ABSTRACT: This experiment includes treatment of human pulmonary fibroblasts obtained from IPF patients with metformin. Since, we would like to investigate the transcriptome profile of these samples following metformin treatment. There will be two groups consist of four samples each. First group treated with metformin for 72 hours, while the second group treated with vehicle.
Project description:To determine whether exposure of endometrial cancer cells to metformin would induce changes in global DNA methylation, ARK2 cells were incubated with metformin for 48 h, followed by genome-scale DNA methylation profiling using platform of an improved version of Reduced Representation Bisulfite Sequencing (RRBS). Metformin treatment led to extensive methylation changes genome-wide compared to control-treated cells. We found 2000 genes became hypermethylated, and 2000 genes became hypomethylated in ARK2 treatment group.
Project description:NOD-SCID mouse were treated with metformin for 11 and 24 days, the gene expression of tumors of mice treated with metformin were compared with respect to the expression of the tumors of mouse treated with vehicle (water). We evaluated the effect of Metformin (525mg/kg/day) for two times of treatment (11 days and 24 days) upon gene expression in tumors of mice treated or not with metformin. Metformin treatment decreased of tumor growth in both treatment regimens. A complete genomic analysis of transcriptomic status after treatment with metformin revealed an impact on the overall expression of transcripts.
Project description:Objective: To study the effect of astragalus polysaccharide combined with metformin on mRNA expression profile of type 2 diabetic mice, and to explore the molecular mechanism of astragalus polysaccharide combined with metformin in the treatment of type 2 aging diabetes. Methods: Natural aging mice were induced by high-sugar and high-fat diet combined with streptozotocin to prepare aging diabetes model. The experimental mice were divided into aging control group, aging diabetes model group, metformin treatment group, astragalus polysaccharide and metformin. The treatment group was treated with gavage for 60 consecutive days. Immunohistochemical detection of insulin levels in pancreatic tissue of each group of mice, serum insulin levels were measured by mouse insulin kit to observe the treatment of aging diabetes and astragalus polysaccharide combined with metformin; using Agilent mouse whole gene expression profile chip The mRNA expression changes of liver tissues in each group were analyzed, and the differential genes were screened by bioinformatics tools and the differential genes and signal pathways were enriched and analyzed. Results: Compared with the aging group, the insulin and insulin antibody levels in the model group were significantly decreased (P<0.05). Compared with the model group, the insulin and insulin antibody levels in the two treatment groups increased (P<0.05), and jaundice The level of polysaccharide in combination with metformin was significantly higher than that in metformin group (P<0.05). The differential gene analysis of the chip showed that there were 5617 differential genes in the aging diabetes model group, 3131 were up-regulated, and 2486 were down-regulated; the Astragalus polysaccharide combined with metformin treatment group had 4767 differential genes, compared with the aging diabetes model group. 2143 up-regulated, 2624 down-regulated, genes with significant differences were mainly involved in protease activity and drug metabolism, and significantly enriched into 33 signaling pathways (P<0.01). Conclusion: The gene regulatory network plays an important role in the intervention of Astragalus polysaccharides and metformin in the treatment of aging type 2 diabetes.
Project description:Objective: To study the effect of astragalus polysaccharide combined with metformin on mRNA expression profile of type 2 diabetic mice, and to explore the molecular mechanism of astragalus polysaccharide combined with metformin in the treatment of type 2 aging diabetes. Methods: Natural aging mice were induced by high-sugar and high-fat diet combined with streptozotocin to prepare aging diabetes model. The experimental mice were divided into aging control group, aging diabetes model group, metformin treatment group, astragalus polysaccharide and metformin. The treatment group was treated with gavage for 60 consecutive days. Immunohistochemical detection of insulin levels in pancreatic tissue of each group of mice, serum insulin levels were measured by mouse insulin kit to observe the treatment of aging diabetes and astragalus polysaccharide combined with metformin; using Agilent mouse whole gene expression profile chip The mRNA expression changes of liver tissues in each group were analyzed, and the differential genes were screened by bioinformatics tools and the differential genes and signal pathways were enriched and analyzed. Results: Compared with the aging group, the insulin and insulin antibody levels in the model group were significantly decreased (P<0.05). Compared with the model group, the insulin and insulin antibody levels in the two treatment groups increased (P<0.05), and jaundice The level of polysaccharide in combination with metformin was significantly higher than that in metformin group (P<0.05). The differential gene analysis of the chip showed that there were 5617 differential genes in the aging diabetes model group, 3131 were up-regulated, and 2486 were down-regulated; the Astragalus polysaccharide combined with metformin treatment group had 4767 differential genes, compared with the aging diabetes model group. 2143 up-regulated, 2624 down-regulated, genes with significant differences were mainly involved in protease activity and drug metabolism, and significantly enriched into 33 signaling pathways (P<0.01). Conclusion: The gene regulatory network plays an important role in the intervention of Astragalus polysaccharides and metformin in the treatment of aging type 2 diabetes.
