Metabolic Profiling of Plasma from Benign and Malignant Pulmonary Nodules Patients Using Mass Spectrometry-Based Metabolomics

Metabolites

Liang Gao³  Zongmei Wen¹  Chunyan Wu¹  Tao Wen² 

[1]Department of Anesthesiology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai 200433, China

[2] E-Mails:

[3]Saw Swee Hock School of Public Health, National University of Singapore, 16 Medical Drive, Singapore 117597, Singapore

[4] E-Mails:

[5]NUS Environmental Research Institute, National University of Singapore, 5A Engineering Drive 1, Singapore 117411, Singapore

[6] E-Mail:

关键词: metabolomics;    solitary pulmonary nodules;    plasma;    biomarkers;    mass spectrometry;   

DOI  :  10.3390/metabo3030539

来源: mdpi

【 摘 要 】

Solitary pulmonary nodule (SPN or coin lesion) is a mass in the lung and can be commonly found in chest X-rays or computerized tomography (CT) scans. However, despite the advancement of imaging technologies, it is still difficult to distinguish malignant cancer from benign SPNs. Here we investigated the metabolic profiling of patients with benign and malignant pulmonary nodules. A combination of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS) was used to profile the plasma metabolites in 17 patients with malignant SPNs, 15 patients with benign SPNs and 20 healthy controls. The metabolic profiles were assayed using OPLS-DA, and further analyzed to identify marker metabolites related to diseases. Both GC/MS- and LC/MS-derived models showed clear discriminations in metabolic profiles among three groups. It was found that 63 metabolites (12 from GC/MS, 51 from LC/MS) contributed to the differences. Of these, 48 metabolites showed same change trend in both malignant and benign SPNs as compared with healthy controls, indicating some common pathways including inflammation and oxidative injury shared by two diseases. In contrast, 14 metabolites constituted distinct profiles that differentiated malignant from benign SPNs, which might be a unique biochemical feature associated with lung cancer. Overall, our data suggested that integration of two highly sensitive and complementary metabolomics platforms could enable a comprehensive metabolic profiling and assist in discrimination malignant from benign SPNs.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.