Metabolomics Profiling in Prediction of Immunotherapy Efficacy in Advanced Non-small Cell Lung Cancer

Objective: To explore potential metabolomics biomarker in predicting the efficacy and the survival outcomes after the first-line programmed death-1 (PD-1) immunotherapy in the patients with advanced non-small cell lung cancer (NSCLC). Methods: A total of 46 consecutive eligible patients were assigned to receive first-line PD-1 immunotherapy. Serum samples were prospectively collected before initial treatment to perform metabolomics profiling analyses under the application of gas chromatography mass spectrometry (GC-MS). The metabolomics signatures were extracted by using a binary least absolute shrinkage and selection operator (LASSO) logistic regression and calculated as a metabolomics score by liner fit for each patients. The metabolomics score was further combined with the clinical predictors to build a metabolomics nomogram for predicting the immunotherapy efficacy in advanced NSCLC patients. The ROC curves were used to evaluate the predicting performance of the metabolomics score, the clinical predictors and the metabolomics nomogram. Results: Seven metabolites including Urea, Tyrosine, L-threonine, Xylitol, Thymol, Linoleic acid and DL-isoleucine were identified associated with the immunotherapy response. Age was identified as the clinical predictor by the logistic regression. The receiver operating characteristic curve (AUC) was 0.96 (95% CI: 0.92-1.00) for metabolomics score, 0.72 (95% CI: 0.53-0.91) for the clinical predictor and 0.97 (95% CI: 0.93-1.00) for the metabolomics nomogram in differentiating progressive disease (PD) groups from disease control (DC) groups. The median progression-free survival (PFS) after immunotherapy in patients with low risk was significantly longer than those with high risk in the metabolomics nomogram (11.8 vs.2.8 months, P < .001). Conclusion: This study developed an effective and convenient discriminant metabolomics nomogram that can predict the efficacy and the survival outcomes of PD-1 immunotherapy in advanced NSCLC.