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Martin JDM, Claudia F, Romain AC. How well does your e-nose detect cancer? Application of artificial breath analysis for performance assessment. J Breath Res 2024; 18:026002. [PMID: 38211310 DOI: 10.1088/1752-7163/ad1d64] [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] [Received: 10/02/2023] [Accepted: 01/11/2024] [Indexed: 01/13/2024]
Abstract
Comparing electronic nose (e-nose) performance is a challenging task because of a lack of standardised method. This paper proposes a method for defining and quantifying an indicator of the effectiveness of multi-sensor systems in detecting cancers by artificial breath analysis. To build this method, an evaluation of the performances of an array of metal oxide sensors built for use as a lung cancer screening tool was conducted. Breath from 20 healthy volunteers has been sampled in fluorinated ethylene propylene sampling bags. These healthy samples were analysed with and without the addition of nine volatile organic compound (VOC) cancer biomarkers, chosen from literature. The concentration of the VOC added was done in increasing amounts. The more VOC were added, the better the discrimination between 'healthy' samples (breath without additives) and 'cancer' samples (breath with additives) was. By determining at which level of concentration the e-nose fails to reliably discriminate between the two groups, we estimate its ability to well predict the presence of the disease or not in a realistic situation. In this work, a home-made e-nose is put to the test. The results underline that the biomarkers need to be about 5.3 times higher in concentration than in real breath for the home-made nose to tell the difference between groups with a sufficient confidence.
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Affiliation(s)
- Justin D M Martin
- Department of Environmental Sciences, Sensing of Atmospheres and Monitoring (SAM), SPHERES Research Unit, University of Liège, 6700 Arlon, Belgium
| | - Falzone Claudia
- Department of Environmental Sciences, Sensing of Atmospheres and Monitoring (SAM), SPHERES Research Unit, University of Liège, 6700 Arlon, Belgium
| | - Anne-Claude Romain
- Department of Environmental Sciences, Sensing of Atmospheres and Monitoring (SAM), SPHERES Research Unit, University of Liège, 6700 Arlon, Belgium
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2
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Wang H, Wei X, Wu Y, Zhang B, Chen Q, Fu W, Sun M, Li H. A combined screening study for evaluating the potential of exhaled acetone, isoprene, and nitric oxide as biomarkers of lung cancer. RSC Adv 2023; 13:31835-31843. [PMID: 37908654 PMCID: PMC10614752 DOI: 10.1039/d3ra04522f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 09/21/2023] [Indexed: 11/02/2023] Open
Abstract
Background: the early lung cancer (LC) screening strategy significantly reduces LC mortality. According to previous studies, lung cancer can be effectively diagnosed by analyzing the concentration of volatile organic compounds (VOCs) in human exhaled breath and establishing a diagnosis model based on the different VOCs. This method, called breath analysis, has the advantage of being rapid and non-invasive. To develop a non-invasive, portable breath detection instrument based on cavity ring-down spectroscopy (CRDS), we explored the feasibility of establishing a model with acetone, isoprene, and nitric oxide (NO) exhaled through human breath, which can be detected on the CRDS instrument. Methods: a total of 511 participants were recruited from the Cancer Institute and Hospital, Tianjin Medical University as the discovery set and randomly split (2 : 1) into training set and internal validation set with stratification. For external validation, 51 participants were recruited from the General Hospital, Tianjin Medical University. Acetone and isoprene from exhaled breath were detected by proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS), and NO was measured using CRDS. The model was constructed using the ensemble learning method that set eXtreme gradient boosting and logistic regression as the basis model and logistic regression as the senior model. The model was evaluated based on accuracy, sensitivity, and specificity. Results: the model achieved an accuracy of 78.8%, sensitivity of 81.0%, specificity of 70.0%, and area under the receiver operating curve (ROC, AUC) of 0.8341 (95% CI from 0.8055 to 0.8852) in the internal validation set. Furthermore, it attained an accuracy of 66.7%, sensitivity of 68.2%, specificity of 65.5%, and AUC of 0.6834 (95% CI from 0.5259 to 0.7956) in the external validation set. Conclusion: the model, established with acetone, isoprene, and NO as predictors, possesses the ability to identify LC patients from healthy control (HC) participants. The CRDS instrument, which simultaneously detects acetone, isoprene, and NO, is expected to be a non-invasive, rapid, portable, and accurate device for early screening of LC.
