The rationale for the proposed research is the need to better understand the effects of allogeneic CD8+ T cell immunotherapy on desirable graft versus leukemia (GVL) and undesirable graft versus host disease (GVHD). Immunotherapy is curative for many patients suffering from acute myeloid leukemia (AML). However, we currently lack a method to optimally select a donor immune system predicted to maximally elicit GVL while minimizing GVHD, an unpredictable and potentially lethal side effect. Therefore, the objective of this research is to study the effects of thymic selection on the probability for a given T cell repertoire to recognize and target AML cells and to inform the selection of donor immune systems that maximally target AML while minimizing collateral damage to the patient. The fundamental hypothesis for this research is that thymic selection limits the ability of a patient's CD8+ repertoire to identify evolving AML cells and that immune therapy can be employed to drastically reduce AML heterogeneity in a matter that independently affects GVL and GVHD. The proposed project will be investigated by studying three specific aims. In the first specific aim, we will evaluate differences in host and donor cancer recognition potentials by developing a generalized model of thymic selection. The outcome will relate differences between host and donor cancer targeting to differences between host and donor self-antigens. In the second specific aim, we will characterize the effect of allogeneic immunotherapy on GVL and GVHD by developing a theoretical model of AML/T cell co-evolution. We will study the effect of co-evolution on AML heterogeneity and compare our predictions to cancer survival data. We will also simulate immunotherapy treatment in order to predict the resulting extent of GVL and GVHD. The outcome will provide a prediction for the level of cancer targeting vs. side effects between a host and donor pair prior to immunotherapy. In the third specific aim, we will characterize the effect of immunotherapy in AML patient samples by the resulting extent of GVL and GVHD. We will sequence blood samples from AML patients before and after treatment in order to characterize cancer clones and the T cell repertoire. The outcome will relate the extent of GVL and GVHD to differences in donor and host immune cells. By completing the research above, we will determine how thymic selection of T cells affects the ability of an immune repertoire to identify and target cancer cells, compare differences in cancer targeting by both host and donor immune systems, predict the levels of patient GVL and GVHD prior to administering immunotherapy, and relate this to actual levels in AML patient samples. We expect that immunotherapy can be tailed on an individual-patient basis to independently maximize GVL and minimize GVHD. Because of the current risk of immunotherapy-related toxicity, the proposed research has immense translational potential to directly improve treatment outcomes, both in AML and other cancers.
Harnessing the power of another person's immune system holds the potential to cure many cancers, including leukemia; however, it is currently impossible to fully predict the effect of foreign immune cells in the body of a cancer patient. This project proposes to develop a model of the battle between cancer cells and donor immune cells in order to predict the effects of immune therapy on the patient prior to treatment. This work will provide clinicians with valuable information that can be used to maximally utilize immune therapy and more aggressively attack cancer.
| George, Jason T; Levine, Herbert (2018) Stochastic modeling of tumor progression and immune evasion. J Theor Biol 458:148-155 |
| George, Jason T; Kessler, David A; Levine, Herbert (2017) Effects of thymic selection on T cell recognition of foreign and tumor antigenic peptides. Proc Natl Acad Sci U S A 114:E7875-E7881 |
| George, Jason T; Jolly, Mohit Kumar; Xu, Shengnan et al. (2017) Survival Outcomes in Cancer Patients Predicted by a Partial EMT Gene Expression Scoring Metric. Cancer Res 77:6415-6428 |
