PubMed · 15958607
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Pavan Bachireddy, Pavan K Bendapudi, Dean W Felsher. 2005-06-15. Getting at MYC through RAS.. https://doi.org/10.1158/1078-0432.ccr-05-0534
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The effects of echovirus 11 infection on RD human cell line (derived from rhabdomyosarcoma) were studied using (1)H NMR spectroscopy and optical microscopy. Both uninfected and infected cells consumed glucose and produced lactate, acetate and formate as extracellular metabolites. In infected whole cells, phosphocholine and uridine-sugar were observed in addition to the metabolites observed in uninfected cells. Water-soluble intracellular metabolites of infected cells showed glutamine, phosphocholine and glycine which were not observed in uninfected cells. Cellular metabolites except lipid components gradually decreased and disappeared during 24-48 h of viral infection. The quantity of lipid components in infected cells was comparable with that in uninfected cells, indicating that echovirus 11 does not utilize cell lipid molecules. Unlike optical microscopy, (1)H NMR spectroscopy identified early stages of infection through metabolic changes. These results may have potential implications in probing virus-cell interactions using NMR-based metabolomics.
A macrokinetic model for a myeloma cell line is proposed. The model describes the dynamic balances of lactate, alanine, ATP and NADH during the metabolsim of glucose, glutamine and other amino acids. The metabolic pathways mainly include glycolysis, glutaminolysis, the trcicarboxylic acid cycle, the formation and utilization of amino acids, the respiratory chain, cell growth and cell death. The metabolic shift of glucose is especially considered because of a change in the rate of glycolysis. Thus the model functions in three modes to describe the behaviour of the myeloma cell line. On the basis of this model the macrokinetic bioreaction rates such as the specific substrate consumption rate, the specific growth rate, the specific acetyl-CoA formation rate, as well as the specific oxygen uptake rate, are estimated. The specific substrate consumption rate and the specific growth rate are then coupled into a bioreactor model such that the key variables, i.e., the cell density, the substrate and metabolite concentrations, are obtained. Experiments with batch and fed-batch cultures of a myeloma cell line (X63-Ag8.653) were used to validate the model. The prediction of the model was simulated by the rolling prediction approach.
The EphA2 tyrosine kinase receptor is frequently overexpressed in ovarian cancer and this feature is predictive of poor clinical outcome. Preclinical investigation has also linked EphA2 with p53. In our present study, we examined EphA2 and p53 status (both expression and full-length mutation status) in 6 ovarian cell lines and 79 human ovarian cancers to determine potential associations. EphA2 was overexpressed in 80% of ovarian cancer cell lines and in 75% of clinical specimens. In particular, high levels of EphA2 occurred in 91% of tumors with p53 null mutations compared to 68% in tumors with wild-type or missense mutations (p=0.027). EphA2 expression did not relate to critical versus non-critical site missense p53 mutations or the location of mutations on specific p53 exons. We also demonstrated that while EphA2 and p53 can provide independent information regarding clinical status, the combination of EphA2 and p53 status can predict poor clinical outcome. In particular, the combination of EphA2 overexpression and p53 null status was associated with decreased overall patient survival and related to increased incidence of ascites and distant metastasis. Taken together, these data indicate a complex relationship between EphA2 and p53 that appears to regulate EphA2 expression and clinical outcome.