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Golfinopoulou R, Hatziagapiou K, Mavrikou S, Kintzios S. Unveiling Colorectal Cancer Biomarkers: Harnessing Biosensor Technology for Volatile Organic Compound Detection. SENSORS (BASEL, SWITZERLAND) 2024; 24:4712. [PMID: 39066110 PMCID: PMC11281049 DOI: 10.3390/s24144712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2024] [Revised: 07/16/2024] [Accepted: 07/18/2024] [Indexed: 07/28/2024]
Abstract
Conventional screening options for colorectal cancer (CRC) detection are mainly direct visualization and invasive methods including colonoscopy and flexible sigmoidoscopy, which must be performed in a clinical setting and may be linked to adverse effects for some patients. Non-invasive CRC diagnostic tests such as computed tomography colonography and stool tests are either too costly or less reliable than invasive ones. On the other hand, volatile organic compounds (VOCs) are potentially ideal non-invasive biomarkers for CRC detection and monitoring. The present review is a comprehensive presentation of the current state-of-the-art VOC-based CRC diagnostics, with a specific focus on recent advancements in biosensor design and application. Among them, breath-based chromatography pattern analysis and sampling techniques are overviewed, along with nanoparticle-based optical and electrochemical biosensor approaches. Limitations of the currently available technologies are also discussed with an outlook for improvement in combination with big data analytics and advanced instrumentation, as well as expanding the scope and specificity of CRC-related volatile biomarkers.
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Affiliation(s)
- Rebecca Golfinopoulou
- Laboratory of Cell Technology, Department of Biotechnology, Agricultural University of Athens, EU-CONEXUS European University, 11855 Athens, Greece;
| | - Kyriaki Hatziagapiou
- First Department of Pediatrics, National and Kapodistrian University of Athens, “Aghia Sophia” Children’s Hospital, Thivon 1, 11527 Athens, Greece;
| | - Sophie Mavrikou
- Laboratory of Cell Technology, Department of Biotechnology, Agricultural University of Athens, EU-CONEXUS European University, 11855 Athens, Greece;
- CeBTec, 40 Vatatzi, 11472 Athens, Greece
| | - Spyridon Kintzios
- Laboratory of Cell Technology, Department of Biotechnology, Agricultural University of Athens, EU-CONEXUS European University, 11855 Athens, Greece;
- CeBTec, 40 Vatatzi, 11472 Athens, Greece
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Mohamadbeigi N, Shooshtari L, Fardindoost S, Vafaiee M, Iraji Zad A, Mohammadpour R. Self-powered triboelectric nanogenerator sensor for detecting humidity level and monitoring ethanol variation in a simulated exhalation environment. Sci Rep 2024; 14:1562. [PMID: 38238422 PMCID: PMC10796746 DOI: 10.1038/s41598-024-51862-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/10/2024] [Indexed: 01/22/2024] Open
Abstract
Respiration stands as a vital process reflecting physiological and pathological human health status. Exhaled breath analysis offers a facile, non-invasive, swift, and cost-effective approach for diagnosing and monitoring diseases by detecting concentration changes of specific biomarkers. In this study, we employed Polyethylene oxide/copper (I) oxide composite nanofibers (PCNFs), synthesized via the electrospinning method as the sensing material to measure ethanol levels (1-200 ppm) in an exhaled breath simulator environment. The integrated contact-separation triboelectric nanogenerator was utilized to power the self-powered PCNFs exhaled breath sensor. The PCNFs-based gas sensor demonstrates promising results with values of 0.9 and 3.2 for detecting 5 ppm and 200 ppm ethanol, respectively, in the presence of interfering gas at 90% relative humidity (RH). Notably, the sensor displayed remarkable ethanol selectivity, with ratios of 10:1 to methanol and 25:1 to acetone. Response and recovery times for 200 ppm ethanol at 90 RH% were rapid, at 2.7 s and 5.8 s, respectively. The PCNFs-based exhaled breath sensor demonstrated consistent and stable performance in practical conditions, showcasing its potential for integration into wearable devices. This self-powered breath sensor enabling continuous monitoring of lung cancer symptoms and facilitating compliance checks with legal alcohol consumption limits.
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Affiliation(s)
- Nima Mohamadbeigi
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
| | - Leyla Shooshtari
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
| | - Somayeh Fardindoost
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
- Faculty of Engineering, Department of Mechanical Engineering, University of Victoria, P.O. Box 1700 STN CSC, Victoria, BC, V8W 2Y2, Canada
| | - Mohaddese Vafaiee
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
| | - Azam Iraji Zad
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran.
- Department of Physics, Sharif University of Technology, Azadi Street, P.O. Box 11365-9161, Tehran, Iran.
| | - Raheleh Mohammadpour
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran.
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González-Ruíz J, A Baccarelli A, Cantu-de-Leon D, Prada D. Air Pollution and Lung Cancer: Contributions of Extracellular Vesicles as Pathogenic Mechanisms and Clinical Utility. Curr Environ Health Rep 2023; 10:478-489. [PMID: 38052753 PMCID: PMC10822800 DOI: 10.1007/s40572-023-00421-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/13/2023] [Indexed: 12/07/2023]
Abstract
PURPOSE OF REVIEW This review addresses the pressing issue of air pollution's threat to human health, focusing on its connection to non-small cell lung cancer (NSCLC) development. The aim is to explore the role of extracellular vesicles (EVs) as potential pathogenic mechanisms in lung cancer, including NSCLC, induced by air pollutants. RECENT FINDINGS Recent research highlights EVs as vital mediators of intercellular communication and key contributors to cancer progression. Notably, this review emphasizes the cargo of EVs released by both cancerous and non-cancerous lung cells, shedding light on their potential role in promoting various aspects of tumor development. The review underscores the importance of comprehending the intricate interplay between air pollution, biological damage mechanisms, and EV-mediated communication during NSCLC development. Major takeaways emphasize the significance of this understanding in addressing air pollution-related lung cancer. Future research avenues are also highlighted, aiming to enhance the applicability of EVs for diagnosis and targeted therapies, ultimately mitigating the inevitable impact of air pollution on NSCLC development and treatment.
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Affiliation(s)
| | - Andrea A Baccarelli
- Mailman School of Public Health, Department of Environmental Health Sciences, Columbia University, New York City, NY, 10032, USA
| | | | - Diddier Prada
- Department of Population Health Science and Policy and the Department of Environmental Medicine and Public Health, Institute for Health Equity Research, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl · (212) 241-6500, Room L2-38, New York City, NY, 10029, USA.
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Vassilenko V, Moura PC, Raposo M. Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends. Biomedicines 2023; 11:3029. [PMID: 38002028 PMCID: PMC10669878 DOI: 10.3390/biomedicines11113029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/08/2023] [Accepted: 11/09/2023] [Indexed: 11/26/2023] Open
Abstract
The assessment of volatile breath biomarkers has been targeted with a lot of interest by the scientific and medical communities during the past decades due to their suitability for an accurate, painless, non-invasive, and rapid diagnosis of health states and pathological conditions. This paper reviews the most relevant bibliographic sources aiming to gather the most pertinent volatile organic compounds (VOCs) already identified as putative cancer biomarkers. Here, a total of 265 VOCs and the respective bibliographic sources are addressed regarding their scientifically proven suitability to diagnose a total of six carcinogenic diseases, namely lung, breast, gastric, colorectal, prostate, and squamous cell (oesophageal and laryngeal) cancers. In addition, future trends in the identification of five other forms of cancer, such as bladder, liver, ovarian, pancreatic, and thyroid cancer, through perspective volatile breath biomarkers are equally presented and discussed. All the results already achieved in the detection, identification, and quantification of endogenous metabolites produced by all kinds of normal and abnormal processes in the human body denote a promising and auspicious future for this alternative diagnostic tool, whose future passes by the development and employment of newer and more accurate collection and analysis techniques, and the certification for utilisation in real clinical scenarios.
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Affiliation(s)
- Valentina Vassilenko
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516 Caparica, Portugal;
| | - Pedro Catalão Moura
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516 Caparica, Portugal;
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Tan SY, Ma Q, Li F, Jiang H, Peng XY, Dong J, Ye X, Wang QL, You FM, Fu X, Ren YF. Does the last 20 years paradigm of clinical research using volatile organic compounds to non-invasively diagnose cancer need to change? Challenges and future direction. J Cancer Res Clin Oncol 2023; 149:10377-10386. [PMID: 37273109 DOI: 10.1007/s00432-023-04940-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 05/24/2023] [Indexed: 06/06/2023]
Abstract
PURPOSE Volatile organic compounds (VOCs) have shown great potential as novel biomarkers for cancer detection; however, comprehensive quantitative analysis is lacking. In this study, we performed a bibliometric analysis of non-invasive cancer diagnosis using VOCs to better characterise international trends and to predict future hotspots in this field, and then we focussed on human studies to analyse clinical characteristics for presenting the current controversies and future perspectives of further clinical work. METHODS Publications, from 2002 to 2022, were retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer were used to generate network maps and identify the annual publications, top countries, authors, institutions, journals, references, and keywords. Then, we further screened clinical trials, and the key information was extracted into Microsoft Excel for further systematical analysis. RESULTS Six hundred and forty-one articles were identified to evaluate research trends, of which 301 clinical trials were selected for further systematical analysis. Overall, the annual publications in this area increased, with an overall upward trend, while the quality of clinical research remains remarkably uneven. CONCLUSION The study of non-invasive cancer diagnosis using VOCs would continue to be an active field. However, without stringent clinical design criteria, most suitable acquisition and analysis devices and statistical approaches, a list of exclusive, specific, reliable and reproducible VOCs to identify a disease and these VOCs appearing in a breath at detectable levels at early stage disease, the clinical utility of VOC tests will be difficult to have any breakthroughs.
