Michael Phillips1, Thomas L Bauer, Harvey I Pass. 1. Menssana Research Inc, 1 Horizon Road, Suite 1415, Fort Lee, NJ 07024, United States of America. Department of Medicine, New York Medical College, Valhalla, NY, United States of America.
Abstract
BACKGROUND: previous studies have reported volatile organic compounds (VOCs) in the breath as apparent biomarkers of lung cancer. We tested the hypothesis that a robust breath VOC biomarker of lung cancer should also predict pulmonary nodules in chest CT images. METHODS: Biomarker discovery study (unblinded): 301 subjects were screened for lung cancer with low dose chest CT (LDCT), and donated duplicate samples of alveolar breath for analysis with gas chromatography mass spectrometry (GC MS). Monte Carlo analysis of breath chromatograms revealed a mass ion as a biomarker that identified biopsy-proven lung cancer as well as suspicious pulmonary nodules on LDCT. The biomarker was termed Mass Abnormalities in Gaseous Ions with Imaging Correlates (MAGIIC). The chemical structure of MAGIIC was tentatively identified from the NIST library of mass spectra; the best-fit compounds included C4 and C5 alkane derivatives that were consistent with metabolic products of oxidative stress. Blinded validation of MAGIIC: the abundance of the MAGIIC biomarker was determined in a different group of 161 subjects undergoing screening with LDCT. They donated duplicate alveolar breath VOC samples that were analyzed at two independent laboratories. The study was blinded and monitored with Good Clinical Practice. The abundance of MAGIIC in breath predicted biopsy-proven lung cancer with 84% accuracy, sensitivity = 75.4% and specificity = 85.0%. MAGIIC also predicted pulmonary nodules in LDCT with 80.5% accuracy, sensitivity = 80.1% and specificity = 75.0%. Breath MAGIIC abundance was not significantly affected by tobacco smoking history. CONCLUSIONS: in a blinded study, breath VOC MAGIIC accurately predicted lung cancer confirmed on a tissue biopsy, as well as suspicious pulmonary nodules observed on LDCT. MAGIIC may have been a product of oxidative stress and it could potentially be employed as an ancillary to LDCT to predict the likelihood that a pulmonary nodule is malignant.
BACKGROUND: previous studies have reported volatile organic compounds (VOCs) in the breath as apparent biomarkers of lung cancer. We tested the hypothesis that a robust breath VOC biomarker of lung cancer should also predict pulmonary nodules in chest CT images. METHODS: Biomarker discovery study (unblinded): 301 subjects were screened for lung cancer with low dose chest CT (LDCT), and donated duplicate samples of alveolar breath for analysis with gas chromatography mass spectrometry (GC MS). Monte Carlo analysis of breath chromatograms revealed a mass ion as a biomarker that identified biopsy-proven lung cancer as well as suspicious pulmonary nodules on LDCT. The biomarker was termed Mass Abnormalities in Gaseous Ions with Imaging Correlates (MAGIIC). The chemical structure of MAGIIC was tentatively identified from the NIST library of mass spectra; the best-fit compounds included C4 and C5 alkane derivatives that were consistent with metabolic products of oxidative stress. Blinded validation of MAGIIC: the abundance of the MAGIIC biomarker was determined in a different group of 161 subjects undergoing screening with LDCT. They donated duplicate alveolar breath VOC samples that were analyzed at two independent laboratories. The study was blinded and monitored with Good Clinical Practice. The abundance of MAGIIC in breath predicted biopsy-proven lung cancer with 84% accuracy, sensitivity = 75.4% and specificity = 85.0%. MAGIIC also predicted pulmonary nodules in LDCT with 80.5% accuracy, sensitivity = 80.1% and specificity = 75.0%. Breath MAGIIC abundance was not significantly affected by tobacco smoking history. CONCLUSIONS: in a blinded study, breath VOCMAGIIC accurately predicted lung cancer confirmed on a tissue biopsy, as well as suspicious pulmonary nodules observed on LDCT. MAGIIC may have been a product of oxidative stress and it could potentially be employed as an ancillary to LDCT to predict the likelihood that a pulmonary nodule is malignant.