The investigation of the volatile metabolites of lung cancer from the microenvironment of malignant pleural effusion

Abstract

For malignant pleural effusions, pleural fluid cytology is a diagnostic method, but sensitivity is low. The pleural fluid contains metabolites directly released from cancer cells. The objective of this study was to diagnose lung cancer with malignant pleural effusion using the volatilomic profiling method. We recruited lung cancer patients with malignant pleural effusion and patients with nonmalignant diseases with pleural effusion as controls. We analyzed the headspace air of the pleural effusion by gas chromatography-mass spectrometry. We used partial least squares discriminant analysis (PLS-DA) to identify metabolites and the support vector machine (SVM) to establish the prediction model. We split data into a training set (80%) and a testing set (20%) to validate the accuracy. A total of 68 subjects were included in the final analysis. The PLS-DA showed high discrimination with an R2 of 0.95 and Q2 of 0.58. The accuracy of the SVM in the test set was 0.93 (95% CI 0.66, 0.998), the sensitivity was 83%, the specificity was 100%, and kappa was 0.85, and the area under the receiver operating characteristic curve was 0.96 (95% CI 0.86, 1.00). Volatile metabolites of pleural effusion might be used in patients with cytology-negative pleural effusion to rule out malignancy.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

“…Chen et al. used GC-MS to compare the volatile metabolites of malignant pleural effusion in lung cancer patients with or without EGFR mutations ( 143 ). There was a clear separation between the clustering of patients with and without EGFR mutations from the score plot.…”

“…Selecting appropriate sample sources based on the physiological characteristics of tumors can provide more valuable information for metabolomics studies. For example, as a crucial component of the lung cancer microenvironment, pleural effusion can more directly reflect metabolic changes in lung cancer patients and is less influenced by the body’s systemic metabolism ( 143 ). Uniform collection time and appropriate storage conditions are crucial for accurate metabolomics data.…”

The LncRNA DUXAP10 Could Function as a Promising Oncogene in Human Cancer

“…Lung cancer (Molina et al, 2008;Zhang et al, 2019;Chen et al, 2021b) remains the leading cause of cancer-related mortality worldwide, with approximately 1.8 million (Chen et al, 2021a;Sung et al, 2021) deaths per year. While there has been a modest improvement in lung cancer (Sławińska-Brych et al, 2021) OS in recent decades, further studies are needed to improve patients' clinical outcomes.…”

Assessment of a Large-Scale Unbiased Malignant Pleural Effusion Proteomics Study of a Real-Life Cohort

“…Lung cancer accounts for 36.0% of MPEs, followed by breast cancer and lymphoma [ 9 ]. Around 40% of lung cancer patients with exudative PE are undetected by current thoracentesis and require thoracoscopy for detection [ 10 ].…”