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Affiliation(s)
- Shi-Yan Tan
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Qiong Ma
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Fang Li
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Hua Jiang
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Xiao-Yun Peng
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Jing Dong
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Xin Ye
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Qiao-Ling Wang
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Feng-Ming You
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Xi Fu
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China.
| | - Yi-Feng Ren
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China.
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6
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Moura PC, Raposo M, Vassilenko V. Breath volatile organic compounds (VOCs) as biomarkers for the diagnosis of pathological conditions: A review. Biomed J 2023; 46:100623. [PMID: 37336362 PMCID: PMC10339195 DOI: 10.1016/j.bj.2023.100623] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 06/06/2023] [Accepted: 06/14/2023] [Indexed: 06/21/2023] Open
Abstract
Normal and abnormal/pathological status of physiological processes in the human organism can be characterized through Volatile Organic Compounds (VOCs) emitted in breath. Recently, a wide range of volatile analytes has risen as biomarkers. These compounds have been addressed in the scientific and medical communities as an extremely valuable metabolic window. Once collected and analysed, VOCs can represent a tool for a rapid, accurate, non-invasive, and painless diagnosis of several diseases and health conditions. These biomarkers are released by exhaled breath, urine, faeces, skin, and several other ways, at trace concentration levels, usually in the ppbv (μg/L) range. For this reason, the analytical techniques applied for detecting and clinically exploiting the VOCs are extremely important. The present work reviews the most promising results in the field of breath biomarkers and the most common methods of detection of VOCs. A total of 16 pathologies and the respective database of compounds are addressed. An updated version of the VOCs biomarkers database can be consulted at: https://neomeditec.com/VOCdatabase/.
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Affiliation(s)
- Pedro Catalão Moura
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, Caparica, Portugal
| | - Maria Raposo
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, Caparica, Portugal.
| | - Valentina Vassilenko
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, Caparica, Portugal.
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Lv JJ, Li XY, Shen YC, You JX, Wen MZ, Wang JB, Yang XT. Assessing volatile organic compounds exposure and chronic obstructive pulmonary diseases in US adults. Front Public Health 2023; 11:1210136. [PMID: 37475768 PMCID: PMC10354632 DOI: 10.3389/fpubh.2023.1210136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 06/13/2023] [Indexed: 07/22/2023] Open
Abstract
Background Volatile organic compounds (VOCs) are a large group of chemicals widely used in People's Daily life. There is increasing evidence of the cumulative toxicity of VOCs. However, the association between VOCs and the risk of COPD has not been reported. Objective We comprehensively evaluated the association between VOCs and COPD. Methods Our study included a total of 1,477 subjects from the National Health and Nutrition Examination Survey, including VOCs, COPD, and other variables in the average US population. Multiple regression models and smooth-curve fitting (penalty splines) were constructed to examine potential associations, and stratified analyses were used to identify high-risk groups. Results We found a positive association between blood benzene and blood o-xylene concentrations and COPD risk and identified a concentration relationship between the two. That is, when the blood benzene and O-xylene concentrations reached 0.28 ng/mL and 0.08 ng/mL, respectively, the risk of COPD was the highest. In addition, we found that gender, age, and MET influence the relationship, especially in women, young people, and people with low MET. Significance This study revealed that blood benzene and blood o-xylene were independently and positively correlated with COPD risk, suggesting that long-term exposure to benzene and O-xylene may cause pulmonary diseases, and providing a new standard of related blood VOCs concentration for the prevention of COPD.
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Affiliation(s)
- Jia-jie Lv
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
- Department of Vascular Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xin-yu Li
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
- Department of Neurosurgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yu-chen Shen
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jian-xiong You
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ming-zhe Wen
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jing-bing Wang
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xi-tao Yang
- Department of Interventional Therapy, Multidisciplinary Team of Vascular Anomalies, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University, Shanghai, China
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Acem I, van Praag VM, Mostert CQ, van der Wal RJ, Neijenhuis RM, Verhoef C, Grünhagen DJ, van de Sande MA. Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study. Future Oncol 2023; 19:697-704. [PMID: 37129048 DOI: 10.2217/fon-2022-1122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023] Open
Abstract
Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.
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Affiliation(s)
- Ibtissam Acem
- Department of Surgical Oncology & Gastrointestinal Surgery, Erasmus MC Cancer Institute, Dr. Molewaterplein 40, Rotterdam, 3015, GD, The Netherlands
- Department of Orthopedic Oncology, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333, ZA, The Netherlands
| | - Veroniek M van Praag
- Department of Orthopedic Oncology, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333, ZA, The Netherlands
| | - Cassidy Qb Mostert
- Department of Orthopedic Oncology, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333, ZA, The Netherlands
| | - Robert Jp van der Wal
- Department of Orthopedic Oncology, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333, ZA, The Netherlands
| | - Ralph Ml Neijenhuis
- Department of Orthopedic Oncology, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333, ZA, The Netherlands
| | - Cornelis Verhoef
- Department of Surgical Oncology & Gastrointestinal Surgery, Erasmus MC Cancer Institute, Dr. Molewaterplein 40, Rotterdam, 3015, GD, The Netherlands
| | - Dirk J Grünhagen
- Department of Surgical Oncology & Gastrointestinal Surgery, Erasmus MC Cancer Institute, Dr. Molewaterplein 40, Rotterdam, 3015, GD, The Netherlands
| | - Michiel Aj van de Sande
- Department of Orthopedic Oncology, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333, ZA, The Netherlands
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Meller S, Al Khatri MSA, Alhammadi HK, Álvarez G, Alvergnat G, Alves LC, Callewaert C, Caraguel CGB, Carancci P, Chaber AL, Charalambous M, Desquilbet L, Ebbers H, Ebbers J, Grandjean D, Guest C, Guyot H, Hielm-Björkman A, Hopkins A, Kreienbrock L, Logan JG, Lorenzo H, Maia RDCC, Mancilla-Tapia JM, Mardones FO, Mutesa L, Nsanzimana S, Otto CM, Salgado-Caxito M, de los Santos F, da Silva JES, Schalke E, Schoneberg C, Soares AF, Twele F, Vidal-Martínez VM, Zapata A, Zimin-Veselkoff N, Volk HA. Expert considerations and consensus for using dogs to detect human SARS-CoV-2-infections. Front Med (Lausanne) 2022; 9:1015620. [PMID: 36569156 PMCID: PMC9773891 DOI: 10.3389/fmed.2022.1015620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022] Open
Affiliation(s)
- Sebastian Meller
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany,*Correspondence: Sebastian Meller,
| | | | - Hamad Khatir Alhammadi
- International Operations Department, Ministry of Interior of the United Arab Emirates, Abu Dhabi, United Arab Emirates
| | - Guadalupe Álvarez
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Guillaume Alvergnat
- International Operations Department, Ministry of Interior of the United Arab Emirates, Abu Dhabi, United Arab Emirates
| | - Lêucio Câmara Alves
- Department of Veterinary Medicine, Federal Rural University of Pernambuco, Recife, Brazil
| | - Chris Callewaert
- Center for Microbial Ecology and Technology, Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Charles G. B. Caraguel
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, SA, Australia
| | - Paula Carancci
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Anne-Lise Chaber
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, SA, Australia
| | - Marios Charalambous
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Loïc Desquilbet
- École Nationale Vétérinaire d’Alfort, IMRB, Université Paris Est, Maisons-Alfort, France
| | | | | | - Dominique Grandjean
- École Nationale Vétérinaire d’Alfort, Université Paris-Est, Maisons-Alfort, France
| | - Claire Guest
- Medical Detection Dogs, Milton Keynes, United Kingdom
| | - Hugues Guyot
- Clinical Department of Production Animals, Fundamental and Applied Research for Animals & Health Research Unit, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Anna Hielm-Björkman
- Department of Equine and Small Animal Medicine, University of Helsinki, Helsinki, Finland
| | - Amy Hopkins
- Medical Detection Dogs, Milton Keynes, United Kingdom
| | - Lothar Kreienbrock
- Department of Biometry, Epidemiology and Information Processing, University of Veterinary Medicine Hannover, Hanover, Germany
| | - James G. Logan
- Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom,Arctech Innovation, The Cube, Dagenham, United Kingdom
