Cortisol, cortisone, and 4-methoxyphenylacetic acid as potential plasma biomarkers for early detection of non-small cell lung cancer.

BACKGROUND

Lung cancer is the most common cause of cancer-related deaths in men and women worldwide. Novel diagnostic biomarkers are urgently required to enable the early detection and treatment of lung cancer, and using novel methods to explore tumor-related biomarkers is a hot topic in lung cancer research. The purpose of this study was to use ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) metabolomics analysis technology combined with multivariate data processing methods to identify potential plasma biomarkers for non-small cell lung cancer (NSCLC).

METHODS

Plasma samples from 99 NSCLC patients and 112 healthy controls were randomly divided into the screening group and the validation group, respectively. UPLC-MS metabolomics analysis technology combined with multivariate data processing methods were used to identify potential plasma biomarkers for NSCLC.

RESULTS

A total of 254 metabolites were detected and validated in plasma. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) modeling indicated that 28 endogenous metabolites were present at significantly different levels in patients with NSCLC than healthy controls (variable importance in projection (VIP)>1 and P<0.001 (independent samples t-test) in both the screening group and the validation group). Further analysis revealed that cortisol, cortisone, and 4-methoxyphenylacetic acid had high sensitivity and specificity values as biomarkers for discriminating between NSCLC and healthy controls. Significant associations between specific plasma metabolites and the pathological type or stage of NSCLC were also observed.

CONCLUSIONS

Metabolomics has the potential to distinguish between NSCLC patients and healthy controls, and may reveal new plasma biomarkers for the early detection of NSCLC.