T cells have built-in brakes that prevent them from overreacting, and this project will map exactly how three of those brakes—PD1, Lag3, and IL-10—switch on and off during normal immune responses and in cancer. This matters because those same brakes that protect the body from autoimmune damage also stop T cells from killing tumours. Drugs that block these brakes, called immune checkpoint inhibitors, can unleash T cells against cancer, but they work in only a fraction of patients. No one knows why. The researcher has developed new tools to track T cell behaviour in real time and has early evidence that blocking different brakes leaves distinct molecular fingerprints—biomarkers—inside the cells. If this succeeds, it will identify which biomarkers predict whether a patient will respond to a particular immunotherapy. That could allow doctors to match treatments to individuals, sparing non-responders from ineffective drugs and their side effects. The work is primarily fundamental science—understanding how the immune system tunes its own responses—but the biomarker discovery component has a direct path to clinical use, potentially improving how oncologists decide which checkpoint inhibitor to prescribe.
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T cells are vital immune cells that help fight infections and cancer. T cells must strike a balance between successfully clearing harmful invaders and the collateral damage they might inflict in achieving this (called immunopathology). The T cell system therefore has many brakes which it can apply to control the level of immune response. I have developed new tools that can follow T cell responses and identify when and how they switch on these immune brakes. I believe that these brakes that have developed to prevent autoimmunity account for why T cells are prevented from killing cancer cells. This study will initially utilise normal healthy settings to understand how three key brakes, PD1, Lag3 (also called immune 'checkpoints') and IL-10 control T cell responses. My early data suggest that drugs that block the functions of some of these molecules can induce unique features within T cells, called 'biomarkers', which could be used to monitor whether an individual is responding to therapy. I will therefore apply the knowledge gained from studying how these brakes control T cell responses in normal settings to several cancer models in mice. The aim will be to identify biomarkers for successful responders to immune checkpoint blockade in cancer. I envisage that this work will lead to a better understanding of these immune 'checkpoints' in both normal and cancer settings. In addition, the study will identify potential 'biomarkers' that could be used in the future to predict patient responses to particular immunotherapies.
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