Project description:Senotherapeutics are new drugs, which can modulate senescence phenomena within tissues and reduces the onset of age-related pathologies. Senotherapeutics are divided in senolytics and senomorphics. The senolytics kill selectively senescent cells, while the senomorphics may delay or block the onset of senescence. Metformin is used for treatment of diabetes since several decades. Recently, it has been evidenced that metformin may have anti-aging properties by preventing DNA damage and inflammation. We evaluated the senomorphics effect of metformin on the biology human adipose mesenchymal stromal cells (MSCs) treated for six weeks with therapeutic doses of metformin. The study was combined with proteome analysis of changes occurring in MSCs intracellular and secretome protein composition, this to identify molecular pathways associated with the observed biological phenomena. The metformin reduced the replicative senescence and cell death phenomena, which are associated with prolonged in vitro cultivation. The continuous metformin supplementation delayed/reduced the impairment of MSC functions as evidenced by the presence of specific pathways in metformin treated samples: i) the alpha-adrenergic signaling, which contributes to regulation of MSCs physiological secretory activity; the signaling pathway associated with MSCs detoxification activity; the aspartate degradation pathway for optimal energy production. The senomorphics function of metformin seemed related to its reactive oxygen species (ROS) scavenging activity. In metformin treated samples, the CEBPA, TP53 and USF1 transcription factors appeared implicated in the regulation of several factors (SOD1, SOD2, CAT, GLRX, GSTP1) involved in blocking ROS.
Project description:Metformin is effective for prevention or treatment of various tumors. There are a lot of studies on the underlying mechanisms of metformin as respect to its anti-tumor action. We used microarrays to detail the global programme of gene expression underlying the anti-tumor effects of metformin on LoVo cells. Human derived LoVo cells were treated with metformin (10mM) for 8 and 24h, and the control and treated cells were harvested for RNA extraction and hybridization on Affymetrix microarrays.The samples were grouped as Met8h, Met24h, Con8h, and Con24h, respectively.
Project description:C20 were pre-treated with metformin at specified concentration (5 mM) for 2 h, followed by ZIKV infection at MOI 3. After infection of 1.5 h, cells were washed three times with PBS. Medium containing metformin was again supplemented and maintained during the culture. The total RNA of samples at 16 and 48 h were extracted for RNA-seq analysis. We then performed differential expression analysis using data obtained by RNA-seq of ZIKV infection and metformin treatment (16 h and 48 h).
Project description:Reduced cancer incidence has been reported among type II diabetics treated with metformin. Metformin exhibits anti-proliferative and anti-neoplastic effects associated with inhibition of mTORC1, but the mechanisms are poorly understood. We provide the first genome-wide analysis of translational targets of canonical mTOR inhibitors (rapamycin and PP242) and metformin, revealing that metformin controls gene expression at the level of mRNA translation to an extent comparable to that of canonical mTOR inhibitors. Importantly, metformin's anti-proliferative activity can be explained by selective translational suppression of mRNAs encoding cell cycle regulators via the mTORC1/4E-BP pathway. Thus, metformin selectively inhibits mRNA translation of encoded proteins that promote neoplastic proliferation, motivating further studies of this compound and related biguanides in cancer prevention and treatment. MCF7 cells were treated with rapamycin, metformin or PP242 at concentrations that inhibited proliferation to 50% of control. Both cytoplasmic and polysome-associated mRNA was extracted from treatments and a vehicle treated control and probed with microarrays.
Project description:Background: Metformin, one of the first-line medication for the treatment of type 2 diabetes and gestational diabetes, has recently be suggested for targeting cardiovascular disease, cancer and aging. Therefore, current understanding of the mechanism of this drug is incompletely understood, and the function of multiple tissues, other than liver metabolism alone, may be influenced. Methods: The wildtype healthy mice treated with metformin were compared with controls (treated with double distilled water). The transcriptome changes with/without metformin treatment were probed by using high-throughput RNA-seq techniques Results: A comprehensive mouse transcriptome map with metformin treatment across ten tissues including aorta, eyeball, brain, adipose tissue, heart, kidney, liver, skeletal muscle, stomach and testis, was provided. Function enrichment, network characteristics and disease association of the differentially expressed genes were analyzed. We also compared our expression profiles with related microarray data in order to find conditions that share similar expression profiles with metformin treatment. Conclusions: This dataset could serve as a baseline resource for investigating the potential beneficial or adverse effects of metformin across different tissues.