“The growth and survival of cancer cells can often be impaired by treatment with drugs that interfere with the actions of one or more oncogenes,” said Prahlad Ram, the senior author of the study and Professor at the University of Texas MD Anderson Cancer Center, Houston, Texas. “However, the clinical benefits to patients are often short lived due to acquired drug resistance. Finding alternative intervention points or so-called new addictions for cancer cells is of critical importance for designing novel therapeutic strategies against tumours. Our results reveal specific new targets for drug intervention in the metabolic pathways of cancer cells and identify existing drugs that can be used to treat drug-resistant cancer.”
The scientists used microarrays to measure gene expression in breast cancer cells with and without treatment with Lapatinib. Computational analysis of more than 15000 gene interactions revealed four major populations of genes that were regulated in a significant way. Three of these groups were the regular suspects related to drug resistance, such as genes involved in oxidation and reduction reactions or cell cycle processes. A fourth group comprised a network of reactions linked to the deprivation of glucose.
Analysis of the gene expression networks of ErbB2-positive breast cancer patients revealed that the glucose deprivation network is linked to low survival rates of the patients. Computational screening of a library of existing drugs for therapeutics that target the glucose deprivation response identified several drugs that could be effective in treating drug-resistant breast cancer.
“By developing novel gene expression analysis algorithms and integrating diverse data, we have been able to look beyond changes in the immediate molecular signaling pathways of breast cancer cells and to consider the wider system of molecular networks within the cell,” remarked Ram. “Our approach predicts new uses for existing drugs that impact the metabolism of breast cancer cells and may offer an expedient route to improved treatments for breast cancer patients.”The glucose-deprivation response network counteracts EGFR signalling in lapatinib resistant cells
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A human liver cell atlas
15.07.2019 | Max Planck Institute of Immunobiology and Epigenetics
Researchers reveal mechanisms for regulating temperature sensitivity of soil organic matter decompos
15.07.2019 | Chinese Academy of Sciences Headquarters
For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.
Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...
An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".
The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...
An interdisciplinary research team at the Technical University of Munich (TUM) has built platinum nanoparticles for catalysis in fuel cells: The new size-optimized catalysts are twice as good as the best process commercially available today.
Fuel cells may well replace batteries as the power source for electric cars. They consume hydrogen, a gas which could be produced for example using surplus...
The fly agaric with its red hat is perhaps the most evocative of the diverse and variously colored mushroom species. Hitherto, the purpose of these colors was...
Physicists at the Max Planck Institute for Nuclear Physics in Heidelberg report the first result of the new Alphatrap experiment. They measured the bound-electron g-factor of highly charged (boron-like) argon ions with unprecedented precision of 9 digits. In comparison with a new highly accurate quantum electrodynamic calculation they found an excellent agreement on a level of 7 digits. This paves the way for sensitive tests of QED in strong fields like precision measurements of the fine structure constant α as well as the detection of possible signatures of new physics. [Physical Review Letters, 27 June 2019]
Quantum electrodynamics (QED) describes the interaction of charged particles with electromagnetic fields and is the most precisely tested physical theory. It...
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