Breath mass ion biomarkers of breast cancer.

BACKGROUND: Breath volatile organic compounds (VOCs) contain biomarkers of breast cancer that are detectable with gas chromatography mass spectrometry (GC MS). However, chemical identification of breath VOC biomarkers may be erroneous because spectral matching can misidentify their structure. Breath mass ions detected with GC MS have been proposed as intrinsically robust biomarkers because they can be identified without spectral matching. We investigated whether breath mass ion biomarkers could identify breast cancer. METHODS: We re-analyzed data from a previous study of breath VOCs in 54 women with biopsy-proven breast cancer and in 204 healthy controls. Subjects were randomly assigned to a training set (2/3) and a test set (1/3). Chromatograms were processed with metabolomic analysis software (XCMS in R) in order to generate a table listing retention times with their associated ion masses and intensities, and binned into a series of 5 sec retention time segments. In the training set, mass ions in each time segment were ranked according to their diagnostic accuracy i.e. the area under curve (AUC) of the receiver operating characteristic (ROC) curve. We employed multiple Monte Carlo simulations to select the biomarker mass ions in each time segment that identified breast cancer with greater than random accuracy and combined those with the highest diagnostic accuracy in a predictive algorithm using multivariate weighted digital analysis (WDA). We then employed this algorithm to predict the diagnosis in the test set. RESULTS: The training set WDA algorithm employing 21 mass ion biomarkers identified breast cancer with ROC curve AUC = 0.79. In the test set, this algorithm predicted breast cancer with ROC curve AUC = 0.77. CONCLUSION: Breath mass ions biomarkers accurately identified women with breast cancer and could potentially be used in early diagnosis and treatment monitoring.

Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening.

BACKGROUND: Breath volatile organic compounds (VOCs) have been reported as biomarkers of lung cancer, but it is not known if biomarkers identified in one group can identify disease in a separate independent cohort. Also, it is not known if combining breath biomarkers with chest CT has the potential to improve the sensitivity and specificity of lung cancer screening. METHODS: Model-building phase (unblinded): Breath VOCs were analyzed with gas chromatography mass spectrometry in 82 asymptomatic smokers having screening chest CT, 84 symptomatic high-risk subjects with a tissue diagnosis, 100 without a tissue diagnosis, and 35 healthy subjects. Multiple Monte Carlo simulations identified breath VOC mass ions with greater than random diagnostic accuracy for lung cancer, and these were combined in a multivariate predictive algorithm. Model-testing phase (blinded validation): We analyzed breath VOCs in an independent cohort of similar subjects (n = 70, 51, 75 and 19 respectively). The algorithm predicted discriminant function (DF) values in blinded replicate breath VOC samples analyzed independently at two laboratories (A and B). Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening. RESULTS: Unblinded model-building phase. The algorithm identified lung cancer with sensitivity 74.0%, specificity 70.7% and C-statistic 0.78. Blinded model-testing phase: The algorithm identified lung cancer at Laboratory A with sensitivity 68.0%, specificity 68.4%, C-statistic 0.71; and at Laboratory B with sensitivity 70.1%, specificity 68.0%, C-statistic 0.70, with linear correlation between replicates (r = 0.88). In a projected outcome model, breath biomarkers increased the sensitivity, specificity, and positive and negative predictive values of chest CT for lung cancer when the tests were combined in series or parallel. CONCLUSIONS: Breath VOC mass ion biomarkers identified lung cancer in a separate independent cohort, in a blinded replicated study. Combining breath biomarkers with chest CT could potentially improve the sensitivity and specificity of lung cancer screening. TRIAL REGISTRATION: ClinicalTrials.gov NCT00639067.

Breath biomarkers of whole-body gamma irradiation in the Göttingen minipig.

