实验动物与比较医学 ›› 2024, Vol. 44 ›› Issue (1): 52-61.DOI: 10.12300/j.issn.1674-5817.2023.094

• 人类疾病动物模型 • 上一篇    下一篇

树鼩乳腺肿瘤模型的代谢组学分析

方茜1, 敖青青2, 李春宏1, 欧阳轶强1, 郭松超1, 胡冰1()   

  1. 1.广西医科大学实验动物中心, 南宁 530021
    2.桂林市人民医院, 桂林 541002
  • 收稿日期:2023-06-30 修回日期:2023-12-12 出版日期:2024-02-25 发布日期:2024-03-07
  • 通讯作者: 胡 冰(1978—),女,硕士,助理研究员,主要从事实验动物学研究。E-mail:1020360353@qq.com
  • 作者简介:方 茜(1991—),女,硕士,实验师,主要从事实验动物微生物学研究。E-mail:290227387@qq.com
  • 基金资助:
    国家自然科学基金资助项目"DMBA诱发高脂饮食模式乳腺癌模型的比较代谢组学分析"(31760642)

Metabolomics Analysis of Tupaia belangeri Breast Tumor Model

Xi FANG1, Qingqing AO2, Chunhong LI1, Yiqiang OUYANG1, Songchao GUO1, Bing HU1()   

  1. 1.Laboratory Animal Center, Guangxi Medical University, Nanning 530021, China
    2.Guilin People's Hospital, Guilin 541002, China
  • Received:2023-06-30 Revised:2023-12-12 Published:2024-02-25 Online:2024-03-07
  • Contact: Hu Bing, E-mail: 1020360353@qq.com

摘要:

目的 研究树鼩乳腺肿瘤发生、发展过程中代谢组学的变化,探讨机体代谢物质改变与肿瘤发生、发展的密切关系,以期筛选出反映乳腺肿瘤病情进展的生物标志物。 方法 通过连续3次、每次间隔15 d的方式给20只树鼩每只灌胃7,12-二甲基苯并蒽(7,12-dimethylbenzoanthracene,DMBA)0.15 mg/kg,并添加高脂高糖饲料,诱导实验观察24个月或直至树鼩生成乳腺肿瘤。使用气相色谱-飞行时间质谱联用技术(gas chromatography-time-of-flight mass spectrometry,GC-TOFMS)对DMBA诱导发生乳腺肿瘤的树鼩、DMBA诱导未发生乳腺肿瘤的树鼩以及未诱导正常树鼩(12只)的血清代谢物进行非靶向测定,通过主成分分析(principal component analysis,PCA)、正交偏最小二乘法分析(orthogonal partial least squares analysis,OPLS-DA)等多维统计分析,进一步结合t检验进行组间差异比较,以VIP>1且P<0.05的标准筛选差异性代谢物,并结合HMDB在线数据库对显著变化的差异代谢物进行鉴定,最后应用京都基因与基因组百科全书(Kyoto Encyclopedia of Genesand Genomes,KEGG)通路数据库富集代谢相关基因调控通路。 结果 DMBA诱导后树鼩的乳腺肿瘤发生率为40%(8/20)。DMBA造模成瘤组与正常对照组相比,树鼩血清中检测到有30种代谢差异产物,其中18种下调,12种上调,差异均具有统计学意义(VIP>1,P<0.05);KEGG通路分析发现,谷氨酸代谢、甘油酯代谢、柠檬酸循环、丙氨酸代谢这4个代谢通路发生显著改变。DMBA造模成瘤组与DMBA造模未成瘤组相比,检测到有18种代谢差异产物,其中7种下调,11种上调,差异具有统计学意义(VIP>1,P<0.05);KEGG通路分析发现,柠檬酸循环、谷氨酸代谢这2个代谢通路发生显著改变。DMBA造模未成瘤组与正常对照组相比,检测到有31种代谢差异产物,其中14种下调,17种上调,差异具有统计学意义(VIP>1,P<0.05);KEGG通路分析发现,柠檬酸循环、谷氨酸代谢、甘油酯代谢这3个代谢通路发生显著改变。 结论 代谢组学分析可展示乳腺肿瘤树鼩血清中代谢产物的变化特点,结果提示谷氨酸代谢、甘油酯代谢、柠檬酸循环、丙氨酸代谢途径与高脂高糖饮食下DMBA诱导树鼩乳腺肿瘤的发生与发展有相关性,这为进一步研究乳腺肿瘤发病的生物机制奠定了基础。

关键词: 树鼩, 乳腺肿瘤, 代谢组学, 7, 12-二甲基苯并蒽, 高脂高糖

Abstract:

Objective To explore the metabolic changes during the development of Tupaia belangeri breast tumors, to investigate the close relationship between the changes of serum metabolic substances and the occurrence and progression of tumors, and to screen for biomarkers reflecting the progression of breast tumors. Methods Breast tumors in Tupaia belangeri were induced by orally administering 7,12-dimethylbenzoanthracene (DMBA) three times, with a 15-day interval between each administration, along with a high-fat and high-sugar diet. The DMBA-induced breast cancer group and the DMBA-inducedwithout breast cancer group were compared with the control group. Untargeted determination of serum metabolites was performed using gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) in DMBA-induced Tupaia belangeri with breast cancer, DMBA-induced without breast cancer and the control group. Multidimensional statistical analysis including unsupervised principal component analysis (PCA), and orthogonal partial least squares analysis (OPLS-DA) were conducted. Furthermore, t-test was used for intergroup differential comparison. Differential metabolites were screened under VIP>1 and P<0.05 conditions, and significantly changing differential metabolites were identified using the HMDB online database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was utilized to enrich metabolic-related gene regulatory pathways. Results The incidence of breast tumors was 40% in DMBA-induced Tupaia belangeri. Compared with the control group, 30 metabolic differential products were detected in the serum of the group with breast cancer, with 18 down-regulated and 12 up-regulated (VIP>1, P<0.05). KEGG pathway analysis revealed significant changes in four metabolic pathways: glutamate metabolism, glyceride metabolism, citric acid cycle, and alanine metabolism. Compared with the group without breast cancer, 18 metabolic differential products were detected, with 7 down-regulated and 11 up-regulated (VIP>1, P<0.05). KEGG pathway analysis revealed significant changes in the citric acid cycle and glutamate metabolism. Compared with the control group, 31 metabolic differential products were detected in the serum of the groups without breast cancer, with 14 down-regulated and 17 up-regulated (VIP>1, P<0.05). KEGG pathway analysis revealed significant changes in three metabolic pathways: glutamate metabolism, glyceride metabolism, and citric acid cycle. Conclusion Metabolomics analysis can reveal the characteristics of changes in metabolites in the serum of breast tumors. The results suggest that glutamate metabolism, glyceride metabolism, citric acid cycle, and alanine metabolism pathways are associated with the occurrence and development of DMBA-induced breast tumors in Tupaia belangeri. It provides a foundation for further research into the biological mechanism of breast cancer.

Key words: Tupaia belangeri, Breast tumors, Metabolomics, 7,12-Dimethylbenzoanthracene, High fat and sugar

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