| | - Hector Lorenzo
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | | | | | - Fernando O. Mardones
- Escuela de Medicina Veterinaria, Facultad de Agronomía e Ingeniería Forestal and Facultad de Ciencias Biológicas y Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Leon Mutesa
- Center for Human Genetics, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda,Rwanda National Joint Task Force COVID-19, Kigali, Rwanda
| | | | - Cynthia M. Otto
- Penn Vet Working Dog Center, Department of Clinical Sciences and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Marília Salgado-Caxito
- Escuela de Medicina Veterinaria, Facultad de Agronomía e Ingeniería Forestal and Facultad de Ciencias Biológicas y Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | | | | | - Esther Schalke
- Bundeswehr Medical Service Headquarters, Koblenz, Germany
| | - Clara Schoneberg
- Department of Biometry, Epidemiology and Information Processing, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Anísio Francisco Soares
- Department of Animal Morphology and Physiology, Federal Rural University of Pernambuco, Recife, Brazil
| | - Friederike Twele
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Victor Manuel Vidal-Martínez
- Laboratorio de Parasitología y Patología Acuática, Departamento de Recursos del Mar, Centro de Investigación y de Estudios Avanzados del IPN Unidad Mérida, Mérida, Yucatán, Mexico
| | - Ariel Zapata
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Natalia Zimin-Veselkoff
- Escuela de Medicina Veterinaria, Facultad de Agronomía e Ingeniería Forestal and Facultad de Ciencias Biológicas y Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Holger A. Volk
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany,Center for Systems Neuroscience Hannover, Hanover, Germany
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Teränen V, Nissinen S, Roine A, Antila A, Siiki A, Vaalavuo Y, Kumpulainen P, Oksala N, Laukkarinen J. Bile-volatile organic compounds in the diagnostics of pancreatic cancer and biliary obstruction: A prospective proof-of-concept study. Front Oncol 2022; 12:918539. [PMID: 36479080 PMCID: PMC9720309 DOI: 10.3389/fonc.2022.918539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 10/31/2022] [Indexed: 08/30/2023] Open
Abstract
OBJECTIVES Detection of volatile organic compounds (VOCs) from bodily fluids with field asymmetric waveform ion mobility spectrometry (FAIMS) and related methods has been studied in various settings. Preliminary results suggest that it is possible to detect prostate, colorectal, ovarian and pancreatic cancer from urine samples. In this study, our primary aim was to differentiate pancreatic cancer from pancreatitis and benign tumours of the pancreas by using bile samples obtained during endoscopic retrograde cholangiopancreatography (ERCP). Secondarily, we aimed to differentiate all pancreatic region malignancies from all other kinds of benign causes of biliary obstruction. METHODS A bile sample was successfully aspirated from 94 patients during ERCP in Tampere University Hospital. Hospital and patient records were prospectively followed up for at least two years after ERCP. Bile samples were analysed using a Lonestar chemical analyser (Owlstone, UK) using an ATLAS sampling system and a split-flow box. Diagnoses and corresponding data from the analyses were matched and divided into two subcategories for comparison. Statistical analysis was performed using linear discriminant analysis, support vector machines, and 5-fold cross-validation. RESULTS Pancreatic cancers (n=8) were differentiated from benign pancreatic lesions (n=9) with a sensitivity of 100%, specificity of 77.8%, and correct rate of 88%. All pancreatic region cancers (n=19) were differentiated from all other kinds of benign causes of biliary obstruction (n=75) with corresponding values of 21.1%, 94.7%, and 80.7%. The sample size was too small to try to differentiate pancreatic cancers from adjacent cancers. CONCLUSION Analysing bile VOCs using FAIMS shows promising capability in detecting pancreatic cancer and other cancers in the pancreatic area.
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Affiliation(s)
- Ville Teränen
- Department of Gastroenterology and Alimentary Tract Surgery, Tampere University Hospital, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Samuli Nissinen
- Department of Internal Medicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Antti Roine
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Anne Antila
- Department of Gastroenterology and Alimentary Tract Surgery, Tampere University Hospital, Tampere, Finland
| | - Antti Siiki
- Department of Gastroenterology and Alimentary Tract Surgery, Tampere University Hospital, Tampere, Finland
| | - Yrjö Vaalavuo
- Department of Gastroenterology and Alimentary Tract Surgery, Tampere University Hospital, Tampere, Finland
| | - Pekka Kumpulainen
- Department of Internal Medicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Niku Oksala
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Johanna Laukkarinen
- Department of Gastroenterology and Alimentary Tract Surgery, Tampere University Hospital, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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11
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Barucha A, Mauch RM, Duckstein F, Zagoya C, Mainz JG. The potential of volatile organic compound analysis for pathogen detection and disease monitoring in patients with cystic fibrosis. Expert Rev Respir Med 2022; 16:723-735. [PMID: 35853615 DOI: 10.1080/17476348.2022.2104249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Airway infection with pathogens and its associated pulmonary exacerbations (PEX) are the major causes of morbidity and premature death in cystic fibrosis (CF). Preventing or postponing chronic infections requires early diagnosis. However, limitations of conventional microbiology-based methods can hamper identification of exacerbations and specific pathogen detection. Analyzing volatile organic compounds (VOCs) in breath samples may be an interesting tool in this regard, as VOC-biomarkers can characterize specific airway infections in CF. AREAS COVERED We address the current achievements in VOC-analysis and discuss studies assessing VOC-biomarkers and fingerprints, i.e. a combination of multiple VOCs, in breath samples aiming at pathogen and PEX detection in people with CF (pwCF). We aim to provide bases for further research in this interesting field. EXPERT OPINION Overall, VOC-based analysis is a promising tool for diagnosis of infection and inflammation with potential to monitor disease progression in pwCF. Advantages over conventional diagnostic methods, including easy and non-invasive sampling procedures, may help to drive prompt, suitable therapeutic approaches in the future. Our review shall encourage further research, including validation of VOC-based methods. Specifically, longitudinal validation under standardized conditions is of interest in order to ensure repeatability and enable inclusion in CF diagnostic routine.
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Affiliation(s)
- Anton Barucha
- Cystic Fibrosis Center for Children and Adults, Brandenburg Medical School (MHB) University, Klinikum Westbrandenburg, Brandenburg an der Havel, Germany
| | - Renan M Mauch
- Center for Investigation in Pediatrics, School of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil
| | - Franziska Duckstein
- Cystic Fibrosis Center for Children and Adults, Brandenburg Medical School (MHB) University, Klinikum Westbrandenburg, Brandenburg an der Havel, Germany
| | - Carlos Zagoya
- Cystic Fibrosis Center for Children and Adults, Brandenburg Medical School (MHB) University, Klinikum Westbrandenburg, Brandenburg an der Havel, Germany
| | - Jochen G Mainz
- Cystic Fibrosis Center for Children and Adults, Brandenburg Medical School (MHB) University, Klinikum Westbrandenburg, Brandenburg an der Havel, Germany.,Faculty of Health Sciences, joint Faculty of the Brandenburg University of Technology Cottbus-Senftenberg, the Brandenburg Medical School Theodor Fontane and the University of Potsdam, Germany
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12
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Hidayat SN, Julian T, Dharmawan AB, Puspita M, Chandra L, Rohman A, Julia M, Rianjanu A, Nurputra DK, Triyana K, Wasisto HS. Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose. Artif Intell Med 2022; 129:102323. [PMID: 35659391 PMCID: PMC9110307 DOI: 10.1016/j.artmed.2022.102323] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 05/05/2022] [Accepted: 05/12/2022] [Indexed: 01/31/2023]
Abstract
Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast, and low-cost method, has been continuously used for detecting human diseases, including the coronavirus disease 2019 (COVID-19). Nevertheless, having big data with several available features is not always beneficial because only a few of them will be relevant and useful to distinguish different breath samples (i.e., positive and negative COVID-19 samples). In this study, we develop a hybrid machine learning-based algorithm combining hierarchical agglomerative clustering analysis and permutation feature importance method to improve the data analysis of a portable e-nose for COVID-19 detection (GeNose C19). Utilizing this learning approach, we can obtain an effective and optimum feature combination, enabling the reduction by half of the number of employed sensors without downgrading the classification model performance. Based on the cross-validation test results on the training data, the hybrid algorithm can result in accuracy, sensitivity, and specificity values of (86 ± 3)%, (88 ± 6)%, and (84 ± 6)%, respectively. Meanwhile, for the testing data, a value of 87% is obtained for all the three metrics. These results exhibit the feasibility of using this hybrid filter-wrapper feature-selection method to pave the way for optimizing the GeNose C19 performance.
