ABSTRACT
Diabetes mellitus (DM) is a chronic metabolic disease caused by multiple etiologies.Diabetic retinopathy (DR), as a primary ocular complication of DM, is the leading cause of blindness among working-age adults in the world.With the rapid increase of diabetes incidence worldwide, the diagnosis of DR is often delayed because few symptoms of the retinal vessel-nurse unit lesion are found in early DR.Therefore, the early diagnosis, prevention and treatment of DR are facing much more challenges.At present, the early clinical biomarkers of DR, such as glycosylated hemoglobin and blood glucose, are of great value in predicting and preventing the occurrence and development of DR, but there is still a lack of research on the pathological effect of metabolic heterogeneity and its potential induction of DR.Multi-omics methods, such as metabolomics and single-cell transcriptome, as well as deep learning techniques, are powerful tools for the study of DR pathophysiological processes, which can be used to reveal the metabolic characteristics of DR, discover early biomarkers and new metabolic pathways and identify targets for treatment.Future advances which aim to diagnose and treat DR should consider the metabolic remodeling induced by genetic background and environmental factors comprehensively, combine omics approaches and the measurement of clinical indicators of DR occurrence and development to find biomarkers of early DR and targets so as to achieve early prediction and accurate prevention of DR.
ABSTRACT
OBJECTIVE Gastric cancer is one of the most common malignant tumors,and the inci-dence rate is the highest in all kinds of tumors in China. However,it remains unclear that how signifi-cantly gastric cells are dependent on glycolysis,and which type of gastric cells are sensitive to glycolysis inhibition. In this study, several kind of gastric cancer cell lines were used as the research object, and the metabolic characteristics of different cell lines were systematically analyzed to provide theoretical support for the accurate treatment of gastric cancer. METHODS We examined the energy metabolism of four gastric cancer cell lines(MGC-803,SGC-7901,HGC-27 and BGC-823)by using glycolysis inhibitor, 2-deoxy-D-glucose(2-DG)and inhibitor of oxidative phosphorylation,oligomycin.Oxygen consumption rates(OCR)and L-lactate were also measured with an XF96 Analyzer(Seahorse Biosciences)to deter-mine the significance of metabolism of oxidative phosphorylation and aerobic glycolysisin gastric cells. In addition, western blot was used to detect the contribution of AMP-activated protein kinase (AMPK), and anti-apoptotic proteins(Bcl-2 and survivin)to clarify the mechanism of death or survival of gastric cancer cells treated by 2-DG or oligomycin. RESULTS In this study, it was shown that the growth of gastric cell lines were suppressed by 2-DG.However,the sensitivity to 2-DG was quite different among cell lines:IC 50 of 2-DG was from 3.28 mmol·L-1(MGC-803)to 15.57 mmol·L-1(BGC-823).MGC-803 was relatively sensitive to 2-DG (IC 50:3.28 mmol·L-1), consumed more glucose and produced more lactate (waste product of glycolysis) than the three other cell lines. Consequently, MGC-803 could be more dependent on glycolysis than other cell lines, which was further confirmed by the fact that glucose (+)FCS(-)medium showed more growth and survival than glucose(-)FCS(+)medium.Alternatively, BGC-823, most resistant to 2-DG (IC50: 15.57 mmol·L- 1), was most sensitive to oligomycin, and showed more growth and survival in glucose(-)FCS(+)medium than in glucose(+)FCS(-)medium. Thus,we had reasons to think BGC-823 cells depended on oxidative phosphorylation for energy production. In BGC-823,AMPK,which is activated when ATP becomes limiting,was rapidly phosphorylated by 2-DG, and expression of Bcl-2 was augmented,which might result in resistance to 2-DG.Interestingly,AMPK phosphorylation and augmentation of Bcl-2 expression by 2-DG were not observed in MGC-803,which is 2-DG sensitive. CONCLUSION There is a large metabolic difference between gastric cancer cell lines,which will facilitate the future gastric cancer therapy by targeting metabolic pathways.