树鼩乳腺肿瘤模型的代谢组学分析  

Metabolomics Analysis of Tupaia belangeri Breast Tumor Model

作　　者：方茜 敖青青 李春宏 欧阳轶强 郭松超 胡冰 FANG Xi;AO Qingqing;LI Chunhong;OUYANG Yiqiang;GUO Songchao;HU Bing(Laboratory Animal Center,Guangxi Medical University,Nanning 530021,China;Guilin People's Hospital,Guilin 541002,China)

机构地区：[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

出　　处：《实验动物与比较医学》2024年第1期52-61,共10页Laboratory Animal and Comparative Medicine

基　　金：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)。

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3Objective To explore the metabolic changes during the development of Tupaiabelangeri 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 Tupaiabelangeri 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 Tupaiabelangeriwith 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 Tupaiabelangeri.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 citr

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 

分 类 号：Q95-33[生物学—动物学] R-332[医药卫生]