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Potential Metabolites with Diagnostic Value in Plasma for Angioimmunoblastic T-Cell Lymphoma By LC-MS Based Untargeted Metabonomics Study

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Background: Angioimmunoblastic T-cell lymphoma (AITL) is an uncommon subtype of mature peripheral T-cell lymphoma (PTCL). and its characteristics is not fully understood. Because it is a rare form of lymphoma,… Click to show full abstract

Background: Angioimmunoblastic T-cell lymphoma (AITL) is an uncommon subtype of mature peripheral T-cell lymphoma (PTCL). and its characteristics is not fully understood. Because it is a rare form of lymphoma, there is difficulty in diagnosis based on current traditional method. Metabolic reprogramming is a major cancer hallmark, which provides cancer cells with vital energy and metabolites. Mass spectrometry-based metabolomics has emerged as an informative technique for profiling metabolic features associated with cancers. Objective: This study aim to discover metabolites with potential diagnostic value in plasma of AITL patient. Methods: Plasma was collected from 27 patients newly diagnosed with AITL in Zhejiang Cancer Hospital and 30 age- and gender- matched healthy controls. An aliquot of 50 μL plama was added with 150 μL of chilled acetonitrile, vortexed and centrifuged. the supernatant was dried, reconstituted for metabolomics. Mass spectrometry analysis was performed on a UPLC coupled with a Q Exactive Orbitrap mass spectrometer. "XCMS" and "MetaX" were used to analyze LC-MS data. Significant features were selected as candidate for identification by matching their MS and MS/MS data with online databases HMDB and METLIN. Results: Eighteen altered metabolites (choline, betaine, L-leucine, creatine, 2-butyl-1H-benzimidazole, hypoxanthine, methionine sulfoximine, L-carnitine, 2-hydroxycinnamic acid, L-tyrosine, D-tryptophan, indoleacrylic acid, lysoPC(P-18:0), 5-aminopentanoic acid, uric acid, sucrose, L-lactic) were indentified (VIP value>1, p<0.05) in AITL patient plasma. The altered metabolites contributed to different metabolic pathways including glycine, serine and threonine metabolism (P=0.003), glycerophospholipid metabolism (P=0.024), Phenylalanine metabolism (P=.030). Conclusion: This study revealed metabolic reprogram and potential diagnostic metabolites in plasma for AITL, and gave more metabolic information for carcinogenesis of AITL. No relevant conflicts of interest to declare.

Keywords: plasma; cell lymphoma; diagnostic value; cell; angioimmunoblastic cell

Journal Title: Blood
Year Published: 2019

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