Prediction of platinum-based chemotherapy efficacy in lung cancer based on LC-MS metabolomics approach

Lung cancer is the common cause of cancer-related death worldwide. Platinum-based chemotherapy is the cornerstone of treatment for lung cancer. Platinum sensitivity is a major possibility for effective cancer treatment. In this study, several potential biomarkers were identified for evaluating and predicting the response to platinum-based chemotherapy. LC-MS-based metabolomics was performed on plasma samples from 43 lung cancer patients with different chemotherapy efficacy. By combing multivariate statistical analysis, pathway analysis with correlation analysis, 8 potential biomarkers were significantly associated with platinum chemotherapy response. Moreover, a prediction model with these biomarkers involved in citric acid cycle, glutamate metabolism and amino acid metabolism, showed 100% sensitivity and 100% specificity for predicting chemotherapy response in a validation set. Interestingly, 2-hydroxyglutaric acid (2-HG) as an oncometabolite accumulated in lung cancer was remarkably elevated in the partial response (PR) patients. Collectively, our findings implicated that metabolomics can serve as a potential tool to select lung cancer patients that are more likely to benefit from the platinum-based treatment.