
Chang, Ji-Eun., et al., Analysis of volatile organic compounds in exhaled breath for lung cancer diagnosis using a sensor system." Sensors and Actuators B: Chemical 255 (2018): 800-807.
[37]
Chen X., et al., A study of the volatile organic compounds exhaled by lung cancer cells in vitro for breath diagnosis. Cancer. 2007 Aug 15; 110 (4): 835-44.
[38]
Chen X., et al., A Non-invasive detection of lung cancer combined virtual gas sensors array with imaging recognition technique. Conf Proc IEEE Eng Med Biol Soc. 2005; 2005: 5873-6.
[39]
Corradi, M., et al., Exhaled breath analysis in suspected cases of non-small-cell lung cancer: a cross-sectional study. J Breath Res, 2015. 9 (2): p. 027101.
[40]
D'Amico, A., et al., An investigation on electronic nose diagnosis of lung cancer. Lung Cancer, 2010. 68 (2): p. 170-6.
[41]
Di Natale C., et al., Lung cancer identification by the analysis of breath by means of an array of non-selective gas sensors. Biosens Bioelectron. 2003 Sep; 18 (10): 1209-18.
[42]
Dragonieri, S., et al., An electronic nose in the discrimination of patients with non-small cell lung cancer and COPD. Lung Cancer, 2009. 64 (2): p. 166-70.
[43]
Fu, X. A., et al., Noninvasive detection of lung cancer using exhaled breath. Cancer Med, 2014. 3 (1): p. 174-81.
[44]
Fuchs P., et al., Breath gas aldehydes as biomarkers of lung cancer. Int J Cancer. 2010 Jun 1; 126 (11): 2663-70.
[45]
Gaspar EM., et al., Organic metabolites in exhaled human breath--a multivariate approach for identification of biomarkers in lung disorders. J Chromatogr A. 2009 Apr 3; 1216 (14): 2749-56.
[46]
Gasparri, R., et al., Volatile signature for the early diagnosis of lung cancer. J Breath Res, 2016. 10 (1): p. 016007.
[47]
Handa, H., et al., Exhaled breath analysis for lung cancer detection using ion mobility spectrometry. PLoS One, 2014. 9 (12): p. e114555.
[48]
Huang CH, et al., A Study of Diagnostic Accuracy Using a Chemical Sensor Array and a Machine Learning Technique to Detect Lung Cancer. Sensors (Basel). 2018 Aug 28; 18 (9): 2845.
[49]
Hubers AJ., et al., Combined sputum hypermethylation and eNose analysis for lung cancer diagnosis. J Clin Pathol. 2014 Aug; 67 (8): 707-11.
[50]
Kischkel, S., et al., Breath biomarkers for lung cancer detection and assessment of smoking related effects—confounding variables, influence of normalization and statistical algorithms. 2010. 411 (21-22): p. 1637-1644.
[51]
Kononov A., et al. Online breath analysis using metal oxide semiconductor sensors (electronic nose) for diagnosis of lung cancer. J Breath Res. 2019 Oct 23; 14 (1): 016004.
[52]
Kort, S., et al., Multi-centre prospective study on diagnosing subtypes of lung cancer by exhaled-breath analysis. Lung Cancer, 2018. 125: p. 223-229.
[53]
Ligor M., et al., Determination of volatile organic compounds in exhaled breath of patients with lung cancer using solid phase microextraction and gas chromatography mass spectrometry. Clin Chem Lab Med. 2009; 47 (5): 550-60.
[54]
Lu, B., et al., A Novel Framework with High Diagnostic Sensitivity for Lung Cancer Detection by Electronic Nose. Sensors (Basel), 2019. 19 (23).
[55]
Machado RF., et al., Detection of lung cancer by sensor array analyses of exhaled breath. Am J Respir Crit Care Med. 2005 Jun 1; 171 (11): 1286-91.
[56]
Mazzone, P. J., et al., Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer. J Thorac Oncol, 2012. 7 (1): p. 137-42.
[57]
Mazzone, P. J., et al., Diagnosis of lung cancer by the analysis of exhaled breath with a colorimetric sensor array. Thorax. 2007 Jul; 62 (7): 565-8.
[58]
Molina, A., et al., Identification of metabolomics panels for potential lung cancer screening by analysis of exhaled breath condensate. J Breath Res, 2016. 10 (2): p. 026002.
[59]
Oguma, T., et al., Clinical contributions of exhaled volatile organic compounds in the diagnosis of lung cancer. PLoS One, 2017. 12 (4): p. e0174802.
[60]
Peled, N., et al., Non-invasive breath analysis of pulmonary nodules. J Thorac Oncol, 2012. 7 (10): p. 1528-33.
[61]
Phillips M., et al., Prediction of lung cancer using volatile biomarkers in breath. Cancer Biomark. 2007; 3 (2): 95-109.
