Abstract
Background: Cancer is a group of diseases involving changes in the cell's genome. Some cancers are inherent, while some develop from infections such as the human papillomavirus (HPV). HPV is the main cause of cervical cancer in women. Despite available treatment and prevention methods, cervical cancer is ranked fourth in both cancer incident and cancer death in women worldwide. Most available treatments are successful in treating and/or reducing cancer growth, however, cervical cancer treatment is associated with several complications such as resistance and adverse cytotoxic side effects. It is therefore crucial to continue the development of improved cancer treatments. As such, the aim of this study was to investigate the potential anti-cancerous activity of a ruthenium-based complex on HeLa cells. In addition, we sought out to gain an insight on the possible mechanism of action. Methods: Metals are known to possess bioactivity and in this study, the bioactivity of a ruthenium complex was investigated for its cytotoxicity against a HeLa cell model, which is representative of cervical cancer. The HeLa cells were cultured and the anti-tumour activity of the complex was measured using alamar blue dye reduction assay. The alamar blue assay was also used to determine the inhibitory concentration of the cell, were 50% of cells were viable (IC50). To confirm cytotoxicity, morphological studies through light microscopy, Mitotracter staining and Hoechst staining were performed. Flow cytometry double staining with propidium iodide and annexin- V was performed to detect the mode of cell death (apoptosis or necrosis) following treatment with various concentrations of the Ru (II) complex. Apoptotic cell death is primarily accompanied by caspase 3/7 activity. Caspase 3/7 activity was therefore measured using the caspase 3/7 activity assay on the HeLa cells. To decipher metabolic reprogramming induced by the ruthenium complex on the Hela cellular metabolome, 1H NMR-based untargeted metabolomics was conducted. NMR data pre-processing was done using TopSpin 3.6.2, imported to AMIX-viewer 3.9.12 and exported to Soft Independent Modeling of Class Analogy (SIMCA) for statistical analysis. Multivariate statistical analysis such as Principal Component Analysis (PCA) and partial least square discriminant analysis (PLS-DA) were applied to determine significantly altered metabolites...
M.Sc. (Biotechnology)