Title: Translating genomic signatures in kidney cancer into patient care
Funder: Department of Health and Social Care

Abstract: Background: Renal cell carcinoma (RCC) is the seventh commonest cancer in Europe and its incidence is rising. Clinical prognosis is notoriously difficult to predict and although new medical treatments (rapamycin analogues and multi-kinase inhibitors) show some efficacy, in the absence of surgical excision the prognosis of most patients remains very poor. There is an urgent need for better stratification and new treatment strategies. Most RCCs (both sporadic and familial) manifest biallelic inactivation of the von Hippel Lindau tumour suppressor (pVHL), a ubiquitin E3 ligase that normally (in oxygenated cells) targets the transcription factor hypoxia-inducible factor (HIF) for degradation. Thus, in VHL-defective RCC, HIF is constitutively activated. New opportunities to study the HIF pathway at the pan-genomic level have revealed the enormous complexity of primary and secondary transcription cascades, and multiple interactions with non-coding RNA networks and protein translational controls that result in thousands of changes in the molecular profile of the cell. Although activation of HIF (particularly the HIF2 iso-form) promotes cancer progression, it has become clear that HIF pathway activation results in multiple pro- and anti-tumourigenic effects and that it is the balance of these activities that is important. In RCC, evolution to a more oncogenic HIF2-driven profile is observed, but even within HIF1 and HIF2 target repertoires there are multiple pro- and anti-tumour activities. It is argued that the co-selection' penalty of activating anti-tumourigenic components of large pathways imposes a general restraint on cancer evolution, the importance of which has been under-estimated in approaches to clinical stratification and therapy. Aims and experimental strategy: The aims are (i) to define the pro- and anti-tumourigenic components of HIF activation in RCC (ii) to define the mechanisms that modulate this balance during RCC progression (iii) to use this data to define new prognostic algorithms which integrate this data for patient stratification (iv) to define new treatment targets and optimise the use of existing treatments, based on this framework. The pan-genomic architecture of HIF binding and associated chromatin conformation will be defined in RCC cells and patient tumour samples, and interfaced with large-scale cancer genomics databases and parallel sequencing programmes to define germ-line and somatic signatures of selection and epigenetic mechanisms that affect key driver or restrictor components of the HIF pathway. This data will be used to derive and test new prognostic algorithms that focus on functionally important components of the HIF pathway, incorporate complex bi-directional changes in gene expression, and integrate expression and DNA sequence data. RCC-relevant cell based assays (including the use of patient material and genetic engineering of markers at key HIF target loci) will be derived. These cells and other assays (e.g. for HIF1/2 alpha expression ratios) will be used in focussed screens to identify targets and lead molecules that modify the HIF response to generate a less oncogenic profile, and to determine whether, in selected patients, existing agents have the potential to do this. Context: The NIHR chair would enable DRM to capitalise on, and link several major strengths in Oxford, including the University's recently commissioned Target Discovery Institute, Big Data Centre (due for completion Q4, 2016), the new 109M NHS Cancer Hospital and the regional referral centre for kidney cancer. It would also build on local strengths in hypoxia biology, including those of the applicant. Patient benefit: The work should be of direct benefit to patients with RCC where there is an urgent need to define new methods for prognostic stratification, develop new treatments and optimise existing treatments. It leverages enormous accruing cancer (RCC) genetic databases to develop a framework in which this type of information can be interpreted in terms relevant to the patient.

Lay abstract: New techniques in genetic research have changed our preconceptions about cancer and revealed the involvement of far more widespread pathways than previously considered. These drive changes that both promote and inhibit progression of tumours. In order to advance, the cancer has to alter the balance of these pathways to favour its growth. Aims of the research: The aim is to translate this shift in thinking into improved healthcare for patients suffering from kidney cancer. In particular, it will use innovative types of (large-scale DNA-sequencing) data and methods of analysis to find new ways to predict how tumours will behave, which patients will respond to existing treatments and what new treatments might be effective. Background to the research: Kidney cancer is the seventh commonest cancer in Europe and is becoming more frequent. For patients with advanced disease that cannot be cured by surgery, the outlook is poor, with an average life expectancy of about 2 years. Current treatments are only partly effective and have considerable side effects. Therefore patients and carers are keen to find ways of determining which patients will do poorly and which will respond to treatment, as well as finding new ways of tackling the disease. Kidney cancer is also a good example for this type of approach, since most tumours are associated with the activation of a major pathway that controls the cell's normal response to oxygen. David Mole has helped show that when this pathway is switched on' in kidney cancer, 1000s of changes occur. Some of these drive the cancer, some slow the cancer and many are neutral or passive changes. In addition, these pathways are also activated in many other types of tumour. Thus, studying how kidney cancer alters oxygen pathways to favour its growth will have implications for these types of cancer as well. It will also shed light on how these cancers might also modify other pathways to their advantage. Design and methods used: The work will study how oxygen pathways are altered following their activation in kidney cancer. It will use large genetic datasets deposited by international consortia working on kidney cancer, and the applicant's expertise in defining the binding of proteins that signal oxygen across the genome. It will define and test new ways of combining the different types of data to predict cancer behaviour and treatment responses. This will have major implications for classifying cancers (i.e. distinguishing more, from less, aggressive tumours). In particular, it will be important to distinguish which components of large pathways are promoting or slowing tumour growth, and to use these (rather than all the genes whose expression is changed) for the classification. The findings also suggest new directions for developing treatments. Classically, the aim has been to find drugs, which block entire pathways that are switched' in cancer (i.e. the whole oxygen pathway). This new work suggests that it might be better to find drugs that modify the pathway to a less cancer-promoting' profile. This will be addressed by first defining the parts of the hypoxia pathway that are pro- and anti-cancer and then testing for drugs that modify these components. This includes agents that target molecules called epigenetic regulators' that are known to act in this way. It will also use kidney cancer cells (including those from patients) to study the effects of these drugs and drug-like molecules to identify candidates for medicine development, and guide the more accurate use of existing drugs. Patient and public involvement: The work will position the applicant at the interface between high-technology biomedical research and the care of his patients. It will take place within the Nuffield Department of Medicine in close association with the Oxford NIHR Biomedical Research Centre, both of which host major programmes (including national award winning work) in patient and public engagement, to which the applicant contributes. The work is closely aligned with the top 10 priorities for kidney cancer research identified by the James Lind Alliance. The applicant has active interactions with local (UCARE) and international (VHL family alliance) patient groups. Dissemination: Findings will be disseminated through open-access publications and international conferences (to which the applicant is a frequent invitee). Large datasets will be placed in web-based repositories (e.g. NCBI and EBI). The applicant is closely engaged with local patient groups such as Friends of Renal Oncology'. The Target Discovery Institute (containing the applicant's laboratory) has excellent interactions with pharmaceutical partners, which will be engaged under appropriate agreements, when necessary to translate findings into improved patient care.

Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS