Advanced strategy for cancer detection based on volatile organic compounds in breath
Abstract The analysis of volatile organic compounds (VOCs) in exhaled breath has emerged as a promising non-invasive approach for cancer diagnosis, offering advantages in speed, safety, cost-effectiveness, and real-time monitoring. Two primary methodologies are employed for VOCs detection: mass spec...
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| Language: | English |
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BMC
2025-07-01
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| Series: | Journal of Nanobiotechnology |
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| Online Access: | https://doi.org/10.1186/s12951-025-03526-4 |
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| author | Ziqi Jia Yiwen Jiang Tongxuan Shang Heng Cao Jiayi Li Lin Cong Pengming Pu Hengyi Xu Yuchen Liu Yansong Huang Dongxu Ma Jiang Wu Ruijie Zhou Xiang Wang Chang bao Han Jiaqi Liu |
| author_facet | Ziqi Jia Yiwen Jiang Tongxuan Shang Heng Cao Jiayi Li Lin Cong Pengming Pu Hengyi Xu Yuchen Liu Yansong Huang Dongxu Ma Jiang Wu Ruijie Zhou Xiang Wang Chang bao Han Jiaqi Liu |
| author_sort | Ziqi Jia |
| collection | DOAJ |
| description | Abstract The analysis of volatile organic compounds (VOCs) in exhaled breath has emerged as a promising non-invasive approach for cancer diagnosis, offering advantages in speed, safety, cost-effectiveness, and real-time monitoring. Two primary methodologies are employed for VOCs detection: mass spectrometry (MS)-based techniques, which provide high-precision identification and quantification of individual compounds, and sensor-based pattern recognition methods, which detect disease-specific VOC signatures. Despite their diagnostic potential, inconsistencies in accuracy highlight the need for a comprehensive evaluation of these techniques. This review synthesizes evidence from clinical studies through meta-analysis to assess the diagnostic performance of MS and sensor-based approaches. Furthermore, we examine variations in VOC profiles across cancer types, which may influence diagnostic precision, and discuss key biomarkers, analytical methodologies, current challenges, and future directions in VOCs-based diagnostics. Meta-analysis revealed a high diagnostic accuracy, with a mean area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI 0.91-0.96), sensitivity of 89% (95% CI 87%-90%), and specificity of 87% (95% CI 84%-88%). Notably, no significant difference was observed between MS and sensor-based methods (AUC: 0.91 vs. 0.93, p = 0.286), supporting the potential of sensor technologies for clinical application. Subgroup analysis further indicated no statistical difference in AUCs between heterogeneous and homogeneous sensor groups, suggesting that simplified detection systems may be feasible. Despite these promising results, standardization of protocols and methodological consistency remain critical challenges. Future efforts should focus on large-scale, well-designed clinical trials to validate and optimize VOCs-based breath tests, enhancing their diagnostic reliability and translational potential in oncology. Graphical Abstract |
| format | Article |
| id | doaj-art-4087e32054c9486fb41696ab0f2d0956 |
| institution | DOAJ |
| issn | 1477-3155 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Nanobiotechnology |
| spelling | doaj-art-4087e32054c9486fb41696ab0f2d09562025-08-20T03:04:17ZengBMCJournal of Nanobiotechnology1477-31552025-07-0123112610.1186/s12951-025-03526-4Advanced strategy for cancer detection based on volatile organic compounds in breathZiqi Jia0Yiwen Jiang1Tongxuan Shang2Heng Cao3Jiayi Li4Lin Cong5Pengming Pu6Hengyi Xu7Yuchen Liu8Yansong Huang9Dongxu Ma10Jiang Wu11Ruijie Zhou12Xiang Wang13Chang bao Han14Jiaqi Liu15Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegePeking Union Medical College and Chinese Academy of Medical SciencesDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegePeking Union Medical College and Chinese Academy of Medical SciencesPeking Union Medical College and Chinese Academy of Medical SciencesDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeKey Laboratory of Advanced Functional Materials, Ministry of Education, College of Materials Science and Engineering, Beijing University of TechnologyDepartment of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeAbstract The analysis of volatile organic compounds (VOCs) in exhaled breath has emerged as a promising non-invasive approach for cancer diagnosis, offering advantages in speed, safety, cost-effectiveness, and real-time monitoring. Two primary methodologies are employed for VOCs detection: mass spectrometry (MS)-based techniques, which provide high-precision identification and quantification of individual compounds, and sensor-based pattern recognition methods, which detect disease-specific VOC signatures. Despite their diagnostic potential, inconsistencies in accuracy highlight the need for a comprehensive evaluation of these techniques. This review synthesizes evidence from clinical studies through meta-analysis to assess the diagnostic performance of MS and sensor-based approaches. Furthermore, we examine variations in VOC profiles across cancer types, which may influence diagnostic precision, and discuss key biomarkers, analytical methodologies, current challenges, and future directions in VOCs-based diagnostics. Meta-analysis revealed a high diagnostic accuracy, with a mean area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI 0.91-0.96), sensitivity of 89% (95% CI 87%-90%), and specificity of 87% (95% CI 84%-88%). Notably, no significant difference was observed between MS and sensor-based methods (AUC: 0.91 vs. 0.93, p = 0.286), supporting the potential of sensor technologies for clinical application. Subgroup analysis further indicated no statistical difference in AUCs between heterogeneous and homogeneous sensor groups, suggesting that simplified detection systems may be feasible. Despite these promising results, standardization of protocols and methodological consistency remain critical challenges. Future efforts should focus on large-scale, well-designed clinical trials to validate and optimize VOCs-based breath tests, enhancing their diagnostic reliability and translational potential in oncology. Graphical Abstracthttps://doi.org/10.1186/s12951-025-03526-4Cancer diagnosticsVolatile organic compoundBreath analysisNon-invasive biomarkerMass spectrometrySensor |
| spellingShingle | Ziqi Jia Yiwen Jiang Tongxuan Shang Heng Cao Jiayi Li Lin Cong Pengming Pu Hengyi Xu Yuchen Liu Yansong Huang Dongxu Ma Jiang Wu Ruijie Zhou Xiang Wang Chang bao Han Jiaqi Liu Advanced strategy for cancer detection based on volatile organic compounds in breath Journal of Nanobiotechnology Cancer diagnostics Volatile organic compound Breath analysis Non-invasive biomarker Mass spectrometry Sensor |
| title | Advanced strategy for cancer detection based on volatile organic compounds in breath |
| title_full | Advanced strategy for cancer detection based on volatile organic compounds in breath |
| title_fullStr | Advanced strategy for cancer detection based on volatile organic compounds in breath |
| title_full_unstemmed | Advanced strategy for cancer detection based on volatile organic compounds in breath |
| title_short | Advanced strategy for cancer detection based on volatile organic compounds in breath |
| title_sort | advanced strategy for cancer detection based on volatile organic compounds in breath |
| topic | Cancer diagnostics Volatile organic compound Breath analysis Non-invasive biomarker Mass spectrometry Sensor |
| url | https://doi.org/10.1186/s12951-025-03526-4 |
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