Application of an artificial neural network model for selection of potential lung cancer biomarkers

Determination of volatile organic compounds (VOCs) in the exhaled breath samples of lung cancer patients and healthy controls was carried out by SPME-GC/MS (solid phase microextraction- gas chromatography combined with mass spectrometry) analyses. In order to compensate for the volatile exogenous contaminants, ambient air blank samples were also collected and analyzed. We recruited a total of 123 patients with biopsy-confirmed lung cancer and 361 healthy controls to find the potential lung cancer biomarkers. Automatic peak deconvolution and identification were performed using chromatographic data processing software (AMDIS with NIST database). All of the VOCs sample data operation, storage and management were performed using the SQL (structured query language) relational database. The selected eight VOCs could be possible biomarker candidates. In cross-validation on test data sensitivity was 63.5% and specificity 72.4% AUC 0.65. The low performance of the model has been mainly due to overfitting and the exogenous VOCs that exist in breath. The dedicated software implementing a multilayer neural network using a genetic algorithm for training was built. Further work is needed to confirm the performance of the created experimental model.

[1]  M. Zeelenberg,et al.  Data analysis 4 , 2016 .

[2]  Begoña Garcia-Zapirain,et al.  EEG artifact removal—state-of-the-art and guidelines , 2015, Journal of neural engineering.

[3]  A Smolinska,et al.  Current breathomics—a review on data pre-processing techniques and machine learning in metabolomics breath analysis , 2014, Journal of breath research.

[4]  Yoshihiro Saito,et al.  Double-bed-type extraction needle packed with activated-carbon-based sorbents for very volatile organic compounds. , 2014, Journal of pharmaceutical and biomedical analysis.

[5]  Bogusław Buszewski,et al.  Detection of volatile organic compounds as biomarkers in breath analysis by different analytical techniques. , 2013, Bioanalysis.

[6]  Jan Baumbach,et al.  Peak Detection Method Evaluation for Ion Mobility Spectrometry by Using Machine Learning Approaches , 2013, Metabolites.

[7]  A. Dzien,et al.  Dependence of exhaled breath composition on exogenous factors, smoking habits and exposure to air pollutants , 2012, Journal of breath research.

[8]  F. V. van Schooten,et al.  The versatile use of exhaled volatile organic compounds in human health and disease , 2012, Journal of breath research.

[9]  Ki-Hyun Kim,et al.  A review of breath analysis for diagnosis of human health , 2012 .

[10]  Sabine Kischkel,et al.  Needle trap micro-extraction for VOC analysis: effects of packing materials and desorption parameters. , 2012, Journal of chromatography. A.

[11]  B. Buszewski,et al.  The application of statistical methods using VOCs to identify patients with lung cancer , 2011, Journal of breath research.

[12]  H. Haick,et al.  Diagnosis of head-and-neck cancer from exhaled breath , 2011, British Journal of Cancer.

[13]  Sven Rahmann,et al.  Differentiation of chronic obstructive pulmonary disease (COPD) including lung cancer from healthy control group by breath analysis using ion mobility spectrometry , 2010 .

[14]  Massimo Corradi,et al.  Determination of aldehydes in exhaled breath of patients with lung cancer by means of on-fiber-derivatisation SPME-GC/MS. , 2010, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[15]  Ralf Zimmermann,et al.  Automated needle trap heart-cut GC/MS and needle trap comprehensive two-dimensional GC/TOF-MS for breath gas analysis in the clinical environment. , 2010, Analytical chemistry.

[16]  G. Sun,et al.  Quantitative breath analysis of volatile organic compounds of lung cancer patients. , 2010, Lung cancer.

[17]  Anton Amann,et al.  TD-GC-MS Analysis of Volatile Metabolites of Human Lung Cancer and Normal Cells In vitro , 2010, Cancer Epidemiology, Biomarkers & Prevention.

[18]  M. Fiegl,et al.  Noninvasive detection of lung cancer by analysis of exhaled breath , 2009, BMC Cancer.

[19]  W. Miekisch,et al.  Multibed needle trap devices for on site sampling and preconcentration of volatile breath biomarkers. , 2009, Analytical chemistry.

[20]  K. Unterkofler,et al.  Breath acetone—aspects of normal physiology related to age and gender as determined in a PTR-MS study , 2009, Journal of breath research.

[21]  B. Buszewski,et al.  Analysis of exhaled breath from smokers, passive smokers and non-smokers by solid-phase microextraction gas chromatography/mass spectrometry. , 2009, Biomedical chromatography : BMC.

[22]  Magdalena Ligor,et al.  Determination of volatile organic compounds in exhaled breath of patients with lung cancer using solid phase microextraction and gas chromatography mass spectrometry , 2009, Clinical chemistry and laboratory medicine.

[23]  A. Dzien,et al.  The analysis of healthy volunteers' exhaled breath by the use of solid-phase microextraction and GC-MS , 2008, Journal of breath research.

[24]  J. Austin,et al.  Detection of lung cancer using weighted digital analysis of breath biomarkers. , 2008, Clinica chimica acta; international journal of clinical chemistry.

[25]  K. Unterkofler,et al.  Breath isoprene – aspects of normal physiology related to age, gender and cholesterol profile as determined in a proton transfer reaction mass spectrometry study , 2008, Clinical chemistry and laboratory medicine.

[26]  Bogusław Buszewski,et al.  Human exhaled air analytics: biomarkers of diseases. , 2007, Biomedical chromatography : BMC.

[27]  Wolfram Miekisch,et al.  From highly sophisticated analytical techniques to life-saving diagnostics: Technical developments in breath analysis , 2006 .

[28]  R. Sacks,et al.  Development of a multibed sorption trap, comprehensive two-dimensional gas chromatography, and time-of-flight mass spectrometry system for the analysis of volatile organic compounds in human breath. , 2006, Analytical chemistry.

[29]  W. Miekisch,et al.  Diagnostic potential of breath analysis--focus on volatile organic compounds. , 2004, Clinica chimica acta; international journal of clinical chemistry.

[30]  M. Phillips,et al.  Volatile Markers of Breast Cancer in the Breath , 2003, The breast journal.

[31]  M. Phillips,et al.  Effect of age on the breath methylated alkane contour, a display of apparent new markers of oxidative stress. , 2000, The Journal of laboratory and clinical medicine.

[32]  M. Phillips,et al.  Variation in volatile organic compounds in the breath of normal humans. , 1999, Journal of chromatography. B, Biomedical sciences and applications.

[33]  R. Cataneo,et al.  Volatile organic compounds in breath as markers of lung cancer: a cross-sectional study , 1999, The Lancet.

[34]  Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography , 1972, Proceedings of the National Academy of Sciences.

[35]  A. B. Robinson,et al.  Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. , 1971, Proceedings of the National Academy of Sciences of the United States of America.