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Affiliation(s)
- Hao Wang
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Peking Union Medical College Tianjin China
| | - Xin Wei
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Peking Union Medical College Tianjin China
| | - Yinghua Wu
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Peking Union Medical College Tianjin China
| | - Bojun Zhang
- State Key Laboratory of Separation Membrane and Membrane Processes, School of Materials Science and Engineering, Tianjin University of Technology Tianjin China
| | - Qing Chen
- Department of Cardio-Pulmonary Function, National Clinical Research Center for Cancer, Cancer Institute & Hospital, Tianjin Medical University Tianjin China
| | - Weigui Fu
- State Key Laboratory of Separation Membrane and Membrane Processes, School of Materials Science and Engineering, Tianjin University of Technology Tianjin China
| | - Meixiu Sun
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Peking Union Medical College Tianjin China
| | - Hongxiao Li
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Peking Union Medical College Tianjin China
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Paez R, Kammer MN, Tanner NT, Shojaee S, Heideman BE, Peikert T, Balbach ML, Iams WT, Ning B, Lenburg ME, Mallow C, Yarmus L, Fong KM, Deppen S, Grogan EL, Maldonado F. Update on Biomarkers for the Stratification of Indeterminate Pulmonary Nodules. Chest 2023; 164:1028-1041. [PMID: 37244587 PMCID: PMC10645597 DOI: 10.1016/j.chest.2023.05.025] [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: 02/21/2023] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 05/29/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related deaths. Early detection and diagnosis are critical, as survival decreases with advanced stages. Approximately 1.6 million nodules are incidentally detected every year on chest CT scan images in the United States. This number of nodules identified is likely much larger after accounting for screening-detected nodules. Most of these nodules, whether incidentally or screening detected, are benign. Despite this, many patients undergo unnecessary invasive procedures to rule out cancer because our current stratification approaches are suboptimal, particularly for intermediate probability nodules. Thus, noninvasive strategies are urgently needed. Biomarkers have been developed to assist through the continuum of lung cancer care and include blood protein-based biomarkers, liquid biopsies, quantitative imaging analysis (radiomics), exhaled volatile organic compounds, and bronchial or nasal epithelium genomic classifiers, among others. Although many biomarkers have been developed, few have been integrated into clinical practice as they lack clinical utility studies showing improved patient-centered outcomes. Rapid technologic advances and large network collaborative efforts will continue to drive the discovery and validation of many novel biomarkers. Ultimately, however, randomized clinical utility studies showing improved patient outcomes will be required to bring biomarkers into clinical practice.
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Affiliation(s)
- Rafael Paez
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Michael N Kammer
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Nicole T Tanner
- Department of Medicine, Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Medical University of South Carolina, Charleston, SC
| | - Samira Shojaee
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Brent E Heideman
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Tobias Peikert
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN
| | - Meridith L Balbach
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Wade T Iams
- Department of Medicine, Division of Hematology-Oncology, Vanderbilt University Medical Center, Nashville, TN; Vanderbilt-Ingram Cancer Center, Nashville, TN
| | - Boting Ning
- Department of Medicine, Section of Computational Biomedicine, Boston University School of Medicine, Boston, MA
| | - Marc E Lenburg
- Department of Medicine, Section of Computational Biomedicine, Boston University School of Medicine, Boston, MA
| | - Christopher Mallow
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Miami, Miami, FL
| | - Lonny Yarmus
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, MD
| | - Kwun M Fong
- University of Queensland Thoracic Research Centre, The Prince Charles Hospital, Brisbane, QLD, Australia
| | - Stephen Deppen
- Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville, TN; Vanderbilt-Ingram Cancer Center, Nashville, TN; Tennessee Valley Healthcare System, Nashville, TN
| | - Eric L Grogan
- Department of Thoracic Surgery, Vanderbilt University Medical Center, Nashville, TN; Vanderbilt-Ingram Cancer Center, Nashville, TN; Tennessee Valley Healthcare System, Nashville, TN
| | - Fabien Maldonado
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN.