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Affiliation(s)
- Shidiq Nur Hidayat
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia,Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, BLS 21, Yogyakarta 55281, Indonesia
| | - Trisna Julian
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia
| | - Agus Budi Dharmawan
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia,Faculty of Information Technology, Universitas Tarumanagara, Jl. Letjen S. Parman No. 1, Jakarta 11440, Indonesia
| | - Mayumi Puspita
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia
| | - Lily Chandra
- RS Bhayangkara Polda Daerah Istimewa Yogyakarta, Jl. Raya Solo-Yogyakarta KM. 14, Sleman 55571, Indonesia
| | - Abdul Rohman
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia
| | - Madarina Julia
- Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia
| | - Aditya Rianjanu
- Department of Materials Engineering, Institut Teknologi Sumatera, Terusan Ryacudu, Way Hui, Jati Agung, Lampung 35365, Indonesia
| | - Dian Kesumapramudya Nurputra
- Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia
| | - Kuwat Triyana
- Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, BLS 21, Yogyakarta 55281, Indonesia,Corresponding author
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13
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Kabir KM, Baker MJ, Donald WA. Micro- and nanoscale sensing of volatile organic compounds for early-stage cancer diagnosis. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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14
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Kaloumenou M, Skotadis E, Lagopati N, Efstathopoulos E, Tsoukalas D. Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors. SENSORS (BASEL, SWITZERLAND) 2022; 22:1238. [PMID: 35161984 PMCID: PMC8840008 DOI: 10.3390/s22031238] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 05/07/2023]
Abstract
Early-stage disease diagnosis is of particular importance for effective patient identification as well as their treatment. Lack of patient compliance for the existing diagnostic methods, however, limits prompt diagnosis, rendering the development of non-invasive diagnostic tools mandatory. One of the most promising non-invasive diagnostic methods that has also attracted great research interest during the last years is breath analysis; the method detects gas-analytes such as exhaled volatile organic compounds (VOCs) and inorganic gases that are considered to be important biomarkers for various disease-types. The diagnostic ability of gas-pattern detection using analytical techniques and especially sensors has been widely discussed in the literature; however, the incorporation of novel nanomaterials in sensor-development has also proved to enhance sensor performance, for both selective and cross-reactive applications. The aim of the first part of this review is to provide an up-to-date overview of the main categories of sensors studied for disease diagnosis applications via the detection of exhaled gas-analytes and to highlight the role of nanomaterials. The second and most novel part of this review concentrates on the remarkable applicability of breath analysis in differential diagnosis, phenotyping, and the staging of several disease-types, which are currently amongst the most pressing challenges in the field.
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Affiliation(s)
- Maria Kaloumenou
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
| | - Evangelos Skotadis
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
| | - Nefeli Lagopati
- Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias Str., Goudi, 11527 Athens, Greece; (N.L.); (E.E.)
| | - Efstathios Efstathopoulos
- Medical School, National and Kapodistrian University of Athens, 75, Mikras Asias Str., Goudi, 11527 Athens, Greece; (N.L.); (E.E.)
| | - Dimitris Tsoukalas
- Department of Applied Physics, National Technical University of Athens, 15780 Athens, Greece; (M.K.); (D.T.)
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15
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Zhang ZJ, Li PW, Liu LP, Ru LH, Tang HX, Feng WS. Amine-functionalized UiO-66 as a fluorescent sensor for highly selective detecting volatile organic compound biomarker of lung cancer. J SOLID STATE CHEM 2022. [DOI: 10.1016/j.jssc.2021.122623] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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16
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Volatile organic compounds as a potential screening tool for neoplasm of the digestive system: a meta-analysis. Sci Rep 2021; 11:23716. [PMID: 34887450 PMCID: PMC8660806 DOI: 10.1038/s41598-021-02906-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 11/24/2021] [Indexed: 02/02/2023] Open
Abstract
This meta-analysis was aimed to estimate the diagnostic performance of volatile organic compounds (VOCs) as a potential novel tool to screen for the neoplasm of the digestive system. An integrated literature search was performed by two independent investigators to identify all relevant studies investigating VOCs in diagnosing neoplasm of the digestive system from inception to 7th December 2020. STATA and Revman software were used for data analysis. The methodological quality of each study was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. A bivariate mixed model was used and meta-regression and subgroup analysis were performed to identify possible sources of heterogeneity. A total of 36 studies comprised of 1712 cases of neoplasm and 3215 controls were included in our meta-analysis. Bivariate analysis showed a pooled sensitivity of 0.87 (95% confidence interval (CI) 0.83–0.90), specificity of 0.86 (95% CI 0.82–0.89), a positive likelihood ratio of 6.18 (95% CI 4.68–8.17), and a negative likelihood ratio of 0.15 (95% CI 0.12–0.20). The diagnostic odds ratio and the area under the summary ROC curve for diagnosing neoplasm of the digestive system were 40.61 (95% CI 24.77–66.57) and 0.93 (95% CI 0.90–0.95), respectively. Our analyses revealed that VOCs analysis could be considered as a potential novel tool to screen for malignant diseases of the digestive system.
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17
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The Potential Use of Volatile Biomarkers for Malaria Diagnosis. Diagnostics (Basel) 2021; 11:diagnostics11122244. [PMID: 34943481 PMCID: PMC8700171 DOI: 10.3390/diagnostics11122244] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 11/23/2022] Open
Abstract
Pathogens may change the odor and odor-related biting behavior of the vector and host to enhance pathogen transmission. In recent years, volatile biomarker investigations have emerged to identify odors that are differentially and specifically released by pathogens and plants, or the pathogen-infected or even cancer patients. Several studies have reported odors or volatile biomarkers specifically detected from the breath and skin of malaria-infected individuals. This review will discuss the potential use of these odors or volatile biomarkers for the diagnosis of malaria. This approach not only allows for the non-invasive mean of sample collection but also opens up the opportunity to develop a biosensor for malaria diagnosis in low-resource settings.
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18
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Prediction of oral squamous cell carcinoma based on machine learning of breath samples: a prospective controlled study. BMC Oral Health 2021; 21:500. [PMID: 34615514 PMCID: PMC8496028 DOI: 10.1186/s12903-021-01862-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 09/24/2021] [Indexed: 12/30/2022] Open
Abstract
Background The aim of this study was to evaluate the possibility of breath testing as a method of cancer detection in patients with oral squamous cell carcinoma (OSCC). Methods Breath analysis was performed in 35 OSCC patients prior to surgery. In 22 patients, a subsequent breath test was carried out after surgery. Fifty healthy subjects were evaluated in the control group. Breath sampling was standardized regarding location and patient preparation. All analyses were performed using gas chromatography coupled with ion mobility spectrometry and machine learning. Results Differences in imaging as well as in pre- and postoperative findings of OSCC patients and healthy participants were observed. Specific volatile organic compound signatures were found in OSCC patients. Samples from patients and healthy individuals could be correctly assigned using machine learning with an average accuracy of 86–90%. Conclusions Breath analysis to determine OSCC in patients is promising, and the identification of patterns and the implementation of machine learning require further assessment and optimization. Larger prospective studies are required to use the full potential of machine learning to identify disease signatures in breath volatiles. Supplementary Information The online version contains supplementary material available at 10.1186/s12903-021-01862-z.
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19
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Bordbar MM, Sheini A, Hashemi P, Hajian A, Bagheri H. Disposable Paper-Based Biosensors for the Point-of-Care Detection of Hazardous Contaminations-A Review. BIOSENSORS 2021; 11:316. [PMID: 34562906 PMCID: PMC8464915 DOI: 10.3390/bios11090316] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 08/29/2021] [Accepted: 09/01/2021] [Indexed: 02/07/2023]
Abstract
The fast detection of trace amounts of hazardous contaminations can prevent serious damage to the environment. Paper-based sensors offer a new perspective on the world of analytical methods, overcoming previous limitations by fabricating a simple device with valuable benefits such as flexibility, biocompatibility, disposability, biodegradability, easy operation, large surface-to-volume ratio, and cost-effectiveness. Depending on the performance type, the device can be used to analyze the analyte in the liquid or vapor phase. For liquid samples, various structures (including a dipstick, as well as microfluidic and lateral flow) have been constructed. Paper-based 3D sensors are prepared by gluing and folding different layers of a piece of paper, being more user-friendly, due to the combination of several preparation methods, the integration of different sensor elements, and the connection between two methods of detection in a small set. Paper sensors can be used in chromatographic, electrochemical, and colorimetric processes, depending on the type of transducer. Additionally, in recent years, the applicability of these sensors has been investigated in various applications, such as food and water quality, environmental monitoring, disease diagnosis, and medical sciences. Here, we review the development (from 2010 to 2021) of paper methods in the field of the detection and determination of toxic substances.
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Affiliation(s)
- Mohammad Mahdi Bordbar
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran 19945, Iran;
| | - Azarmidokht Sheini
- Department of Mechanical Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dashte Azadegan 78986, Iran;
| | - Pegah Hashemi
- Research and Development Department, Farin Behbood Tashkhis Ltd., Tehran 16471, Iran;
| | - Ali Hajian
- Institute of Sensor and Actuator Systems, TU Wien, Gusshausstrasse 27-29, 1040 Vienna, Austria;
| | - Hasan Bagheri
- Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran 19945, Iran;
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20
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Gashimova E, Osipova A, Temerdashev A, Porkhanov V, Polyakov I, Perunov D, Dmitrieva E. Study of confounding factors influence on lung cancer diagnostics effectiveness using gas chromatography-mass spectrometry analysis of exhaled breath. Biomark Med 2021; 15:821-829. [PMID: 34223778 DOI: 10.2217/bmm-2020-0828] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 03/30/2021] [Indexed: 01/11/2023] Open
Abstract
Aim: The purpose of this study was to estimate volatile organic compounds (VOCs) ability to distinguish exhaled breath samples of lung cancer patients and healthy volunteers and to assess the effect of smoking status and gender on parameters. Patients & methods: Exhaled breath samples of 40 lung cancer patients and 40 healthy individuals were analyzed using gas chromatography-mass spectrometry. Influence of other factors on the exhaled breath VOCs profile was investigated. Results: Some parameters correlating with the disease status were affected by other factors. Excluding these parameters allows creating a logistic regression diagnostic model with 83% sensitivity and 81% specificity. Conclusion: Influence of other factors on the exhaled breath VOCs profile has to be taken into account to avoid misleading results.
