IDENTIFYING AND FUNCTIONALLY CHARACTERISING RENAL CANCER DRIVER MUTATIONS

Worldwide kidney cancer causes over 140,000 deaths each year and its incidence of has markedly increased over the past 30 years. Despite advances in the treatment of kidney cancer many patients still have an unfavourable outlook. Cancers are caused by DNA mutations. Identifying these mutations is crucial for understanding what drives kidney cancer and devising new treatments. Studies of kidney cancer have, however, largely focused on mutations that cause changes in the proteins, without considering the remaining 98% of the cell's DNA. Some examples of cancer promoting mutations in this "non-coding DNA" have been identified but there has not been a comprehensive analysis for kidney cancer. To address this deficiency we shall therefor scrutinise the non-coding DNA cataloguing mutations and deciphering their functional consequences. This work should allow patient prognosis to be more accriyately defined and inform new targets for therapy.

Renal cell cancer (RCC) is a common cancer and despite recent improvements in its management the outcome remains poor for many patients. The identification of cancer driver genes is central to understanding carcinogenesis and treating cancer. In RCC few common driver genes are established. The full complement of molecular lesions that cause RCC and explain its diversity is unkown because the search for RCC drivers has focused mainly on coding regions of the genome. The recent availability of whole genome sequencing (WGS) data on RCC on a large-scale through initiatives including the 100,000 Genomes Project (100KGP) offers the opportunity to identify different classes of functional mutations for RCC and decipher their biological impact.

Our work programme will comprise three phases: (1) cataloguing the mutational landscape of RCC by analysis of 100KGP, in-house and publicly accessible data; (2) identifying recurrently mutated driver loci (coding, non-coding and copy number) by integrating mutation data with tissue-specific gene expression, epigenetic and topographical data; and (3) functional analyses to validate and delineate oncogenic mechanisms.

Identifying novel oncogenic pathways will improve patient stratification for personalising therapy using existing agents and facilitate discovery of novel therapeutic and chemoprevention agents.

This programme of work will deliver on three levels:

Molecular biology
A fuller understanding of the role of non-coding and structural variation in the development and evolution of renal cell cancer will be useful for cancer geneticists and molecular biologists. Satisfactory results attained within this proposal are therefore likely to seed fresh lines on enquiry into defining oncogenic addition.

Clinical translation
The increasing incidence and the poor outcome from renal cell cancer highlight the need to identify novel oncogenic drivers/mechanisms. Our research will benefit clinicians and patients directly by identifying targets for future drug development and improve patient prognostician.

Career development
Funding will support the training the training of three full time staff members and it is envisaged that the project will offer a gateway to developing their own careers.