去甲缬氨酸
代谢物
乳腺癌
生物
丁酸
代谢组
癌症
代谢组学
普雷沃菌属
生物化学
微生物学
药理学
化学
细菌
缬氨酸
生物信息学
氨基酸
遗传学
作者
Qin Zhu,Hongyan Zai,Kejing Zhang,Xian Zhang,Na Luo,Xin Li,Yu Hu,Yuhui Wu
摘要
The altered faecal metabolites and microbiota might be involved in the development of breast cancer. We aimed to investigate the effect of differential metabolites on the proliferative activity of breast cancer cells.We collected faecal samples from 14 breast cancer patients and 14 healthy subjects. Untargeted metabolomics analysis, short-chain fatty acid (SCFA) targeted analysis, and 16S rDNA sequencing was performed. The gut metabolite composition of patients changed significantly. Levels of norvaline, glucuronate and galacturonate were lower in the cancer group than in the Control (p < 0.05). 4-Methylcatechol and guaiacol increased (p < 0.05). Acetic acid and butyric acid were lower in the cancer group than in the control group (p < 0.05). Isobutyric acid and pentanoic acid were higher in the cancer group than in the control (p < 0.05). In the genus, the abundance of Rothia and Actinomyces increased in the cancer group, compared with the control group (p < 0.05). The differential microbiotas were clearly associated with differential metabolites but weakly with SCFAs. The abundance of Rothia and Actinomyces was markedly positively correlated with 4-methylcatechol and guaiacol (p < 0.05) and negatively correlated with norvaline (p < 0.05). L-norvaline inhibited the content of Arg-1 in a concentration-dependent manner. Compared with the L-norvaline or doxorubicin hydrochloride (DOX) group, the proliferation abilities of 4 T1 cells were the lowest in the L-norvaline combined with DOX (p < 0.05). The apoptosis rate increased (p < 0.05).Faecal metabolites and microbiota were significantly altered in breast cancer. Levels of differential metabolites (i.e. Norvaline) were significantly correlated with the abundance of differential microbiota. L-norvaline combined with DOX could clearly inhibit the proliferation activity of breast cancer cells.This might provide clues to uncover potential biomarkers for breast cancer diagnosis and treatment.
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