Metabolomic analysis based on 1H-nuclear magnetic resonance spectroscopy metabolic profiles in tuberculous, malignant and transudative pleural effusion

Abstract

Abstract. Pleural effusion is a common clinical manifestation with various causes. Current diagnostic and therapeutic methods have exhibited numerous limitations. By involving the analysis of dynamic changes in low molecular weight catabolites, metabolomics has been widely applied in various types of disease and have provided platforms to distinguish many novel biomarkers. However, to the best of our knowledge, there are few studies regarding the metabolic profiling for pleural effusion. In the current study, 58 pleural effusion samples were collected, among which 20 were malignant pleural effusions, 20 were tuberculous pleural effusions and 18 were transudative pleural effusions. The small molecule metabolite spectrums were obtained by adopting 1 H nuclear magnetic resonance technology, and pattern-recognition multi-variable statistical analysis was used to screen out different metabolites. One-way analysis of variance, and Student-Newman-Keuls and the Kruskal-Wallis test were adopted for statistical analysis. Over 400 metabolites were identified in the untargeted metabolomic analysis and 26 metabolites were identified as significantly different among tuberculous, malignant and transudative pleural effusions. These metabolites were predominantly involved in the metabolic pathways of amino acids metabolism, glycometabolism and lipid metabolism. Statistical analysis revealed that eight metabolites contributed to the distinction between the three groups: Tuberculous, malignant and transudative pleural effusion. In the current study, the feasibility of identifying small molecule biochemical profiles in different types of pleural effusion were investigated reveal novel biological insights into the underlying mechanisms. The results provide specific insights into the biology of tubercular, malignant and transudative pleural effusion and may offer novel strategies for the diagnosis and therapy of associated diseases, including tuberculosis, advanced lung cancer and congestive heart failure.

Metabolomics in cancer research and emerging applications in clinical oncology

“…However, many other types of biofluids have also been used, including sputum, bronchial washings, saliva, sweat, tears, cerebrospinal fluid, pleural or ascitic effusions, fecal water, bile, breast milk, amniotic fluid, seminal plasma, expressed prostatic secretions, and others. 270,[286][287][288][289][290] Regardless of the material used, the methods of collection, storage, and processing must be appropriately selected for the desired analysis. Many chemical species are labile or undergo rapid chemical modification by molecular oxygen or metabolic enzymes.…”

Tuberculosis: advances and challenges in development of new diagnostics and biomarkers

“…metabolites that are involved in the glucose, lipid and amino acid metabolism pathways. 48 Although findings from these studies continue to provide useful information about our understanding of the host metabolic response to infection with MTB, and ultimately help in shedding more light on the intracellular survival of MTB, 49 the potential of these approaches as tuberculosis diagnostics still has to be confirmed. Validated signatures will also have to be translated from the current mass-spectrometry platforms into tools that are appropriate for resourceconstrained, high burden settings.…”

Machine learning applied to near-infrared spectra for clinical pleural effusion classification

“…However, to the best of our knowledge, our study is the first one that applyed NIRS to the classification of pleural effusion. MPE usually indicates advanced development in cancer, which contributes to a unique cancerous microenvironment that is significantly different from the surrounding healthy tissues, featured with variations in metabolites including proteins and lipids 1 , 8 , 10 , 21 . Therefore, NIRS can be used to distinguish the variation of chemicals in samples 17 – 20 .…”

“…Lung cancer patients with complicated MPE are usually classified as stage IV, and facing significantly different treatments and poor prognosis from those without MPE 10 . In the meantime, patients of pulmonary tuberculosis also show similar exudative effusions and overlapping symptoms as lung cancer, including short breath, chronic cough, fatigue and unexplained weight loss, making accurate diagnosis of MPEs more important and challenging 8 .…”

“…NIRS has been utilized as a fast, non-invasive tool for disease diagnosis, including cancer diagnosis, due to its ability of reflecting changes in molecular compositions by identifying different bonds vibrations in functional groups 17 – 20 . The variations in metabolites between MPE and BPE have been revealed by past metabonomic studies, indicated an increased amount of valine, lactate, alanine, lipids, and free fatty acids (FFAs) (16:0, 18:0, and 18:1) along with a decreased amount of acetoacetate, creatinine, β-glucose, and α-glucose in MPE 1 , 8 , 21 . In addition, our previous metabolomics results revealed that the metabolites composition, such as lipids and oxidized polyunsaturated fatty acids, varies between MPE and BPE.…”