There is widespread interest in the development of tools to estimate radiation exposures. Exhaled breath provides a novel matrix for assessing biomarkers that could be correlated with exposures. The use of exhaled breath for estimating radiation exposure is warranted, as studies have shown that external exposure to ionizing radiation causes oxidative stress that accelerates lipid peroxidation of polyunsaturated fatty acids, liberating alkanes and alkane metabolites that are excreted in the breath as volatile organic compounds (VOCs). As a proof of principle study, small groups (n = 4) of Göttingen minipigs were whole-body irradiated with gamma rays delivered by a 60Co source at absorbed doses of 0, 0.25, 0.5, 0.75, 1, 1.25, 2, and 4 Gy. Additional groups (n = 4) were treated with lipopolysaccharide (LPS) or granulocyte colony stimulating factor (G-CSF), with and without concurrent 60Co exposure, at an absorbed dose of 1 Gy. Breath and background air VOC samples were collected on days -3, -2, -1, 0 pre-irradiation, then at 0.25, 24, 48, 72, and 168 h post-irradiation. VOCs were analyzed by automated thermal desorption with two-dimensional gas chromatography and time-of-flight mass spectrometry (ATD GCxGC TOF MS). The results show significant changes in 58 breath VOCs post-irradiation, mainly consisting of methylated and other derivatives of alkanes, alkenes, and benzene. Using a multivariate combination of these VOCs, a radiation response function was constructed, which was significantly elevated at 15 min post irradiation and remained elevated throughout the study (to 168 h post irradiation). As a binary test of radiation absorbed doses ≥ 0.25 Gy, the radiation response function distinguished irradiated animals from shams (0 Gy) with 83-84% accuracy. A randomly derived radiation response function was robust: When half of the biomarkers were removed, accuracy was 75%. An optimally derived function with two biomarkers was 82% accurate. As a binary test of radiation absorbed doses ≥ 0.5 Gy, the radiation response function identified irradiated animals with an accuracy of 87% at 15 min post irradiation and 75.5% at 168 h post irradiation. Treatment with LPS and G-CSF did not affect the radiation response function. This proof-of-principle study supports the hypothesis that breath VOCs may be used for estimating radiation exposures. Further studies will be required to validate the sensitivity and specificity of these potential biomarkers.

Rapid point-of-care breath test for biomarkers of breast cancer and abnormal mammograms.

BACKGROUND: Previous studies have reported volatile organic compounds (VOCs) in breath as biomarkers of breast cancer and abnormal mammograms, apparently resulting from increased oxidative stress and cytochrome p450 induction. We evaluated a six-minute point-of-care breath test for VOC biomarkers in women screened for breast cancer at centers in the USA and the Netherlands. METHODS: 244 women had a screening mammogram (93/37 normal/abnormal) or a breast biopsy (cancer/no cancer 35/79). A mobile point-of-care system collected and concentrated breath and air VOCs for analysis with gas chromatography and surface acoustic wave detection. Chromatograms were segmented into a time series of alveolar gradients (breath minus room air). Segmental alveolar gradients were ranked as candidate biomarkers by C-statistic value (area under curve [AUC] of receiver operating characteristic [ROC] curve). Multivariate predictive algorithms were constructed employing significant biomarkers identified with multiple Monte Carlo simulations and cross validated with a leave-one-out (LOO) procedure. RESULTS: Performance of breath biomarker algorithms was determined in three groups: breast cancer on biopsy versus normal screening mammograms (81.8% sensitivity, 70.0% specificity, accuracy 79% (73% on LOO) [C-statistic value], negative predictive value 99.9%); normal versus abnormal screening mammograms (86.5% sensitivity, 66.7% specificity, accuracy 83%, 62% on LOO); and cancer versus no cancer on breast biopsy (75.8% sensitivity, 74.0% specificity, accuracy 78%, 67% on LOO). CONCLUSIONS: A pilot study of a six-minute point-of-care breath test for volatile biomarkers accurately identified women with breast cancer and with abnormal mammograms. Breath testing could potentially reduce the number of needless mammograms without loss of diagnostic sensitivity.

Detection of an extended human volatome with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry.

BACKGROUND: Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOF MS) has been proposed as a powerful new tool for multidimensional analysis of complex chemical mixtures. We investigated GCxGC-TOF MS as a new method for identifying volatile organic compounds (VOCs) in normal human breath. METHODS: Samples of alveolar breath VOCs and ambient room air VOC were collected with a breath collection apparatus (BCA) onto separate sorbent traps from 34 normal healthy volunteers (mean age = 40 yr, SD = 17 yr, male/female = 19/15). VOCs were separated on two serial capillary columns separated by a cryogenic modulator, and detected with TOF MS. The first and second dimension columns were non-polar and polar respectively. RESULTS: BCA collection combined with GC×GC-TOF MS analysis identified approximately 2000 different VOCs in samples of human breath, many of which have not been previously reported. The 50 VOCs with the highest alveolar gradients (abundance in breath minus abundance in ambient room air) mostly comprised benzene derivatives, acetone, methylated derivatives of alkanes, and isoprene. CONCLUSIONS: Collection and analysis of breath VOCs with the BCA-GC×GC-TOF MS system extended the size of the detectable human volatile metabolome, the volatome, by an order of magnitude compared to previous reports employing one-dimensional GC-MS. The size of the human volatome has been under-estimated in the past due to coelution of VOCs in one-dimensional GC analytical systems.

