Loading…
Loading grant details…
| Funder | Medical Research Council |
|---|---|
| Recipient Organization | University of Glasgow |
| Country | United Kingdom |
| Start Date | Mar 31, 2022 |
| End Date | Mar 30, 2027 |
| Duration | 1,825 days |
| Number of Grantees | 1 |
| Roles | Award Holder |
| Data Source | UKRI Gateway to Research |
| Grant ID | MC_PC_21042 |
Cancer remains one of the most prevalent health conditions for our population and, whilst great strides have been made in diagnosis and treatment, 1 in 4 people in the UK currently die of the disease, affirming that the science community must address the need for better treatments. Cancer is a complex and dynamic process which involves the transformation of a normal cell into an aggressively malignant one through a series of genetic changes, but is also strongly influenced by the local environment in which a tumour co-evolves.
The complex interactions and cross-talk between tumour cells and their neighbouring tissues is a vital component of how a cancer develops, spreads through the body and responds to anti-cancer therapies. These processes can only be fully explored in the context of the living animal. Mouse models have been crucial in deepening our understanding of cancer and in the discovery of novel therapies.
For cancers of certain organs mouse models now exist that recapitulate the full cancer journey, but for other cancers these models have fallen short of replicating the complexity of human disease. There is an urgent need therefore to develop the next generation of mouse models that will allow the research community to better understand the biology underpinning the major cancer types, generate novel targets and rigorously apply these to a therapeutic pipeline with better prediction to patient response.
This proposal brings together leading clinicians, cancer biologists, computational biologists partnered with technology clusters in a coordinated national effort. Our pertinent aims will be to exploit new and emerging technologies that will i) allow us to characterise how accurately mouse models reflect specific subsets of human cancers (so called disease-positioning); ii) build better mouse models that mirror the full spectrum of human tumour evolution; iii) create robust mouse models that significantly improve predictability of novel cancer treatments.
In addressing these aims we will create an outward facing, easily accessible compendium of models and data for the UK community, opening out availability of resources, technologies and expertise. We will improve and extend our repertoire of models to cover those cancers where no quality models exist. With access to huge human data sets we can reiteratively refine the mouse models to faithfully reflect human disease, and utilize sophisticated imaging techniques to study the dynamic changes at the cell, tissue and organ level.
This is vital to ensure that new knowledge gleaned from these models is applicable to human disease, and to ensure that therapeutic testing in mouse models accurately predicts how human cancers will respond to the same treatments.
In collaboration with the Mary Lyon Centre (MLC), and leveraging the cluster expertise within the National Mouse Genetics Network, we will develop platforms for integrating many different types of data across our spectrum of models, increasing their value as predictive pre-clinical tools. Specialist expertise in surgery, radiotherapy, imaging and standard-of-care treatment will be centralised through MLC that will act as a repository of models for wider distribution and promote best practice and 3Rs (refinement, replacement and reduction) nationally.
We aim to expand upon our established links with industry, particularly in the SME space, to promote job creation and commercialisation of new therapeutic discoveries and to leverage further significant investment in disease modelling through collaborative engagement. Ultimately we expect to translate new treatments and drug combinations validated in our cancer models into the clinic through our already extensive clinical network.
University of Glasgow
Complete our application form to express your interest and we'll guide you through the process.
Apply for This Grant