Funding opportunities

Mathematic Optimization of Multiple Signals for Stem Cell Differentiation into Hepatocytes

Funding Type: 
Basic Biology I
Grant Number: 
Funds requested: 
$1 304 745
Funding Recommendations: 
Not recommended
Grant approved: 
Public Abstract: 
Hepatitis C virus (HCV) is a major human health concern with an estimated 170 million people infected with HCV worldwide. In comparison, 40 million people are infected with HIV in the world. HCV causes liver diseases including chronic hepatitis, cirrhosis, and hepatocellular carcinoma. Approximately 5 million people in the United State are infected with HCV. Persons with HCV often show no signs or symptoms of the disease until they have reached end-stage liver disease, 20, 30 even 50 years after the initial infection. Many people do not realize that they are infected. Treatment for HCV is only efficient in a portion of patients. Once a patient has developed end-stage liver disease, their only treatment option is often a liver transplant, which only extends their life for a short period of time. Liver failure due to HCV infection presents an excellent case calling for improvement of stem cell technology as a potential therapeutic approach. Liver tissue is one of the tissues that can be most easily regenerated, offering a favorable opportunity to demonstrate the promise of stem cell therapy. There are a few rate limiting steps in stem cell therapy. One is the low efficiency of differentiation into specific cell types. The differentiation process involves multiple signals. Defining the optimal combination of multiple signals is a challenge to traditional biology. We will use a mathematic approach to overcome this problem. The mathematic modeling and search algorithms will allow us to understand the interactions among multiple signals that control the cell differentiation and thereby optimize the process. Another rate limiting step in cell therapy is how to replace the existing cells with the newly derived cells. Here the cell killing due to HCV infection offers the opportunity. We can modify the stem cells to confer resistance to HCV infection, which will provide selection advantage over the original liver cells that are more susceptible to HCV infection. The selection pressure imposed by HCV can be used to efficiently replace the original liver cells with modified liver cells derived from stem cells. Thus, the proposed study can be a good test case. This proposal addresses fundamental issues in stem cell biology while providing potential application. It combines the expertise of cell biology and virology with mathematics to define and optimize stem cell differentiation process. The utilization of a tractable mouse model that directly reflects human cell differentiation, viral infection, and tissue regeneration process, establishes a solid foundation for future clinical application.
Statement of Benefit to California: 
An estimated 600,000 Californians are infected with HCV. Many of them are unaware of the fact that they are infected. California’s public and private healthcare systems have experienced increased demand for Hepatitis C services, including patient and provider education and case management. California’s public and private healthcare systems are therefore under great economic pressure to treat Hepatitis C, a life threatening liver disease. Hepatitis C impacts the families, friends, employees and communities of those with HCV. California’s economic loss due to HCV infection is several billion dollars annually. The treatment for HCV is only partially effective. Once a patient has advanced to end-stage liver disease, current drug treatments may not be well tolerated and could worsen the health status of the patient. For these patients the only available treatment option is liver transplantation. Liver transplantation however can only extend the life and cannot eliminate viral infection, which will recur soon. Although several HCV-drugs are in pipelines, the potential emerging of drug-resistant HCV is well expected for fast mutating RNA viruses. Up to 10 percent of HCV+ individuals are also HIV+. Roughly 6 percent of individuals co-infected with both viruses will not develop antibodies to HCV, making detection of the virus and the treatment more complicated. Thus a new treatment approach is urgently needed. Stem cell therapy is one of the promising approaches to treat HCV infected patients. California Hepatitis C Task Force is one of the organizations that strongly support the legislation that resulted in the establishment of the California Institute for Regenerative Medicine. One of the bottle necks of applying stem cell treatment is the low efficiency of differentiating progeny cells into liver cells. Here we are taking a novel approach by combining mathematics with updated stem cells technology to generate liver cells. Furthermore, we will modify the cells to make them resistant to HCV infection or slow down their replication. Such HCV-resistant cells will be injected into the patients’ liver and will gradually replace the original susceptible liver cells. Thus this liver regeneration approach will cure or prevent liver failure with a relatively simple procedure in comparison with liver transplantation. Although this proposal focuses on liver cell regeneration and the potential therapeutic application for HCV infected patients, the methods being developed in this proposal are generally applicable to stem cell biology as well as the applications. Therefore, this research can significantly accelerate the advancement of CIRM’s mission.
Review Summary: 
The goal of this proposal is to use mathematical algorithms to improve the efficiency of differentiation of human pluripotent stem cells (hPSCs) into hepatocytes. In Aim 1, the applicant proposes to construct predictive models of hepatocyte differentiation by testing many combinations of stimuli and applying mathematical algorithms to the resultant data. Differentiated hepatocytes will be generated and evaluated for function in vitro, including the ability to support infection by Hepatitis C Virus (HCV). The applicant will attempt to address the mechanisms of differentiation by quantifying changes in protein phosphorylation states in individual cells along the differentiation axis. In Aim 2, the applicant proposes to verify the biological relevance of their findings by examining the ability of the hPSC-derived hepatocytes generated in Aim 1 to functionally engraft in a permissive immunodeficient mouse model. Reviewers agreed that this proposal addresses a major unsolved problem and would have a significant impact if successful. However, they did not find it innovative, noting that with the exception of the proposed mathematical modeling, the experiments described are a collection of well-established and only partially successful protocols for differentiating hepatocytes. Furthermore, they did not feel the applicant clearly articulated the rationale for using a mathematical algorithm to model and optimize multifactorial cell signaling. Reviewers also did not find the proposal to be particularly focused on molecular mechanisms. One reviewer felt that development of the mathematical approach was the real goal of the proposal, with improved hepatocyte differentiation a secondary outcome. Reviewers identified a number of problems with the research plan that caused them to doubt its feasibility. They found Aim 1 overly elaborate and ambitious, involving the testing of hundreds to thousands of combinations of stimuli in six cell lines. Reviewers weren’t convinced this aim could be completed in the proposed timeframe. One suggested limiting the model building experiments to the H1 cell line. Another concern relates to the use of albumin expression as the initial readout for hepatocyte differentiation; this is not a mature hepatocyte marker. Differentiation will most likely result in a mixed population of cell types; investigators should therefore further purify hepatocyte-like cells prior to use in functional and in vivo assays. Reviewers were unsure of the rationale for using phospho-specific flow cytometry to identify signaling pathways activated during differentiation. One reviewer noted that the downstream targets of these pathways are already well understood, while another felt that phosphorylation states are not likely to be a key measure of successful differentiation. The rationale for Aim 2 is sound, but its success depends on an extremely ambitious Aim 1. Furthermore, there is no evidence that the research team has experience with the mouse model for hepatocyte regeneration. Reviewers also did not find the preliminary data compelling. While the preliminary results section demonstrates the capacity to obtain iPSCs and induce differentiation, it contains very little information demonstrating that the phospho-specific flow cytometry technique can be used to elucidate particular pathways. The applicants have a solid foundation in mathematical modeling in viral systems; however, the modeling to be used for the proposed studies is inadequately described. Reviewers found the preliminary data describing HCV to be excessive and not particularly relevant to the proposal. Reviewers noted that the applicant and assembled research team are strong in their fields but, with the exception of a co-investigator at 5% effort, have limited experience in stem cell biology and pluripotency. Liver systems biology expertise is also lacking. One reviewer recommended the recruitment of an established scientist with expertise in stochastic optimization methods to push the mathematical aspects forward. Overall, while reviewers agreed that this proposal addresses a significant problem, they were not convinced of the rationale or feasibility of its approach.

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