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Li X, Shi L, Long Y, Wang C, Qian C, Li W, Tian Y, Duan Y. Volatile organic compounds in exhaled breath: a promising approach for accurate differentiation of lung adenocarcinoma and squamous cell carcinoma. J Breath Res 2024; 18:046007. [PMID: 39019071 DOI: 10.1088/1752-7163/ad6474] [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: 06/21/2024] [Accepted: 07/17/2024] [Indexed: 07/19/2024]
Abstract
Lung cancer subtyping, particularly differentiating adenocarcinoma (ADC) from squamous cell carcinoma (SCC), is paramount for clinicians to develop effective treatment strategies. In this study, we aimed: (i) to discover volatile organic compound (VOC) biomarkers for precise diagnosis of ADC and SCC, (ii) to investigated the impact of risk factors on ADC and SCC prediction, and (iii) to explore the metabolic pathways of VOC biomarkers. Exhaled breath samples from patients with ADC (n= 149) and SCC (n= 94) were analyzed by gas chromatography-mass spectrometry. Both multivariate and univariate statistical analysis method were employed to identify VOC biomarkers. Support vector machine (SVM) prediction models were developed and validated based on these VOC biomarkers. The impact of risk factors on ADC and SCC prediction was investigated. A panel of 13 VOCs was found to differ significantly between ADC and SCC. Utilizing the SVM algorithm, the VOC biomarkers achieved a specificity of 90.48%, a sensitivity of 83.50%, and an area under the curve (AUC) value of 0.958 on the training set. On the validation set, these VOC biomarkers attained a predictive power of 85.71% for sensitivity and 73.08% for specificity, along with an AUC value of 0.875. Clinical risk factors exhibit certain predictive power on ADC and SCC prediction. Integrating these risk factors into the prediction model based on VOC biomarkers can enhance its predictive accuracy. This work indicates that exhaled breath holds the potential to precisely detect ADCs and SCCs. Considering clinical risk factors is essential when differentiating between these two subtypes.
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Affiliation(s)
- Xian Li
- College of Biology Pharmacy and Food Engineering, Shangluo University, Shangluo 726000, People's Republic of China
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
| | - Lin Shi
- College of Food Engineering and Nutrition Science, Shaanxi Normal University, Xi'an 710062, People's Republic of China
| | - Yijing Long
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, College of Life Sciences, Sichuan University, Chengdu 610065, People's Republic of China
| | - Chunyan Wang
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, College of Life Sciences, Sichuan University, Chengdu 610065, People's Republic of China
| | - Cheng Qian
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
| | - Wenwen Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610064, People's Republic of China
| | - Yonghui Tian
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
| | - Yixiang Duan
- Research Center of Analytical Instrumentation, Key Laboratory of Synthetic and Natural Functional Molecule Chemistry of Ministry of Education, College of Chemistry & Materials Science, Northwest University, Xi'an 710069, People's Republic of China
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, College of Life Sciences, Sichuan University, Chengdu 610065, People's Republic of China
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Bajo-Fernández M, Souza-Silva ÉA, Barbas C, Rey-Stolle MF, García A. GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review. Front Mol Biosci 2024; 10:1295955. [PMID: 38298553 PMCID: PMC10828970 DOI: 10.3389/fmolb.2023.1295955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 12/05/2023] [Indexed: 02/02/2024] Open
Abstract
Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.
