Objective
Our goal is to develop and validate a new way to image two major immune cell types (that are critical in the processes of immune rejection of transplants in Type 1 diabetes) in living animals and eventually in humans in the clinic. Currently, there is a critical lack of available methods to sensitively image more than one cell type at the same time. In our approach, we will label each immune cell type with a type of magnetic nanoparticle. Each nanoparticle has different magnetic properties associated with it. In this project, our objective is to use the differing magnetic properties to generate different “colors”—that is, a way to distinguish between the two types—using a new type of imaging instrument called magnetic particle imaging. Magnetic particle imaging is, unlike many other imaging instruments, very sensitive (meaning it can detect relatively few cells, even down to 1000 cells) and it can do so quantitatively—that is, it can estimate the absolute numbers of cells at a site anywhere in the body. Our primary objective in this context is to develop a novel ‘immunoimaging’ strategy that will enable the ability to rapidly and efficiently provide deep insights into the immune response to emerging transplant therapies. We will test our ability to quantify the immune response in a mouse Type 1 diabetes transplant model.
In summary, in this proposal, our first objective is to safely and effectively label our nanoparticles into the two immune cell types. We will also prove that the labels do not affect the cell health or function. We then aim to develop the software to discriminate, or ‘colorize’, each immune cell type from one another in the imaging instrument based on differences in the physical properties of the nanoparticles in a test tube. Next, we will apply the nanoparticle-labeled immune cells in a mouse model of immune rejection of islet transplants, to ensure that we can track the travels of both immune cell types simultaneously. Our objective is to perform ‘color’, or multi-plexed, immune cell imaging studies that will allow the ability measure immune responses of multiple different immune cell types to islet transplant therapies that seek to reduce or eliminate the immune response. In this project, we propose two immune cell types, but in theory in the future we will extend this capability to three or more different immune cell types. Our aim is for our imaging measurements to provide key information on immune rejection of new transplant therapies, and clinically to ultimately serve as a sort of early warning signal of transplant rejection. Thus, our goal is to develop a robust method to measure immune trafficking to islets as both a critical research tool, which measures immune cell influx during transplant rejection, and a potential clinical assessment of transplant rejection in patients.
Background Rationale
The selection of the appropriate immune cell types to image is important. Until recently, it has been unclear which immune cell subsets indicate transplant rejection. Recent studies implicate CD8+ T cells and macrophages, and several others, into islet transplants as drivers of rejection. Their presence and travel to the site generates worse graft function and prognosis. It follows that imaging these immune cell types is likely to yield important insights into transplant immunity and rejection. We chose CD8+ T cells and macrophages because they infiltrate very wall into transplants, and CD8+ T cells are the cells that directly kill the transplant cells. As causal factors of rejection, imaging the trafficking of CD8+ T cells and macrophages to the transplant site could provide a research method to test new therapeutic transplant strategies that seek to minimize the likelihood of the transplant to be rejected by the immune system in Type 1 diabetes animal models, as well as an imaging method that could be used in patients to provide an early warning of transplant rejection.
Typical immune cell imaging methods include positron emission tomography (PET) and magnetic resonance imaging (MRI), which can be used to image immune cells traveling through the body. Yet PET and MRI suffer from low sensitivity or require radiation, and can only track one cell type at a time, limiting potential information on the likelihood of transplant rejection. Magnetic particle imaging is a novel, recently invented imaging modality that resolves many issues with other imaging modalities including providing near infinite contrast, real-time imaging, is fully quantitative (for example, this means that it allows direct and absolute estimation of cell numbers at any site in the body), and displays high sensitivity. Importantly, while trafficking of one immune cell type (for example, CD8+ T cells OR macrophages) may have value in understanding the immune response to therapeutic transplants (which also remains untested), biology is complex; thus, only visualizing one immune cell type provides a very limited picture of what is really happening in the body. This complexity requires imaging of multiple immune cell types simultaneously to understand each individually and potential interactions. This is why we are developing a magnetic particle imaging-based strategy to image multiple (currently two) cell types in the body in a novel, rapid and efficient approach to visualize the immune response to transplants in Type 1 diabetes. We develop ‘color’ in magnetic particle imaging due to differences in the magnetic properties between two magnetic nanoparticles we use, which we estimate using ‘colorizing’ software that we are developing in this project. Thus, in this proposal we will test the travel in the body of two different immune cell subsets labeled with MNPs possessing different magnetic properties, which allows their discrimination by MPI.
Description of Project
Considering the high rate of islet transplant rejection in Type 1 diabetes patients, and the need to understand the immune response to newly emerging transplant therapies, new strategies to be able to visualize immune cell trafficking to transplant sites are critical. The standard method to monitor transplant rejection is to track increased patient blood glucose levels, which occurs at advanced stages of rejection. This method also does not consider the immune response to the transplant. Indeed, the immune response, including infiltration of key immune cells into the transplant, is primarily responsible for transplant rejection. So the development of new transplant therapeutic modalities associated with decreased immune responses are critical for Type 1 diabetes patients. The importance of these strategies is highlighted by the requirement for immunosuppressive therapy with transplants. Immunosuppressive therapy is very risky, with outcomes that can include infections, cardiovascular disease, and cancer. Thus, by eliminating the requirement for immunosuppressive therapy, islet transplants would be a robust and accessible option for all types of Type 1 diabetes patients. This would greatly broaden the population that would benefit from the emerging therapies to include even those who are reasonably healthy with the capacity to control their diabetes by delivering their own insulin. However, the problem is that there is no rapid, effective strategy available to monitor in vivo the immune response to the newly emerging alternative transplant strategies in order to evaluate their efficacy.
