Invariant natural killer T (iNKT) cells are unconventional T-cells that are ubiquitously found in mammals and provide immunity to pathogens and against tumours. Through their T-cell receptor (TCR), iNKT cells respond to glycolipid antigens, a class of antigens that is invisible to conventional CD4 or CD8 T-cells. Furthermore, these cells are heterogenous and can differentiate into discrete effector subsets. Using advanced functional genomics, we identified a bona fide cytotoxic iNKT cell subset, which is functionally equivalent to cytotoxic CD8 T-cells. These cytotoxic iNKT cells efficiently kill tumour cells in vitro/in vivo and provide several advantages over their CD8 T-cell counterparts. Interestingly, cytotoxic iNKT cells recognize and kill tumour cells through several modalities that are both TCR-dependent and TCR-independent. Together, our findings indicate that cytotoxic iNKT cells could be used to develop novel cancer immunotherapies with a lower risk of tumour evasion, although a mechanistic understanding of their function remains to be understood. The goal of this project is to leverage available single cell RNA sequencing datasets to identify immune receptors expressed by cytotoxic iNKT cells that may be involved in recognition of or response against tumour cells. Results from this work will inform the rational design of iNKT-targeted cancer immunotherapies. This project is co-supervised with Dr. Thierry Mallevaey (Department of Immunology, Temerty Faculty of Medicine, University of Toronto).

The responsibilities of the student will include, although are not limited to:

• Review the primary literature to find important immune receptors expressed by cytotoxic iNKT cells
• Assess the quality of available scRNA seq datasets, with consideration of experimental design/statistics
• Establish a scRNA seq data processing workflow
• Perform data reduction and clustering of available scRNA seq datasets using R software
• Identify genes driving cluster formation from scRNA seq data and extract biological knowledge from cluster-specific biomarkers
• Attend weekly lab meetings (~1 hour/week) and present research updates biweekly
• If time: validate identified biomarkers on iNKT cell subsets in the laboratory setting via flow cytometry or through performing gene expression analyses using qRT-PCR