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Affiliation(s)
- María Bajo-Fernández
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
| | - Érica A. Souza-Silva
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
- Departmento de Química, Universidade Federal de São Paulo (UNIFESP), Diadema, Brazil
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
| | - Ma Fernanda Rey-Stolle
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
| | - Antonia García
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
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Yu Q, Chen J, Fu W, Muhammad KG, Li Y, Liu W, Xu L, Dong H, Wang D, Liu J, Lu Y, Chen X. Smartphone-Based Platforms for Clinical Detections in Lung-Cancer-Related Exhaled Breath Biomarkers: A Review. BIOSENSORS 2022; 12:bios12040223. [PMID: 35448283 PMCID: PMC9028493 DOI: 10.3390/bios12040223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 04/01/2022] [Accepted: 04/05/2022] [Indexed: 12/24/2022]
Abstract
Lung cancer has been studied for decades because of its high morbidity and high mortality. Traditional methods involving bronchoscopy and needle biopsy are invasive and expensive, which makes patients suffer more risks and costs. Various noninvasive lung cancer markers, such as medical imaging indices, volatile organic compounds (VOCs), and exhaled breath condensates (EBCs), have been discovered for application in screening, diagnosis, and prognosis. However, the detection of markers still relies on bulky and professional instruments, which are limited to training personnel or laboratories. This seriously hinders population screening for early diagnosis of lung cancer. Advanced smartphones integrated with powerful applications can provide easy operation and real-time monitoring for healthcare, which demonstrates tremendous application scenarios in the biomedical analysis region from medical institutions or laboratories to personalized medicine. In this review, we propose an overview of lung-cancer-related noninvasive markers from exhaled breath, focusing on the novel development of smartphone-based platforms for the detection of these biomarkers. Lastly, we discuss the current limitations and potential solutions.
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Affiliation(s)
- Qiwen Yu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Jing Chen
- School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou 310051, China;
| | - Wei Fu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Kanhar Ghulam Muhammad
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Yi Li
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Wenxin Liu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Linxin Xu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Hao Dong
- Research Center for Sensing Materials and Devices, Zhejiang Lab, Hangzhou 311100, China; (H.D.); (D.W.)
| | - Di Wang
- Research Center for Sensing Materials and Devices, Zhejiang Lab, Hangzhou 311100, China; (H.D.); (D.W.)
| | - Jun Liu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
| | - Yanli Lu
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
- Correspondence: (Y.L.); (X.C.)
| | - Xing Chen
- Biosensor National Special Laboratory, Key Laboratory for Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China; (Q.Y.); (W.F.); (K.G.M.); (Y.L.); (W.L.); (L.X.); (J.L.)
- Correspondence: (Y.L.); (X.C.)
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Li C, Zhou T, Chen J, Li R, Chen H, Luo S, Chen D, Cai C, Li W. The role of Exosomal miRNAs in cancer. J Transl Med 2022; 20:6. [PMID: 34980158 PMCID: PMC8722109 DOI: 10.1186/s12967-021-03215-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 12/22/2021] [Indexed: 02/08/2023] Open
Abstract
Exosomal miRNAs have attracted much attention due to their critical role in regulating genes and the altered expression of miRNAs in virtually all cancers affecting humans (Sun et al. in Mol Cancer 17(1):14, 2018). Exosomal miRNAs modulate processes that interfere with cancer immunity and microenvironment, and are significantly involved in tumor growth, invasion, metastasis, angiogenesis and drug resistance. Fully investigating the detailed mechanism of miRNAs in the occurrence and development of various cancers could help not only in the treatment of cancers but also in the prevention of malignant diseases. The current review highlighted recently published advances regarding cancer-derived exosomes, e.g., sorting and delivery mechanisms for RNAs. Exosomal miRNAs that modulate cancer cell-to-cell communication, impacting tumor growth, angiogenesis, metastasis and multiple biological features, were discussed. Finally, the potential role of exosomal miRNAs as diagnostic and prognostic molecular markers was summarized, as well as their usefulness in detecting cancer resistance to therapeutic agents.
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Affiliation(s)
- Chuanyun Li
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China
| | - Tong Zhou
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Jing Chen
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China.,Beijing Institute of Hepatology, Beijing, China
| | - Rong Li
- Chengde Medical University, Chengde, China
| | - Huan Chen
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China
| | - Shumin Luo
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China.,Beijing Institute of Hepatology, Beijing, China
| | - Dexi Chen
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China.,Beijing Institute of Hepatology, Beijing, China
| | - Cao Cai
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China.
| | - Weihua Li
- Fengtai District, YouAn Hospital, Capital Medical University, NO. 8, Xitoutiao, Youanmen wai, Beijing, China. .,Beijing Institute of Hepatology, Beijing, China.
