Abstract

Background: In the past years, treatment of advanced non-small cell lung cancer (NSCLC) has suffered a variety of alterations. Chemotherapy (QT), immune checkpoint inhibitors (ICIs), tyrosina kinase inhibitors have shown remarkable results. However, not all patients with NSCLC respond to these treatments or receive durable benefits. Thus, patient selection, as well as the identification of predictive biomarkers, represent a vital approach in the study of lung cancer.In this framework, metabolomicshas been used in early diagnosis, to personalize treatment and to improve prognosis.

Aims:To use metabolomic alterations in order to guide treatment choice.

Methods: Metabolomics was used to analyze the serum samples from 18 patients with Lung Adenocarcinoma (AdC) treated with QT and ICIs. All the samples were collected before, after 3 and 6 treatments, and were analyzed by NMR spectroscopy.Multivariate/univariate statistical analyses were used to discover significant differences between the two treatment groups.

Results: Significantly, we showed that the serum glucose levels of patients under QT became higher throughout the treatment course, which could be related to tumour response to therapy. It was also significantly found that alanine levels were higher in the QT group, and became lower during the treatment course, fact that was not observed in the IT group. This lead to the hypothesis that it could be associated to frailty.

Conclusions: Metabolomics represents a potential strategy for the real-time patient selection and monitoring of therapy efficacy in treated patients with AdC. Newer studies are needed in order to improve the prospective identification of predictive markers.