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Hu W, Zhang X, Saber A, Cai Q, Wei M, Wang M, Da Z, Han B, Meng W, Li X. Development and validation of a nomogram model for lung cancer based on radiomics artificial intelligence score and clinical blood test data. Front Oncol 2023; 13:1132514. [PMID: 37064148 PMCID: PMC10090418 DOI: 10.3389/fonc.2023.1132514] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 03/10/2023] [Indexed: 03/30/2023] Open
Abstract
BackgroundArtificial intelligence (AI) discrimination models using single radioactive variables in recognition algorithms of lung nodules cannot predict lung cancer accurately. Hence, we developed a clinical model that combines AI with blood test variables to predict lung cancer.MethodsBetween 2018 and 2021, 584 individuals (358 patients with lung cancer and 226 individuals with lung nodules other than cancer as control) were enrolled prospectively. Machine learning algorithms including lasso regression and random forest (RF) were used to select variables from blood test data, Logistic regression analysis was used to reconfirm the features to build the nomogram model. The predictive performance was assessed by performing the receiver operating characteristic (ROC) curve analysis as well as calibration, clinical decision and impact curves. A cohort of 48 patients was used to independently validate the model. The subgroup application was analyzed by pathological diagnosis.FindingsA total of 584 patients were enrolled (358 lung cancers, 61.30%,226 patients for the control group) to establish the model. The integrated model identified eight potential factors including carcinoembryonic antigen (CEA), AI score, Pro-Gastrin Releasing Peptide (ProGRP), cytokeratin 19 fragment antigen21-1(CYFRA211), squamous cell carcinoma antigen(SCC), indirect bilirubin(IBIL), activated partial thromboplastin time(APTT) and age. The area under the curve (AUC) of the nomogram was 0.907 (95% CI, 0.881-0.929). The decision and clinical impact curves showed good predictive accuracy of the model. An AUC of 0.844 (95% CI, 0.710 - 0.932) was obtained for the external validation group.ConclusionThe nomogram model integrating AI and clinical data can accurately predict lung cancer, especially for the squamous cell carcinoma subtype.
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Affiliation(s)
- Wenteng Hu
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
- Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Xu Zhang
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
| | - Ali Saber
- Saber Medical Genetics Laboratory, Almas Medical Complex, Rasht, Iran
| | - Qianqian Cai
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
| | - Min Wei
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
- Department of Emergency, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Mingyuan Wang
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
- Department of Ultrasonography, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Zijian Da
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
| | - Biao Han
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
- Department of Thoracic Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Wenbo Meng
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
- *Correspondence: Wenbo Meng,
| | - Xun Li
- The First Clinical Medical School of Lanzhou University, Lanzhou, Gansu, China
- Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, Gansu, China
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Schmidt F, Kohlbrenner D, Malesevic S, Huang A, Klein SD, Puhan MA, Kohler M. Mapping the landscape of lung cancer breath analysis: A scoping review (ELCABA). Lung Cancer 2023; 175:131-140. [PMID: 36529115 DOI: 10.1016/j.lungcan.2022.12.003] [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] [Received: 10/19/2022] [Revised: 11/23/2022] [Accepted: 12/10/2022] [Indexed: 12/14/2022]
Abstract
Lung cancer is the leading cause of cancer death worldwide due to its late-stage detection. Lung cancer screening, including low-dose computed tomography (low-dose CT), provides an initial clinical solution. Nevertheless, further innovations and refinements would help to alleviate remaining limitations. The non-invasive, gentle, and fast nature of breath analysis (BA) makes this technology highly attractive to supplement low-dose CT for an improved screening algorithm. However, BA has not taken hold in everyday clinical practice. One reason might be the heterogeneity and variety of BA methods. This scoping review is a comprehensive summary of study designs, breath analytical methods, and suggested biomarkers in lung cancer. Furthermore, this synthesis provides a framework with core outcomes for future studies in lung cancer BA. This work supports future research for evidence synthesis, meta-analysis, and translation into clinical routine workflows.
