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Metabolomics based plasma biomarkers for diagnosis of oral squamous cell carcinoma and oral erosive lichen planus

Backgrounds: To identify diagnostic biomarkers for differentiating oral squamous cell carcinoma (OSCC) from oral erosive lichen planus (OELP) and investigate potential biomarkers associated with malignant transformation. Methods: In this study, 72 patients with OSCC, 75 patients with OELP subjects w...

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Detalles Bibliográficos
Autores principales: Li, Xibo, Liu, Liwei, Li, Na, Jia, Qingquan, Wang, Xiaoshuang, Zuo, Lihua, Long, Jianglan, Xue, Peng, Sun, Zhi, Zhao, Hongyu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8692701/
https://www.ncbi.nlm.nih.gov/pubmed/34976172
http://dx.doi.org/10.7150/jca.59777
Descripción
Sumario:Backgrounds: To identify diagnostic biomarkers for differentiating oral squamous cell carcinoma (OSCC) from oral erosive lichen planus (OELP) and investigate potential biomarkers associated with malignant transformation. Methods: In this study, 72 patients with OSCC, 75 patients with OELP subjects were recruited. Their plasma samples were analyzed by ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry, (UHPLC/Q-Orbitrap HRMS). Principal component analysis, orthogonal partial least square discrimination analysis, t-test analysis and false discovery rate were used to identify different metabolites in patients with OSCC and OELP. The metabolic pathway analysis was performed by MetaboAnalyst. To further screen and identify the biomarkers of OSCC and establish a diagnostic panel, binary logistic regression analysis and receiver operating characteristic analysis were used. The data were then combined with blood samples from healthy individuals for mass spectrometry analysis to obtain biomarkers related to malignant transformation. Results: A total of 20 kinds of endogenous metabolites were identified from plasma samples of OSCC patients and OELP patients. Metabolic pathway analysis showed that the biomarkers associated with OSCC were closely related to cholic acid metabolism and amino acid metabolism. Finally, a diagnostic panel composed of decanoylcarnitine, cysteine and cholic acid was established. This diagnostic panel had good diagnostic efficiency with the AUC=0.998. Other metabolites including uridine, taurine, glutamate, citric acid and LysoPC(18:1) were identified to be general biomarkers for malignant transformation of OELP. Conclusion: Biomarkers based on plasma metabolomics are of great significance for the prediction of malignant transformation of OELP and early diagnosis of OSCC.