CD8+ T-lymphocytes (CTLs) are central to the immunologic control of infections and are currently at the forefront of strategies that enhance immune based treatment of a variety of tumors. Effective T-cell based vaccines and immunotherapies fundamentally rely on the interaction of CTLs with peptide-human leukocyte antigen class I (HLA-I) complexes on the infected/malignant cell surface. However, how CTLs are able to respond to antigenic peptides with high specificity is largely unknown. Also unknown, are the different mechanisms underlying tumor immune evasion from CTL-mediated cytotoxicity. In this dissertation, I investigate the immunogenicity and dysfunction of CTLs for the development of novel T-cell therapies. Project 1 explores the biochemical hallmarks associated with HLA-I binding peptides that result in a CTL-immune response. The results reveal amino acid hydrophobicity of T-cell receptor (TCR) contact residues within immunogenic CTL-epitopes as a critical parameter for CTL-self
onself discrimination. Project 2 develops a bioinformatic and experimental methodology for the identification of CTL-epitopes from low frequency T-cells against tumor antigens and chronic viruses. This methodology is employed in Project 3 to identify novel immunogenic CTL-epitopes from human papillomavirus (HPV)-associated head and neck cancer patients. In Project 3, I further study the mechanisms of HPV-specific T-cell dysfunction, and I demonstrate that combination inhibition of Indoleamine 2, 3-dioxygenase (IDO-1) and programmed cell death protein (PD-1) can be a potential immunotherapy against HPV+ head and neck cancers. Lastly, in Project 4, I develop a single-cell assay for high-throughput identification of antigens targeted by CTLs from whole pathogenome libraries. Thus, this dissertation contributes to fundamental T-cell immunobiology by identifying rules of T-cell immunogenicity and dysfunction, as well as to translational immunology by identifying novel CTL-epitopes, and therapeutic targets for T-cell immunotherapy.

The immune system plays a dual role during neoplastic progression. It can suppress tumor growth by eliminating cancer cells, and also promote neoplastic expansion by either selecting for tumor cells that are fitter to survive in an immunocompetent host or by establishing the right conditions within the tumor microenvironment. First, I present a model to study the dynamics of subclonal evolution of cancer. I model selection through time as an epistatic process. That is, the fitness change in a given cell is not simply additive, but depends on previous mutations. Simulation studies indicate that tumors are composed of myriads of small subclones at the time of diagnosis. Because some of these rare subclones harbor pre-existing treatment-resistant mutations, they present a major challenge to precision medicine. Second, I study the question of self and non-self discrimination by the immune system, which is fundamental in the field in cancer immunology. By performing a quantitative analysis of the biochemical properties of thousands of MHC class I peptides, I find that hydrophobicity of T cell receptors contact residues is a hallmark of immunogenic epitopes. Based on these findings, I further develop a computational model to predict immunogenic epitopes which facilitate the development of T cell vaccines against pathogen and tumor antigens. Lastly, I study the effect of early detection in the context of Ebola. I develope a simple mathematical model calibrated to the transmission dynamics of Ebola virus in West Africa. My findings suggest that a strategy that focuses on early diagnosis of high-risk individuals, caregivers, and health-care workers at the pre-symptomatic stage, when combined with public health measures to improve the speed and efficacy of isolation of infectious individuals, can lead to rapid reductions in Ebola transmission.

Currently in the US, many patients with cancer do not benefit from the population-based screening, due to challenges associated with the existing cancer screening scheme. Blood-based diagnostic assays have the potential to detect diseases in a non-invasive way. Proteins released from small early tumors may only be present intermittently and get diluted to tiny concentrations in the blood, making them difficult to use as biomarkers. However, they can induce autoantibody (AAb) responses, which can amplify the signal and persist in the blood even if the antigen is gone. Circulating autoantibodies is a promising class of molecules that have potential to serve as early detection biomarkers for cancers. This Ph.D thesis aims to screen for autoantibody biomarkers for the early detection of two deadly cancer, basal-like breast cancer and lung adenocarcinoma. First, a method was developed to display proteins in both native and denatured conformation on protein array. This method adopted a novel protein tag technology, called HaloTag, to covalently immobilize proteins on glass slide surface. The covalent attachment allowed these proteins to endure harsh treatment without getting dissociated from slide surface, which enabled the profiling of antibody responses against both conformational and linear epitopes. Next, a plasma screening protocol was optimized to significantly increase signal to noise ratio of protein array based AAb detection. Following this, the AAb responses in basal-like breast cancer were explored using nucleic acid programmable protein arrays (NAPPA) containing 10,000 full-length human proteins in 45 cases and 45 controls. After verification in a large sample set (145 basal-like breast cancer cases / 145 controls / 70 non-basal breast cancer) by ELISA, a 13-AAb classifier was developed to differentiate patients from controls with a sensitivity of 33% at 98% specificity. Similar approach was also applied to the lung cancer study to identify AAbs that distinguished lung cancer patients from computed-tomography positive benign pulmonary nodules (137 lung cancer cases, 127 smoker controls, 170 benign controls). In this study, two panels of AAbs were discovered that showed promising sensitivity and specificity. Six out of eight AAb targets were also found to have elevated mRNA level in lung adenocarcinoma patients using TCGA data. These projects as a whole provide novel insights on the association between AAbs and cancer, as well as general B cell antigenicity against self-proteins.