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Affiliation(s)
- Elina Gashimova
- Department of Analytical Chemistry, Kuban State University, Krasnodar, Russia
| | - Anna Osipova
- Department of Analytical Chemistry, Kuban State University, Krasnodar, Russia
| | - Azamat Temerdashev
- Department of Analytical Chemistry, Kuban State University, Krasnodar, Russia
| | - Vladimir Porkhanov
- Research Institute - Regional Clinical Hospital No. 1 named after Prof. SV Ochapovsky, Krasnodar, Russia
| | - Igor Polyakov
- Research Institute - Regional Clinical Hospital No. 1 named after Prof. SV Ochapovsky, Krasnodar, Russia
| | - Dmitry Perunov
- Research Institute - Regional Clinical Hospital No. 1 named after Prof. SV Ochapovsky, Krasnodar, Russia
| | - Ekaterina Dmitrieva
- Department of Analytical Chemistry, Kuban State University, Krasnodar, Russia
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21
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Pulido H, Stanczyk NM, De Moraes CM, Mescher MC. A unique volatile signature distinguishes malaria infection from other conditions that cause similar symptoms. Sci Rep 2021; 11:13928. [PMID: 34230505 PMCID: PMC8260776 DOI: 10.1038/s41598-021-92962-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 05/06/2021] [Indexed: 01/18/2023] Open
Abstract
Recent findings suggest that changes in human odors caused by malaria infection have significant potential as diagnostic biomarkers. However, uncertainty remains regarding the specificity of such biomarkers, particularly in populations where many different pathological conditions may elicit similar symptoms. We explored the ability of volatile biomarkers to predict malaria infection status in Kenyan schoolchildren exhibiting a range of malaria-like symptoms. Using genetic algorithm models to explore data from skin volatile collections, we were able to identify malaria infection with 100% accuracy among children with fever and 75% accuracy among children with other symptoms. While we observed characteristic changes in volatile patterns driven by symptomatology, our models also identified malaria-specific biomarkers with robust predictive capability even in the presence of other pathogens that elicit similar symptoms.
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Affiliation(s)
- Hannier Pulido
- Department of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland
| | - Nina M Stanczyk
- Department of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland
| | - Consuelo M De Moraes
- Department of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland
| | - Mark C Mescher
- Department of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland.
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22
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Belluomo I, Boshier PR, Myridakis A, Vadhwana B, Markar SR, Spanel P, Hanna GB. Selected ion flow tube mass spectrometry for targeted analysis of volatile organic compounds in human breath. Nat Protoc 2021; 16:3419-3438. [PMID: 34089020 DOI: 10.1038/s41596-021-00542-0] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/22/2021] [Indexed: 02/05/2023]
Abstract
The analysis of volatile organic compounds (VOCs) within breath for noninvasive disease detection and monitoring is an emergent research field that has the potential to reshape current clinical practice. However, adoption of breath testing has been limited by a lack of standardization. This protocol provides a comprehensive workflow for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS). Following the suggested protocol, 50 human breath samples can be analyzed and interpreted in <3 h. Key advantages of SIFT-MS are exploited, including the acquisition of real-time results and direct compound quantification without need for calibration curves. The protocol includes details of methods developed for targeted analysis of disease-specific VOCs, specifically short-chain fatty acids, aldehydes, phenols, alcohols and alkanes. A procedure to make custom breath collection bags is also described. This standardized protocol for VOC analysis using SIFT-MS is intended to provide a basis for wider application and the use of breath analysis in clinical studies.
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Affiliation(s)
- Ilaria Belluomo
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Piers R Boshier
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Antonis Myridakis
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Bhamini Vadhwana
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Sheraz R Markar
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Patrik Spanel
- Department of Surgery and Cancer, Imperial College London, London, UK
- J. Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Prague, Czechia
| | - George B Hanna
- Department of Surgery and Cancer, Imperial College London, London, UK.
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23
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Hong Y, Che X, Su H, Mai Z, Huang Z, Huang W, Chen W, Liu S, Gao W, Zhou Z, Tan G, Li X. Exhaled breath analysis using on-line preconcentration mass spectrometry for gastric cancer diagnosis. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4588. [PMID: 32633879 DOI: 10.1002/jms.4588] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 06/03/2020] [Accepted: 06/07/2020] [Indexed: 06/11/2023]
Abstract
Breath volatile biomarkers are capable of distinguishing patients with various cancers. However, high throughput analytical technology is a prerequisite to a large-cohort study intended to discover reliable breath biomarkers for cancer diagnosis. Single-photon ionization (SPI) is a universal ionization technology, and SPI-mass spectrometry (SPI-MS) shows a remarkable advantage in the comprehensive detection of volatile organic compounds (VOCs), in particular, nonpolar compounds. In this study, we have introduced SPI-MS coupled with on-line thermal desorption (TD-SPI-MS) to demonstrate nontarget analysis of breath VOCs for gastric cancer patients. The breath fingerprints of the gastric cancer patients were significantly distinct from that of the control group. Acetone, isoprene, 1,3-dioxolan-2-one, phenol, meta-xylene, 1,2,3-trimethylbenzene, and phenyl acetate showed higher relative peak intensities in the breath profiles of gastric cancer patients. A diagnostic prediction model was further developed by using a training set (121 samples) and validated with a test set (53 samples). The predication accuracy of the developed model was 96.2%, and the area under the curve (AUC) of the receiver operator characteristic curve (ROC) was 0.997, indicating a satisfactory prediction ability of the developed model. Thus, by taking gastric cancer as an example, we have shown that TD-SPI-MS will be a promising tool for high throughput analysis of breath samples to discover characteristic VOCs in patients with various cancers.
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Affiliation(s)
- Yi Hong
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China
| | - Xinxin Che
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
| | - Haibo Su
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
| | - Zebin Mai
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
| | - Zhengxu Huang
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, China
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Guangzhou, China
| | - Weibin Huang
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wei Chen
- Department of Gastrointestinal Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Shulin Liu
- Institute of High Energy Physics, the Chinese Academy of Sciences, Beijing, China
| | - Wei Gao
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, China
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Guangzhou, China
| | - Zhen Zhou
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, China
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Guangzhou, China
| | - Guobin Tan
- Guangzhou Hexin Instrument Co., LTD., Guangzhou, China
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, China
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Guangzhou, China
| | - Xue Li
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou, China
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24
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Aasi A, Mehdi Aghaei S, Panchapakesan B. Outstanding Performance of Transition-Metal-Decorated Single-Layer Graphene-like BC 6N Nanosheets for Disease Biomarker Detection in Human Breath. ACS OMEGA 2021; 6:4696-4707. [PMID: 33644577 PMCID: PMC7905814 DOI: 10.1021/acsomega.0c05495] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 01/25/2021] [Indexed: 06/12/2023]
Abstract
In the present work, we report highly sensitive and selective nanosensors constructed with metal-decorated graphene-like BC6N employing nonequilibrium Green's function (NEGF) formalism combined by density functional theory (DFT) toward multiple inorganic and sulfur-containing gas molecules (NO, NO2, NH3, CO, CO2, H2S, and SO2) as disease biomarkers from human breath. Monolayer sheets of pristine BC6N and Pd-decorated BC6N were evaluated for their gas adsorption properties, electronic property changes, sensitivity, and selectivity toward disease biomarkers. The pristine BC6N nanosheets exhibited sharp drops in the bandgap when interacted with gases such as NO2 while barely affected by other gases. However, the nanosecond recovery time and low adsorption energies limit the gas sensing applications of the pristine BC6N sheet. On the other hand, the Pd-decorated BC6N-based sensor underwent a semiconductor to metal transition upon the adsorption of NO x gas molecules. The conductance change of the sensor's material in terms of I-V characteristics revealed that the Pd-decorated BC6N sensor is highly sensitive (98.6-134%) and selective (12.3-74.4 times) toward NO x gas molecules with a recovery time of 270 s under UV radiation at 498 K while weakly interacting with interfering gases in exhaled breath such as CO2 and H2O. The gas adsorption behavior suggests that metal-decorated BC6N sensors are excellent candidates for analyzing pulmonary disease and cardiovascular biomarkers, among other ailments of the stomach, kidney, and intestine.
