A study of 9 common breath VOCs in 504 healthy subjects using PTR-TOF-MS.

INTRODUCTION: This study employs Proton-Transfer-Reaction Mass Spectrometry (PTR-MS) to analyze exhaled breath profiles of 504 healthy adults, focusing on nine common volatile organic compounds (VOCs): acetone, acetaldehyde, acetonitrile, ethanol, isoprene, methanol, propanol, phenol, and toluene. PTR-MS offers real-time VOC measurement, crucial for understanding breath biomarkers and their applications in health assessment. OBJECTIVES: The study aims to investigate how demographic factors-gender, age, and smoking history-affect VOC concentrations in exhaled breath. The objective is to enhance our understanding of breath biomarkers and their potential for health monitoring and clinical diagnosis. METHODS: Exhaled breath samples were collected using PTR-MS, measuring concentrations of nine VOCs. The data were analyzed to discern distribution patterns across demographic groups. RESULTS: Males showed higher average VOC levels for certain compounds. Propanol and methanol concentrations significantly increased with age. Smoking history influenced VOC levels, with differences among non-smokers, current smokers, and ex-smokers. CONCLUSION: This research provides valuable insights into demographic influences on exhaled VOC profiles, emphasizing the potential of breath analysis for health assessment. PTR-MS's real-time measurement capabilities are crucial for capturing dynamic VOC changes, offering advantages over conventional methods. These findings lay a foundation for advancements in non-invasive disease detection, highlighting the importance of considering demographics in breath biomarker research.

Metabolic signatures of four major histological types of lung cancer cells.

INTRODUCTION: Histologically lung cancer is classified into four major types: adenocarcinoma (Ad), squamous cell carcinoma (SqCC), large cell carcinoma (LCC), and small cell lung cancer (SCLC). Presently, our understanding of cellular metabolism among them is still not clear. OBJECTIVES: The goal of this study was to assess the cellular metabolic profiles across these four types of lung cancer using an untargeted metabolomics approach. METHODS: Six lung cancer cell lines, viz., Ad (A549 and HCC827), SqCC (NCl-H226 and NCl-H520), LCC (NCl-H460), and SCLC (NCl-H526), were analyzed using liquid chromatography quadrupole time-of-flight mass spectrometry, with normal human small airway epithelial cells (SAEC) as the control group. The principal component analysis (PCA) was performed to identify the metabolic signatures that had characteristic alterations in each histological type. Further, a metabolite set enrichment analysis was performed for pathway analysis. RESULTS: Compared to the SAEC, 31, 27, 34, 34, 32, and 39 differential metabolites mainly in relation to nucleotides, amino acid, and fatty acid metabolism were identified in A549, HCC827, NCl-H226, NCl-H520, NCl-H460, and NCl-H526 cells, respectively. The metabolic signatures allowed the six cancerous cell lines to be clearly separated in a PCA score plot. CONCLUSION: The metabolic signatures are unique to each histological type, and appeared to be related to their cell-of-origin and mutation status. The changes are useful for assessing the metabolic characteristics of lung cancer, and offer potential for the establishment of novel diagnostic tools for different origin and oncogenic mutation of lung cancer.

Breath Analysis for Lung Cancer Early Detection-A Clinical Study.

This clinical study presents a comprehensive investigation into the utility of breath analysis as a non-invasive method for the early detection of lung cancer. The study enrolled 14 lung cancer patients, 14 non-lung cancer controls with diverse medical conditions, and 3 tuberculosis (TB) patients for biomarker discovery. Matching criteria including age, gender, smoking history, and comorbidities were strictly followed to ensure reliable comparisons. A systematic breath sampling protocol utilizing a BIO-VOC sampler was employed, followed by VOC analysis using Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). The resulting VOC profiles were subjected to stringent statistical analysis, including Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA), Kruskal-Wallis test, and Receiver Operating Characteristic (ROC) analysis. Notably, 13 VOCs exhibited statistically significant differences between lung cancer patients and controls. The combination of eight VOCs (hexanal, heptanal, octanal, benzaldehyde, undecane, phenylacetaldehyde, decanal, and benzoic acid) demonstrated substantial discriminatory power with an area under the curve (AUC) of 0.85, a sensitivity of 82%, and a specificity of 76% in the discovery set. Validation in an independent cohort yielded an AUC of 0.78, a sensitivity of 78%, and a specificity of 64%. Further analysis revealed that elevated aldehyde levels in lung cancer patients' breath could be attributed to overactivated Alcohol Dehydrogenase (ADH) pathways in cancerous tissues. Addressing methodological challenges, this study employed a matching of physiological and pathological confounders, controlled room air samples, and standardized breath sampling techniques. Despite the limitations, this study's findings emphasize the potential of breath analysis as a diagnostic tool for lung cancer and suggest its utility in differentiating tuberculosis from lung cancer. However, further research and validation are warranted for the translation of these findings into clinical practice.

Critical Review of Volatile Organic Compound Analysis in Breath and In Vitro Cell Culture for Detection of Lung Cancer.

Breath analysis is a promising technique for lung cancer screening. Despite the rapid development of breathomics in the last four decades, no consistent, robust, and validated volatile organic compound (VOC) signature for lung cancer has been identified. This review summarizes the identified VOC biomarkers from both exhaled breath analysis and in vitro cultured lung cell lines. Both clinical and in vitro studies have produced inconsistent, and even contradictory, results. Methodological issues that lead to these inconsistencies are reviewed and discussed in detail. Recommendations on addressing specific issues for more accurate biomarker studies have also been made.

Detection of Lung Cancer: Concomitant Volatile Organic Compounds and Metabolomic Profiling of Six Cancer Cell Lines of Different Histological Origins.

In recent years, there has been an extensive search for a non-invasive screening technique for early detection of lung cancer. Volatile organic compound (VOC) analysis in exhaled breath is one such promising technique. This approach is based on the fact that tumor growth is accompanied by unique oncogenesis, leading to detectable changes in VOC emitting profile. Here, we conducted a comprehensive profiling of VOCs and metabolites from six different lung cancer cell lines and one normal lung cell line using mass spectrometry. The concomitant VOCs and metabolite profiling allowed significant discrimination between lung cancer and normal cell, nonsmall cell lung cancer (NSCLC) and small cell lung cancer (SCLC), as well as between different subtypes of NSCLC. It was found that a combination of benzaldehyde, 2-ethylhexanol, and 2,4-decadien-1-ol could serve as potential volatile biomarkers for lung cancer. A detailed correlation between nonvolatile metabolites and VOCs can demonstrate possible biochemical pathways for VOC production by the cancer cells, thus enabling further optimization of VOCs as biomarkers. These findings could eventually lead to noninvasive early detection of lung cancer and differential diagnosis of lung cancer subtypes, thus revolutionizing lung cancer treatment.