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Wu X, Zhu T, Zhang H, Lu L, He X, Liu C, Fan SJ. Identification of odor biomarkers in irradiation injury urine based on headspace SPME-GC-MS. Int J Radiat Biol 2021; 97:1597-1605. [PMID: 34402727 DOI: 10.1080/09553002.2021.1969050] [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: 10/20/2022]
Abstract
PURPOSE The threat of population exposure to ionizing radiation is increasing rapidly worldwide. Such exposure, especially at high-dose, is known to cause acute radiation syndrome (ARS). Hence, it is necessary to develop specific and sensitive biomarkers to accurately diagnose radiation injury and evaluate medical countermeasures. MATERIALS AND METHODS Caenorhabditis elegans (C. elegans), a model organism with a fine and sound olfactory system, was used to examine the odor of urine samples collected from irradiation-injured rats, and compared with those from un-irradiated control rats to investigate the 'special odor' of radiation injury. Subsequently, headspace SPME-GC-MS was applied for non-targeted metabolomic analysis of volatile organic compounds (VOCs) in urine, with the aim to discover changes of small molecule metabolites and identify odor biomarkers of irradiation injury. RESULTS C. elegans showed significant attraction to the urine of total body irradiation (TBI) rats compared with control rats, indicating that irradiation injury can emit 'special odor' and the metabolites in urine VOCs were changed. Using metabolomics based on headspace SPME-GC-MS for metabolic profiles analysis, we screened 63 differentially expressed metabolites. Among them, 10 metabolites including p-Cresol with excellent diagnostic ability were identified as odor biomarkers according to receiver operating characteristic (ROC) curve analysis. CONCLUSIONS This study confirmed the 'special odor' induced by irradiation injury, and identified biomarkers through urine VOCs analysis for the first time, which can provide a novel approach and insight to evaluate irradiation injury noninvasively, accurately and conveniently.[Figure: see text].
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Affiliation(s)
- Xin Wu
- Tianjin Key Laboratory of Radiation Medicine and Molecular Nuclear Medicine, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, PR China
| | - Tong Zhu
- Tianjin Key Laboratory of Radiation Medicine and Molecular Nuclear Medicine, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, PR China
| | - Hongbing Zhang
- State Key Laboratory of Drug Delivery Technology and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research, Tianjin, PR China
| | - Lu Lu
- Tianjin Key Laboratory of Radiation Medicine and Molecular Nuclear Medicine, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, PR China
| | - Xin He
- Tianjin Key Laboratory of Radiation Medicine and Molecular Nuclear Medicine, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, PR China
| | - Changxiao Liu
- State Key Laboratory of Drug Delivery Technology and Pharmacokinetics, Tianjin Institute of Pharmaceutical Research, Tianjin, PR China
| | - Sai-Jun Fan
- Tianjin Key Laboratory of Radiation Medicine and Molecular Nuclear Medicine, Institute of Radiation Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, PR China
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Feil C, Staib F, Berger MR, Stein T, Schmidtmann I, Forster A, Schimanski CC. Sniffer dogs can identify lung cancer patients from breath and urine samples. BMC Cancer 2021; 21:917. [PMID: 34388977 PMCID: PMC8362224 DOI: 10.1186/s12885-021-08651-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 07/26/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Lung cancer is the most common oncological cause of death in the Western world. Early diagnosis is critical for successful treatment. However, no effective screening methods exist. A promising approach could be the use of volatile organic compounds as diagnostic biomarkers. To date there are several studies, in which dogs were trained to discriminate cancer samples from controls. In this study we evaluated the abilities of specifically trained dogs to distinguish samples derived from lung cancer patients of various tumor stages from matched healthy controls. METHODS This single center, double-blind clinical trial was approved by the local ethics committee, project no FF20/2016. The dog was conditioned with urine and breath samples of 36 cancer patients and 150 controls; afterwards, further 246 patients were included: 41 lung cancer patients comprising all stages and 205 healthy controls. From each patient two breath and urine samples were collected and shock frozen. Only samples from new subjects were presented to the dog during study phase randomized, double-blinded. This resulted in a specific conditioned reaction pointing to the cancer sample. RESULTS Using a combination of urine and breath samples, the dog correctly predicted 40 out of 41 cancer samples, corresponding to an overall detection rate of cancer samples of 97.6% (95% CI [87.1, 99.9%]). Using urine samples only the dog achieved a detection rate of 87.8% (95% CI [73.8, 95.9%]). With breath samples, the dog correctly identified cancer in 32 of 41 samples, resulting in a detection rate of 78% (95% CI [62.4, 89.4%]). CONCLUSIONS It is known from current literature that breath and urine samples carry VOCs pointing to cancer growth. We conclude that olfactory detection of lung cancer by specifically trained dogs is highly suggestive to be a simple and non-invasive tool to detect lung cancer. To translate this approach into practice further target compounds need to be identified.
