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中性解吸萃取电喷雾电离质谱分析法检测痰液用于非侵入性肺腺癌诊断

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

作者信息

Zheng Qiaoling, Zhang Jianyong, Wang Xinchen, Zhang Wenxiong, Xiao Yipo, Hu Sheng, Xu Jianjun

机构信息

Department of Cardiothoracic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, People's Republic of China.

Jiangxi Health Vocational College, Nanchang, Jiangxi 330000, People's Republic of China.

出版信息

Onco Targets Ther. 2021 Jan 15;14:469-479. doi: 10.2147/OTT.S269300. eCollection 2021.

Abstract

PURPOSE

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.

摘要

目的

低剂量螺旋计算机断层扫描(LDCT:低剂量计算机断层扫描)筛查的使用增加,使得外周肺结节的偶然发现更为频繁,其中部分为腺癌,需要进一步评估以明确诊断。在此,我们的主要目的是评估常压质谱(AMS)痰液分析作为一种非侵入性肺腺癌(LAC)诊断方法。

患者与方法

采用中性解吸萃取电喷雾电离质谱(ND-EESI-MS)和碰撞诱导解离(CID)检测143份自发痰液样本中的痰液代谢物。偏最小二乘判别分析(PLS-DA)用于优化生物标志物组,而正交偏最小二乘判别分析(OPLS-DA)用于将增强后的生物标志物组用于诊断。

结果

在该方法中,通过ND-EESI-MS从76例LAC患者和67例对照中检测到19种改变的代谢物。显著性检验和受试者工作特征(ROC)分析分别确定了5种代谢物[羟基苯乳酸、植物鞘氨醇、N-壬酰甘氨酸、二氢鞘氨醇、S-羧甲基-L-半胱氨酸],其p<0.05且AUC>0.75。LAC预测模型性能评估的交叉验证分类准确率为87.9%。代谢途径分析表明,鞘脂代谢、脂肪酸代谢、肉碱合成和瓦伯格效应在疾病反应中受到的影响最大。

结论

本研究表明,将ND-EESI-MS应用于痰液分析可用于外周肺结节的非侵入性检测。痰液代谢物生物标志物的使用可能有助于制定进一步的肺腺癌评估方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1cf8/7816046/c5056304369b/OTT-14-469-g0001.jpg

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