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Affiliation(s)
- Aref Aasi
- Small Systems Laboratory,
Department of Mechanical Engineering, Worcester
Polytechnic Institute, Worcester, Massachusetts 01609, United States
| | - Sadegh Mehdi Aghaei
- Small Systems Laboratory,
Department of Mechanical Engineering, Worcester
Polytechnic Institute, Worcester, Massachusetts 01609, United States
| | - Balaji Panchapakesan
- Small Systems Laboratory,
Department of Mechanical Engineering, Worcester
Polytechnic Institute, Worcester, Massachusetts 01609, United States
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25
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Politi L, Monasta L, Rigressi MN, Princivalle A, Gonfiotti A, Camiciottoli G, Perbellini L. Discriminant Profiles of Volatile Compounds in the Alveolar Air of Patients with Squamous Cell Lung Cancer, Lung Adenocarcinoma or Colon Cancer. Molecules 2021; 26:molecules26030550. [PMID: 33494458 PMCID: PMC7866040 DOI: 10.3390/molecules26030550] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 01/15/2021] [Accepted: 01/15/2021] [Indexed: 12/18/2022] Open
Abstract
The objective of the present work was to analyze volatile compounds in alveolar air in patients with squamous cell lung cancer, lung adenocarcinoma or colon cancer, to prepare algorithms able to discriminate such specific pathological conditions. The concentration of 95 volatile compounds was measured in the alveolar air of 45 control subjects, 36 patients with lung adenocarcinoma, 25 patients with squamous cell lung cancer and 52 patients with colon cancer. Volatile compounds were measured with ion molecule reaction mass spectrometry (IMR-MS). An iterated least absolute shrinkage and selection operator multivariate logistic regression model was used to generate specific algorithms and discriminate control subjects from patients with different kinds of cancer. The final predictive models reached the following performance: by using 11 compounds, patients with lung adenocarcinoma were identified with a sensitivity of 86% and specificity of 84%; nine compounds allowed us to identify patients with lung squamous cell carcinoma with a sensitivity of 88% and specificity of 84%; patients with colon adenocarcinoma could be identified with a sensitivity of 96% and a specificity of 73% using a model comprising 13 volatile compounds. The different alveolar profiles of volatile compounds, obtained from patients with three different kinds of cancer, suggest dissimilar biological–biochemistry conditions; each kind of cancer has probably got a specific alveolar profile.
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Affiliation(s)
- Leonardo Politi
- Department of Clinical and Experimental Medicine, Careggi University Hospital, 50134 Florence, Italy; (L.P.); (M.N.R.); (A.G.); (G.C.)
| | - Lorenzo Monasta
- Institute for Maternal and Child Health—IRCCS Burlo Garofolo, 34137 Trieste, Italy
- Correspondence:
| | - Maria Novella Rigressi
- Department of Clinical and Experimental Medicine, Careggi University Hospital, 50134 Florence, Italy; (L.P.); (M.N.R.); (A.G.); (G.C.)
| | - Andrea Princivalle
- Occupational Medicine, Department of Diagnostics and Public Health, University of Verona, 37134 Verona, Italy; (A.P.); (L.P.)
| | - Alessandro Gonfiotti
- Department of Clinical and Experimental Medicine, Careggi University Hospital, 50134 Florence, Italy; (L.P.); (M.N.R.); (A.G.); (G.C.)
| | - Gianna Camiciottoli
- Department of Clinical and Experimental Medicine, Careggi University Hospital, 50134 Florence, Italy; (L.P.); (M.N.R.); (A.G.); (G.C.)
| | - Luigi Perbellini
- Occupational Medicine, Department of Diagnostics and Public Health, University of Verona, 37134 Verona, Italy; (A.P.); (L.P.)
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26
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Pseudomonas aeruginosa Volatilome Characteristics and Adaptations in Chronic Cystic Fibrosis Lung Infections. mSphere 2020; 5:5/5/e00843-20. [PMID: 33028687 PMCID: PMC7568651 DOI: 10.1128/msphere.00843-20] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Pseudomonas aeruginosa is a leading cause of chronic lung infections in cystic fibrosis (CF), which are correlated with lung function decline. Significant clinical efforts are therefore aimed at detecting infections and tracking them for phenotypic changes, such as mucoidy and antibiotic resistance. Both the detection and tracking of lung infections rely on sputum cultures, but due to improvements in CF therapies, sputum production is declining, although risks for lung infections persist. Therefore, we are working toward the development of breath-based diagnostics for CF lung infections. In this study, we characterized of the volatile metabolomes of 81 P. aeruginosa clinical isolates collected from 17 CF patients over a duration of at least 5 years of a chronic lung infection. We found that the volatilome of P. aeruginosa adapts over time and is correlated with infection phenotype changes, suggesting that it may be possible to track chronic CF lung infections with a breath test. Pseudomonas aeruginosa chronic lung infections in individuals with cystic fibrosis (CF) significantly reduce quality of life and increase morbidity and mortality. Tracking these infections is critical for monitoring patient health and informing treatments. We are working toward the development of novel breath-based biomarkers to track chronic P. aeruginosa lung infections in situ. Using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC–TOF-MS), we characterized the in vitro volatile metabolomes (“volatilomes”) of 81 P. aeruginosa isolates collected from 17 CF patients over at least a 5-year period of their chronic lung infections. We detected 539 volatiles produced by the P. aeruginosa isolates, 69 of which were core volatiles that were highly conserved. We found that each early infection isolate has a unique volatilome, and as infection progresses, the volatilomes of isolates from the same patient become increasingly dissimilar, to the point that these intrapatient isolates are no more similar to one another than to isolates from other patients. We observed that the size and chemical diversity of P. aeruginosa volatilomes do not change over the course of chronic infections; however, the relative abundances of core hydrocarbons, alcohols, and aldehydes do change and are correlated with changes in phenotypes associated with chronic infections. This study indicates that it may be feasible to track P. aeruginosa chronic lung infections by measuring changes to the infection volatilome and lays the groundwork for exploring the translatability of this approach to direct measurement using patient breath. IMPORTANCEPseudomonas aeruginosa is a leading cause of chronic lung infections in cystic fibrosis (CF), which are correlated with lung function decline. Significant clinical efforts are therefore aimed at detecting infections and tracking them for phenotypic changes, such as mucoidy and antibiotic resistance. Both the detection and tracking of lung infections rely on sputum cultures, but due to improvements in CF therapies, sputum production is declining, although risks for lung infections persist. Therefore, we are working toward the development of breath-based diagnostics for CF lung infections. In this study, we characterized of the volatile metabolomes of 81 P. aeruginosa clinical isolates collected from 17 CF patients over a duration of at least 5 years of a chronic lung infection. We found that the volatilome of P. aeruginosa adapts over time and is correlated with infection phenotype changes, suggesting that it may be possible to track chronic CF lung infections with a breath test.
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27
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Djozan D, Norouzi J, Farajzadeh MA. On-Line Sorbentless Cryogenic Needle Trap and GC–FID Method for the Extraction and Analysis of Trace Volatile Organic Compounds from Soil Samples. J Chromatogr Sci 2020; 58:887-895. [DOI: 10.1093/chromsci/bmaa056] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 05/01/2020] [Accepted: 07/26/2020] [Indexed: 01/12/2023]
Abstract
Abstract
In this study, an automated sorbentless cryogenic needle trap device (ASCNTD) coupled with a gas chromatograph (GC) was developed with the aim of sampling, pre-concentration and determination of volatile organic compounds (VOCs) from soil sample. This paper describes optimization of relevant parameters, performance evaluation and an illustrative application of ASCNTD. The ASCNTD system consists of a 5 cm stainless steel needle passed through a hollow ceramic rod which is coiled with resistive nichrome wire. The set is placed in a PVC (Polyvinyl chloride) chamber through which liquid nitrogen can flow. The headspace components are circulated with a pump to pass through the needle, and this results in freeze-trapping of the VOCs on the inner surface of the needle. When extraction is completed, the analytes trapped in the inner wall of the needle were thermally desorbed and swept by the carrier gas into the GC capillary column. The parameters being effective on the extraction processes, namely headspace flow rate, the temperature and time of extraction and desorption were optimized and evaluated. The developed technique was compared to the headspace solid-phase microextraction method for the analysis of soil samples containing BTEX (Benzene, Toluene, Ethylbenzene and Xylene). The relative standard deviation values are below 8% and detection limits as low as 1.2 ng g−1 were obtained for BTEX by ASCNTD.
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Affiliation(s)
- Djavanshir Djozan
- Department of Analytical Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran
| | - Jamal Norouzi
- Department of Chemistry, Shabestar Branch, Islamic Azad University, Shabestar, Iran
| | - Mir Ali Farajzadeh
- Department of Analytical Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz, Iran
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28
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Robust and Rapid Detection of Mixed Volatile Organic Compounds in Flow Through Air by a Low Cost Electronic Nose. CHEMOSENSORS 2020. [DOI: 10.3390/chemosensors8030073] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
This work aims to detect volatile organic compounds (VOC), i.e., acetone, ethanol and isopropyl alcohol (IPA) and their binary and ternary mixtures in a simulated indoor ventilation system. Four metal-oxide-semiconductor (MOS) gas sensors were chosen to form an electronic nose and it was used in a flow-through system. To speed up the detection process, transient signals were used to extracted features, as opposed to commonly used steady-state signals, which would require long time stabilization of testing parameters. Five parameters were extracted including three in phase space and two in time space. Classifier and regression models based on backpropagation neural network (BPNN) were used for the qualitative and quantitative detection of VOC mixtures. The VOCs were mixed at different ratios; ethanol and isopropyl alcohol had similar physical and chemical properties, both being challenging in terms of obtaining quantitative results. To estimate the amounts of VOC in the mixtures, the Levenberg–Marquardt algorithm was chosen in network training. When compared with the multivariate linear regression method, the BPNN-based model offered better performance on differentiating ethanol and IPA. The test accuracy of the classification was 82.6%. The concept used in this work could be readily translated for detecting closely related chemicals.