Detection of volatile biomarkers of therapeutic radiation in breath.

Breath testing could provide a rational tool for radiation biodosimetry because radiation causes distinct stress-producing molecular damage, notably an increased production of reactive oxygen species. The resulting oxidative stress accelerates lipid peroxidation of polyunsaturated fatty acids, liberating alkanes and alkane metabolites that are excreted in the breath as volatile organic compounds (VOCs). Breath tests were performed before and after radiation therapy over five days in 31 subjects receiving daily fractionated doses: 180-400 cGy d(-1) standard radiotherapy (n = 26), or 700-1200 cGy d(-1) high-dose stereotactic body radiotherapy (n = 5). Breath VOCs were assayed using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. Multiple Monte Carlo simulations identified approximately 50 VOCs as greater-than-chance biomarkers of radiation on all five days of the study. A consistent subset of 15 VOCs was observed at all time points. A radiation response function was built by combining these biomarkers and the resulting dose-effect curve was significantly elevated at all exposures ⩾1.8 Gy. Cross-validated binary algorithms identified radiation exposures ⩾1.8 Gy with 99% accuracy, and ⩾5 Gy with 78% accuracy. In this proof of principal study of breath VOCs, we built a preliminary radiation response function based on 15 VOCs that appears to identify exposure to localized doses of 1.8 Gy and higher. VOC breath testing could provide a new tool for rapid and non-invasive radiation biodosimetry.

A Dose-Dependent Hematological Evaluation of Whole-Body Gamma-Irradiation in the Göttingen Minipig.

There is a great deal of interest in the establishment of a standardized animal model for the acute radiation syndrome to allow development of diagnostic approaches and countermeasure treatments following radiological terrorist events. Due to physiological, anatomical, and biochemical similarities to humans, the minipig is an attractive large animal model for evaluating countermeasure efficacy. This study was conducted in order to aid in the establishment of the minipig, and the Göttingen minipig in particular, as an animal model for the hematopoietic acute radiation syndrome. Animals were exposed whole-body to Co at doses of 0 (sham control), 0.25, 0.5, 0.75, 1.0, and 2.0 Gy, and hematological parameters followed in time from pre-irradiation to post-irradiation Day 7. Following irradiation, a dose-dependent decrease in total white blood cells was observed, which was determined to be statistically different as compared to control animals at all dose levels above 0.25 Gy at 24 h post-irradiation. Similarly, a dose-dependent reduction in both absolute lymphocyte count and absolute neutrophil count occurred by the earliest time point measured for all exposed animals. A significant decrease in platelets was observed at post-irradiation Day 7 in animals exposed only at the highest (2.0 Gy) level. The platelet-to-lymphocyte ratio generated for exposures ranging from 0.25-2.0 Gy was able to differentiate response between high and low exposure levels even at 7 d post exposure. In conclusion, the present study supports the development of the Göttingen minipig as a suitable large animal model to study radiation-induced hematopoietic syndrome.

Development of bilayer floating tablet of amoxicillin and Aloe vera gel powder for treatment of gastric ulcers.

Usual treatment for Helicobacter pylori-induced peptic ulcer includes a 'triple therapy' consisting of two antibiotics (amoxicillin and clarithromycin) and a proton pump inhibitor (omeprazole). The objective of this project work was defined with a view to retain the drug in stomach for better antiulcer activity and substituting one of the synthetic drugs in this therapy with a herbal alternative. Hence, aim of the present work was to design and develop a bilayer floating tablet of amoxicillin and Aloe vera gel powder for the treatment of peptic ulcer. A. vera gel powder is used for its cytoprotective action. Bilayer floating tablets were prepared by applying direct compression technique. The proportion of sodium bicarbonate and citric acid was adjusted to get the least possible lag time with good matrix integrity and total floating time. Polymer concentration was adjusted to get the maximum release in 8 h. The formulation was developed using hydroxypropyl methyl cellulose (HPMC) K4M and HPMC K100M in a ratio of 85:15 along with 1:4 ratio of effervescent agents was found to give floating lag time of less than 1 min with total floating time of more than 8 h and 97.0% drug release in 8 h. In vivo study in rats meets the requirement of antiulcer activity for bilayer tablet in comparison to single amoxicillin as standard.