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Affiliation(s)
- Felix Schmidt
- University of Zurich, Faculty of Medicine, Zurich, Switzerland; University Hospital Zurich, Department of Pulmonology, Zurich, Switzerland.
| | - Dario Kohlbrenner
- University of Zurich, Faculty of Medicine, Zurich, Switzerland; University Hospital Zurich, Department of Pulmonology, Zurich, Switzerland
| | - Stefan Malesevic
- University of Zurich, Faculty of Medicine, Zurich, Switzerland; University Hospital Zurich, Department of Pulmonology, Zurich, Switzerland
| | - Alice Huang
- University Hospital Zurich, Department of Medical Oncology and Hematology, Zurich, Switzerland
| | - Sabine D Klein
- University of Zurich, University Library, Zurich, Switzerland
| | - Milo A Puhan
- University of Zurich, Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
| | - Malcolm Kohler
- University of Zurich, Faculty of Medicine, Zurich, Switzerland; University Hospital Zurich, Department of Pulmonology, Zurich, Switzerland; University of Zurich, Zurich Centre for Integrative Human Physiology, Zurich, Switzerland
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Tyagi H, Daulton E, Bannaga AS, Arasaradnam RP, Covington JA. Urinary Volatiles and Chemical Characterisation for the Non-Invasive Detection of Prostate and Bladder Cancers. BIOSENSORS 2021; 11:bios11110437. [PMID: 34821653 PMCID: PMC8615657 DOI: 10.3390/bios11110437] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/27/2021] [Accepted: 10/29/2021] [Indexed: 05/08/2023]
Abstract
Bladder cancer (BCa) and prostate cancer (PCa) are some of the most common cancers in the world. In both BCa and PCa, the diagnosis is often confirmed with an invasive technique that carries a risk to the patient. Consequently, a non-invasive diagnostic approach would be medically desirable and beneficial to the patient. The use of volatile organic compounds (VOCs) for disease diagnosis, including cancer, is a promising research area that could support the diagnosis process. In this study, we investigated the urinary VOC profiles in BCa, PCa patients and non-cancerous controls by using gas chromatography-ion mobility spectrometry (GC-IMS) and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) to analyse patient samples. GC-IMS separated BCa from PCa (area under the curve: AUC: 0.97 (0.93-1.00)), BCa vs. non-cancerous (AUC: 0.95 (0.90-0.99)) and PCa vs. non-cancerous (AUC: 0.89 (0.83-0.94)) whereas GC-TOF-MS differentiated BCa from PCa (AUC: 0.84 (0.73-0.93)), BCa vs. non-cancerous (AUC: 0.81 (0.70-0.90)) and PCa vs. non-cancerous (AUC: 0.94 (0.90-0.97)). According to our study, a total of 34 biomarkers were found using GC-TOF-MS data, of which 13 VOCs were associated with BCa, seven were associated with PCa, and 14 VOCs were found in the comparison of BCa and PCa.
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Affiliation(s)
- Heena Tyagi
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (H.T.); (E.D.)
| | - Emma Daulton
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (H.T.); (E.D.)
| | - Ayman S. Bannaga
- Department of Gastroenterology, University Hospital Coventry & Warwickshire, Coventry CV2 2DX, UK; (A.S.B.); (R.P.A.)