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Affiliation(s)
- Charlotte Feil
- 2nd Department of Internal Medicine, Municipal Hospital Darmstadt, Grafenstraße 9, 64283, Darmstadt, Germany
| | - Frank Staib
- 2nd Department of Internal Medicine, Municipal Hospital Darmstadt, Grafenstraße 9, 64283, Darmstadt, Germany
| | - Martin R Berger
- Toxicology and Chemotherapy Unit, German Cancer Research Center, Heidelberg, Germany
| | - Thorsten Stein
- 2nd Department of Internal Medicine, Municipal Hospital Darmstadt, Grafenstraße 9, 64283, Darmstadt, Germany
| | - Irene Schmidtmann
- Institute for Medical Biostatistics, Epidemiology and Informatics, Johannes Gutenberg-University Mainz, Mainz, Germany
| | | | - Carl C Schimanski
- 2nd Department of Internal Medicine, Municipal Hospital Darmstadt, Grafenstraße 9, 64283, Darmstadt, Germany.
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Oh Y, Kwon O, Min SS, Shin YB, Oh MK, Kim M. Multi-Odor Discrimination by Rat Sniffing for Potential Monitoring of Lung Cancer and Diabetes. SENSORS 2021; 21:s21113696. [PMID: 34073351 PMCID: PMC8198436 DOI: 10.3390/s21113696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 05/20/2021] [Accepted: 05/21/2021] [Indexed: 11/16/2022]
Abstract
The discrimination learning of multiple odors, in which multi-odor can be associated with different responses, is important for responding quickly and accurately to changes in the external environment. However, very few studies have been done on multi-odor discrimination by animal sniffing. Herein, we report a novel multi-odor discrimination system by detection rats based on the combination of 2-Choice and Go/No-Go (GNG) tasks into a single paradigm, in which the Go response of GNG was replaced by 2-Choice, for detection of toluene and acetone, which are odor indicators of lung cancer and diabetes, respectively. Three of six trained rats reached performance criterion, in 12 consecutive successful tests within a given set or over 12 sets with a success rate of over 90%. Through a total of 1300 tests, the trained animals (N = 3) showed multi-odor sensing performance with 88% accuracy, 87% sensitivity and 90% specificity. In addition, a dependence of behavior response time on odor concentrations under given concentration conditions was observed, suggesting that the system could be used for quantitative measurements. Furthermore, the animals’ multi-odor sensing performance has lasted for 45 days, indicating long-term stability of the learned multi-odor discrimination. These findings demonstrate that multi-odor discrimination can be achieved by rat sniffing, potentially providing insight into the rapid, accurate and cost-effective multi-odor monitoring in the lung cancer and diabetes.
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Affiliation(s)
- Yunkwang Oh
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB) 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- Department of Chemical and Biological Engineering, Korea University, 145 Anam-ro, Sungbuk-gu, Seoul 02841, Korea
| | - Ohseok Kwon
- Infectious Disease Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB) 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea;
| | - Sun-Seek Min
- Department of Physiology and Biophysics, Eulji University School of Medicine, 77 Gyeryong-ro, Jung-gu, Daejeon 34824, Korea;
| | - Yong-Beom Shin
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB) 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- KRIBB School, Korea University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
| | - Min-Kyu Oh
- Department of Chemical and Biological Engineering, Korea University, 145 Anam-ro, Sungbuk-gu, Seoul 02841, Korea
- Correspondence: (M.-K.O.); (M.K.); Tel.: +82-2-3290-3308 (M.-K.O.); +82-42-879-8447 (M.K.); Fax: +82-2-926-6102 (M.-K.O.); +82-42-879-8594 (M.K.)
| | - Moonil Kim
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB) 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- KRIBB School, Korea University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
- Correspondence: (M.-K.O.); (M.K.); Tel.: +82-2-3290-3308 (M.-K.O.); +82-42-879-8447 (M.K.); Fax: +82-2-926-6102 (M.-K.O.); +82-42-879-8594 (M.K.)
