Modeling pro-death signaling pathways in cancer hepatocytes using multi-combinatorial treatments of inhibitors and stimuli

Cell death in hepatocellular carcinoma (HCC) cells as well as in other cell types is driven by a complex signaling transduction network comprised of several different pathways. In this study, we measured cell death of the HCC cell line C3A and we quantify the contribution of several signaling pathways using a reverse approach; namely instead of measuring the activity of the intracellular signal, we correlated the inhibition of that signal to the cell death. To achieve that, cells were treated with 6 stimuli and 7 inhibitors in a multi-combinatorial manner. Approximately 400 observations were made with the simultaneous treatment of up to 2 inhibitors with up to 3 stimuli. A modified linear regression model was developed to predict cell death as indicated by lactate dehydrogenase (LDH) activity. The correlation coefficients of this model were used to quantify the role of each pathway on HCC cell death. Our results are in good agreement with the literature; caspase 8 was revealed as the strongest pro-death mediator whereas the Akt pathway was shown to be the most pro-survival signal. MEK/ERK pathway had a dual role depending on the applied stimuli. Experimentally, the present method is fast, cost efficient, and easy. The coupling of the experiments to a mathematical model allowed us to quantify the contributions of a broad spectrum of pathways on cellular behavior. Additionally, such approach has a significant advantage in cases where measurements of signaling activities (i.e. from cell lysates) are experimentally impractical. For example, using the current methodology we might be able to monitor chondrocyte signaling transduction within its native environment: the articular cartilage extracellular matrix which presents a major challenge in cartilage biology.