| Lung cancer is one of the leading cause of cancer-related death worldwide,whose morbidity and mortality have been reported as increased in recent years.Pleural effusion is the most specific pathological accumulation of fluid in the pleural cavity that surrounds the lung,whose appearance mainly associated with the occurrence of lung disease,reflecting the body in a variety of diseases on the pleura.Malignant pleural effusion is one of the common complications in patients with advanced cancer,and accounts for approximately 25%of all pleural effusions.There are more than 60%of lung cancer patients diagnosed with malignant pleural effusions at the late disease stage.Thus,malignant pleural effusion is the clinic problem of tumor-related patients especially for lung cancer patients,and the differentiation between benign and malignant pleural effusions is still a clinical challenge.In the present study,the volatile organic metabolites(VOMs)in pleural effusion samples were extracted by headspace-solid phase microextraction(HS-SPME)and analyzed by gas chromatography/mass spectrometry(GC/MS).XCMS Online combined with multivariate statistical analysis were applied to process the data for screening significantly dysregulated VOMs.Further qualitative and quantitative analysis of the significant VOMs were carried out to provide a valuable reference for distinguishing malignant pleural effusions from lung cancer patients.The main work and results of this thesis are as follows:1.A method of HS-SPME-GC/MS for investigation of VOMs in pleural effusion samples has been established and optimized.As a result,using the 75 ?m CAR/PDMS fiber with the extraction temperature at 50?,and 2 mL of samples with sodium chloride saturation were transferred into a 15 mL vial at the stirring rate of 800 rpm,extracted for 20 min and desorbed at 250 C in the GC injector for 3 min.Under these optimum experimental conditions,the VOMs in pleural effusion samples from 15 lung cancer and 20 benign lung disease patients were analyzed.2.A free web-based software XCMS Online has been used for automated pre-processing of the GC/MS-based metabolomic data.Then,multivariate statistical analyses including principle component analysis(PCA),partial least squares discriminant analysis(PLS-DA)and orthogonal PLS-DA(OPLS-DA)have been conducted to classify the two effusion groups.Consequently,9 VOMs exhibited a statistic difference(p<0.05)in benign and malignant pleural effusions,and the OPLS-DA was good enough for classification of the two groups.According to the rule of VIP values more than 1,4 VOMs have been screened with a significant influence on the explanation of the classification.3.Identification of the 4 selected VOMs were carried out by comparison of the standard mass spectrum library(NIST 02)and confirmed by the commercially available standards.Furthermore,the external standard method was performed to determine the concentrations of above 4 identified VOMs in pleural effusions.As a result,the 4 selected VOMs were identified as cyclohexanone,2-ethyl-1-hexanol,1,2,4,5-tetramethylbenzene and naphthalene.The average concentrations of them varied from 62.75 to 102,213.45 nmol/1 in malignant effusion samples,whereas the average levels were 3.88?667.55 nmol/1 in benign ones.Moreover,they have good predictive ability with high sensitivity(>67%)and specificity(>80%)for distinguishing the malignant from benign pleural effusions by ROC curve analysis.It revealed that cyclohexanone,2-ethyl-l-hexanol,1,2,4,5-tetramethyl-benzene and naphthalene might be promising to be useful biomarkers for diagnosis of the malignant effusions,and that would provide good reference for investigation of lung cancer biomarkers.In addition,the proposed GC/MS-based metabolomic approach combined with XCMS Online data processing provided a potential valuable reference to rapidly predict the malignant pleural effusions from lung cancer patients. |
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