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Oh Y, Kwon OS, Min SS, Shin YB, Oh MK, Kim M. Olfactory Detection of Toluene by Detection Rats for Potential Screening of Lung Cancer. SENSORS 2021; 21:s21092967. [PMID: 33922694 PMCID: PMC8123061 DOI: 10.3390/s21092967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 04/21/2021] [Accepted: 04/22/2021] [Indexed: 12/02/2022]
Abstract
Early detection is critical to successfully eradicating a variety of cancers, so the development of a new cancer primary screening system is essential. Herein, we report an animal nose sensor system for the potential primary screening of lung cancer. To establish this, we developed an odor discrimination training device based on operant conditioning paradigms for detection of toluene, an odor indicator component of lung cancer. The rats (N = 15) were trained to jump onto a floating ledge in response to toluene-spiked breath samples. Twelve rats among 15 trained rats reached performance criterion in 12 consecutive successful tests within a given set, or over 12 sets, with a success rate of over 90%. Through a total of 1934 tests, the trained rats (N = 3) showed excellent performance for toluene detection with 82% accuracy, 83% sensitivity, 81% specificity, 80% positive predictive value (PPV) and 83% negative predictive value (NPV). The animals also acquired considerable performance for odor discrimination even in rigorous tests, validating odor specificity. Since environmental and long-term stability are important factors that can influence the sensing results, the performance of the trained rats was studied under specified temperature (20, 25, and 30 °C) and humidity (30%, 45%, and 60% RH) conditions, and monitored over a period of 45 days. At given conditions of temperature and humidity, the animal sensors showed an average accuracy within a deviation range of ±10%, indicating the excellent environmental stability of the detection rats. Surprisingly, the trained rats did not differ in retention of last odor discrimination when tested 45 days after training, denoting that the rats’ memory for trained odor is still available over a long period of time. When taken together, these results indicate that our odor discrimination training system can be useful for non-invasive breath testing and potential primary screening of lung cancer.
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Affiliation(s)
- Yunkwang Oh
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- Department of Chemical and Biological Engineering, Korea University, 145 Anam-ro, Sungbuk-gu, Seoul 02841, Korea
| | - Oh-Seok Kwon
- Infectious Disease Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea;
| | - Sun-Seek Min
- Department of Physiology and Biophysics, Eulji University School of Medicine, 77 Gyeryong-ro, Jung-gu, Daejeon 34824, Korea;
| | - Yong-Beom Shin
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- KRIBB School, Korea University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
| | - Min-Kyu Oh
- Department of Chemical and Biological Engineering, Korea University, 145 Anam-ro, Sungbuk-gu, Seoul 02841, Korea
- Correspondence: (M.-K.O.); (M.K.); Tel.: +82-2-3290-3308 (M.-K.O.); +82-42-8798447 (M.K.); Fax: +82-2-926-6102 (M.-K.O.); +82-42-879-8594 (M.K.)
| | - Moonil Kim
- Bionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahang-ro, Yuseong-gu, Daejeon 34141, Korea; (Y.O.); (Y.-B.S.)
- KRIBB School, Korea University of Science and Technology (UST), 217 Gajeong-ro, Yuseong-gu, Daejeon 34113, Korea
- Correspondence: (M.-K.O.); (M.K.); Tel.: +82-2-3290-3308 (M.-K.O.); +82-42-8798447 (M.K.); Fax: +82-2-926-6102 (M.-K.O.); +82-42-879-8594 (M.K.)