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29
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Lan H, Hartonen K, Riekkola ML. Miniaturised air sampling techniques for analysis of volatile organic compounds in air. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.115873] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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30
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Miller-Atkins G, Acevedo-Moreno LA, Grove D, Dweik RA, Tonelli AR, Brown JM, Allende DS, Aucejo F, Rotroff DM. Breath Metabolomics Provides an Accurate and Noninvasive Approach for Screening Cirrhosis, Primary, and Secondary Liver Tumors. Hepatol Commun 2020; 4:1041-1055. [PMID: 32626836 PMCID: PMC7327218 DOI: 10.1002/hep4.1499] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 12/30/2019] [Accepted: 02/07/2020] [Indexed: 12/20/2022] Open
Abstract
Hepatocellular carcinoma (HCC) and secondary liver tumors, such as colorectal cancer liver metastases are significant contributors to the overall burden of cancer‐related morality. Current biomarkers, such as alpha‐fetoprotein (AFP) for HCC, result in too many false negatives, necessitating noninvasive approaches with improved sensitivity. Volatile organic compounds (VOCs) detected in the breath of patients can provide valuable insight into disease processes and can differentiate patients by disease status. Here, we investigate whether 22 VOCs from the breath of 296 patients can distinguish those with no liver disease (n = 54), cirrhosis (n = 30), HCC (n = 112), pulmonary hypertension (n = 49), or colorectal cancer liver metastases (n = 51). This work extends previous studies by evaluating the ability for VOC signatures to differentiate multiple diseases in a large cohort of patients. Pairwise disease comparisons demonstrated that most of the VOCs tested are present in significantly different relative abundances (false discovery rate P < 0.1), indicating broad impacts on the breath metabolome across diseases. A predictive model developed using random forest machine learning and cross validation classified patients with 85% classification accuracy and 75% balanced accuracy. Importantly, the model detected HCC with 73% sensitivity compared with 53% for AFP in the same cohort. An added value of this approach is that influential VOCs in the predictive model may provide insight into disease etiology. Acetaldehyde and acetone, both of which have roles in tumor promotion, were considered important VOCs for differentiating disease groups in the predictive model and were increased in patients with cirrhosis and HCC compared to patients with no liver disease (false discovery rate P < 0.1). Conclusion: The use of machine learning and breath VOCs shows promise as an approach to develop improved, noninvasive screening tools for chronic liver disease and primary and secondary liver tumors.
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Affiliation(s)
- Galen Miller-Atkins
- Department of Quantitative Health Sciences Lerner Research Institute Cleveland Clinic Cleveland OH
| | | | - David Grove
- Department of Inflammation and Immunity Lerner Research Institute Cleveland Clinic Cleveland OH
| | - Raed A Dweik
- Respiratory Institute Cleveland Clinic Cleveland OH
| | | | - J Mark Brown
- Department of Cardiovascular and Metabolic Sciences Cleveland Clinic Cleveland OH.,Center for Microbiome in Human Health Cleveland Clinic Cleveland OH
| | | | | | - Daniel M Rotroff
- Department of Quantitative Health Sciences Lerner Research Institute Cleveland Clinic Cleveland OH
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31
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Biobanking in Molecular Biomarker Research for the Early Detection of Cancer. Cancers (Basel) 2020; 12:cancers12040776. [PMID: 32218259 PMCID: PMC7226426 DOI: 10.3390/cancers12040776] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 03/23/2020] [Accepted: 03/24/2020] [Indexed: 12/23/2022] Open
Abstract
Although population-wide screening programs for several cancer types have been implemented in multiple countries, screening procedures are invasive, time-consuming and often perceived as a burden for patients. Molecular biomarkers measurable in non-invasively collected samples (liquid biopsies) could facilitate screening, as they could have incremental value on early diagnosis of cancer, but could also predict prognosis or monitor treatment response. Although the shift towards biomarkers from liquid biopsies for early cancer detection was initiated some time ago, there are many challenges that hamper the development of such biomarkers. One of these challenges is large-scale validation that requires large prospectively collected biobanks with liquid biopsies. Establishing those biobanks involves several considerations, such as standardization of sample collection, processing and storage within and between biobanks. In this perspective, we will elaborate on several issues that need to be contemplated in biobanking, both in general and for certain specimen types specifically, to be able to facilitate biomarker validation for early detection of cancer.
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32
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Xia Y, Hong Y, Geng R, Li X, Qu A, Zhou Z, Zhang Z. Amine-Functionalized ZIF-8 as a Fluorescent Probe for Breath Volatile Organic Compound Biomarker Detection of Lung Cancer Patients. ACS OMEGA 2020; 5:3478-3486. [PMID: 32118162 PMCID: PMC7045493 DOI: 10.1021/acsomega.9b03793] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 01/28/2020] [Indexed: 05/09/2023]
Abstract
The highly thermally and chemically stable imidazole framework ZIF-8 samples were separately postmodified with amine groups by using N,N'-dimethylethylenediamine (MMEN) and N,N-dimethylaminoethylamine (MAEA), which had the same molecular formula but different structures. The modified ZIF-8 samples (ZIF-8@amine) were thoroughly characterized, including powder X-ray diffractometry, Fourier-transformed infrared spectroscopy, and physical adsorption at 77 K by nitrogen, thermogravimetric analysis, and photophysical characterization. Results showed that after modification, the Brunauer-Emmett-Teller surface area and total pore volume both increased, almost one time higher than those of the original ZIF-8 sample, and followed the order: ZIF-8-MMEN > ZIF-8-MAEA > ZIF-8. Furthermore, the N-H group was successfully grafted into the modified ZIF-8 samples. To examine the sensing properties of the modified ZIF-8@amine samples toward the breath biomarkers of lung cancer, five potential volatile organic compound biomarkers were used as analytes. ZIF-8-MMEN and ZIF-8-MAEA revealed a unique capacity for sensing hexanal, ethylbenzene, and 1-propanol with high efficiency and sensitivity. The three samples all did not show sensing ability toward styrene and isoprene. In addition, ZIF-8, ZIF-8-MMEN, and ZIF-8-MAEA all can sense hexanal with a detection limit as low as 1 ppb.
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Affiliation(s)
- Yuanhan Xia
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Yi Hong
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Rongchuang Geng
- College
of Pharmacy, Henan University of Chinese
Medicine, Zhengzhou, Henan 450046, China
| | - Xue Li
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Ailan Qu
- College
of Chemistry and Materials Science, Jinan
University, Guangzhou 510632, China
| | - Zhen Zhou
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Zhijuan Zhang
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
- College
of Pharmacy, Henan University of Chinese
Medicine, Zhengzhou, Henan 450046, China
- E-mail: ,
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33
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Xu B, Moradi M, Kuplicki R, Stewart JL, McKinney B, Sen S, Paulus MP. Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample With a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms. Front Psychiatry 2020; 11:503248. [PMID: 33192639 PMCID: PMC7524957 DOI: 10.3389/fpsyt.2020.503248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 08/24/2020] [Indexed: 11/25/2022] Open
Abstract
Non-intrusive, easy-to-use and pragmatic collection of biological processes is warranted to evaluate potential biomarkers of psychiatric symptoms. Prior work with relatively modest sample sizes suggests that under highly-controlled sampling conditions, volatile organic compounds extracted from the human breath (exhalome), often measured by an electronic nose ("e-nose"), may be related to physical and mental health. The present study utilized a streamlined data collection approach and attempted to replicate and extend prior e-nose links to mental health in a standard research setting within large transdiagnostic community dataset (N = 1207; 746 females; 18-61 years) who completed a screening visit at the Laureate Institute for Brain Research between 07/2016 and 05/2018. Factor analysis was used to obtain latent exhalome variables, and machine learning approaches were employed using these latent variables to predict three types of symptoms independent of each other (depression, anxiety, and substance use disorder) within separate training and a test sets. After adjusting for age, gender, body mass index, and smoking status, the best fitting algorithm produced by the training set accounted for nearly 0% of the test set's variance. In each case the standard error included the zero line, indicating that models were not predictive of clinical symptoms. Although some sample variance was predicted, findings did not generalize to out-of-sample data. Based on these findings, we conclude that the exhalome, as measured by the e-nose within a less-controlled environment than previously reported, is not able to provide clinically useful assessments of current depression, anxiety or substance use severity.
