Analysis of steady-state and dynamic properties of human ovarian cancer cell metabolism

Τούμπε, Ηλίας; Toumpe, Ilias

dc.contributor.author	Τούμπε, Ηλίας	el
dc.contributor.author	Toumpe, Ilias	en
dc.date.accessioned	2023-03-10T08:36:07Z
dc.date.available	2023-03-10T08:36:07Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/57222
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.24920
dc.rights	Αναφορά Δημιουργού-Όχι Παράγωγα Έργα 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nd/3.0/gr/	*
dc.subject	Μεταβολική Μηχανική	el
dc.subject	Καρκίνος	el
dc.subject	Μεταβολισμός	el
dc.subject	Φαρμακευτικοί στόχοι	el
dc.subject	Κινητικά μοντέλα	el
dc.subject	Metabolic Engineering	en
dc.subject	Cancer	en
dc.subject	Drug targets	en
dc.subject	Constraint-based modeling	en
dc.subject	Kinetic modeling	en
dc.title	Analysis of steady-state and dynamic properties of human ovarian cancer cell metabolism	en
dc.title	Ανάλυση μόνιμης κατάστασης και δυναμικών ιδιοτήτων του μεταβολισμού των ανθρώπινων καρκινικών κυττάρων ωοθήκης	el
heal.type	bachelorThesis
heal.generalDescription	H διπλωματική εργασία πραγματοποιήθηκε σε συνεργασία με την ομάδα του Καθηγητή Β. Χατζημανικάτη, LCSB, EPFL.	el
heal.classification	Μεταβολική Μηχανική	el
heal.classification	Βιοτεχνολογία	el
heal.classification	Συστημική Βιολογία	el
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2022-09-26
heal.abstract	This thesis aimed to build dynamic and steady-state models that describe the physiology of human ovarian cancer cells. A reduced constraint-based metabolic model derived from the Recon3D GEM was used along with thermodynamic, transcriptomic, metabolomic, and fluxomic data to examine the steady-state properties of ovarian cancer metabolism. To build the kinetic models, the directionalities of all reactions should be predefined. While the integrated data and other manually added constraints significantly reduced the number of bidirectional reactions, many remained. A modified ACHR sampling algorithm was used to sample feasible steady-state profiles, and the average sample point was used to extract directionalities for the remaining bidirectional reactions. Further thermodynamic curations and modal analysis implementation resulted in the production of steady sets of kinetic parameters that could also operate in physiologically relevant timeframes. Possible drug targets were proposed through Metabolic Control Analysis and further examined through simulations of enzyme perturbations. Enzymes Hexokinase (HEX1) and ATPM (ATP maintenance requirement reaction) significantly affected the cell’s survival, and Long-chain-fatty- acid—CoA ligase (FACOAL1821) showcased similar results, although to a lesser extent. Lastly, the model responses uncovered reaction r0474, which represents one of the many catalyzed reactions of the enzyme Ribonucleoside diphosphate reductase, as a promising drug target for mitigating cancer proliferation. All these enzymes are connected with deregulated metabolic pathways in cancer cells and have been suggested as interesting points for treatment development. Overall, the methods used and developed allowed for the production of the first large-scale kinetic model of ovarian cancer. Using this model, it is possible to identify drug targets for cancer elimination, perform simulations of dynamic responses of the cancer cell’s metabolic network as well as quantify the effects of candidate drug targets on cancer proliferation. Using such models can assist the study of specific types of cancer cells’ physiology and accelerate the drug development process. Physiology-specific drug targets can be suggested, and early estimations of the toxicity response and effective drug dosages can be calculated.	en
heal.sponsor	Masters Thesis Grant - Zeno Karl Schindler Foundation	en
heal.advisorName	Μπουντουβής, Ανδρέας	el
heal.committeeMemberName	Μπουντουβής, Ανδρέας	el
heal.committeeMemberName	Μαμμά, Διομή	el
heal.committeeMemberName	Χατζημανικάτης, Βασίλης	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Χημικών Μηχανικών. Τομέας Ανάλυσης, Σχεδιασμού και Ανάπτυξης Διεργασιών και Συστημάτων (ΙΙ)	el
heal.academicPublisherID	ntua
heal.numberOfPages	50 σ.	el
heal.fullTextAvailability	false