[62]
Phillips, M., T. L. Bauer, and H. I. Pass, A volatile biomarker in breath predicts lung cancer and pulmonary nodules. J Breath Res, 2019. 13 (3): p. 036013.
[63]
Phillips M., et al., Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening. PLoS One. 2015 Dec 23; 10 (12): e0142484.
[64]
Phillips M., et al., Detection of lung cancer using weighted digital analysis of breath biomarkers. Clin Chim Acta. 2008 Jul 17; 393 (2): 76-84.
[65]
Phillips M., et al., Detection of lung cancer with volatile markers in the breath. Chest. 2003 Jun; 123 (6): 2115-23.
[66]
Phillips M., et al., Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study. Lancet. 1999 Jun 5; 353 (9168): 1930-3.
[67]
Poli, D., et al., Exhaled volatile organic compounds in patients with non-small cell lung cancer: cross sectional and nested short-term follow-up study. Respir Res, 2005. 6: p. 71.
[68]
Rocco R., et al., BIONOTE e-nose technology may reduce false positives in lung cancer screening programmes†. Eur J Cardiothorac Surg. 2016 Apr; 49 (4): 1112-7; discussion 1117.
[69]
Rudnicka J., et al., Searching for selected VOCs in human breath samples as potential markers of lung cancer. Lung Cancer. 2019 Sep; 135: 123-129.
[70]
Rudnicka J., et al., Determination of volatile organic compounds as biomarkers of lung cancer by SPME-GC-TOF/MS and chemometrics. J Chromatogr B Analyt Technol Biomed Life Sci. 2011 Nov 15; 879 (30): 3360-6.
[71]
Sakumura Y., et al., Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm. Sensors (Basel). 2017 Feb 4; 17 (2): 287.
[72]
Schallschmidt K, et al., Comparison of volatile organic compounds from lung cancer patients and healthy controls-challenges and limitations of an observational study. J Breath Res. 2016 Oct 12; 10 (4): 046007.
[73]
Shehada, N., et al., Silicon Nanowire Sensors Enable Diagnosis of Patients via Exhaled Breath. ACS Nano, 2016. 10 (7): p. 7047-57.
[74]
Shlomi, D., et al., Detection of Lung Cancer and EGFR Mutation by Electronic Nose System. J Thorac Oncol, 2017. 12 (10): p. 1544-1551.
[75]
Song, G., et al., Quantitative breath analysis of volatile organic compounds of lung cancer patients. Lung Cancer, 2010. 67 (2): p. 227-31.
[76]
Tirzite, M., et al., Detection of lung cancer with electronic nose and logistic regression analysis. J Breath Res, 2018. 13 (1): p. 016006.
[77]
Tirzite M., et al., Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis. J Breath Res. 2017 Aug 21; 11 (3): 036009.
[78]
Ulanowska, A., et al., The application of statistical methods using VOCs to identify patients with lung cancer. J Breath Res, 2011. 5 (4): p. 046008.
[79]
van de Goor R., et al., Training and Validating a Portable Electronic Nose for Lung Cancer Screening. J Thorac Oncol. 2018 May; 13 (5): 676-681.
[80]
Wang, M., et al., Confounding effect of benign pulmonary diseases in selecting volatile organic compounds as markers of lung cancer. J Breath Res, 2018. 12 (4): p. 046013.
[81]
Wang, Y., et al., The analysis of volatile organic compounds biomarkers for lung cancer in exhaled breath, tissues and cell lines. Cancer Biomark, 2012. 11 (4): p. 129-37.
[82]
Westhoff M., et al., Ion mobility spectrometry for the detection of volatile organic compounds in exhaled breath of patients with lung cancer: results of a pilot study. Thorax. 2009 Sep; 64 (9): 744-8.
[83]
Yu H., et al., Solid phase microextraction for analysis of alkanes and aromatic hydrocarbons in human breath. J Chromatogr B Analyt Technol Biomed Life Sci. 2005 Nov 5; 826 (1-2): 69-74.
[84]
Zou Y., et al., Optimization of volatile markers of lung cancer to exclude interferences of non-malignant disease. Cancer Biomark. 2014; 14 (5): 371-9.
[85]
Chapman, E. A., et al., A breath test for malignant mesothelioma using an electronic nose. 2012. 40 (2): p. 448-454.
[86]
de Gennaro, G., et al., Chemical characterization of exhaled breath to differentiate between patients with malignant plueral mesothelioma from subjects with similar professional asbestos exposure. 2010. 398 (7-8): p. 3043-3050.
[87]
Dragonieri, S., et al., An electronic nose distinguishes exhaled breath of patients with Malignant Pleural Mesothelioma from controls. Lung Cancer, 2012. 75 (3): p. 326-31.
