Application of Lipidomics for Assessing Tissue Lipid Profiles of Patients With Squamous Cell Carcinoma. (November 2021)

• Record Type: Journal Article
• Authors: Zeng, Weibiao; Zheng, Wen; Hu, Sheng; Zhang, Jianyong; Zhang, Wenxiong; Xu, Jianjun; Yu, Dongliang; Peng, Jinhua; Zhang, Lu; Gong, Meng; Wei, Yiping
• Is Part Of: Technology in cancer research & treatment. Volume 20(2021)
• Publication Date: 2021-11
• Subjects: non-small-cell lung carcinoma -- squamous cell carcinoma -- lipidomics -- lipid metabolism -- mass spectrometry; Oncology -- Periodicals; Cancer -- Diagnosis -- Periodicals; Cancer -- Treatment -- Technological innovations -- Periodicals; 616.994
• DOI: 10.1177/15330338211049903
• Languages: English
• ISSNs: 1533-0346

Abstract

Background: Lipid metabolism disorders play a key role in the pathogenesis of squamous cell carcinoma (SqCC). Herein we used lipidomics to study the tissue lipid profiles of 40 patients with SqCC.Methods: Lipidomics, based on ultrahigh-performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high-resolution accurate mass spectrometry, was applied to identify altered lipid metabolites between tumor and adjacent noninvolved tissues (ANIT), and partial least squares-discriminant analysis model facilitated the identification of differentially abundant lipids. The area under the receiver operator characteristic curve and variable importance in projection scores of the aforementioned model were calculated to select lipid profiles. Metabolic pathway analyses were completed using Kyoto Encyclopedia of Genes and Genomes and MetaboAnalyst.Results: Differences in lipid profiles were found between tumor and ANIT, early- and advanced-stage SqCC, and positive and negative lymph node metastases. The lipid profile panel was composed of five lipids—PC(44:4), diacylglycerol(36:5), sphingomyelin(d18:1/20:0), phosphatidylinositol(46:7), and HexCer-AP(t8:0/32:2 + O)—and could effectively differentiate between tumor and ANIT. Further, pathway analyses revealed alterations in several lipid metabolism pathways, including glycerophospholipid metabolism, glycosylphosphatidylinositol anchor biosynthesis, linoleic acid metabolism, glycerolipid metabolism, and sphingolipid metabolism.Conclusion: Our data revealed several changes in the tissue lipid profiles of patients with SqCC; moreover, we identified a lipid profile panel that could effectually distinguish tumor tissues from ANIT. We believe that our results provide new insights into the biological behavior of lung SqCC.