Histological and genetic features and therapeutic responses of lung cancers explored via the global analysis of their metabolome profile.

BACKGROUND

Lung cancer is the deadliest disease globally, with more than 120,000 diagnosed cases and more than 75,000 deaths annually in Japan. Several treatment options for advanced lung cancer are available, and the discovery of biomarkers will be useful for personalized medicine. Using metabolome analysis, we aimed to identify biomarkers for diagnosis and treatment response by examining the changes in metabolites associated with lung cancer progression.

METHODS

Plasma samples from patients with recurrent or metastatic non-small cell lung carcinomas diagnosed at Tohoku University Hospital between 2019 and 2024 were used in this study. Metabolomic analysis was performed using the Biocrates Life Sciences MxP Quant 500 kit. Multivariate, principal component, and orthogonal partial least squares discriminant analyses were performed.

RESULTS

The triglyceride and phosphatidylcholine concentrations were higher in the patients with early than in those with advanced lung adenocarcinomas. However, the cholesterol ester concentrations were higher for the patients with advanced lung cancer. The concentrations of hexosylceramide were higher in patients with early lung adenocarcinoma than in those with squamous cell carcinoma. Relative to epidermal growth factor receptor (EGFR)-mutation negative cases, the EGFR-mutation positive cases showed marked differences between the ceramide and triglyceride concentrations. For the best therapeutic effect of EGFR-TKI treatment, the hexosylceramide (HexCer) (d18:1/24:0), ceramide (Cer) (d18:2/22:0), and ceramide (Cer) (d18:2/24:0) concentrations were higher for the stable and progressive disease groups. The concentrations of phosphatidylcholine (PC) ae C42:2, sphingomyelin (SM) C24:1, and lysophosphatidylcholine (lysoPC) a C18:2 were higher in the partial response group treated with immune checkpoint inhibitors and chemotherapy.

CONCLUSION

Metabolomic analysis may be useful for the diagnosis and treatment of lung cancer and may provide clues for new therapeutic strategies. PC ae C42:2, SM C24:1, and lysoPC a C18:2 can serve as predictive biomarkers for monitoring the therapeutic effects of the combination of immune checkpoint inhibitors and chemotherapy.