Perfiles metabolómicos de sujetos sanos y con cáncer de pulmón. Influencia de la carga tabáquica / The metabolomics of healthy subjects and those with lung cancer: the influence of smoking

RESUMEN

INTRODUCCIÓN: la aplicación de técnicas metabolómicas presenta un gran potencial para la búsqueda de posibles biomarcadores de diagnóstico precoz en numerosas enfermedades. El empleo de procedimientos metabolómicos basados en espectrometría de masas permite estudiar las modificaciones metabólicas subyacentes al cáncer de pulmón (CP) y la influencia de la carga tabáquica (CT), medida en paquetes-año, en los correspondientes perfiles metabólicos. METODOLOGÍA: se estudió el suero de 9 controles sanos (no fumadores), 6 enfermos de CP con carga tabáquica moderada (CT 70). Se analizaron los metabolitos mediante técnicas de espectrometría de masas de alta resolución (DI-ESI-QTOFMS). Los perfiles metabólicos obtenidos se sometieron a análisis estadístico multivariante (PCA, PLS-DA). RESULTADOS: los tres grupos de estudio mostraron perfiles metabólicos claramente diferentes, lo que permitió identificar algunos posibles biomarcadores. Los niveles de glutatión se encontraron disminuidos en muestras de suero de pacientes con CP, mientras que se incrementó el contenido de distintos fosfolípidos de membrana (PL). La mayoría de estas anormalidades metabólicas se acentuó en pacientes con una CT elevada. CONCLUSIONES: el análisis metabolómico en muestras de suero permitió diferenciar claramente entre sujetos sanos y pacientes con CP. Así mismo, se identificaron posibles biomarcadores para el diagnóstico del CP (relacionados con rutas previamente conocidas en el proceso del cáncer). Además, estas alteraciones se vieron influenciadas por la carga tabáquica, confirmando la importancia del tabaquismo como factor de riesgo primario en el desarrollo del CP

ABSTRACT

By using high resolution metabolomics, we obtained the metabolomic profiles for patients who smoked and had lung cancer (LC) and a healthy, non-smoker control (HC) group; we assessed the influence of smoking on said profiles. The results show a clear discrimination between the metabolomic profiles of both groups studied; the metabolites causing said difference could be determined. Moreover, differences were encountered between the metabolomic profiles of heavy smokers with lung cancer compared to moderate smokers. INTRODUCTION: theapplicationof metabolomic techniques offers extensive potential to search for possible biomarkers in the early detection of several diseases. Using metabolomic procedures based on mass spectrometry allow us to study underlying metabolic changes in lung cancer and the influence of smoking, measured as packets/year, in the corresponding metabolic profiles. METHOD: the serum from 9 healthy control subjects (nonsmokers) was studied, as well as that of 6 patients with lung cancer who were moderate smokers (CT 70). The metabolites were analyzed using high resolution mass spectrometer techniques (DI-ESI-QTOF-MS). The metabolic profiles obtained were subject to multivariate statistical analysis (PCA, PLS-DA). RESULTS: the three groups studied showed clearly differentiated metabolic profiles, which facilitated the identification of certain biomarkers. Glutathione levels were found to be decreased in the sample from patients with lung cancer, while the content of various membrane phospholipids increased. Most of these metabolic abnormalities were heightened in patients who were heavy smokers. CONCLUSIONS: the metabolomics analysis in serum samples clearly differentiated healthy subjects from patients with lung cancer. Also, possible biomarkers were identified to diagnose lung cancer (linked to previously known routes in the cancer process. Moreover, these alterations were influenced by the amount smoked, thus confirming the importance of smoking as a primary risk factor in developing lung cáncer