(182e) Metabolomic Analysis of Ovarian Cancer | AIChE

(182e) Metabolomic Analysis of Ovarian Cancer

Authors 

Styczynski, M. P. - Presenter, Georgia Institute of Technology
Vermeersch, K. - Presenter, Georgia Institute of Technology


Here, we present a metabolomic analysis of two ovarian cancer cell lines: OVCAR-3, and a tumor-initiating cell line derived from OVCAR-3.  We aim to characterize the metabolic differences between these two lines in physiologically relevant perturbations representative of conditions encountered in the tumor microenvironment.  Conditions studied include carbon source deprivation, hypoxia, pH change, and chemotherapy treatment.  Additionally, we also aim to characterize the metabolic phenotype associated with the mesenchymal-epithelial transition (MET).

The contribution of dysfunctional metabolism to the progression and phenotypes of cancer is increasingly being recognized, despite a decades-long stretch when genetics drove the vast majority of cancer research.  While it is now well-known that cancers are usually characterized by an increase in glycolytic flux and fermentation, the extent of the impact of metabolism on cancer’s phenotypes and progression is still uncertain.  We hypothesize that there is a distinct metabolic signature for the two cell lines under study in different physiological conditions that contributes to their different phenotypes – most notably, the resistance to chemotherapy that is characteristic of tumor-initiating cells.  Additionally, we also hypothesize that there are gross metabolic changes that characterize the mesenchymal-epithelial transition.

Here, we use two-dimensional gas chromatography coupled to mass spectrometry (GCxGC-MS) to measure intracellular and extracellular metabolites in ovarian cancer cell lines.  As expected, we are able to capture metabolic changes in response to different perturbations, both on an individual metabolite level as well as via dimensional reduction analysis of the entire dataset.  We report the differences observed between the two cell lines’ metabolic responses and present a pathway-based analysis of the metabolic behaviors observed.