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.
Keywords: Large cell carcinoma; Lung adenocarcinoma; Metabolic signatures; Pathway analysis; Small cell lung cancer; Squamous cell carcinoma.