[88]
Gilio, A., et al., Breath Analysis for Early Detection of Malignant Pleural Mesothelioma: Volatile Organic Compounds (VOCs) Determination and Possible Biochemical Pathways. Cancers, 2020. 12 (5): p. 1262.
[89]
Lamote, K., et al., Breath analysis by gas chromatography-mass spectrometry and electronic nose to screen for pleural mesothelioma: a cross-sectional case-control study. 2017. 8 (53): p. 91593.
[90]
Lamote, K., et al., Detection of malignant pleural mesothelioma in exhaled breath by multicapillary column/ion mobility spectrometry (MCC/IMS). J Breath Res, 2016. 10 (4): p. 046001.
[91]
Lamote, K., et al., Exhaled breath to screen for malignant pleural mesothelioma: a validation study. Eur Respir J, 2017. 50 (6).
[92]
Chan, D. K., et al., Breath Testing for Barrett's Esophagus Using Exhaled Volatile Organic Compound Profiling With an Electronic Nose Device. Gastroenterology, 2017. 152 (1): p. 24-26.
[93]
Kumar, S., et al., Selected ion flow tube mass spectrometry analysis of exhaled breath for volatile organic compound profiling of esophago-gastric cancer. Anal Chem, 2013. 85 (12): p. 6121-8.
[94]
Kumar, S., et al., Mass Spectrometric Analysis of Exhaled Breath for the Identification of Volatile Organic Compound Biomarkers in Esophageal and Gastric Adenocarcinoma. Ann Surg, 2015. 262 (6): p. 981-90.
[95]
Markar, S. R., et al., Assessment of a Noninvasive Exhaled Breath Test for the Diagnosis of Oesophagogastric Cancer. JAMA Oncol, 2018. 4 (7): p. 970-976.
[96]
Peters, Y., et al., Detection of Barrett’s oesophagus through exhaled breath using an electronic nose device. 2020. 69 (7): p. 1169-1172.
[97]
Zou, X., et al., Exhaled gases online measurements for esophageal cancer patients and healthy people by proton transfer reaction mass spectrometry. J Gastroenterol Hepatol, 2016. 31 (11): p. 1837-1843.
[98]
National Lung Screening Trial Research Team., et al., Reduced lung-cancer mortality with low-dose computed tomographic screening. 2011. 365 (5): p. 395-409.
[99]
Lemjabbar-Alaoui, H., et al., Lung cancer: Biology and treatment options. Biochimica et biophysica acta, 2015. 1856 (2): p. 189-210.
[100]
Noone, A., et al., SEER cancer statistics review, 1975-2015. 2018. 4.
[101]
Stanton, MF., et al., Mechanisms of mesothelioma induction with asbestos and fibrous glass. 1972. 48 (3): p. 797-821.
[102]
Cugell, D. W. and D. W. J. C. Kamp, Asbestos and the pleura: a review. 2004. 125 (3): p. 1103-1117.
[103]
Wagner, J. C., et al., Diffuse pleural mesothelioma and asbestos exposure in the North Western Cape Province. 1960. 17 (4): p. 260-271.
[104]
Bhat, S. K., et al., Oesophageal adenocarcinoma and prior diagnosis of Barrett's oesophagus: a population-based study. Gut, 2015. 64 (1): p. 20-5.
[105]
Horvath, I., et al., Exhaled biomarkers in lung cancer. 2009. 34 (1): p. 261-275.
[106]
Haick, H., et al., Assessment, origin, and implementation of breath volatile cancer markers. 2014. 43 (5): p. 1423-1449.
[107]
Miekisch, W., J. K. Schubert, and G. F. J. C. c. a. Noeldge-Schomburg, Diagnostic potential of breath analysis—focus on volatile organic compounds. 2004. 347 (1-2): p. 25-39.
[108]
Wang, L., et al., 1H-NMR based metabonomic profiling of human esophageal cancer tissue. Molecular Cancer, 2013. 12 (1): p. 25.
[109]
Tan, B., et al., Metabonomics identifies serum metabolite markers of colorectal cancer. Journal of proteome research, 2013. 12 (6): p. 3000-3009.
[110]
Horváth, I., et al., A European Respiratory Society technical standard: exhaled biomarkers in lung disease. Eur Respir J, 2017. 49 (4).
[111]
Beale, D. J., et al., A review of analytical techniques and their application in disease diagnosis in breathomics and salivaomics research. 2017. 18 (1): p. 24.
[112]
ReCIVA Breath Sampler. [cited 2020 September 21]; Available from: https://www.owlstonemedical.com/products/reciva/.
[113]
Van Der Schee, M., et al., MS29. 04 LuCID Exhaled Breath Analysis. 2018. 13 (10): p. S302.
[114]
PAN cancer study. [cited 2020 September 21]; Available from: https://www.owlstonemedical.com/clinical-pipeline/pan/.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186