Modeling hepatitis C virus protein and p53 interactions in hepatocytes: Implications for carcinogenesis

Hepatitis C virus (HCV) infection has reached epidemic proportions worldwide. Individuals with chronic HCV infection and without access to treatment are at high risk for developing hepatocellular carcinoma (HCC), a liver cancer that is rapidly fatal after diagnosis. A number of factors have been identified that contribute to HCV-driven carcinogenesis such as scarring of the liver, and chronic inflammation. Recent evidence indicates a direct role for HCV-encoded proteins themselves in oncogenesis of infected hepatocytes. The viral protein HCV core has been shown to interact directly with the host tumor suppressor protein p53, and to modulate p53-activity in a biphasic manner. Here, biochemically-motivated mathematical models of HCV-p53 interactions are developed to elucidate the mechanisms underlying this phenomenon. We show that by itself, direct interaction between HCV core and p53 is insufficient to recapitulate the experimental data. We postulate the existence of an additional factor, activated by HCV core that inhibits p53 function. We present experimental evidence in support of this hypothesis. The model including this additional factor reproduces the experimental results, validating our assumptions. Finally, we investigate what effect HCV core-p53 interactions could have on the capacity of an infected hepatocyte to repair damage to its DNA. Integrating our model with an existing model of the oscillatory response of p53 to DNA damage predicts a biphasic relationship between HCV core and the transformative potential of infected hepatocytes. In addition to providing mechanistic insights, these results suggest a potential biomarker that could help in identifying those HCV patients most at risk of progression to HCC.

Nonlinear modelling of cancer: bridging the gap between cells and tumours

Despite major scientific, medical and technological advances over the last few decades, a cure for cancer remains elusive. The disease initiation is complex, and including initiation and avascular growth, onset of hypoxia and acidosis due to accumulation of cells beyond normal physiological conditions, inducement of angiogenesis from the surrounding vasculature, tumour vascularization and further growth, and invasion of surrounding tissue and metastasis. Although the focus historically has been to study these events through experimental and clinical observations, mathematical modelling and simulation that enable analysis at multiple time and spatial scales have also complemented these efforts. Here, we provide an overview of this multiscale modelling focusing on the growth phase of tumours and bypassing the initial stage of tumourigenesis. While we briefly review discrete modelling, our focus is on the continuum approach. We limit the scope further by considering models of tumour progression that do not distinguish tumour cells by their age. We also do not consider immune system interactions nor do we describe models of therapy. We do discuss hybrid-modelling frameworks, where the tumour tissue is modelled using both discrete (cell-scale) and continuum (tumour-scale) elements, thus connecting the micrometre to the centimetre tumour scale. We review recent examples that incorporate experimental data into model parameters. We show that recent mathematical modelling predicts that transport limitations of cell nutrients, oxygen and growth factors may result in cell death that leads to morphological instability, providing a mechanism for invasion via tumour fingering and fragmentation. These conditions induce selection pressure for cell survivability, and may lead to additional genetic mutations. Mathematical modelling further shows that parameters that control the tumour mass shape also control its ability to invade. Thus, tumour morphology may serve as a predictor of invasiveness and treatment prognosis.