10 research outputs found

    Metformin prevents aggressive ovarian cancer growth driven by high-energy diet: similarity with calorie restriction.

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    Caloric restriction (CR) was recently demonstrated by us to restrict ovarian cancer growth in vivo. CR resulted in activation of energy regulating enzymes adenosine monophosphate activated kinase (AMPK) and sirtuin 1 (SIRT1) followed by downstream inhibition of Akt-mTOR. In the present study, we investigated the effects of metformin on ovarian cancer growth in mice fed a high energy diet (HED) and regular diet (RD) and compared them to those seen with CR in an immunocompetent isogeneic mouse model of ovarian cancer. Mice either on RD or HED diet bearing ovarian tumors were treated with 200 mg/kg metformin in drinking water. Metformin treatment in RD and HED mice resulted in a significant reduction in tumor burden in the peritoneum, liver, kidney, spleen and bowel accompanied by decreased levels of growth factors (IGF-1, insulin and leptin), inflammatory cytokines (MCP-1, IL-6) and VEGF in plasma and ascitic fluid, akin to the CR diet mice. Metformin resulted in activation of AMPK and SIRT1 and inhibition of pAkt and pmTOR, similar to CR. Thus metformin can closely mimic CR\u27s tumor suppressing effects by inducing similar metabolic changes, providing further evidence of its potential not only as a therapeutic drug but also as a preventive agent

    Folic acid tagged nanoceria as a novel therapeutic agent in ovarian cancer

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    BACKGROUND: Nanomedicine is a very promising field and nanomedical drugs have recently been used as therapeutic agents against cancer. In a previous study, we showed that Nanoceria (NCe), nanoparticles of cerium oxide, significantly inhibited production of reactive oxygen species, cell migration and invasion of ovarian cancer cells in vitro, without affecting cell proliferation and significantly reduced tumor growth in an ovarian cancer xenograft nude model. Increased expression of folate receptor-α, an isoform of membrane-bound folate receptors, has been described in ovarian cancer. To enable NCe to specifically target ovarian cancer cells, we conjugated nanoceria to folic acid (NCe-FA). Our aim was to investigate the pre-clinical efficacy of NCe-FA alone and in combination with Cisplatin. METHODS: Ovarian cancer cell lines were treated with NCe or NCe-FA. Cell viability was assessed by MTT and colony forming units. In vivo studies were carried in A2780 generated mouse xenografts treated with 0.1 mg/Kg NCe, 0.1 mg/Kg; NCe-FA and cisplatinum, 4 mg/Kg by intra-peritoneal injections. Tumor weights and burden scores were determined. Immunohistochemistry and toxicity assays were used to evaluate treatment effects. RESULTS: We show that folic acid conjugation of NCe increased the cellular NCe internalization and inhibited cell proliferation. Mice treated with NCe-FA had a lower tumor burden compared to NCe, without any vital organ toxicity. Combination of NCe-FA with cisplatinum decreased the tumor burden more significantly. Moreover, NCe-FA was also effective in reducing proliferation and angiogenesis in the xenograft mouse model. CONCLUSION: Thus, specific targeting of ovarian cancer cells by NCe-FA holds great potential as an effective therapeutic alone or in combination with standard chemotherapy

    A metabolomic approach to identifying platinum resistance in ovarian cancer

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    BACKGROUND: Acquisition of metabolic alterations has been shown to be essential for the unremitting growth of cancer, yet the relation of such alterations to chemosensitivity has not been investigated. In the present study our aim was to identify the metabolic alterations that are specifically associated with platinum resistance in ovarian cancer. A global metabolic analysis of the A2780 platinum-sensitive and its platinum-resistant derivative C200 ovarian cancer cell line was performed utilizing ultra-high performance liquid chromatography/mass spectroscopy and gas chromatography/mass spectroscopy. Per-metabolite comparisons were made between cell lines and an interpretive analysis was carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic library and the Ingenuity exogenous molecule library. RESULTS: We observed 288 identified metabolites, of which 179 were found to be significantly different (t-test p \u3c 0.05) between A2780 and C200 cells. Of these, 70 had increased and 109 had decreased levels in platinum resistant C200 cells. The top altered KEGG pathways based on number or impact of alterations involved the cysteine and methionine metabolism. An Ingenuity Pathway Analysis also revealed that the methionine degradation super-pathway and cysteine biosynthesis are the top two canonical pathways affected. The highest scoring network of altered metabolites was related to carbohydrate metabolism, energy production, and small molecule biochemistry. Compilation of KEGG analysis and the common network molecules revealed methionine and associated pathways of glutathione synthesis and polyamine biosynthesis to be most significantly altered. CONCLUSION: Our findings disclose that the chemoresistant C200 ovarian cancer cells have distinct metabolic alterations that may contribute to its platinum resistance. This distinct metabolic profile of platinum resistance is a first step towards biomarker development for the detection of chemoresistant disease and metabolism-based drug targets specific for chemoresistant tumors

    Isatin Derived Spirocyclic Analogues with α‑Methylene-γ-butyrolactone as Anticancer Agents: A Structure–Activity Relationship Study

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    Design, synthesis, and evaluation of α-methylene-γ-butyrolactone analogues and their evaluation as anticancer agents is described. SAR identified a spirocyclic analogue <b>19</b> that inhibited TNFα-induced NF-κB activity, cancer cell growth and tumor growth in an ovarian cancer model. A second iteration of synthesis and screening identified <b>29</b> which inhibited cancer cell growth with low-μM potency. Our data suggest that an isatin-derived spirocyclic α-methylene-γ-butyrolactone is a suitable core for optimization to identify novel anticancer agents

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