This proposal develops a novel immunoimaging approach using magnetic particle imaging (MPI) that bridges the gap in imaging technology and enables the ability to simultaneously and quantitatively track the infiltration of two different immune cell types into diabetic transplants in Type 1 diabetes. It improves upon more conventional imaging approaches such as magnetic resonance imaging (MRI) and positron emission tomography (PET) in this context because it offers high sensitivity, near-infinite contrast, does not require radiation, and, as we show in this proposal, it can be used to simultaneously visualize the trafficking of at least two different immune cell types anywhere in the body. We will test and validate this approach in Type 1 diabetes animal models, and then we will validate the approach by checking for the arrival of the immune cells in transplant tissues removed from the body after the imaging is completed. This immune cell imaging strategy has potential for not only rapidly screening the efficacy of new pre-clinical therapies, but could be used eventually in the clinic to monitor transplant recipients to test whether the immune system is responding to the transplants.
Anticipated Outcome
As a result of this proposal, we expect to develop a novel imaging strategy that can simultaneously visualize at least two immune cell types traveling to, and infiltrating, an islet transplant. This strategy will be tested in animal models of transplant rejection, and it is designed with the potential to translate it clinically. That is, it is expected to be capable of clinically monitoring transplant recipients for an immune response that could be used as an early signal of transplant rejection.
In order to accomplish this work, we anticipate magnetically labeling immune cells types and ensuring that the labels do not affect cell trafficking or function. We also expect to develop software codes that enable us to distinguish colors—that is, to discriminate between the two magnetically-labeled immune cell types—and then validating the accuracy of this software in experiments performed in cell culture. Finally, we will test our color imaging strategy in a standard diabetes animal model, and potentially a pre-clinical diabetes model using another transplant site that may be used in the clinic, the epididymal fat pad. We anticipate that two-color (two immune cell types) will better represent the immune response to a transplant than only one immune cell type. We will also validate the imaged immune cell trafficking using standard laboratory procedures, and we expect these validations to confirm the trafficking of the two immune cell types to the transplant.
Relevance to T1D
There remains a high rate of islet transplant rejection in Type 1 diabetes patients. The reason these transplants are rejected is due to the transplant recipient’s immune response to the transplant. Therefore, new strategies are required to visualize immune cell trafficking to these sites. The standard method to monitor transplant rejection is to track increased patient blood glucose levels, which occurs at advanced stages of rejection. However, the immune response, such as infiltration of immune cells like T cells and macrophages, is primarily responsible for transplant rejection. Hence, new therapeutic transplant modalities are needed that elicit a reduced or ideally no immune response. A number of emerging therapeutic approaches using genetics, immunology, and engineering are being developed to do exactly that, and their development and evaluation is critical for Type 1 diabetes patients. Indeed, the importance of these strategies is highlighted by the present requirement in the clinical for immunosuppressive therapy in combination with transplants. Immunosuppressive therapy is rather risky, including infection, cardiovascular disease, and cancer. Thus, by eliminating the requirement for immunosuppressive therapy, islet transplants would be a robust and accessible option for all types of Type 1 diabetes patients: this means that transplants would be an option not only for those suffering from severe forms of diabetes, but also could benefit even those who are reasonably healthy with the capacity to control their diabetes by using doses of insulin. However, a critical problem in the field of emerging transplant therapy is that there is no rapid and efficient strategy available to evaluate the effectiveness of these therapies; in particular, the field requires new imaging strategies to monitor the immune response to these newly-emerging alternative transplant strategies in order to quickly evaluate their efficacy. If successful, this would rapidly accelerate these therapies’ optimization and the ability to use them for patients in the clinic. Similarly, it would provide a potential monitoring strategy of immune responses for human transplant recipients.
From another perspective, it is notable that biopsy approaches are often used to assess immune cell homing into the transplant site. However, these approaches do not provide dynamic information, are invasive, inadequate, can easily miss regions of implanted islets, and when done in animal models, they usually require sacrifice of many animals. On the other hand, dynamic imaging that can produce whole body visualizations of immune cell localization in vivo is likely ideal. Indeed, so-called ‘immunoimaging’ allows the specific imaging of cells traveling to a particular place in the body, such as the transplant site. Immunoimaging can therefore shed light on the rejection processes, including how the immune system responds to the transplant over time. Assessment of immune trafficking to, and interaction with, the transplant is needed to dynamically monitor the post-transplant immune response in order to evaluate the effectiveness of the transplant non-invasively—that is, without needing to go in and do a biopsy. In this proposal, we develop a robust method to measure immune trafficking to islets that would not only provide a needed research tool, e.g., a method to dynamically quantify immune cell infiltration changes and interactions during the development of rejection, but also could potentially offer a clinical risk assessment strategy in Type 1 diabetes transplant patients.