Effect of Delphinidin on Metabolomic Profile in Breast Carcinogenesis

飞燕草素 乳腺癌 代谢组学 癌变 化学 内科学 医学 肿瘤科 癌症研究 计算生物学 癌症 生物 食品科学 色谱法 氰化物 花青素
作者
Bin Han,Fanqi Meng,Yun Niu,Hao Líu,Ju Li,Xiaoli Peng
出处
期刊:Anti-cancer Agents in Medicinal Chemistry [Bentham Science Publishers]
卷期号:22 被引量:3
标识
DOI:10.2174/1871520622666220616101659
摘要

Background: Breast cancer is a malignant tumor which threat to women’s physical and mental health. Delphinidin, one of the main anthocyanidins, has potent anti-cancer properties. In previous study, we found that delphinidin has the preventive role in MNU-induced breast carcinogenesis of rats, but the molecular mechanism by which delphinidin combats breast cancer has not been completely elucidated.The aim of the present study was to identify metabolic profile that account for delphinidin on the preventive effect on 1-methyl-1-nitrosourea (MNU)-induced breast carcinogenesis of rats. Methods: In the present study, liquid chromatography-mass spectrometry (LC-MS) was conducted to identify metabolic profiles of rat tissues collected from normal mammary glands (normal group), breast tumors derived from MNU-induced breast carcinogenesis models (control group) and delphinidin administration models (delphinidin group). Principal component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA) were employed to identify biochemical patterns. The values of variable importance in the projection (VIP) in PLS-DA model combined with the P value of Student’s t-test were used to determine important metabolites. An orthogonal partial least square discriminant analysis (OPLS-DA) was used to conduct the supervised analysis. The fitness and prediction capabilities of PCA modes were measured by R 2 and Q 2 value respectively. Potential biomarkers were subjected to pathway analysis with Metaboanalyst 3.0 based on the KEGG Pathway Database to identify related metabolic pathways. Results: The PCA and PLS-DA analysis indicated that the proposed method were satisfactory for metabolomic analysis. Metabolites from the obtained features were further filtered by PLS-DA analysis with VIP>1.0 and P<0.05. The significant difference was appeared in 190 metabolites between normal group and control group (P<0.05). Eight most significant metabolic pathways were obtained on the basis of the results of P<0.05 data analysis between control and normal group, embodying in aminoacyl-tRNA biosynthesis, arginine biosynthesis, biosynthesis of unsaturated fatty acids, valine, leucine and isoleucine biosynthesis, purine metabolism, alanine, aspartate and glutamate metabolism, glycerophospholipid metabolism, histidine metabolism. A total of 48 metabolites were identified to be associated with protective effects of delphinidin on MNU-induced rats significantly(P<0.05). Compared with control group, a total of 5 metabolic pathways were significantly perturbed in response to delphinidin administration (p<0.05), including in taurine and hypotaurine metabolism, Glycerophospholipid metabolism, arachidonic acid metabolism, aminoacyl-tRNA biosynthesis and primary bile acid biosynthesis. Conclusion: Metabolites and metabolic pathways were identified to be associated with protective effects of delphinidin on MNU-induced rats. The findings provided new insights into the precise mechanism of delphinidin in preventing breast carcinogenesis.

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