- Warwick Medical School, University of Warwick, Coventry CV4 7HL, UK
| | - Ramesh P. Arasaradnam
- Department of Gastroenterology, University Hospital Coventry & Warwickshire, Coventry CV2 2DX, UK; (A.S.B.); (R.P.A.)
- Warwick Medical School, University of Warwick, Coventry CV4 7HL, UK
- School of Health Sciences, Coventry University, Coventry CV1 5FB, UK
- School of Biological Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - James A. Covington
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK; (H.T.); (E.D.)
- Correspondence:
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Gouzerh F, Bessière JM, Ujvari B, Thomas F, Dujon AM, Dormont L. Odors and cancer: Current status and future directions. Biochim Biophys Acta Rev Cancer 2021; 1877:188644. [PMID: 34737023 DOI: 10.1016/j.bbcan.2021.188644] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 10/22/2021] [Accepted: 10/23/2021] [Indexed: 02/07/2023]
Abstract
Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.
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Affiliation(s)
- Flora Gouzerh
- CREEC/CANECEV (CREES), Montpellier, France; MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France; CEFE, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, France.
| | - Jean-Marie Bessière
- Ecole Nationale de Chimie de Montpellier, Laboratoire de Chimie Appliquée, Montpellier, France
| | - Beata Ujvari
- Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic 3216, Australia
| | - Frédéric Thomas
- CREEC/CANECEV (CREES), Montpellier, France; MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France
| | - Antoine M Dujon
- CREEC/CANECEV (CREES), Montpellier, France; MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France; Deakin University, School of Life and Environmental Sciences, Centre for Integrative Ecology, Waurn Ponds, Vic 3216, Australia
| | - Laurent Dormont
- CEFE, Univ Montpellier, CNRS, EPHE, IRD, Univ Paul Valéry Montpellier 3, Montpellier, France
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Long Y, Wang C, Wang T, Li W, Dai W, Xie S, Tian Y, Liu M, Liu Y, Peng X, Liu Y, Zhang Y, Wang R, Li Q, Duan Y. High performance exhaled breath biomarkers for diagnosis of lung cancer and potential biomarkers for classification of lung cancer. J Breath Res 2021; 15:016017. [PMID: 33586667 DOI: 10.1088/1752-7163/abaecb] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Exhaled breath analysis has emerged as a promising non-invasive method for diagnosing lung cancer (LC), whereas reliable biomarkers are lacking. Herein, a standardized and systematic study was presented for LC diagnosis, classification and metabolism exploration. To improve the reliability of biomarkers, a validation group was included, and quality control for breath sampling and analysis, comprehensive pollutants analysis, and strict biomarker screening were performed. The performance of exhaled breath biomarkers was shown to be excellent in diagnosing LC even in early stages (stage I and II) with surpassing 0.930 area under the receiver operating characteristic (ROC) curve (AUC), 90% of sensitivity and 88% of specificity both in the discovery and validation analyses. Meanwhile, in these two groups, diagnosing subtypes of LC attained AUCs over 0.930 and reached 1.00 in the two subtypes of adenocarcinomas. It is demonstrated that the metabolism changes in LC are possibly related to lipid oxidation, gut microbial, cytochrome P450 and glutathione S-transferase, and glutathione pathways change in LC progression. Overall, the reliable biomarkers contribute to the clinical application of breath analysis in screening LC patients as well as those in early stages.
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Affiliation(s)
- Yijing Long
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, People's Republic of China
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9
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Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD. J Clin Med 2020; 10:jcm10010032. [PMID: 33374433 PMCID: PMC7796324 DOI: 10.3390/jcm10010032] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/14/2020] [Accepted: 12/22/2020] [Indexed: 12/11/2022] Open
Abstract
Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.
