Relevant Degree Programs
Graduate Student Supervision
Doctoral Student Supervision (Jan 2008 - May 2019)
The adaptive immune system is a complex network of cells working towards a common goal: detection and elimination of foreign cells that can harm the host. In cancer, malignant cells acquire mutations which can appear foreign to the adaptive immune system. The immune cells most directly involved in destruction of cancer cells are CD8+ T cells, using their T cell receptor (TCR) to recognize mutated peptides presented on cancer cells in the context of class I Major Histocompatibility Complex (MHC) molecules (pMHC). Immunogenomics methods offer ways to interrogate this TCR-pMHC interaction using genomics data.The aim of this thesis is to adapt and apply novel and existing immunoinformatic methods to cancer datasets to identify relationships between the immune system and cancer in a pan-cancer context. This involves prediction of cancer neoantigens derived from single nucleotide variants (SNVs) from tumours, and correlation of this neoantigen burden with outcomes and markers of immune inhibition. It involves extraction of TCR sequences from RNA-seq datasets to gain value-added information from these existing datasets, with demonstrated utility in solid tumours and lymphomas. Finally, it defines and explores the size of the self-immunopeptidome to classify individuals based on their ability to present peptides on class I MHC molecules. I show that T cell infiltration of solid tumours correlates with improved outcomes, neoantigen load, but also markers of T cell inhibition, suggesting that these individuals would benefit from checkpoint blockade therapy. In established tumours, the T cell repertoire is not clonal, and among the most abundant T cells in the tumour are viral-specific T cells also found in the normal repertoire. This information is obtained directly from existing RNA-seq datasets of tumours. When applied to RNA-seq of sorted T cell populations, clonally expanded T cells are detectable by their TCR, and alpha-beta pairing can be inferred. The self-immunopeptidome can be used to predict neoantigen load and is used to infer signatures of neoantigen immunogenicity. This thesis contributes towards a better understanding of the interaction between T cells and cancer cells, which can inform future strategies to improve immunotherapies in cancer.
Though it is understood that T-cells are a critical component of the immune system’s ability to destroy foreign invaders and attack cancerous cells, very little is known regarding the specific epitopes that are recognized by T-cells to carry out these functions. Generally, the epitopes mediating this immunity are short, contiguous peptides derived from antigenic proteins presented on major histocompatibility complex (MHC) molecules for inspection by T-cells. The ability to rapidly and deeply search peptide space to determine specific peptide epitopes that are naturally processed, presented, and capable of eliciting functional T-cell responses is a critical unmet need in the study of adaptive immunity. Here, I describe a novel method for deep T-cell epitope profiling that enables simultaneous in vitro interrogation of target cell populations encoding high-diversity minigene libraries with T-cell populations-of-interest. Targets eliciting T-cell reactivity are selectively isolated by fluorescence-activated cell sorting (FACS) and identified by deep amplicon sequencing. The approach was extensively validated using known murine T-cell receptor (TCR)/peptide-MHC pairs and it was shown that this method can unambiguously identify canonical minigenes from libraries of vastly more candidate antigens in parallel than would be feasibly tractable using conventional methods.The capability of this strategy was extended by applying a synthetic biology approach. Using pairs of immortalized natural killer (NK)-like effector cell lines and naturally tolerated target cell lines, I showed that fully reconstituting the TCR/CD3 complex in effectors and expressing relevant MHC-/minigene-coding sequences in targets is sufficient to re-direct the cytotoxicity of NK-like cell lines towards antigenic targets of recombinant TCR. These results provide indication that it should be possible to use an entirely synthetic framework for functionally screening recombinant TCR-of-interest against minigene libraries without the requirement to first isolate and expand primary T-cell clones or donor-derived antigen-presenting cells.The high-throughput T-cell antigen profiling methods described and validated in this thesis could allow investigators to generate TCR epitope data broader in scope than previously possible to better understand basic T-cell biology, develop better predictive models of T-cell reactivity, and rationally design T-cell-based immunotherapeutics for the treatment of cancer, infectious disease, and autoimmunity.
A hallmark of cancer is the accumulation of mutations, and a small proportion of these give rise to mutant neoantigens – mutated peptides bound to Major Histocompatibility Complex (MHC) and recognized by T cells. Accumulating evidence suggests that mutant neoantigens (hereafter referred to as “neoantigens”) underlie successful immune therapies in cancers with high mutation loads, such as melanoma. Moreover, neoantigen-specific vaccines have successfully targeted highly mutated murine tumor models. However, less is known about neoantigen-specific T cell responses in cancers with moderate mutation loads, such as ovarian cancer. I hypothesized that (1) modified peptide-based vaccination schedules can lead to enhanced antigen-specific T cell responses; (2) neoantigen-specific vaccines can elicit T cell responses that eradicate murine ovarian tumors; and (3) neoantigen-reactive T cells are detectable in human ovarian tumors and peripheral blood. To activate high frequencies of antigen-specific T cells, I developed a vaccination method involving repeated, daily immunizations with long peptides and adjuvant. This method elicited robust T cell responses that eliminated established murine tumors. I used these enhanced vaccination methods to target tumor-specific mutations identified by exome- and RNA-sequencing of the ovarian tumor model ID8-G7. Prophylactic and therapeutic vaccinations were performed targeting all expressed mutations that had a predicted MHCI binding affinity
No abstract available.
Master's Student Supervision (2010 - 2018)
In principle, a pre-constructed library of all possible short oligonucleotides could be used to construct many distinct gene sequences. This approach requires computational methods to accurately determine the assembly procedure, but relieves the current technological constraints of custom oligonucleotide synthesis. In order to assess the feasibility of such an approach, I examined T4 DNA Ligase activity on short oligonucleotides and found that ligation is dependent on the formation of a double-stranded DNA duplex of at least five base pairs flanking the site of ligation. However, ligations could be performed with overhangs smaller than five nucleotides and oligonucleotides as small as octamers, in the presence of a second, complementary oligonucleotide. As a proof of principle for DNA synthesis through the assembly of short oligonucleotides, I performed a hierarchical ligation procedure whereby octamers were combined to construct a target 128 bp segment of the human beta–actin gene coding sequence. Thus, the construction of synthetic genes, without the need for custom oligonucleotide synthesis, is feasible. Algorithmic methods were then developed to extend this approach to DNA on the order of thousands of base pairs.