Metabolomics profiling in prediction of chemo-immunotherapy efficiency in advanced non-small cell lung cancer.

ABSTRACT:

Background

To explore potential metabolomics biomarker in predicting the efficiency of the chemo-immunotherapy in patients with advanced non-small cell lung cancer (NSCLC).

Methods

A total of 83 eligible patients were assigned to receive chemo-immunotherapy. Serum samples were prospectively collected before the treatment to perform metabolomics profiling analyses under the application of gas chromatography mass spectrometry (GC-MS). The key metabolites were identified using projection to latent structures discriminant analysis (PLS-DA). The key metabolites were used for predicting the chemo-immunotherapy efficiency in advanced NSCLC patients.

Results

Seven metabolites including pyruvate, threonine, alanine, urea, oxalate, elaidic acid and glutamate were identified as

SUBMITTER: Mei L 

PROVIDER: S-EPMC9887290 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature