The Development of a Statistical Model to Study How the Deletion of PD-1 Promotes Anti-Tumor Immunity

Abstract

T-cells are an essential component to the immune system, but they do not act alone and are instead a component in the body’s immune system. PD-1 and its ligands PD-L1 and PD-L2 play an important role in the regulation of T-cells which are incredibly important to the treatment of cancer. Tumors have been able to hijack the PD-1 inhibitory pathway to evade our body’s immune response. PD-1 pathway blockade, therefore, can serve as an important approach for cancer immunotherapy. However, we do not fully understand the mechanism by which PD-1 regulates anti-tumor immunity. With the datasets derived from experiments by the Sharpe Lab, we hope to answer two important questions. First, what does PD-1 regulate in a cell intrinsic manner compared to bystander effects on other cells in the tumor micro-environment? Second, which gene expression changes predict response as opposed to resistance to tumor clearance when PD-1 is present or deleted? We hypothesize that a cell intrinsic loss of PD-1 is necessary for improved T-cell fitness and effector functions. This project aims to help answer these questions in three ways. First, the development of an RNA-sequencing pipeline allows the researchers in the lab to analyze the results of datasets that are generated. Second, conducting pathway analyses provides a broader picture of the gene expression landscape, including provide a more complete picture of the tumor micro-environment by indicating which pathways and cellular processes are enriched for the genes affected by the deletion of PD-1. Third, the development of a statistical model which makes predictions on which gene expression changes predict response as opposed to resistance. The results of the statistical model indicate which genes are more closely related to PD-1 when it is deleted versus when it is present. This will help us better understand immune response as opposed to resistance to PD-1 cancer immunotherapy, and its effects on tumor growth. This model therefore provides a valuable tool to the community that would allow researchers to probe the gene expression landscape around PD-1.