INTRODUCTION: Histologically lung cancer is classified into four major types: 
adenocarcinoma (Ad), squamous cell carcinoma (SqCC), large cell carcinoma (LCC), 
and small cell lung cancer (SCLC). Presently, our understanding of cellular 
metabolism among them is still not clear.
OBJECTIVES: The goal of this study was to assess the cellular metabolic profiles 
across these four types of lung cancer using an untargeted metabolomics 
approach.
METHODS: Six lung cancer cell lines, viz., Ad (A549 and HCC827), SqCC (NCl-H226 
and NCl-H520), LCC (NCl-H460), and SCLC (NCl-H526), were analyzed using liquid 
chromatography quadrupole time-of-flight mass spectrometry, with normal human 
small airway epithelial cells (SAEC) as the control group. The principal 
component analysis (PCA) was performed to identify the metabolic signatures that 
had characteristic alterations in each histological type. Further, a metabolite 
set enrichment analysis was performed for pathway analysis.
RESULTS: Compared to the SAEC, 31, 27, 34, 34, 32, and 39 differential 
metabolites mainly in relation to nucleotides, amino acid, and fatty acid 
metabolism were identified in A549, HCC827, NCl-H226, NCl-H520, NCl-H460, and 
NCl-H526 cells, respectively. The metabolic signatures allowed the six cancerous 
cell lines to be clearly separated in a PCA score plot.
CONCLUSION: The metabolic signatures are unique to each histological type, and 
appeared to be related to their cell-of-origin and mutation status. The changes 
are useful for assessing the metabolic characteristics of lung cancer, and offer 
potential for the establishment of novel diagnostic tools for different origin 
and oncogenic mutation of lung cancer.