Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer
- PMID: 22071780
- PMCID: PMC3241851
- DOI: 10.1097/JTO.0b013e318233d80f
Exhaled breath analysis with a colorimetric sensor array for the identification and characterization of lung cancer
Abstract
Introduction: The pattern of exhaled breath volatile organic compounds represents a metabolic biosignature with the potential to identify and characterize lung cancer. Breath biosignature-based classification of homogeneous subgroups of lung cancer may be more accurate than a global breath signature. Combining breath biosignatures with clinical risk factors may improve the accuracy of the signature.
Objectives: To develop an exhaled breath biosignature of lung cancer using a colorimetric sensor array and to determine the accuracy of breath biosignatures of lung cancer characteristics with and without the inclusion of clinical risk factors.
Methods: The exhaled breath of 229 study subjects, 92 with lung cancer and 137 controls, was drawn across a colorimetric sensor array. Logistic prediction models were developed and statistically validated based on the color changes of the sensor. Age, sex, smoking history, and chronic obstructive pulmonary disease were incorporated in the prediction models.
Results: The validated prediction model of the combined breath and clinical biosignature was moderately accurate at distinguishing lung cancer from control subjects (C-statistic 0.811). The accuracy improved when the model focused on only one histology (C-statistic 0.825-0.890). Individuals with different histologies could be accurately distinguished from one another (C-statistic 0.864 for adenocarcinoma versus squamous cell carcinoma). Moderate accuracies were noted for validated breath biosignatures of stage and survival (C-statistic 0.785 and 0.693, respectively).
Conclusions: A colorimetric sensor array is capable of identifying exhaled breath biosignatures of lung cancer. The accuracy of breath biosignatures can be optimized by evaluating specific histologies and incorporating clinical risk factors.
Figures
![Figure 1](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/3241851/bin/nihms326898f1.gif)
![Figure 2](https://www.ncbi.nlm.nih.gov/pmc/articles/instance/3241851/bin/nihms326898f2.gif)
Similar articles
-
Progress in the development of volatile exhaled breath signatures of lung cancer.Ann Am Thorac Soc. 2015 May;12(5):752-7. doi: 10.1513/AnnalsATS.201411-540OC. Ann Am Thorac Soc. 2015. PMID: 25965541 Free PMC article.
-
Detecting cancer by breath volatile organic compound analysis: a review of array-based sensors.J Breath Res. 2014 Jun;8(2):027112. doi: 10.1088/1752-7155/8/2/027112. Epub 2014 May 27. J Breath Res. 2014. PMID: 24862241 Review.
-
Non-invasive breath analysis of pulmonary nodules.J Thorac Oncol. 2012 Oct;7(10):1528-33. doi: 10.1097/JTO.0b013e3182637d5f. J Thorac Oncol. 2012. PMID: 22929969 Free PMC article.
-
Diagnosis of lung cancer by the analysis of exhaled breath with a colorimetric sensor array.Thorax. 2007 Jul;62(7):565-8. doi: 10.1136/thx.2006.072892. Epub 2007 Feb 27. Thorax. 2007. PMID: 17327260 Free PMC article.
-
Serum tumour markers in lung cancer.Scand J Clin Lab Invest Suppl. 1991;206:93-101. doi: 10.3109/00365519109107730. Scand J Clin Lab Invest Suppl. 1991. PMID: 1658919 Review. No abstract available.
Cited by
-
Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies.Biosensors (Basel). 2024 Feb 6;14(2):90. doi: 10.3390/bios14020090. Biosensors (Basel). 2024. PMID: 38392009 Free PMC article. Review.
-
Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends.Biomedicines. 2023 Nov 11;11(11):3029. doi: 10.3390/biomedicines11113029. Biomedicines. 2023. PMID: 38002028 Free PMC article. Review.
-
The Versatility and Diagnostic Potential of VOC Profiling for Noninfectious Diseases.BME Front. 2023 Jan 10;4:0002. doi: 10.34133/bmef.0002. eCollection 2023. BME Front. 2023. PMID: 37849665 Free PMC article.
-
Data-driven design of a multiplexed, peptide-sensitized transistor to detect breath VOC markers of COVID-19.Biosens Bioelectron. 2023 Jun 1;229:115237. doi: 10.1016/j.bios.2023.115237. Epub 2023 Mar 20. Biosens Bioelectron. 2023. PMID: 36965380 Free PMC article.
-
Non-Invasive Lung Cancer Diagnostics through Metabolites in Exhaled Breath: Influence of the Disease Variability and Comorbidities.Metabolites. 2023 Jan 30;13(2):203. doi: 10.3390/metabo13020203. Metabolites. 2023. PMID: 36837822 Free PMC article.
References
-
- Mazzone PJ. Give me a sign, any sign. Thorax. 2009;64:737–738. - PubMed
-
- Goto I, Yoneda S, Yamamoto M, et al. Prognostic significance of germ line polymorphisms of the CYP1A1 and glutathione S-transferase genes in patients with non-small cell lung cancer. Cancer Res. 1996;56:3725–3730. - PubMed
-
- Ho JC, Zheng S, Comhair SAA, et al. Differential expression of manganese superoxide dismutase and catalase in lung cancer. Cancer Res. 2001;61:8578–8585. - PubMed
-
- Patel M, Lu L, Zander DS, et al. ALDH1A1 and ALDH3A1 expression in lung cancers: Correlation with histologic type and potential precursors. Lung Cancer. 2008;59:340–349. - PubMed
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical