Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer

Abstract

Lung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.

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

“…found elevated plasma levels of phenylalanine in NSCLC and suggested that this may be due to abnormal inflammation and immune responses in tumors, which impair the function of phenylalanine hydroxylase ( 54 ). Similarly, two recent studies have reported increased levels of phenylalanine in the blood of lung cancer patients ( 55 , 56 ). In another metabolomic study, patients with lung cancer showed increased sputum levels of tyrosine compared to those with benign lung lesions, and a metabolic panel combining tyrosine with diethanolamine, cytosine, and lysine was proposed for the early diagnosis of lung cancer ( 46 ).…”

Evaluating for Correlations between Specific Metabolites in Patients Receiving First-Line or Second-Line Immunotherapy for Metastatic or Recurrent NSCLC: An Exploratory Study Based on Two Cohorts

“…There have been some studies of metabolomics in NSCLC diagnosis, characterization, and progression ( 20 ). However, the shortcomings of previous studies are the lack of standardized patient selection and few studies have focused on the value of metabolomics in predicting response or long-term survival in patients with lung cancer receiving immunotherapy.…”