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An intelligent scheme to identify novel drug targets through analysing the DNA repairome in drug resistant cancer?

   School of Life Sciences

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  Prof C Parris  No more applications being accepted  Self-Funded PhD Students Only

About the Project

Research Group

Biomedical Research Group

Proposed supervisory team

Prof Christopher Parris


Cancer Cell Biology

Summary of the research project

Efficient and accurate DNA repair is essential for the maintenance of genome stability. Failure to repair DNA accurately can result in cell cycle arrest, apoptosis and at the organismal level, the development of cancer. Sophisticated, multi-protein DNA repair systems in human and eukaryotic cells repair a wide variety of DNA damages generated as a result of exposure to environmental carcinogens and mutagenic compounds generated internally as a result of normal metabolism (Kryston et al., 2011).

Over the past two decades a significant investigative effort has delineated the fundamental mechanisms of DNA repair in human and eukaryotic cells. To date some 150 DNA repair genes have been identified. Importantly, there are a number of rare genetic diseases where an inherited mutation of one or more of the genes involved in DNA repair render the individual hypersensitive to DNA damaging agents and dramatically increased cancer incidence (Wood et a., 2001).

DNA repair capacity also has fundamental implications in the treatment of cancer. The majority of anticancer treatments rely on the ability to introduce DNA damage in cancer cells to bring about cell death. Therefore the DNA repair capacity of cancer cells will have a major impact on the ability to cure a cancer with chemotherapy or radiotherapy (standard methods of treatment). In fact a major driver in the pharmaceutical industry is to target DNA repair pathways for inhibition in order to cure cancer.

An exemplar of the above phenomenon is displayed in the treatment of ovarian cancer (OC) where there are some 7000 cases per year in the UK. The clinical management of OC is challenging with 35% overall 5 year survival rates (Cancer Research UK). A major contributing factor to poor clinical outcomes in OC is the development of resistance to anticancer therapy where enhanced expression of key DNA repair proteins has been demonstrated. While this observation is extremely important most investigations in to DNA repair gene expression in OC have been limited in scope focusing on a single DNA repair gene or pathway (Adam-Zahir, 2014).

The advent of post-genomic technologies has led to the establishment of large genome data repositories freely available to the scientific community. We are now in a position to analyse the expression of the entire complement of DNA repair genes ('the human DNA repairome') in cancer and normal tissue from the same individual (Peng et al., 2015).

The PhD research project hypothesis is that enhancement of DNA repair causes drug resistance in ovarian and other cancers. We will use bioinformatics approaches to determine the expression levels of the entire human repairome in drug resistant cancer.

The aims in Year 1 will be to interrogate The Cancer Genome Atlas (TCGA) and identify RNAseq data sets (the level of expressed genes in the human genome) for ovarian cancer and matched normal tissue.

Year 2 will involve developing an intelligent solution using artificial intelligence (AI) algorithms, particularly machine learning to determine the level of gene expression of all 150 DNA repair genes in:

  • Non cancer tissue
  • Primary ovarian caner
  • Recurrent, drug resistant cancer

Year 3 will be to:

  • Determine patterns of DNA repair gene expression in numerous samples of ovarian cancer.
  • Develop an adaptive scheme to use the proposed intelligent solution to other common cancers (breast, colon, lung, skin, prostate etc).

Taking the research forward, common patterns of DNA repairome expression in cancer will guide the development of novel drugs designed to inhibit DNA repair pathways in cancer cells and lead to innovative methods for the treatment of cancer.

Where you'll study



This project is self-funded.

Details of studentships for which funding is available are selected by a competitive process and are advertised on our jobs website as they become available.

Next steps

If you wish to be considered for this project, you will need to apply for our Biomedical Science PhD. In the section of the application form entitled 'Outline research proposal', please quote the above title and include a research proposal.

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