Neutral Desorption Extractive Electrospray Ionization Mass Spectrometry Analysis Sputum for Non-Invasive Lung Adenocarcinoma Detection

Abstract

Qiaoling Zheng,1,2 Jianyong Zhang,1,3 Xinchen Wang,4 Wenxiong Zhang,1 Yipo Xiao,4 Sheng Hu,1 Jianjun Xu1 1Department of Cardiothoracic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, People’s Republic of China; 2Jiangxi Health Vocational College, Nanchang, Jiangxi 330000, People’s Republic of China; 3The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province 550000, People’s Republic of China; 4Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang, Jiangxi Province 330013, People’s Republic of ChinaCorrespondence: Jianjun Xu Tel + 8613907913526Email [email protected]: Increased use of low-dose spiral computed tomography (LDCT: low-dose computed tomography) screening has contributed to more frequent incidental detection of peripheral lung nodules, part of them were adenocarcinoma, which need to be further evaluated to establish a definitive diagnosis. Here, our primary objective was to evaluate the ambient mass spectrometry (AMS) sputum analysis as a non-invasive lung adenocarcinoma (LAC) diagnosis solution.Patients and Methods: Neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) and collision induced dissociation (CID) were used to detect sputum metabolites from 143 spontaneous sputum samples. Partial least squares-discriminant analysis (PLS-DA) was used to refine the biomarker panel, whereas orthogonal PLS-DA (OPLS-DA) was used to operationalize the enhanced biomarker panel for diagnosis.Results: In this approach, 19 altered metabolites were detected by ND-EESI-MS from 76 cases of LAC and 67 cases of control. Significance testing and receiver operating characteristic (ROC) analysis identified 5 metabolites [hydroxyphenyllactic acid, phytosphingosine, N-nonanoylglycine, sphinganine, S-carboxymethyl-L-cysteine] with p < 0.05 and AUC > 0.75, respectively. Evaluation of model performance for prediction of LAC resulted in a cross-validation classification accuracy of 87.9%. Metabolic pathway analysis showed that sphingolipid metabolism, fatty acid metabolism, carnitine synthesis and Warburg effect were most impacted in response to disease.Conclusion: This study indicates that the application of ND-EESI-MS to sputum analysis can be used as a non-invasive detection of peripheral lung nodules. The use of sputum metabolite biomarkers may aid in the development of a further evaluation program for lung adenocarcinoma.Keywords: lung cancer, metabolomics, ND-EESI-MS, diagnosis, non-invasive detection

Keywords

• lung cancer
• metabolomics
• nd-eesi-ms
• diagnosis
• non-invasive detection.