Líffræðifélag Íslands
Líffræðiráðstefnan 2015
Erindi/veggspjald / Talk/poster E54
Skarphéðinn Halldórsson (1,3), Neha Rohatgi(1), Sonal Kumari(1), Manuela Magnúsdóttir(1) , Thorarinn Gudjonsson(2,3), Magnus K. Magnussson(2,3), Steinn Gudmundsson(1) and, Óttar Rolfsson(1,2)
1. Centre For Systems Biology, University Of Iceland, Reykjavik, Iceland, 2. Medical Department, University of Iceland, Reykjavik, Iceland, 3. Stem Cell Research Unit/Biomedical Centre, University of Iceland, Reykjavik, Iceland
Kynnir / Presenter: Skarphéðinn Halldórsson
Tengiliður / Corresponding author: Skarphéðinn Halldórsson (skarph@hi.is)
In recent years, cancer metabolism has gained increasing attention. A number of distinct metabolic alterations have been described in tumor tissue, such as reduced oxidative phosphorylation and increased glycolysis. However, tumor progression has been less explored with regard to metabolism. Many cancers originate in epithelial tissue but have a tendency to transition from an epithelial to a mesenchymal phenotype (EMT) that is capable of migrating through the body and metastasize elsewhere. EMT depends on a variety of signaling and regulatory pathways as well as epigenetic changes, producing cells with distinct mesenchymal characteristics. We have developed cell specific genome scale computational models based on transcriptomic and metabolomic data from distinct epithelial and mesenchymal phenotypes of a breast epithelial cell line. Metabolic flux changes were observed in core energy pathways including oxidative phosphorylation, glycolysis and the TCA cycle. Epithelial cells were observed to rely more on aerobic glycolysis and oxidative phosphorylation while mesenchymal cells had relatively more flux through the pentose phosphate pathway and reductive glutamine metabolism. Furthermore, we developed a network of EGFR/IGFR and TGFβ signaling pathway using a stoichiometric approach describing molecular transformations involved in EMT. This enabled predictions of how changes in expression of signaling and transcriptional genes alone are translated into flux responses at the metabolic level. We aim to further develop these models by incorporating lipidomic data for both phenotypes as resent studies indicate that membrane reconstruction and lipid signaling may be crucial steps in the development of EMT.