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Our lab focuses on the genomic and transcriptomic drivers of anti-tumour immune response, using cancer bioinformatics and ex-vivo, in-vivo and in-vitro experimental approaches.
Immunotherapeutics have led to breakthrough improvements in cancer survival, with immune checkpoint inhibitor (CPI) treatments now approved for over a dozen different tumour types. However, typically only 20-40% of patients benefit from immunotherapy, and novel immune targets are urgently needed to expand the proportion of patients who respond to treatment. An effective anti-tumour immune response is underpinned by multiple factors, including the presence of immunogenic HLA-presented peptides, a functional immune cell infiltration into the tumour core, as well ongoing T-cell priming in tertiary or secondary structures. These processes are regulated by a network of costimulatory molecules, as well as influenced by tumour cell intrinsic events, and hence we adopt a systems level understanding of immunotherapy response throughout our work.
Experimentally, there are a lack of model systems able to recapitulate the complexity of immunotherapy response, and instead our lab conducts discovery work utilising patient samples from clinical trials. Multi-omic profiling of clinical samples has already enhanced our understanding of immunotherapy activity, establishing for example tumour mutation burden as a key driver of CPI response and hence validating the neoantigen hypothesis. A key capability of our lab is conducting large-scale integrated analysis of multi-omic datasets, generated directly from patient tumour tissue, in order to identify of the next generation of cancer immunotherapy targets. Working over the last five years we have compiled one of the world’s largest exome/RNAseq datasets from immunotherapy treated patients. This work is now formalised through an international consortium, with in total genomic/transcriptomic data already available from n=1500 patients, across eight tumour types.
Once novel therapeutic targets are identified in patient datasets, we then use a combination of in vitro, ex vivo and in vivo techniques to explore the functional basis of anti-tumour immune response and develop candidate therapeutic approaches. Biologically, a key interest of the lab is the identification of novel sources of tumour specific antigen capable of eliciting an anti-tumour immune response, as well as characterising cellular pathways which can be perturbed to increase tumour cell immunogenicity.
Our lab focuses on the genomic and transcriptomic drivers of anti-tumour immune response, using cancer bioinformatics and ex-vivo, in-vivo and in-vitro experimental approaches.
Immunotherapeutics have led to breakthrough improvements in cancer survival, with immune checkpoint inhibitor (CPI) treatments now approved for over a dozen different tumour types. However, typically only 20-40% of patients benefit from immunotherapy, and novel immune targets are urgently needed to expand the proportion of patients who respond to treatment. An effective anti-tumour immune response is underpinned by multiple factors, including the presence of immunogenic HLA-presented peptides, a functional immune cell infiltration into the tumour core, as well ongoing T-cell priming in tertiary or secondary structures. These processes are regulated by a network of costimulatory molecules, as well as influenced by tumour cell intrinsic events, and hence we adopt a systems level understanding of immunotherapy response throughout our work.
Experimentally, there are a lack of model systems able to recapitulate the complexity of immunotherapy response, and instead our lab conducts discovery work utilising patient samples from clinical trials. Multi-omic profiling of clinical samples has already enhanced our understanding of immunotherapy activity, establishing for example tumour mutation burden as a key driver of CPI response and hence validating the neoantigen hypothesis. A key capability of our lab is conducting large-scale integrated analysis of multi-omic datasets, generated directly from patient tumour tissue, in order to identify of the next generation of cancer immunotherapy targets. Working over the last five years we have compiled one of the world’s largest exome/RNAseq datasets from immunotherapy treated patients. This work is now formalised through an international consortium, with in total genomic/transcriptomic data already available from n=1500 patients, across eight tumour types.
Once novel therapeutic targets are identified in patient datasets, we then use a combination of in vitro, ex vivo and in vivo techniques to explore the functional basis of anti-tumour immune response and develop candidate therapeutic approaches. Biologically, a key interest of the lab is the identification of novel sources of tumour specific antigen capable of eliciting an anti-tumour immune response, as well as characterising cellular pathways which can be perturbed to increase tumour cell immunogenicity.
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