HCV Translational Science: Solving Complex Problems Through a Multidisciplinary Approach
At Dahari Lab, we believe solving complex problems is best achieved through a multidisciplinary approach. Our research often includes theoretical (modeling), experimental (cells and animal models) and clinical (patient-based) information to answer research questions. Prof. Susan Uprichard (who participated in the development of the first robust cell culture-based HCV infection system) and Harel Dahari have co-founded a Program for Experimental and Theoretical Modeling (PETM) at Stritch School of Medicine, to promote the interdisciplinary integration of mathematical modeling and experimental biology. Our translational research is undertaken with Prof. Scott Cotler (Director, Division of Hepatology) and partnerships with clinicians from the U.S. and abroad. It is through this research and partnerships that we apply our knowledge from basic biology and clinical trials to techniques and tools designed to improve health outcomes. Overall, the research undertaken often becomes the building blocks for other areas of research. This “Science for the sake of Science” is the first step in any interdisciplinary research. It forms the backbone that leads to work and discoveries that benefit people. This science can also guide or create a check and balance for organizations like the FDA, NIH or pharmaceutical companies. Not every experiment or clinical trial yields a positive result, but it continues to strengthen the foundational knowledge of the scientific community.
Translational Science Used in Promising Results for Transplant Recipients
A compelling example of our interdisciplinary and translational research is the research by Prof. Uprichard and colleagues which revealed that HCV cell-to-cell spread is a critical antiviral drug target and that the FDA-approved drug ezetimibe (EZE; trade name Zetia®) blocks HCV entry and cell-to-cell spread (Nature Medicine). This same foundational knowledge has been applied in a new way with significant results while exploring lung and kidney transplants infected with HCV. Dahari Lab along with Prof. Jordan Feld and colleagues (Canadian cohort) showed that patients can receive a short combo of EZE + direct-acting antiviral (DAA) therapy to block the development of HCV infection once infected transplant is received. This has significant implications for the availability of organs, patient risk and care, as well as DAA cost (Lancet Gastro and Hepatol). This comes at a time when HCV infection and mortality rates in younger populations are on the rise due to the ongoing opioid crisis (CDC).
Better Understanding of the Role of the Liver in HCV Clearance through Modeling
While the liver, specifically hepatocytes, are widely accepted as the main source for HCV production, the role of the liver/hepatocytes in the clearance of circulating HCV remains largely unknown. Through kinetic and theoretical modeling (in silico) results from both liver transplantation (LT) cases (in vivo) and in cell culture experiments (in vitro) we show that the liver (and hepatocytes) plays a major role in clearing HCV from blood circulation (MEDRXIV). To the best of our knowledge, this study is the first one to investigate very detailed HCV kinetics during the absence of the liver and immediately after graft reperfusion. Our study, along with in vitro experiments suggests a role for hepatocytes in the clearance of the virus, a phenomenon which may be limited to hepatotropic viruses. The finding that the liver plays a key role in clearing HCV from the circulation has implications for clinical best practices regarding transplantation and antiviral treatment. For LT, the fact that viral levels remain at a steady state during the absence of the liver phase or anhepatic phase (i.e., the time period after patient liver is removed until the new liver is engrafted), reinforces the need of achieving viral clearance* prior to the anhepatic phase to prevent infection of the liver graft by circulating HCV in blood and avoid antiviral treatment after LT.
* Viral clearance is defined as less than 1 copy of the virus genome in the blood stream. A patient is deemed “cured” (also referred to as a sustained virological response, SVR) if six months after the end of antiviral treatment or after LT the virus is not detected in the blood.
Modeling cell-to-cell spread of hepatitis C viral (HCV) infection in vitro
HCV has two modes of transmission. It enters and spread via the cell-free mode of transmission circulating throughout the host. Once infection is established in the host via cell-free transmission, it can also spread via cell-to-cell. In this case, an infected cell can transmit the virus to adjacent cells. While much is understood about HCV entry and infection via cell-free mode of transmission, the role of HCV cell-to-cell spread in the liver is not as well known. In our research, in collaboration with Dr. Frederik Graw, we set out to quantify cell-to-cell transmission and assess the impact of cellular factors, viral factors, and antivirals (J Virology, Viruses). Our ongoing research using agent-based modeling (ABM) has greatly enhanced our understanding of this phenomenon. The ABM developed for the study more closely mirrors the complex biological system and cellular functions. The model allowed us to better approximate how the virus spreads in the liver. Due to its complexity, study of HCV in the liver is less common, relying typically, on samples found in the blood. This interactive model (Anylogic) shows what happens when direct viral infection is removed as a variable and only cell-to-cell transmission is allowed. As a result, we are able to study not only the specific mechanism by which the drugs block cell-to-cell spread, but more importantly, measure and quantify their efficacy. Our study included the use of EZE, a cell-to-cell inhibitor, which was also used successfully in blocking HCV infection in transplant patients (The Lancet Gastroenterology & Hepatology). An increased understanding of cell-to cell transmission is important because it is seen a major contributor to viral persistence including developing resistance to therapies. In the case of inhibitor drug therapies or the patient’s own antibodies which block the virus from spreading, the virus can continue to spread via cell-to-cell. Conversely, armed with this knowledge, it is possible to develop more effective anti-virals and treatments.
Limitations, Advancements and Free Open Source Numerical Methods for Parameter Estimation of HCV Kinetic Models
Dahari Lab’s commitment to advances in HCV treatment thru viral kinetic models requires constant vigilance in the area of advanced computational and mathematical methods. Modeling is not without its limitations and we are committed to pushing the boundaries in this field. Equally important is the promoting and access of these models for others to build on in their own research. We believe in an open source mindset where applicable, ensuring the greatest number of researchers world-wide have access to advance their own work.
In 2016, a partnership with Prof. Danny Barash and colleagues set in motion a series of papers that exemplify this commitment. In 2017 a robust and efficient numerical method was presented for the solution of HCV multiscale models of partial differential equations (PDE). Based on this method, a simulator for PDE with a graphical user interface (GUI) was developed (Frontiers in Applied Mathematics and Statistics). The following year the properties of the numerical solution were investigated and fine-tuned in light of advances in numerical methods (Mathematical Biosciences). The GUI was also given enhancements improving its utility (AIP Conference Proceedings). A 2019 paper followed up with a unique procedure developed to perform parameter estimation directly from the model equations (Bulletin of Mathematical Biology). This was further developed and improved in 2020 (Mathematics Special Issue Mathematical Modelling in Biomedicine).
The compound effect of this research has resulted in viral kinetic models that can be calibrated efficiently for more complicated cases. The model simulators also allow for associated quantities to be known or predicted like viral trajectory over time and patient treatment time-to-cure (Journal of Infectious Diseases; Antiviral Research).Click here to access our free (HCV) viral kinetic model simulators (standard or multiscale).