Immunotherapy is a rapidly expanding area of research, that focuses on harnessing the power of the immune system to treat cancer. Tumour cells and the tumour microenvironment have the ability to suppress the activation of immune cells. This can be achieved by engaging inhibitory receptors, such as PD1 (Programmed Cell Death 1) and CTLA4 (Cytotoxic T-Lymphocyte Associated Protein 4) on T-cells. A type of drug known as an Immune Checkpoint Inhibitor (ICI) can block these interactions, relieve T-cell suppression and stimulate immune function. These drugs have shown promising success in several tumour types, most notably melanoma, lung and kidney cancers.
Enlisting the immune system to fight cancer is an attractive concept, as it promises to be effective against many different types of cancer. Unfortunately, responses are highly variable, and remain low and unpredictable in many tumour types. Moreover, toxicity due to adverse immune related events can be challenging. Nevertheless, enlisting the immune system to fight cancer is an attractive concept, as it promises to be effective against many different types of cancer. In addition, when patients do respond to ICI’s, the responses tend to be durable and long lasting, asserting that the immune system can successfully eradicate or control cancers which were previously deemed incurable. Thus, ICIs are exciting therapeutic agents, however an improved and deeper mechanistic understanding of their molecular mode of action could lead to wider application and novel combinations with other drugs.
A focus on immunotherapies is a strategic priority for both SBI and the industry partner on this project, AstraZeneca (AZ), and research in this area will be of global impact. Therefore, computational scientists, biologists and clinicians from SBI and AZ have teamed up to analyse the molecular mechanisms of action of ICIs and use this knowledge to improve the development and deployment of ICIs. We will focus on ovarian cancer as a poor prognosis cancer that should respond well to ICIs. To date response rates have been poor and large clinical trials have failed to demonstrate efficacy so we expect decisive improvements to be possible.
This project will focus on: i) Mapping the PD1 and CTLA4 signalling pathways by which ICIs mediate their effects; ii) Identifying new targets in ICI signalling pathways to improve ICIs and develop better combination therapies.
i) Little is known about PD1 and CTLA4 signalling. PD1 impinges on cell survival, cell cycle progression, metabolic pathways and TGFβ signalling, but the molecular mechanisms remain rather obscure. Using our experience in the reconstruction of biological signal transduction networks, we will map the signalling pathways used by PD1 and CTLA4 in T-cells deploying a combination of proteomics, transcriptomics and computational modelling.
ii) Here, we will apply the computational models to analyse information processing by the ICI signal transduction pathways and identify ways how we can improve ICI efficacies. We will evaluate the in silico prediction in various experimental models so that we can make mechanism based recommendations for subsequent preclinical and clinical studies.
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