My research focuses on the biological drivers for prostate cancer progression and treatment-resistance. The startpoints for these studies are transcriptomic and metabolomic datasets generated in pre-clinical models and clinical samples. Pre-clinical models allow temporal datasets to be generated with control over the genomic background and treatment schedules. This enables adaptive responses to oncogenic and treatment stress to be evaluated. Prostate cancer is a high-incidence male cancer which progresses to metastasis in a subset of cases raising a clear need for improved stratification based on profiling and biological modelling of the disease. The most significant biological contributors to progression are likely to be those that are enriched downstream of a range of genomic drivers or treatment regimes in surviving cancer cells. Examples of this include immune modulatory and DNA damage response pathways that allow cancer cells to acquire genomic instability without succumbing to apoptosis or eliciting an effective immune response in the tumour microenvironment. From a start-point of cancer cell-intrinsic pathways driven by the androgen receptor, and latterly by assessing responses to radiotherapy, we are now seeking to address the role of the unfolded protein response and innate immune signalling in these changes. Selection of most important positive and negative regulators of these processes will require genetic screening, further characterisation of clinical sample collections and the further development and use of immune-competent pre-clinical models. A better understanding of these processes will enable effective repurposing of immune therapies and drugs targeting metabolic processes for the treatment of prostate cancer in the appropriate subsets of patients.