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Baldini C, Billeci L, Sansone F, Conte R, Domenici C, Tonacci A. Electronic Nose as a Novel Method for Diagnosing Cancer: A Systematic Review. BIOSENSORS-BASEL 2020; 10:bios10080084. [PMID: 32722438 PMCID: PMC7459473 DOI: 10.3390/bios10080084] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/13/2020] [Accepted: 07/21/2020] [Indexed: 12/13/2022]
Abstract
Cancer is fast becoming the most important cause of death worldwide, its mortality being mostly caused by late or wrong diagnosis. Novel strategies have been developed to identify early signs of cancer in a minimally obtrusive way, including the Electronic Nose (E-Nose) technology, user-friendly, cost- and time-saving alternative to classical approaches. This systematic review, conducted under the PRISMA guidelines, identified 60 articles directly dealing with the E-Nose application in cancer research published up to 31 January 2020. Among these works, the vast majority reported successful E-Nose use for diagnosing Lung Cancer, showing promising results especially when employing the Aeonose tool, discriminating subjects with Lung Cancer from controls in more than 80% of individuals, in most studies. In order to tailor the main limitations of the proposed approach, including the application of the protocol to advanced stage of cancer, sample heterogeneity and massive confounders, future studies should be conducted on early stage patients, and on larger cohorts, as to better characterize the specific breathprint associated with the various subtypes of cancer. This would ultimately lead to a better and faster diagnosis and to earlier treatment, possibly reducing the burden associated to such conditions.
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Affiliation(s)
- Chiara Baldini
- School of Engineering, University of Pisa, Largo Lucio Lazzarino 1, 56122 Pisa, Italy;
| | - Lucia Billeci
- Institute of Clinical Physiology—National Research Council of Italy (IFC-CNR), Via Moruzzi 1, 56124 Pisa, Italy; (L.B.); (F.S.); (R.C.); (C.D.)
| | - Francesco Sansone
- Institute of Clinical Physiology—National Research Council of Italy (IFC-CNR), Via Moruzzi 1, 56124 Pisa, Italy; (L.B.); (F.S.); (R.C.); (C.D.)
| | - Raffaele Conte
- Institute of Clinical Physiology—National Research Council of Italy (IFC-CNR), Via Moruzzi 1, 56124 Pisa, Italy; (L.B.); (F.S.); (R.C.); (C.D.)
| | - Claudio Domenici
- Institute of Clinical Physiology—National Research Council of Italy (IFC-CNR), Via Moruzzi 1, 56124 Pisa, Italy; (L.B.); (F.S.); (R.C.); (C.D.)
| | - Alessandro Tonacci
- Institute of Clinical Physiology—National Research Council of Italy (IFC-CNR), Via Moruzzi 1, 56124 Pisa, Italy; (L.B.); (F.S.); (R.C.); (C.D.)
- Correspondence:
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11
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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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Zhou M, Sharma R, Zhu H, Li Z, Li J, Wang S, Bisco E, Massey J, Pennington A, Sjoding M, Dickson RP, Park P, Hyzy R, Napolitano L, Gillies CE, Ward KR, Fan X. Rapid breath analysis for acute respiratory distress syndrome diagnostics using a portable two-dimensional gas chromatography device. Anal Bioanal Chem 2019; 411:6435-6447. [PMID: 31367803 PMCID: PMC6722019 DOI: 10.1007/s00216-019-02024-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 06/24/2019] [Accepted: 07/05/2019] [Indexed: 12/21/2022]
Abstract
Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies, its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here, we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity (> 200 at the resolution of 1), high sensitivity (sub-ppb), and rapid analysis capability (~ 30 min) was designed and made in-house for on-site analysis of patients' breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 min. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes. Graphical abstract.
