HLA genetics shapes tumor immunosurveillance

PROJECT SUMMARY Cancer is a leading cause of death worldwide, with over 1.9 million new cases in 2022 in the United States, with 10% of that been lung cancer. Cancer risks is associated with multitude of factors including hereditary mutations, environment factors and the recently described bad luck hypothesis. The establishment of immune checkpoint inhibitors as treatment of several cancers, emphasizes the importance of the immune system in tumor control. However, we are yet to fully understand how the immune system contributes to cancer risks as well as cancer heterogeneity. Cancer Immune surveillance is the posits that lymphocytes, particularly T cells, are constantly surveying tissues for neoplastic cells, by recognizing neoantigens presented by the MHC molecules through their T cell receptor (TCR). Our group discovered using population level genetic datasets, that heterozygosity at the HLA class II (HLA-II) loci –rather than the traditionally emphasized HLA-I – is linked with a decreased risks of developing lung cancer among smokers. I plan to follow up on this work and dissect the mechanisms involved in HLA zygosity on tumor development as well as understand the emerging role of HLA II and CD4 T cells in tumor immunosurveillance. Aim 1 focuses on using a murine model that to explore MHC heterozygosity in the development of lung cancer. The murine model, paired with carcinogen induced lung cancer, will be used understand the mechanism behind MHC heterozygosity protective effect against lung cancer as well as explore what T cell type contributes to this protectiveness. Aim 2 seeks to utilize genetically modified cell lines to study exclusively MHC class I versus II heterozygosity in reducing tumor burden and further I will use genetically engineered mouse models to interrogate the role of MHC class II in tumor immunosurveillance and assess the interplay between MHC class II on professional versus nonprofessional antigen presenting cells in controlling tumor growth. However, consistently murine models do not completely reconcile to human biology and will not fully capture the diversity that exists in the immune system. Therefore, Aim 3 will use anonymize and publicly available human lungs single cell datasets to study the HLA heterozygosity on TCR repertoire diversity as well as elucidate clonotypic differences in immune subpopulations. Overall, this proposal combines in vivo models with human datasets to investigate the hypothesis that HLA genetics, specifically HLA-II, shapes cancer immunosurveillance, which can be used to identify biomarkers and inform future treatment strategies.