Radiation Biology, Genomic Instability and Cellular Communication
Source: https://www.brookes.ac.uk/research/units/hls/groups/radiation-induced-genomic-instability Parent: https://www.brookes.ac.uk/engage-and-innovate/consultancy
Group Leader(s): Professor Munira Kadhim
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About us
Research impact
Leadership
Membership
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About us Research impact Leadership Membership
About us
Research in our group focuses on the investigation into non-targeted effects (NTE) of radiation exposure. These effects include delayed effects of radiation, i.e. genomic instability (GI) and bystander effects (BE). A topical issue in the field, at present, is elucidating the mechanisms of long-term health effects from low radiation exposures.
The group’s work focuses on understanding the exact mechanisms underlying radiation-induced genomic instability in irradiated, as well as un-irradiated cells (bystander cells), both in vivo and in vitro human and mouse model system by determining the influence of radiation quality and dose, individual genetic differences, cellular microenvironment signalling molecules such as Microvesicles (MV)/exosomes, cytokines, reactive oxygen species (ROS) and soluble proteins.
On a wider scale, our research contributes to helping identify practical health and risk implications, e.g. the ageing process, initiation and progression of cancer, environmental, occupational and medical risks of radiation exposure.
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Research impact
The impact of our related investigations can be summarised in the following areas:
- Improved understanding of biological effects of radiation leads to better practices with applications of radiation in a biological setting such as:
- radiotherapy and radio-diagnostics
- occupational workers
- space exploration
- Developing biomarkers for radiation protection and radiotherapy /oncology
- Potential deployment in public health setting for healthier society.
Leadership
Professor Munira Kadhim
Professor in Radiation Biology
View profile for Munira Kadhim
Membership
Staff members
- Staff
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Staff
| Name | Role | |
|---|---|---|
| Professor John Harrison | Visiting Professor | jharrison@brookes.ac.uk |
| Dr Seda Tuncay Cagatay | Post Doctoral Research Assistant | stuncay-cagatay@brookes.ac.uk |
Our research themes
Systemic Effects of Partial-body Exposure to Low Radiation Doses
Exosome-mediated changes are well documented in radiation therapy and oncology; however, there is a need to extend our knowledge on the role of exosomes in exosomes derived from inside and outside the radiation field in mediating the early and delayed induction of Non Targeted Effect (NTE) following Ionizing Radiation. In this project, we investigate the changes in exosome profile and the role of exosomes as possible molecular signalling mediators of radiation damage.
Radiation Stimulation of Cell Invasive Capacity: The Role of MV/Exosomes in Metastasis-related Processes
Metastasis is a major clinical problem and tumours are becoming resistant to therapies. In this project, we investigate aspects of metastatic behaviour (e.g. adhesion and invasiveness) following therapeutic dose of X-ray irradiation in vitro. We also aim to determine the role of exosome in this process.
Comparative Investigation of Senescence and Age on Radiation Response
Ionizing Radiation is known to induce cell senescence in healthy cells and therefore has the potential to accelerate aging and the early onset of diseases associated with aging. In this project, we investigate the molecular mechanisms causing radiation-induced senescence (RIS) and determine if these are the same as those that occur in senescence associated with normal aging.
Machine Learning for Exosome Data Analysis in Cancer Induction and Radiation Protection
Currently we are in the process of deploying Machine learning (ML) algorithms to investigate the role of MV including exosomes in aging accelerations post radiation exposure in order to develop quantitative indicators for radiation protection and predicators for cancer induction as well as the risks of long-term detrimental health effects of radiation. The ML technology may lead to a novel program to be used for this proposal. The emphasis will be on establishing a novel analytical scheme and exploiting rapid advances in big data analysis.