目的 基于LC-MS代谢组学技术研究胡桃醌抑制胃癌细胞BGC-823和肝癌细胞HepG 3B增殖的机制。方法 采用MTS法检测胡桃醌（6.25、12.50、25.00、50.00、100.00 μmol·L^-1）对BGC-823、HepG 3B细胞活力的影响，并计算半数抑制浓度（IC₅₀）作为后续给药浓度；使用胡桃醌处理BGC-823、HepG 3B细胞，提取代谢物，基于LC-MS检测样品，进行代谢组学分析；使用Progenesis QI软件进行数据处理，将得到的数据导入EZinfo进行多元统计分析，利用主成分分析（PCA）及正交偏最小二乘-判别分析（OPLS-DA）得到变量权重值（VIP），选取VIP＞1且具有统计学意义的差异代谢物（P＜ 0.05）作为潜在的生物标记物。通过人类代谢组数据库（HMDB）、京都基因和基因组百科全书（KEGG）等代谢物数据库对生物标记物进行鉴定，利用MetaboAnalyst平台进行代谢通路分析。结果 胡桃醌对HepG 3B细胞的IC₅₀为14.17 μmol·L^-1，对BGC-823细胞的IC₅₀为11.19 μmol·L^-1。作用于HepG 3B细胞，筛选出尿苷二磷酸葡萄糖、谷胱甘肽、氧化谷胱甘肽、柠檬酸、L-酪氨酸、L-异亮氨酸、L-苯丙氨酸、泛酸、L-色氨酸、花生四烯酸、棕榈酸共11个生物标记物，涉及谷胱甘肽代谢，泛酸盐和辅酶A（CoA）生物合成，花生四烯酸代谢，淀粉和蔗糖代谢，氨基糖和核苷酸糖代谢，苯丙氨酸代谢，缬氨酸、亮氨酸和异亮氨酸的生物合成，酪氨酸代谢，色氨酸代谢，柠檬酸循环，脂肪酸代谢共11条代谢通路；作用于胃癌BGC-823细胞，筛选出泛硫乙胺、肌酸、鞘氨醇、丙酰肉碱、异戊酰肉碱、L-苯丙氨酸、L-异亮氨酸、L-色氨酸8个生物标记物，涉及鞘脂类代谢，缬氨酸、亮氨酸、异亮氨酸生物合成，苯丙氨酸、酪氨酸、色氨酸生物合成，苯丙氨酸代谢，色氨酸代谢，泛酸与辅酶A生物合成，精氨酸与脯氨酸代谢共7条代谢通路。结论 胡桃醌可抑制BGC-823、HepG3B细胞活力，其机制与影响多种能量及氨基酸代谢通路相关。

Objective To investigate the mechanism of inhibition of proliferation of gastric cancer cell line BGC-823 and hepatocellular carcinoma cell line HepG 3B by juglone based on LC-MS metabolomics. Methods The MTS method was used to detect the effects of juglone (6.25, 12.50, 25.00, 50.00, 100.00 μmol·L^-1) on the viability of BGC-823 and HepG 3B cells and calculate the half-maximal inhibitory concentration (IC₅₀) as the subsequent drug administration concentration. BGC-823 and HepG 3B cells were treated with juglone, and the metabolites were extracted. The samples were detected by LC-MS and subjected to metabolomics analysis. Data processing was performed using Progenesis QI software, and the obtained data were imported into EZinfo for multivariate statistical analysis. Principal component analysis (PCA) and orthogonal partial least squares analysis (OPLS-DA) were used to obtain variable importance in projection (VIP) values. Metabolites with VIP > 1 and statistical significance (P <0.05) were selected as potential biomarkers. The biomarkers were identified using metabolite databases such as HMDB and KEGG, and metabolic pathway analysis was conducted using the MetaboAnalyst platform. Results The IC₅₀ of juglone for HepG 3B cells was 14.17 μmol·L^-1, and for BGC-823 cells, it was 11.19 μmol·L^-1. When acting on HepG 3B cells, 11 biomarkers were screened out, including uridine diphosphate glucose, glutathione, oxidized glutathione, citric acid, L-tyrosine, L-isoleucine, L-phenylalanine, pantothenic acid, L-tryptophan, arachidonic acid, and palmitic acid, involving 11 metabolic pathways such as glutathione metabolism, pantothenate and CoA biosynthesis, arachidonic acid metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, phenylalanine metabolism, valine, leucine and isoleucine biosynthesis, tyrosine metabolism, tryptophan metabolism, citric acid cycle, and fatty acid metabolism. When acting on gastric cancer BGC-823 cells, eight biomarkers were screened out, including pantethine, creatine, sphingosine, propionylcarnitine, isovalerylcarnitine, L-phenylalanine, L-isoleucine, and L-tryptophan, involving seven metabolic pathways such as sphingolipid metabolism, valine, leucine and isoleucine biosynthesis, phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, tryptophan metabolism, pantothenate and CoA biosynthesis, and arginine and proline metabolism. Conclusion Juglone can inhibit the viability of BGC-823 and HepG 3B cells, and its mechanism is related to the influence on multiple energy and amino acid metabolic pathways.

R285.5

黑龙江省中医药学会青年人才托举工程项目（2022-QNRC1-14）