Metabolomics study reveals the potential evidence of metabolic reprogramming towards the Warburg effect in precancerous lesions.
Metabolomics study reveals the potential evidence of metabolic reprogramming towards the Warburg effect in precancerous lesions.
复制标题
代谢组学研究揭示了癌前病变中代谢重编程对 Warburg 效应的潜在证据
DOI:
10.7150/jca.54252
复制
发表时间:
2021
影响因子:
3.9
通讯作者:
Yu D
中科院分区:
文献类型:
--
作者:
Chen X;Yi C;Yang MJ;Sun X;Liu X;Ma H;Li Y;Li H;Wang C;He Y;Chen G;Chen S;Yu L;Yu D
Background: Most tumors have an enhanced glycolysis flux, even when oxygen is available, called the aerobic glycolysis or the Warburg effect. Metabolic reprogramming promotes cancer progression, and is even related to the tumorigenesis. However, it is not clear whether the observed metabolic changes act as a driver or a bystander in cancer development. Methods: In this study, the metabolic characteristics of oral precancerous cells and cervical precancerous lesions were analyzed by metabolomics, and the expression of glycolytic enzymes in cervical precancerous lesions was evaluated by RT-PCR and Western blot analysis. Results: In total, 115 and 23 metabolites with reliable signals were identified in oral cells and cervical tissues, respectively. Based on the metabolome, oral precancerous cell DOK could be clearly separated from normal human oral epithelial cells (HOEC) and oral cancer cells. Four critical differential metabolites (pyruvate, glutamine, methionine and lysine) were identified between DOK and HOEC. Metabolic profiles could clearly distinguish cervical precancerous lesions from normal cervical epithelium and cervical cancer. Compared with normal cervical epithelium, the glucose consumption and lactate production increased in cervical precancerous lesions. The expression of glycolytic enzymes LDHA, HK II and PKM2 showed an increased tendency in cervical precancerous lesions compared with normal cervical epithelium. Conclusions: Our findings suggest that cell metabolism may be reprogrammed at the early stage of tumorigenesis, implying the contribution of metabolic reprogramming to the development of tumor.
登录
查看更多内容
影响因子:
29
作者:
Pavlova NN;Thompson CB
通讯作者:
Thompson CB
影响因子:
21.3
作者:
Cox AG;Hwang KL;Brown KK;Evason K;Beltz S;Tsomides A;O'Connor K;Galli GG;Yimlamai D;Chhangawala S;Yuan M;Lien EC;Wucherpfennig J;Nissim S;Minami A;Cohen DE;Camargo FD;Asara JM;Houvras Y;Stainier DYR;Goessling W
通讯作者:
Goessling W
影响因子:
82.9
作者:
Wang, Zhenxun;Yip, Lian Yee;Tam, Wai Leong
通讯作者:
Tam, Wai Leong
DOI:
10.1093/bioinformatics/bty528
发表时间:
2018-12-15
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Chong J;Xia J
通讯作者:
Xia J
影响因子:
64.8
作者:
Gao, Xia;Sanderson, Sydney M.;Locasale, Jason W.
通讯作者:
Locasale, Jason W.