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Affiliation(s)
- Menglian Zhou
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA
| | - Ruchi Sharma
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA
| | - Hongbo Zhu
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA
| | - Ziqi Li
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA
| | - Jiliang Li
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA
| | - Shiyu Wang
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA
| | - Erin Bisco
- Department of Emergency Medicine, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
| | - Justin Massey
- Department of Emergency Medicine, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
| | - Amanda Pennington
- Department of Emergency Medicine, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
| | - Michael Sjoding
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
- Department of Internal Medicine: Division of Pulmonary and Critical Care, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
| | - Robert P Dickson
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
- Department of Internal Medicine: Division of Pulmonary and Critical Care, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
| | - Pauline Park
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
- Department of Surgery: Section of Acute Care Surgery, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
| | - Robert Hyzy
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
- Department of Internal Medicine: Division of Pulmonary and Critical Care, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
| | - Lena Napolitano
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
- Department of Surgery: Section of Acute Care Surgery, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
| | - Christopher E Gillies
- Department of Emergency Medicine, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA
| | - Kevin R Ward
- Department of Emergency Medicine, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA.
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA.
| | - Xudong Fan
- Department of Biomedical Engineering, University of Michigan, 1101 Beal Ave, Ann Arbor, MI, 48109, USA.
- Michigan Center for Integrative Research in Critical Care, 2800 Plymouth Rd, Ann Arbor, MI, 48109, USA.
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Pan JL, Gao J, Hou JH, Hu DZ, Li L. Interaction Between Environmental Risk Factors and Catechol-O-Methyltransferase (COMT) and X-Ray Repair Cross-Complementing Protein 1 (XRCC1) Gene Polymorphisms in Risk of Lung Cancer Among Non-Smoking Chinese Women: A Case-Control Study. Med Sci Monit 2018; 24:5689-5697. [PMID: 30109864 PMCID: PMC6106617 DOI: 10.12659/msm.908240] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Backgrpound Various studies have highlighted the link between polymorphisms in the XRCC1 gene (encoding X-ray repair cross-complementing group 1) with the incidence of decreased DNA repair capacity and an increased predisposition to cancer. Catechol-O-methyltransferase (COMT) plays a crucial role in estrogen-induced cancers. In the present study was analyzed the potential influence of XRCC1 and COMT gene polymorphisms as predisposing factors from a lung cancer perspective, in addition to conducting an investigation into their interaction with environmental risk factors in relation to lung cancer among non-smoking Chinese women. Material/Methods The XRCC1 gene T-77C, Arg194Trp, Arg280His, Arg399Gln, COMT gene 186C>T, and Val158Met mutations were evaluated in peripheral blood collected from 261 non-smoking female patients diagnosed with primary lung cancer and 265 female patients with benign lung disease. Result The results obtained from this study demonstrated that XRCC1–77TC + CC, XRCC1 399Gln/Gln, COMT 186CT + TT, COMT 158Val/Met genotypes, type of occupation, cooking-oil fumes, and soot exposures were all independent risk factors involved with the occurrence of lung cancer among non-smoking women. Moreover, interactions between environmental exposure factors as well as XRCC1 and COMT gene polymorphisms were determined to play significant contributory roles regarding susceptibility of non-smoking females to lung cancer. Conclusions Taken together, T-77C and Arg399Gln polymorphisms of the XRCC1 gene, as well as the 186C>T and Val158Met polymorphisms of the COMT gene, increased the risk of lung cancer in non-smoking women, with the factors of occupation type, cooking-oil fumes, and soot exposures representing key contributing factors.
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Affiliation(s)
- Jian-Liang Pan
- Department of Respiratory and Critical Care Medicine, The Second People's Hospital of Weifang, Weifang, Shandong, China (mainland)
| | - Jin Gao
- Department of Basic Medicine, Heze Medical College, Heze, Shandong, China (mainland)
| | - Jian-Hua Hou
- Department of Respiratory and Critical Care Medicine, The Second People's Hospital of Weifang, Weifang, Shandong, China (mainland)
| | - De-Zhong Hu
- Department of Respiratory and Critical Care Medicine, The Second People's Hospital of Weifang, Weifang, Shandong, China (mainland)
| | - Lin Li
- Department of Cardiothoracic Surgery, Heze Municipal Hospital of Shandong Province, Heze, Shandong, China (mainland)
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