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Affiliation(s)
- Bohan Xu
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | - Mahdi Moradi
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | - Rayus Kuplicki
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Jennifer L Stewart
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Community Medicine, Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States
| | - Brett McKinney
- Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States.,Department of Mathematics, College of Engineering & Natural Sciences, University of Tulsa, Tulsa, OK, United States
| | - Sandip Sen
- Department of Computer Science, Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | - Martin P Paulus
- Laureate Institute for Brain Research, Tulsa, OK, United States.,Department of Community Medicine, Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States.,Department of Psychiatry, School of Medicine, University of California San Diego, San Diego, CA, United States
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34
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Swanson B, Fogg L, Julion W, Arrieta MT. Electronic Nose Analysis of Exhaled Breath Volatiles to Identify Lung Cancer Cases: A Systematic Review. J Assoc Nurses AIDS Care 2020; 31:71-79. [PMID: 31860595 DOI: 10.1097/jnc.0000000000000146] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
The purpose of our review was to analyze evidence of the validity of electronic noses to discriminate persons with lung cancer from healthy control subjects and to advance implications for this technology in the care of people living with HIV. A computerized database search of the literature (published 1946-2018) was conducted to identify studies that used electronic nose-generated smellprints to discriminate persons with lung cancer from healthy control subjects. Fifteen articles met the sampling criteria. In 14 studies, mean sensitivity and specificity values from a single training sample were 84.1% and 80.9%, respectively. Five studies applied the prediction model obtained from the training sample to a separate validation sample; mean sensitivity was 88.2%, and mean specificity was 70.2%. Findings suggest that breath smellprints are valid markers of lung cancer and may be useful screening measures for cancer. No studies included people living with HIV; additional studies are needed to assess generalizability to this population.
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35
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Mäkitie AA, Almangush A, Youssef O, Metsälä M, Silén S, Nixon IJ, Haigentz M, Rodrigo JP, Saba NF, Vander Poorten V, Ferlito A. Exhaled breath analysis in the diagnosis of head and neck cancer. Head Neck 2019; 42:787-793. [PMID: 31854494 DOI: 10.1002/hed.26043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 11/15/2019] [Accepted: 12/03/2019] [Indexed: 12/24/2022] Open
Abstract
Head and neck cancer (HNC) comprises a heterogeneous group of upper aerodigestive tract malignant neoplasms, the most frequent of which is squamous cell carcinoma. HNC forms the eighth most common cancer type and the incidence is increasing. However, survival has improved only moderately during the past decades. Currently, early diagnosis remains the mainstay for improving treatment outcomes in this patient population. Unfortunately, screening methods to allow early detection of HNC are not yet established. Therefore, many cases are still diagnosed at advanced stage, compromising outcomes. Exhaled breath analysis (EBA) is a diagnostic tool that has been recently introduced for many cancers. Breath analysis is non-invasive, cost-effective, time-saving, and can potentially be applied for cancer screening. Here, we provide a summary of the accumulated evidence on the feasibility of EBA in the diagnosis of HNC.
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Affiliation(s)
- Antti A Mäkitie
- Department of Otorhinolaryngology-Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Division of Ear, Nose and Throat Diseases, Department of Clinical Sciences, Intervention and Technology, Karolinska Institutet and Karolinska Hospital, Stockholm, Sweden
| | - Alhadi Almangush
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Department of Pathology, University of Helsinki, Helsinki, Finland.,Institute of Biomedicine, Pathology, University of Turku, Turku, Finland.,Faculty of Dentistry, University of Misurata, Misurata, Libya
| | - Omar Youssef
- Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Department of Pathology, University of Helsinki, Helsinki, Finland
| | - Markus Metsälä
- Department of Chemistry, University of Helsinki, Helsinki, Finland
| | - Suvi Silén
- Department of Otorhinolaryngology-Head and Neck Surgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Iain J Nixon
- Department of Otolaryngology, Head and Neck Surgery, NHS Lothian, Edinburgh University, Edinburgh, UK
| | - Missak Haigentz
- Division of Hematology/Oncology, Department of Medicine, Morristown Medical Center/Atlantic Health System, Morristown, New Jersey
| | - Juan P Rodrigo
- Department of Otolaryngology, Hospital Universitario Central de Asturias-University of Oviedo, ISPA, IUOPA, CIBERONC, Oviedo, Spain
| | - Nabil F Saba
- Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University, Atlanta, Georgia
| | - Vincent Vander Poorten
- Otorhinolaryngology-Head and Neck Surgery and Department of Oncology, Section of Head and Neck Oncology, University Hospitals Leuven, KU Leuven, Leuven, Belgium
| | - Alfio Ferlito
- International Head and Neck Scientific Group, Padua, Italy
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36
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Li B, Zou X, Wang H, Lu Y, Shen C, Chu Y. Standardization study of expiratory conditions for on-line breath testing by proton transfer reaction mass spectrometry. Anal Biochem 2019; 581:113344. [DOI: 10.1016/j.ab.2019.113344] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 06/19/2019] [Accepted: 06/19/2019] [Indexed: 12/14/2022]
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Chandran D, Ooi EH, Watson DI, Kholmurodova F, Jaenisch S, Yazbeck R. The Use of Selected Ion Flow Tube-Mass Spectrometry Technology to Identify Breath Volatile Organic Compounds for the Detection of Head and Neck Squamous Cell Carcinoma: A Pilot Study. ACTA ACUST UNITED AC 2019; 55:medicina55060306. [PMID: 31242578 PMCID: PMC6631766 DOI: 10.3390/medicina55060306] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Revised: 06/17/2019] [Accepted: 06/20/2019] [Indexed: 12/16/2022]
Abstract
Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common form of cancer worldwide, with approximately 630,000 new cases diagnosed each year. The development of low-cost and non-invasive tools for the detection of HNSCC using volatile organic compounds (VOCs) in the breath could potentially improve patient care. The aim of this study was to investigate the feasibility of selected ion flow tube mass spectrometry (SIFT-MS) technology to identify breath VOCs for the detection of HNSCC. Materials and Methods: Breath samples were obtained from HNSCC patients (N = 23) and healthy volunteers (N = 21). Exhaled alveolar breath samples were collected into FlexFoil® PLUS (SKC Limited, Dorset, UK) sampling bags from newly diagnosed, histologically confirmed, untreated patients with HNSCC and from non-cancer participants. Breath samples were analyzed by Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS) (Syft Technologies, Christchurch, New Zealand) using Selective Ion Mode (SIM) scans that probed for 91 specific VOCs that had been previously reported as breath biomarkers of HNSCC and other malignancies. Results: Of the 91 compounds analyzed, the median concentration of hydrogen cyanide (HCN) was significantly higher in the HNSCC group (2.5 ppb, 1.6–4.4) compared to the non-cancer group (1.1 ppb, 0.9–1.3; Benjamini–Hochberg adjusted p < 0.05). A receiver operating curve (ROC) analysis showed an area under the curve (AUC) of 0.801 (95% CI, 0.65952–0.94296), suggesting moderate accuracy of HCN in distinguishing HNSCC from non-cancer individuals. There were no statistically significant differences in the concentrations of the other compounds of interest that were analyzed. Conclusions: This pilot study demonstrated the feasibility of SIFT-MS technology to identify VOCs for the detection of HNSCC.
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Affiliation(s)
- Dhinashini Chandran
- Discipline of Surgery, College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia.
- Flinders Centre for Innovation in Cancer, Flinders University, Adelaide 5042, South Australia.
| | - Eng H Ooi
- Discipline of Surgery, College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia.
- Flinders Centre for Innovation in Cancer, Flinders University, Adelaide 5042, South Australia.
| | - David I Watson
- Discipline of Surgery, College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia.
- Flinders Centre for Innovation in Cancer, Flinders University, Adelaide 5042, South Australia.
| | - Feruza Kholmurodova
- Flinders Center for Epidemiology and Biostatistics, Flinders University, Adelaide 5042, South Australia.
| | - Simone Jaenisch
- Discipline of Surgery, College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia.
- Flinders Centre for Innovation in Cancer, Flinders University, Adelaide 5042, South Australia.
| | - Roger Yazbeck
- Discipline of Surgery, College of Medicine and Public Health, Flinders University, Adelaide 5042, Australia.
- Flinders Centre for Innovation in Cancer, Flinders University, Adelaide 5042, South Australia.
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Krilaviciute A, Leja M, Kopp-Schneider A, Barash O, Khatib S, Amal H, Broza YY, Polaka I, Parshutin S, Rudule A, Haick H, Brenner H. Associations of diet and lifestyle factors with common volatile organic compounds in exhaled breath of average-risk individuals. J Breath Res 2019; 13:026006. [DOI: 10.1088/1752-7163/aaf3dc] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Gohel JN, Lunagariya KS, Kapadiya KM, Khunt RC. An Efficient Protocol for the Synthesis of 1, 5- disubstituted Tetrazole Derivatives via a TMS-N 3
Based Ugi Reaction and their Anti-cancer Activity. ChemistrySelect 2018. [DOI: 10.1002/slct.201802638] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Jyoti N. Gohel
- Chemical Research Laboratory; Department of Chemistry; Saurashtra University, Rajkot, (Gujarat); India
| | | | - Khushal M. Kapadiya
- School of Science; Department of Chemistry; RK University, Rajkot (Gujarat); India
| | - Ranjan C. Khunt
- Chemical Research Laboratory; Department of Chemistry; Saurashtra University, Rajkot, (Gujarat); India
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