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9
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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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10
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Cainap C, Pop LA, Balacescu O, Cainap SS. Early diagnosis and screening in lung cancer. Am J Cancer Res 2020; 10:1993-2009. [PMID: 32774997 PMCID: PMC7407360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 06/25/2020] [Indexed: 06/11/2023] Open
Abstract
Lung cancer is the third most diagnosed cancer, but the first cause of cancer-related deaths worldwide. This rather high death rate is due mainly to the fact that most patients are diagnosed with advanced-stage cancer, for which the conventional treatment does not work. The most used screening method for lung cancer is a low-dose CT scan, but it is recommended for specific age populations and it also started different debates on its advantages for lung cancer diagnosis. Over the year, several new techniques have been developed that are less invasive, have lower side effect, and can be implemented at all types of populations. This article aimed to present the advantages and disadvantages of using several methods for lung cancer diagnosis, including analysis of volatile organic compounds, exhaled breath condensate analysis and specific genomic approaches.
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Affiliation(s)
- Calin Cainap
- Department of Oncology, “Iuliu Hatieganu” University of Medicine and PharmacyCluj-Napoca, Romania
- Prof. Dr. Ion Chiricuta Institute of OncologyCluj-Napoca, Romania
| | - Laura A Pop
- Research Center for Functional Genomics, Biomedicine and Translational Medicine, University of Medicine and Pharmacy Iuliu HatieganuCluj-Napoca, Romania
| | - Ovidiu Balacescu
- Department of Functional Genomics and Experimental Pathology, Prof. Dr. Ion Chiricuta Institute of OncologyCluj-Napoca, Romania
| | - Simona S Cainap
- Department of Pediatric Cardiology, Emergency County Hospital for Children, Pediatric Clinic no 2Cluj-Napoca, Romania
- Department of Mother and Child, “Iuliu Hatieganu” University of Medicine and PharmacyCluj-Napoca, Romania
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11
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Wang C, Long Y, Li W, Dai W, Xie S, Liu Y, Zhang Y, Liu M, Tian Y, Li Q, Duan Y. Exploratory study on classification of lung cancer subtypes through a combined K-nearest neighbor classifier in breathomics. Sci Rep 2020; 10:5880. [PMID: 32246031 PMCID: PMC7125212 DOI: 10.1038/s41598-020-62803-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 02/05/2020] [Indexed: 11/10/2022] Open
Abstract
Accurate classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) in lung cancer is critical to physicians’ clinical decision-making. Exhaled breath analysis provides a tremendous potential approach in non-invasive diagnosis of lung cancer but was rarely reported for lung cancer subtypes classification. In this paper, we firstly proposed a combined method, integrating K-nearest neighbor classifier (KNN), borderline2-synthetic minority over-sampling technique (borderlin2-SMOTE), and feature reduction methods, to investigate the ability of exhaled breath to distinguish AC from SCC patients. The classification performance of the proposed method was compared with the results of four classification algorithms under different combinations of borderline2-SMOTE and feature reduction methods. The result indicated that the KNN classifier combining borderline2-SMOTE and feature reduction methods was the most promising method to discriminate AC from SCC patients and obtained the highest mean area under the receiver operating characteristic curve (0.63) and mean geometric mean (58.50) when compared to others classifiers. The result revealed that the combined algorithm could improve the classification performance of lung cancer subtypes in breathomics and suggested that combining non-invasive exhaled breath analysis with multivariate analysis is a promising screening method for informing treatment options and facilitating individualized treatment of lung cancer subtypes patients.
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Affiliation(s)
- Chunyan Wang
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, P.R. China
| | - 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, 610064, P.R. China
| | - Wenwen Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, P.R. China
| | - Wei Dai
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Shaohua Xie
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.,Graduate School, Chengdu Medical College, Chengdu, Sichuan, China
| | - Yuanling Liu
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, P.R. China
| | - Yinchenxi Zhang
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, P.R. China
| | - Mingxin Liu
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Yonghui Tian
- College of Chemistry and Material Science, Northwest University Department of Chemistry and Material Science, Xi'an, 710127, Shanxi Province, P.R. China.
| | - Qiang Li
- Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
| | - Yixiang Duan
- Research Center of Analytical Instrumentation, Key Laboratory of Bio-source and Eco-environment, Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, 610064, P.R. China.
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