Stress resistance and cancer evolution
I qualified as M.Biochem (Master of Biochemistry) from Oxford University in 1996 before taking a PhD at the University of Liverpool in Molecular Physiology which I completed in 2000. My PhD focussed on the molecular mechanisms of endosomal membrane fusion and I characterised the function of lipid-binding proteins containing FYVE domains. I then moved to the MRC Laboratory of Molecular Biology in Cambridge on an MRC Career Development Fellowship (2000-2003) with Dr. Harvey McMahon. Here I worked on the role of a mechanochemical enzyme, dynamin3, in the relase of clathrin-coated vesicles from the plasma membrane and then on mechanisms for the induction and sensing of membrane curvature. The first proteins of their kind to be reported in these roles were Epsin1 and Amphiphysin, and Amphiphysin was defined as a founder member of a family of curvature-sensing BAR domain proteins. I was then recruited by Professor David Neal (Professor of Surgical Oncology) to establish a translational urological laboratory with a primary focus on prostate cancer. I worked in this capacity from 2003-2010 and principal findings included the identification of androgen receptor-ETS complexes, the mapping of AR-regulated metabolic gene networks and associated druggable targets and the identification of AR target genes and binding sites in patient tissue samples and derivation of a prognostic transcript signature for castrate-resistant disease.
In 2010 I joined NCMM in Oslo as a group leader. My group there worked on a more comprehensive multi-transcription factor analysis of metabolic control in prostate cancer, the impact of glycosylation and stress response/autophagy pathways on prostate cancer cells, identifying overlapping genetic risk loci between prostate cancer and metabolic conditions and classifying localised prostate cancer in part through transcript and mutational signatures linked to age- and diet-associated metabolic stress. This led to the identification of a number of biomarkers which have gone to form the basis of patents and are being further developed in partnership with companies. This also raised the prospect of repurposing clinically approved metabolic inhibitors to enhance the efficacy of new targeted agents when used as combination therapy. In 2015 I joined Queen’s University of Belfast as a Reader and continued to work on prostate cancer stress response signalling, now including irradiation as a driver for the evolution of resistant of cancer cells. My future will seek to characterise the important regulators within metabolic and stress response pathways that support these adaptive changes and enable cancer cells to survive and prostate cancer to progress.
John Black Associate Professor of Prostate Cancer
- Professor of Translational Prostate Cancer Biology, Queen’s University of Belfast
- Visiting Scientist Cancer Research UK (Cambridge)
- Honorary Senior Visiting Research Fellow, Department of Oncology, University of Cambridge
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.
- Evaluation of the impact of mitochondrial mutations on prostate cancer progression.
- Feedback effects of the hexosamine biosynthesis pathway on the unfolded protein response.
- Impacts of OGlcNAc transferase on chromatin and protein stability.
- Immune modulatory effects of the unfolded protein response.
- Innate immune signalling in the emergence of treatment-resistant prostate cancer.
- Characterisation of epigenetic effects of changes in metabolic flux.
Inhibition of O-GlcNAc transferase activates tumor-suppressor gene expression in tamoxifen-resistant breast cancer cells
Barkovskaya A. et al, (2020), Scientific Reports, 10, 16992 - 16992
Identification and Validation of Leucine-rich α-2-glycoprotein 1 as a Noninvasive Biomarker for Improved Precision in Prostate Cancer Risk Stratification
Guldvik IJ. et al, (2020), European Urology Open Science, 21, 51 - 60
Investigating Radiotherapy Response in a Novel Syngeneic Model of Prostate Cancer.
Haughey CM. et al, (2020), Cancers (Basel), 12
African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer.
Karunamuni RA. et al, (2020), Int J Cancer
Impacts of combining anti-PD-L1 immunotherapy and radiotherapy on the tumour immune microenvironment in a murine prostate cancer model.
Philippou Y. et al, (2020), Br J Cancer, 123, 1089 - 1100